Approches d’aide à la décision pour une transformation efficace de l’industrie forestière au Canada

Cas des compagnies de pâtes et papiers

Thèse

Mahdi Machani

Doctorat en génie mécanique Philosophiae doctor (Ph.D.)

Québec, Canada

© Mahdi Machani, 2014

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Résumé

L'industrie forestière québécoise est à la croisée des chemins. La hausse du prix de l'énergie, la montée du

dollar canadien, ainsi que le déclin de plusieurs marchés conventionnels ont rendu obsolète l'ancien modèle

d'affaires de la plupart des compagnies forestières; cet ancien modèle étant basé sur la production de masse

de produits standards destinés à des marchés conventionnels.

Pour le cas des papetières, la baisse structurelle de la demande pour plusieurs produits de pâtes et papiers

ainsi qu'une structure de coûts lourde, désavantagée face à la compétition à faible coût, ont rendu inévitable la

transformation de ce secteur afin de survivre à la crise. Plusieurs avenues de transformation s’offrent au

secteur de pâtes et papiers incluant la modernisation des processus de production, ou encore la diversification

de la plateforme de production en intégrant des produits de pâtes et papiers innovateurs ou des nouveaux

produits à haute valeur ajoutée tels que les bioproduits.

Notre contribution à travers ce projet est de développer des outils d'aide à la décision permettant aux preneurs

de décision au sein du secteur de pâtes et papiers de revoir et d'innover leurs réseaux de création de valeur,

d’identifier les stratégies de transformation les plus robustes, de réinventer leurs modèles d'affaires et établir

des feuilles de route pour optimiser cette transformation. L'objectif est de proposer à une compagnie forestière

des modèles adaptés aux changements majeurs affectant l'industrie forestière, qui seraient en mesure de

créer et de livrer une valeur ajoutée tout en assurant un avantage concurrentiel durable.

Trois contributions sont ainsi présentées dans de cette thèse. La première propose une approche

décisionnelle à plusieurs niveaux (multi-niveaux) pour réinventer les modèles d’affaires des compagnies de

pâtes et papiers. La deuxième contribution présente un cadre d’aide à la décision pour évaluer le potentiel

technico-économique d’intégrer la bioénergie au sein des compagnies de pâtes et papiers. Quant à la

troisième contribution, elle apporte une approche de modélisation par scénarios permettant d’identifier les

stratégies les plus robustes pour le secteur de pâtes et papiers, qui sauraient résister aux incertitudes

technologiques, économiques et sociopolitiques affectant le secteur dans les années à venir.

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Table des matières

Résumé .............................................................................................................................................................. III 

Table des matières .............................................................................................................................................. V 

Liste des tableaux .............................................................................................................................................. IX 

Liste des figures ................................................................................................................................................. XI 

Remerciements .............................................................................................................................................. XVII 

Avant-propos ................................................................................................................................................... XIX 

Chapitre 1  Introduction générale ..................................................................................................................... 1 

1.1  Introduction ........................................................................................................................................... 2 

1.2  Problématique de recherche ................................................................................................................. 3 

1.2.1 Conception d’un nouveau modèle d’affaire ....................................................................................... 5 1.2.2 Évaluation de la profitabilité d’un modèle d’affaires prometteur : la bioraffinerie forestière intégrée . 6 1.2.3 Évaluer différentes avenues de transformation dans un environnement incertain ............................ 7 

1.3  Revue de littérature ............................................................................................................................... 8 

1.3.1 Conception de nouveaux modèles d’affaires ..................................................................................... 9 1.3.2 Analyse de la profitabilité du modèle d’affaires de la BRFI.............................................................. 12 1.3.3 Évaluation des stratégies de transformation des compagnies de P&P dans un environnement incertain .................................................................................................................................................... 21 

1.4  Méthodologie scientifique et contributions .......................................................................................... 26 

1.5  Conclusion .......................................................................................................................................... 28 

Chapitre 2  Une approche de décision à multi-niveaux pour la conception du modèle d’affaires de la

bioraffinerie forestière intégrée pour le cas des compagnies de pâtes et papiers ............................................. 29 

Résumé ............................................................................................................................................................. 31 

Abstract ............................................................................................................................................................. 32 

2.1  Introduction ......................................................................................................................................... 33 

2.2  Literature review .................................................................................................................................. 35 

2.3  The approach ...................................................................................................................................... 40 

2.3.1 Current state analysis ...................................................................................................................... 43 2.3.2 Opportunity spotting ........................................................................................................................ 43 

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2.3.3 The need for change ........................................................................................................................ 45 2.3.4 Strategic vision ................................................................................................................................ 47 2.3.5 Strategy ........................................................................................................................................... 50 2.3.6 Business model design .................................................................................................................... 58 2.3.7 Business model validation ............................................................................................................... 69 2.3.8 Continuos adaptation ....................................................................................................................... 73 

2.4  Conclusion ........................................................................................................................................... 73 

Chapitre 3  Un cadre de travail basé sur un modèle mathématique pour évaluer le potentiel technico-

économique d’intégrer la bioénergie dans les usines de pâtes et papiers ........................................................ 77 

Résumé ............................................................................................................................................................. 79 

Abstract ............................................................................................................................................................. 80 

3.1  Introduction .......................................................................................................................................... 81 

3.2  Literature Review ................................................................................................................................ 85 

3.2.1 Supply chain design integrating bioenergy ...................................................................................... 85 3.2.2 IFBR potential for P&P mills............................................................................................................. 87 3.2.3 Paper contribution ............................................................................................................................ 88 

3.3  Methodology ........................................................................................................................................ 89 

3.3.1 Initial pool definition ......................................................................................................................... 90 3.3.2 Relevant database construction ....................................................................................................... 91 3.3.3 Mathematical model ......................................................................................................................... 92 3.3.4 The investments roadmap ............................................................................................................... 92 

3.4  Mathematical model ............................................................................................................................ 93 

3.4.1 Model assumptions .......................................................................................................................... 94 3.4.2 Sets.................................................................................................................................................. 95 3.4.3 Parameters ...................................................................................................................................... 96 3.4.4 Decision variables ............................................................................................................................ 97 3.4.5 Costs and Revenues ....................................................................................................................... 99 3.4.6 Objective function .......................................................................................................................... 103 3.4.7 Constraints ..................................................................................................................................... 103 

3.5  Results and Discussion ..................................................................................................................... 106 

3.5.1 Bioenergy investment roadmap ..................................................................................................... 108 3.5.2 P&P operational roadmap .............................................................................................................. 109 3.5.3 Feedstock and product flows ......................................................................................................... 110 3.5.4 Discussion ..................................................................................................................................... 113 3.5.5 Sensitivity analysis ......................................................................................................................... 114 

3.6  Conclusions ....................................................................................................................................... 117 

VII

3.7  Appendix ........................................................................................................................................... 118 

3.7.1 Appendix A: Model database ......................................................................................................... 118 3.7.2 Appendix B: Sensitivity analysis .................................................................................................... 126 

Chapitre 4  Une approche de modélisation par scénarios pour identifier des stratégies de transformation

robustes pour le cas des compagnies de pâtes et papiers ............................................................................. 129 

Résumé ........................................................................................................................................................... 131 

Abstract ........................................................................................................................................................... 132 

4.1  Introduction ....................................................................................................................................... 133 

4.2  Literature review ................................................................................................................................ 134 

4.2.1 Scenario planning .......................................................................................................................... 134 4.2.2 Scenario-based strategic design ................................................................................................... 135 4.2.3 Paper contribution ......................................................................................................................... 136 

4.3  Methodology: A four-step approach .................................................................................................. 137 

4.3.1 Identifying a number of transformation strategies .......................................................................... 138 4.3.2 Scenario design ............................................................................................................................. 141 4.3.3 Scenarios....................................................................................................................................... 143 4.3.4 Strategy/Scenario evaluation ......................................................................................................... 145 4.3.5 Mathematical Model ...................................................................................................................... 146 

4.4  Case-study: A Kraft pulp mill ............................................................................................................. 153 

4.4.1 Future trends for model parameters under the different scenarios ................................................ 153 4.5  Results and Discussion ..................................................................................................................... 155 

4.6  Conclusion ........................................................................................................................................ 163 

4.7  Appendix ........................................................................................................................................... 165 

4.7.1 Appendix A: Model parameters’ future trends ............................................................................... 165 4.7.2 Appendix B: Model database ......................................................................................................... 170 

Chapitre 5  Conclusion générale et perspectives ......................................................................................... 173 

Bibliographie ................................................................................................................................................... 177 

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Liste des tableaux

Tableau 2.1 Literature review on strategic decision support methodologies ..................................................... 39 Tableau 2.2 Strengths and weaknesses of the Canadian P&P sector .............................................................. 43 Tableau 2.3 Federal programs to support the Canadian forest industry ........................................................... 48 Tableau 3.1 Time-related parameters values .................................................................................................. 107 Tableau 3.2 Summary of financial results ....................................................................................................... 108 Tableau 3.3 Roadmap of bioenergy investments ............................................................................................ 109 Tableau 3.4 Operational financial summary of P&P activity over the planning horizon H ............................... 110 Tableau 3.5 Biomass supplied over planning horizon H ................................................................................. 111 Tableau 3.6 P&P and bioenergy production over the planning horizon H ....................................................... 112 Tableau 3.7 Flows of final products within the IFBR and to the market over the planning horizon H .............. 112 Tableau 3.8 Co-products flows within the IFBR and to the market over the planning horizon H ..................... 113 Tableau 3.9 Operational costs and revenues summary over the planning horizon H ..................................... 113 Tableau 3.10 Sensitivity analysis results ......................................................................................................... 115 Tableau 4.1 Summary of the transformation strategies considered ................................................................ 141 Tableau 4.2 Financial summary for the transformation strategies under the scenarios .................................. 158 Tableau 4.3 Summary of min-max regret criterion analysis ............................................................................ 161 Tableau 4.4 Kraft pulp model parameters' future trends ................................................................................. 166 Tableau 4.5 MFP model parameters' future trends ......................................................................................... 167 Tableau 4.6 Bioethanol model parameters' future trends ................................................................................ 168 Tableau 4.7 Forest residues’ supplying cost future trends .............................................................................. 168 Tableau 4.8 Wood chips’ supplying cost future trends .................................................................................... 169 Tableau 4.9 Recycled paper supplying cost future trends ............................................................................... 169 

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Liste des figures

Figure 1.1 Illustration de la problématique liée à la transformation d’une compagnie de pâtes et papiers ......... 4 Figure 1.2 Canevas de modèle d’affaires en neuf blocs ................................................................................... 10 Figure 1.3 Exemple d’un réseau de création de valeur d’une BRFI .................................................................. 17  Figure 2.1 Multi-level decisional approach to design business models ............................................................ 42 Figure 2.2 Perspectives for change using the four-action framework ............................................................... 47 Figure 2.3 The P&P company vision ................................................................................................................. 50 Figure 2.4 Transformational strategies for Canadian forest companies ............................................................ 56 Figure 2.5 The three-step decisional levels ....................................................................................................... 58 Figure 2.6 A multi-scenario development for business model ........................................................................... 60 Figure 2.7 P&P company-based IFBR value creation network ......................................................................... 61 Figure 2.8 Business model canvas ................................................................................................................... 63 Figure 2.9 Potential partnerships for IFBR ........................................................................................................ 67 Figure 2.10 Cost structure for the IFBR ............................................................................................................ 68 Figure 2.11 The business model canvas for a P&P company-based IFBR ....................................................... 69 Figure 3.1 IFBR value creation network ............................................................................................................ 84 Figure 3.2 IFBR design methodology ................................................................................................................ 93 Figure 3.3 Decision variables over the IFBR supply chain ................................................................................ 99 Figure 3.4 Sets and nodes over the IFBR supply chain .................................................................................. 107 Figure 4.1 A four-step methodology to design robust transformation strategies for P&P companies .............. 138 Figure 4.2 Future trend-based scenarios for Canadian P&P companies’ business environment .................... 145 Figure 4.3 The P&P company value creation network integrating the considered strategic options ............... 146 Figure 4.4 Estimated financial values for the different transformation strategies under all the scenarios

considered .............................................................................................................................................. 161 Figure 4.5 Estimated cash flows for the different transformation strategies under all the scenarios considered

............................................................................................................................................................... 162 

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À ma grand-mère Mariem, À mon père, À ma mère,

À mes deux sœurs, À mon Halloul.

Lis, au nom de ton Seigneur qui a créé, qui a créé l´homme d´une adhérence.

Lis! Ton Seigneur est le Très Noble, qui a enseigné par la plume,

a enseigné à l´homme ce qu´il ne savait pas. [Coran 96.1-96.5

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Remerciements

Je tiens à exprimer ma gratitude envers mon directeur de recherche Mustapha Nourelfath pour son soutien

académique et personnel durant cette thèse. Étant déjà mon directeur de recherche durant la maitrise, son

dévouement et son expertise m’ont initié au monde de la recherche et m’ont été d’une grande utilité pour me

lancer dans le long projet qu’est le doctorat. Pr. Nourelfath était toujours à l’écoute, prêt à donner conseil pour

le bien de ma carrière. L’ayant côtoyé durant presque six ans, fût un agréable périple tant au niveau

professionnel qu’au niveau humain.

Je tiens également à remercier Sophie D’Amours pour son support considérable tout au long de la thèse. Par

ses précieux conseils, et son expertise dans l’industrie forestière, j’ai été surement chanceux de l’avoir comme

co-directrice de recherche. Son implication était fort enrichissante pour bien mener ce travail.

Je voudrais aussi exprimer ma reconnaissance pour FORAC pour son support financier et académique durant

la thèse. Les multiples conférences et séminaires auxquels j’ai pu participer m’ont été fortement utiles pour

peaufiner mes habiletés de communication et partager mes travaux avec des chercheurs du monde entier.

Finalement, un grand merci à tous les membres de FORAC, en particulier Catherine Lévesque, Julie Richard,

Anis Ben Amor, et Philippe Marier pour leur disponibilité et leur contribution pour mener à terme ce travail.

Je remercie également Christian Prins, Mikael Rönnqvist et Paul Stuart pour avoir accepté de donner de leur

temps précieux pour évaluer ce travail et faire partie des membres du jury.

Quant à mes parents, Hèdi et Radhia, je leur dois tout simplement l’homme que je suis devenu aujourd’hui.

Durant ces vingt-quatre longues années d’études, leurs prières, leurs larmes de joie, leur fierté de leur fils

étaient mon carburant pour avancer et exceller. Leur offrir cette thèse sera un modeste présent pour tous leurs

sacrifices. Un grand merci à mes deux sœurs Sannouna et Mariouma pour leur amour et leur encouragement

inconditionnels.

Pour Halloul, ma chère femme, son amour et son affection étaient une condition nécessaire et suffisante pour

que je puisse accomplir ce travail. Souffrant d’une sècheresse oculaire parfois invalidante, son sourire et son

cœur rayonnant m’humidifiaient l’esprit dans les moments les plus obscurs. Sans elle à mes côtés, je n’aurais

été surement pas capable d’en arriver là. Je tiens également à remercier chaleureusement mon beau-père

pour son encouragement et ma belle-mère pour son affection et ses belles invocations.

Un grand merci à mon ami Chahir Fitouhi, pour ses conseils tout au long de la thèse et pour l’opportunité qu’il

m’a offerte pour faire de la consultation au Québec. Je voudrais aussi remercier Paul-André Proulx pour

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m’avoir donné la chance d’acquérir une expérience dans l’industrie au Québec. Son expertise exceptionnelle

et ses conseils prodigieux m’ont été d’une énorme valeur pour mon parcours professionnel.

Un grand merci à tous mes chers amis Marouene Ben Jabeur, Mohamed Dhib, Mohamed Jmour, Mahdi

Guellouz, Soumaya Guellouz, Anouar Zouaoui, Slim Ben Ayed, Sabrine Ben Arab, Haythem Ghanouchi, Zied

Chakroun, Naoufel Limayem, Brahim Fazaa, Mohamed Bouchaala, Mohamed Dhiaeddine Boussema, Sam et

Yasmine, pour les moments agréables passés avec eux, qui étaient si importants pour me permettre

d’avancer.

Finalement, je tiens à remercier ma « Tunisie », mon pays, qui m’a permis de poursuivre mes études

supérieures au Canada en m’octroyant une bourse d’excellence gouvernementale. En espérant que demain

sera un jour meilleur pour la terre du Jasmin!

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Avant-propos

Ce travail, intitulé « Approches d’aide à la décision pour une transformation efficace de l’industrie forestière au

Canada - Cas des compagnies de pâtes et papiers », est réalisé dans le but d’obtenir le grade de Doctorat en

Génie Mécanique (Ph.D.) de l’Université Laval. Il a été effectué sous la direction du Pr. Mustapha Nourelfath

et sous la codirection de Pr. Sophie D’Amours, au sein du Consortium de Recherche FORAC.

Cette thèse est rédigée selon le principe d’insertion d’articles. Elle se compose de trois articles qui ont été tous

coécrits avec Pr. Mustapha Nourelfath et Pr Sophie D’Amours. Pour chacun des articles présentés, j’ai agi à

titre de chercheur principal dans le développement des approches proposées, la rédaction des articles ainsi

que la révision des versions soumises aux journaux. Pour les articles 1 et 2, j’ai contribué à la proposition de la

problématique, développé la méthodologie proposée et rédigé l’article. Pour l’article 3, j’ai proposé la

problématique, développé la méthodologie et rédigé l’article. Les trois articles ont été effectués sous la

supervision périodique et la validation des résultats obtenus à chaque étape par Pr. Mustapha Nourelfath et

Pr. Sophie D’Amours.

Le premier article, intitulé « A multi-level decisional approach to design Integrated Forest Biorefinery business

model for pulp and paper companies », a pour auteurs Mahdi Machani, Mustapha Nourelfath et Sophie

D’Amours. Il a été soumis au journal « Long Range Planning » en Décembre 2013 (Facteur d’impact évalué à

3,667 en 2012). La version présentée dans cette thèse est identique à la version soumise.

Le deuxième article, intitulé « A mathematically-based framework for evaluating the technical and economic

potential of integrating bioenergy production within pulp and paper mills », a pour auteurs Mahdi Machani,

Mustapha Nourelfath et Sophie D’Amours. Il a est maintenant publié dans le journal « Biomass & Bioenergy »

(Volume 63, April 2014, Pages 126–139). Le facteur d’impact du journal est évalué à 3,931 pour les cinq

dernières années. La version présentée dans cette thèse est la version complète (plus longue) incluant le

modèle mathématique et la base de données.

Le troisième article, intitulé « A scenario-based modelling approach to identify robust transformation strategies

for pulp and paper companies », a pour auteurs Mahdi Machani, Mustapha Nourelfath et Sophie D’Amours. Il

a été soumis à « International Journal of Production Economics » en janvier 2014 (Facteur d’impact évalué à

2,594 durant les cinq dernières années). La version présentée dans cette thèse est identique à la version

soumise. Il est actuellement en processus de révision.

1

Chapitre 1 Introduction générale

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1.1 Introduction

Dans un contexte compétitif global marqué plus que jamais par des incertitudes économiques et

sociopolitiques accrues, les économies émergentes et l’avènement des nouvelles technologies ont rendu les

stratégies traditionnelles, que les compagnies entreprennent pour faire face à la compétition, de plus en plus

insuffisantes. En particulier, pour le cas des industries évoluant dans des marchés saturés, à l’instar de

l’industrie forestière en Amérique du Nord (PwC, 2010a), les compagnies n’ont plus intérêt à limiter leurs

stratégies à l’emporter face à leurs compétiteurs traditionnels, mais devraient s’orienter vers de nouvelles

manières de penser afin de rendre la compétition sans importance, et ce explorant de nouveaux horizons au-

delà des frontières traditionnelles (Kim and Mauborgne, 2005a). Un tel revirement de cap nécessite une

transformation fondamentale dans la façon à gérer l’entreprise à tous les niveaux de décision, pour lui

permettre d’achever un avantage concurrentiel durable. Dès lors, produire aux meilleurs coûts et livrer aux

meilleurs délais ne suffiraient plus pour assurer la pérennité des compagnies, qui devraient en plus se doter

d’une agilité leur permettant de réagir rapidement aux imprévus, d’une adaptabilité aux tendances

économiques, sociopolitiques et technologiques redessinant les marchés au futur, ainsi que d’une capacité

d’aligner les performances de l’ensemble des maillons de la chaine logistique aux intérêts de l’entreprise

(L.Lee, 2004).

Au Canada, l’industrie forestière, en particulier le secteur de pâtes et papiers (P&P), vit une conjoncture

difficile à cause d’une crise structurelle où la demande pour un nombre de produits conventionnels (papier

journal, papier à écriture, etc.) est en baisse à cause des produits de substitution (MRNF, 2012), conjuguée à

un déclin cyclique de demande pour la plupart des produits forestiers, dû à la hausse du dollar canadien, à la

compétition à faible coût, et à l’incertitude quant aux ressources énergétiques (FPInnovations, 2011).

Ainsi, les compagnies forestières devraient entreprendre une transformation profonde leur permettant aussi

bien de survivre au sein des marchés saturés que de saisir de nouvelles opportunités de croissance en dehors

de ces marchés, afin d’être le mieux possible préparées aux changements majeurs affectant le secteur dans

les années à venir.

Depuis quelques années, praticiens et chercheurs se sont penchés sur le développement de méthodologies et

d’outils (d’aide à la décision) pour aider les compagnies forestières à mieux comprendre les enjeux et les défis

auxquels elles font face, à analyser les opportunités qui s’offrent à elles et en déceler les avenues de

transformation les plus prometteuses, et à se doter des moyens stratégiques pour réussir cette évolution.

Cette thèse de doctorat s’inscrit dans cette thématique de recherche en s’intéressant de près à l’industrie

forestière au Canada, en particulier le secteur de P&P, dans le but de contribuer au développement de

3

nouvelles approches permettant à ces compagnies de s’adapter aux nouvelles réalités des marchés et

d’entreprendre une transformation réussie et durable. Ce travail se veut ainsi une contribution aux efforts déjà

entrepris dans la planification stratégique, la conception et la gestion des réseaux de création de valeur des

produits forestiers intégrant les changements majeurs affectant le secteur, où les outils de recherche

opérationnelle sont combinés à des approches stratégiques pour amener de nouvelles réflexions quant aux

outils d’aide à la décision proposés à une industrie forestière en pleine mutation.

Dans ce qui suit, nous détaillons la problématique de recherche ainsi que les objectifs des contributions

proposées. Nous présentons en deuxième lieu une revue de littérature des travaux de recherche portant sur le

sujet traité tout au long de cette thèse. La troisième partie est consacrée à la présentation des différentes

contributions. Finalement, une conclusion du chapitre est présentée.

1.2 Problématique de recherche

Tout au long de cette thèse, nous nous intéressons à la problématique de transformation de l’industrie

forestière au Canada, en prenant le cas particulier du secteur de P&P. En fait, les papetières ont été fortement

affectées par la crise touchant l’industrie forestière (Marinova et al., 2010), devenant au fil des années un

secteur attirant de moins en moins d’investisseurs à cause de son faible retour d’investissement (CIFQ, 2010).

La baisse soutenue de la demande pour un nombre de produits conventionnels de pâtes et papiers, la hausse

des prix de l’énergie, ainsi que l’émergence d’une compétition à faible coût (Browne, 2011) ont pesé lourd sur

le bilan opérationnel du secteur, engendrant de faibles profits et une surcapacité de ressources de production

(NRC, 2012). Ainsi, de nombreux industriels et chercheurs plaident en faveur d’une transformation du secteur

((PwC, 2010a), (FPAC, 2010), (Stuart, 2006), (Pätäri et al., 2011), (Caisse and Montreuil, 2007), (Thorp,

2005)); une transformation qui pourrait remettre en question un nombre de paradigmes au niveau de la

gestion des ressources de la compagnie, de ses relations d’affaires avec l’ensemble du réseau de création de

valeur des produits proposés, de ses sources d’avantage concurrentiel, voire de sa raison d’être.

Ce questionnement pourrait amener la compagnie à intégrer de nouvelles matières premières telles que la

biomasse forestière, ou encore enlever des matières premières déjà existantes regroupant les matières

premières conventionnelles pour une usine de pâtes et papiers telles que les billes et les copeaux de bois, les

pâtes et papiers, et de l’énergie. Au niveau de l’usine, la compagnie pourrait être amenée à réajuster ses

capacités de production, intégrer de nouvelles technologies produisant de nouveaux produits tels que les

produits de pâtes et papiers innovateurs et les bioproduits. Au niveau des marchés, le maintien ou encore

l’élargissement des marchés conventionnels de pâtes et papiers pourraient être une piste à considérer.

D’autre part, de nouveaux marchés à nouvelles exigences pourraient être accédés.

4

Au delà du réseau de création de valeur, l’ensemble des niveaux décisionnels de la compagnie pourraient être

profondément révisés. Le modèle d’affaires, décrivant la façon avec laquelle la compagnie gère ses affaires

tout en interagissant avec ses différents partenaires du réseau de création de valeur (Osterwalder and

Pigneur, 2010), pourrait être remis en question afin d’optimiser la création, la livraison et la capture de la

valeur. La compagnie pourrait être ainsi amenée à réajuster sa proposition de valeur ou encore redéfinir ses

relations avec les fournisseurs et les marchés. La stratégie de l’entreprise, régissant les sources d’avantage

concurrentiel de la compagnie, pourrait être remodelée afin d’évaluer comment la compagnie fait face à la

compétition, quelles sont dorénavant les sources d’avantage concurrentiel à considérer, et quelles seraient les

limites de la transformation par rapport aux frontières actuelles des marchés desservis. Même au niveau de la

vision globale de la compagnie, des questions fondamentales pourraient être posées quant à la mission de la

compagnie et la direction vers laquelle elle s’en va. La Figure 1.1 résume l’étendue de ces questionnements

et les niveaux décisionnels qui pourraient être sérieusement affectés par une telle transformation. Une liste

non exhaustive des problématiques qui pourraient être considérées, est présentée en couleur verte dans la

figure.

Figure 1.1 Illustration de la problématique liée à la transformation d’une compagnie de pâtes et papiers

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Dès lors, une panoplie de possibilités s’offrent aux compagnies de P&P afin d’entreprendre une

transformation. De la remise en question des ressources de production, jusqu’à la révision de la vision globale

de la compagnie, une telle mutation devrait être accompagnée de cadres méthodologiques afin de supporter

les preneurs de décision dans leurs processus. Ces approches doivent proposer des ‘‘guides’’ de

transformation ayant comme finalité d’assurer la pérennité de la compagnie évoluant dans un environnent

d’affaires de plus en plus dynamique et incertain.

Ainsi vient l’intérêt de développer des outils d’aide à la décision qui permettent aux différents intervenants et

preneurs de décision dans le secteur de P&P d’évaluer les différentes pistes de transformation et de s’orienter

vers les avenues de transformation les plus profitables. C’est la problématique que nous traitons durant ce

travail : la conception d’approches décisionnelles pour supporter une transformation réussie et durable des

compagnies de P&P.

Afin d’aborder cette problématique générale, nous proposons trois contributions portant chacune sur un aspect

spécifique de la problématique présentée. La première contribution porte sur la conception d’un nouveau

modèle d’affaires supportant la transformation des compagnies de P&P. La deuxième contribution traite

l’évaluation de la profitabilité d’un modèle d’affaire prometteur. Quant à la troisième contribution, elle aborde la

problématique de l’évaluation de la profitabilité de différentes avenues de transformation en considérant

l’incertitude au sein de l’environnement d’affaires des compagnies de P&P.

Dans ce qui suit, la problématique ainsi que les objectifs de chacune des trois contributions sont détaillés.

1.2.1 Conception d’un nouveau modèle d’affaire

Cette contribution traite la problématique de la conception de nouveaux modèles d’affaire afin de supporter la

transformation du secteur de P&P. En fait, les compagnies de P&P au Canada doivent plus que jamais revoir

leur façon de gérer leurs affaires en ne se limitant plus aux stratégies d’affaires traditionnelles basées sur

l’efficacité opérationnelle et la réduction des coûts de production. Il est indispensable pour ces compagnies

d’appréhender les défis et d’analyser les opportunités d’affaires afin de survivre à la crise et retrouver leur

compétitivité. Ainsi, créer une nouvelle proposition de valeur, réinventant la manière avec laquelle la valeur

(produits et services) est créée et offerte aux différents segments de clients (Osterwalder and Pigneur, 2010),

est jugée comme vitale pour réussir la transformation voulue (Kim and Mauborgne, 2005a).

Le modèle d’affaire, définissant la logique avec laquelle la compagnie crée, livre et capture la valeur

(Osterwalder and Pigneur, 2010), a pour mission principale de régir les relations d’affaires que l’entreprise

entreprend avec ses différents partenaires à partir des fournisseurs jusqu’aux clients. Transformer ainsi la

proposition de valeur de la compagnie passe obligatoirement par la réinvention de son modèle d’affaires. Par

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ailleurs, la conception d’un nouveau modèle d’affaires nécessite l’interaction avec d’autres niveaux de décision

tels que la vision globale, la stratégie ainsi que le réseau de création de valeur, d’où l’intérêt de proposer une

approche holistique remettant en question différents niveaux décisionnels afin de les aligner dans la même

direction.

La première contribution s’intéresse donc à cette problématique de transformation des modèles d’affaires dans

le cadre d’une approche intégrée permettant aux preneurs de décision dans le secteur de P&P de relever les

défis actuels et de transformer les opportunités d’affaires en une innovation de valeur durable.

Pour aborder cette problématique, les objectifs de la première contribution sont les suivants :

Identifier les défis ainsi que les opportunités de transformation pour le secteur de P&P au Canada;

Proposer une approche décisionnelle à multi-niveaux pour supporter la transformation;

Proposer des outils de conception de modèles d’affaires;

Amener aux preneurs de décision du secteur de P&P un outil de réflexion stratégique sur l’interaction

des différents niveaux de décision dans le processus de transformation.

1.2.2 Évaluation de la profitabilité d’un modèle d’affaires prometteur : la bioraffinerie forestière intégrée

Lors de la deuxième contribution, on aborde la problématique d’évaluation de la profitabilité d’un modèle

d’affaires pour le cas des compagnies de P&P au Canada. Le modèle d’affaires reposant sur le concept de la

bioraffinerie forestière intégrée (BRFI) est identifié en tant qu’avenue prometteuse pour transformer le secteur

de P&P canadien. Pour le cas d’une usine de P&P, le concept de la BRFI repose sur l’intégration d’un

ensemble de bioproduits; des produits obtenus par transformation de biomasse, au sein de l’usine, et ce

parallèlement à l’activité conventionnelle de production des produits de pâtes et papiers (Stuart, 2006). Les

bioproduits englobent une grande famille de produits qui peuvent être produits à partir de la biomasse incluant

chaleur, électricité, biocarburants, biomatériaux, etc. (FPInnovations, 2011).

La biomasse considérée dans une BRFI regroupe les résidus forestiers, les résidus agricoles, les résidus

issus de l’industrie forestière, les cultures énergétiques qui sont des plantes cultivées spécialement pour la

production de l’énergie ou des bioproduits, ainsi que les déchets solides municipaux et urbains (Bradley,

2010).

7

Dans cette contribution, nous nous intéressons à analyser le potentiel d’une famille particulière de bioproduits :

la bioénergie, qui représente une source d’énergie produite à partir de la biomasse incluant chaleur, électricité

et biocarburants.

Pour se transformer en une BRFI, différents types de biomasse sont disponibles et différents processus et

technologies de transformation sont possibles. La maturité technologique et économique de ces technologies,

bien qu’encore instables, connaitraient une évolution durant les prochaines années (de Wit et al., 2010). Un

nombre de nouveaux marchés de bioproduits présentent un potentiel énorme de croissance durant les

prochaines années. Cela exige une adaptabilité exceptionnelle de compagnies de P&P afin de saisir les

opportunités qui s’y présentent avant qu’il ne soit trop tard, une fois que les parts dans ces nouveaux marchés

seraient prises (Nunes and Breene, 2011).

Décider du chemin de transformation optimal est ainsi crucial pour permettre à la compagnie de P&P

d’achever une transformation profitable. L’obtention de ce chemin passe inévitablement par l’évaluation des

différentes options possibles afin d’en dégager la plus profitable. La deuxième contribution traite cette

problématique d’évaluation du potentiel de la transformation d’une compagnie de P&P en une BRFI. Le but est

d’amener aux décideurs du secteur de P&P une approche d’aide à la décision permettant d’analyser

l’intégration de la bioénergie tout au long du réseau de création de valeur des produits considérés, et ce en

considérant l’évolution de l’environnement d’affaires des compagnies de P&P dans les années à venir.

Les objectifs de cette deuxième contribution sont ainsi définis comme suit :

Analyser la profitabilité de l’intégration de la bioénergie tout au long du réseau de création de valeur;

Développer un modèle mathématique pour évaluer le potentiel financier des options considérées;

Proposer une feuille de route des investissements profitables en bioénergie à intégrer.

1.2.3 Évaluer différentes avenues de transformation dans un environnement incertain

La troisième contribution s’intéresse à la problématique d’évaluer plusieurs pistes de transformation pour le

cas des compagnies de P&P, qui évoluent dans un environnement d’affaires de plus en plus incertain.

Un nombre croissant de chercheurs et d’industriels soutient la nécessité d’entreprendre un virage stratégique

pour l’ensemble du secteur de P&P, notamment dans des marchés saturés tels que le Canada ((PwC, 2010a),

(MRNF, 2012), (Pätäri et al., 2011)). Les pistes de transformation proposées varient d’une restructuration

8

opérationnelle basée sur la réduction des coûts, jusqu’à l’intégration de nouvelles technologies et l’accès à de

nouveaux marchés.

Néanmoins, en dépit des nombreuses études soulignant le potentiel d’une stratégie ou d’une autre, la

présence de fortes incertitudes rend la décision de choisir telle ou telle option un exercice complexe; parmi ces

incertitudes, on peut citer par exemple la disponibilité des matières premières, les prix de l’énergie, les

tendances des marchés, ainsi que les orientations sociopolitiques qui affecteraient sérieusement la

compétitivité des compagnies de P&P au Canada dans les années à venir (UNECE/FAO, 2012).

Toute décision relative au choix de transformation stratégique devrait donc considérer les incertitudes qui y

sont liées, afin d’amener une solution robuste qui permettrait aux compagnies d’être mieux préparées aux

changements pouvant affecter le secteur dans les années à venir. Ainsi vient l’intérêt de proposer des

approches d’aide à la décision appliquées au cas du secteur de P&P, ayant pour objectif de supporter

l’orientation stratégique de la compagnie vers une transformation profitable et robuste. De ce fait, nous

abordons cette problématique à travers la troisième contribution dans le but de proposer une approche

permettant aux compagnies de P&P en quête de transformation d’évaluer différentes options stratégiques en

tenant compte de leur environnement d’affaires incertain. En se basant sur une approche par scénarios, où un

nombre de scénarios est conçu dans le but d’identifier différentes tendances futures au sein de

l’environnement d’affaires des compagnies de P&P, notre contribution consiste à proposer un outil d’aide à la

décision pour aider ces compagnies à transformer de potentielles opportunités de transformation en un

avantage concurrentiel, et ce, de façon robuste vis-à-vis des incertitudes.

Ainsi, les objectifs de la troisième contribution sont les suivants :

Identifier des stratégies de transformation prometteuses pour les compagnies de P&P au Canada;

Identifier les tendances majeures affectant leur environnement d’affaires durant les années à venir;

Évaluer la profitabilité de chacune des stratégies sous différents scénarios plausibles basés sur les

principales tendances identifiées;

Proposer un nombre de recommandations stratégiques quant aux options de transformation robustes

pour le secteur de P&P au Canada.

1.3 Revue de littérature

Tout au long de la revue de littérature, nous présentons un aperçu global des principaux travaux de recherche

en rapport avec chacune des trois contributions effectuées. Ainsi, nous nous intéressons dans un premier lieu

9

à la littérature abordant la problématique de la conception de nouveaux modèles d’affaires. Ensuite, nous

passons en revue les principales contributions portant sur l’analyse de profitabilité du modèle d’affaire de la

bioraffinerie forestière intégrée. Finalement, nous examinons de près les travaux traitant la problématique de

l’évaluation des stratégies de transformation dans un environnement incertain.

1.3.1 Conception de nouveaux modèles d’affaires

Les modèles d’affaires décrivent la façon avec laquelle l’entreprise entreprend ses affaires (Osterwalder and

Pigneur, 2010). Dans (Magretta, 2002), le modèle d’affaires d’une compagnie est assimilé à une histoire

expliquant quels sont les consommateurs, quelle est leur valeur, et comment l’entreprise sera profitable en

fournissant à ces consommateurs cette valeur. Ainsi, le modèle d’affaires formule la relation de l’entreprise

avec ses différents partenaires afin d’atteindre ses objectifs stratégiques. Toute compagnie devrait donc se

doter d’un modèle d’affaires bien structuré, afin d’optimiser la façon de gérer ses affaires tout au long du

processus de création de valeur à partir des fournisseurs jusqu’aux consommateurs.

En fait, dans (Johnson et al., 2008), les auteurs définissent comme modèle d’affaires réussi tout modèle

reposant sur trois piliers : une proposition de valeur aux consommateurs supérieure aux offres alternatives,

une formule de profit où les revenus, les marges de profit et les coûts sont bien structurés, et des ressources

et processus clés composés des personnes, des technologies, des produits et des équipements requis afin

d’acheminer la proposition de valeur aux consommateurs ciblés. Les auteurs proposent une analyse

systémique de ces différentes composantes afin de dresser les forces et les limites du modèle d’affaires mis

en place. Selon (Nunes and Breene, 2011), l’analyse des différentes composantes d’un modèle d’affaires

permettrait de déceler tôt les faiblesses du modèle d’affaires et de le réadapter avant qu’il ne soit trop tard.

Une étude présentée dans le même article, constate qu’une compagnie aurait moins de 10% de chance de se

remettre d’une chute significative de ses revenus. Dans (Govindarajan and Trimble, 2011), les auteurs vont

même jusqu’à présenter les modèles d’affaires en tant que concepts périssables que les compagnies doivent

réinventer constamment pour assurer une compétitivité durable. Une méthodologie combinant la préservation

des forces du présent, la destruction sélective des faiblesses du passé, ainsi que la création d’opportunités

durables, est ainsi proposée dans le but de baliser une telle transition. Les auteurs de (Osterwalder et al.,

2005) présentent une revue de littérature approfondie sur les modèles d’affaires en s’intéressant à l’origine du

concept du modèle d’affaires, aux différentes interprétations développées, ainsi qu’à l’évolution de ce concept

dans la littérature. L’un des travaux les plus extensifs sur les modèles d’affaires est celui dans (Osterwalder

and Pigneur, 2010), où les auteurs proposent un manuel de référence pour la conceptualisation, la

caractérisation et la conception des modèles d’affaires, dans le but d’amener un outil pratique pour

accompagner les preneurs de décision au sein des compagnies dans le processus d’innovation de modèle

d’affaires. Un processus de conception de modèle d’affaires à cinq phases est présenté, incluant la

10

mobilisation, l’appréhension, la conception, l’implémentation et la gestion du modèle d’affaires. Pour

accompagner les différentes phases de ce processus, un canevas composé de neuf blocs est développé (voir

Figure 1.2), dans le but d’illustrer la logique avec laquelle l’entreprise crée, livre et capture la valeur.

Dans cette logique, le modèle d’affaires repose sur quatre principales composantes : l’infrastructure, l’offre, les

consommateurs et la viabilité financière.

Pour l’infrastructure, elle repose sur des activités clés, des ressources clés ainsi que les partenaires clés

requis pour créer la valeur. L’offre quant à elle est définie par la proposition de valeur que l’entreprise crée en

exploitant son infrastructure afin de livrer la valeur aux consommateurs. Concernant la composante des

consommateurs, elle inclut les différents segments des consommateurs auxquels l’entreprise livre sa

proposition de valeur, les relations que la compagnie entreprend avec chaque segment de consommateurs,

ainsi que les canaux de communication utilisés pour interagir avec les consommateurs. Finalement, la viabilité

financière inclut la structure de coût engendrée par la création et l’acheminement de la proposition de valeur

aux consommateurs, ainsi que les flux de revenus générés par l’offre à chaque segment de consommateurs.

Avec les changements profonds affectant l’industrie forestière, de nombreuses études s’intéressent de plus en

plus au concept de modèle d’affaires afin d’amener de nouveaux cadres conceptuels supportant la

transformation du secteur. Dans ce qui suit, nous présentons la littérature portant sur l’application du concept

de modèle d’affaires à l’industrie forestière.

Figure 1.2 Canevas de modèle d’affaires en neuf blocs (Osterwalder and Pigneur, 2010)

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1.3.1.1 Le concept de modèle d’affaires dans l’industrie forestière Concernant le cas de l’industrie forestière au Canada, avec la crise cyclique et conjoncturelle affectant la

plupart des secteurs, notamment le secteur de P&P ((MRNF, 2009), (MRNF, 2012)), un nombre croissant de

chercheurs et de praticiens s’intéressent au concept de modèle d’affaires comme solution prometteuse pour la

transformation des compagnies forestières.

D’après un document de travail portant sur les conditions requises pour une transformation réussie pur

l’industrie forestière au Québec (CIFQ, 2010), la transformation du modèle d’affaires, rendu obsolète pour la

plupart des secteurs, sera vitale afin de permettre aux compagnies forestières d’achever une vision basée sur

l’innovation, le développement durable et la compétitivité. À l’échelle du Canada, un rapport d’études détaillé

sur l’état de l’industrie forestière au Canada en 2011-2012, met en valeur la nécessité de transformer les

paradigmes traditionnels de gestion ainsi que les modèles d’affaires traditionnels des compagnies forestières

en vue d’achever une nouvelle vision orientée vers les nouvelles technologies, les nouveaux produits et la

gestion durable des forêts (NRC, 2012).

En termes de travaux de recherche, l’évocation de la problématique liée à la transformation des modèles

d’affaires est souvent limitée au soulignement de la nécessité de transformer le modèle d’affaires pour

entreprendre une transformation réussie. Dans (V. Chambost et al., 2008), une approche à trois phases est

proposée supportant la transformation des compagnies de P&P en un modèle d’affaires basé sur la BRFI, en

argumentant que la réinvention du modèle d’affaires de ces compagnies est essentielle pour assurer la

viabilité de la transformation. Dans un travail complémentaire, une approche de sélection des partenaires de

qualité, présentés comme un élément crucial du modèle d’affaires basé sur la BRFI, est proposée afin de

supporter la transformation de la compagnie (Chambost et al., 2009). Dans (Pätäri et al., 2011), les auteurs

présentent une approche stratégique permettant aux compagnies de P&P de créer un avantage concurrentiel

durable. En analysant les opportunités d’affaires qui se présentent au secteur de P&P, le modèle d’affaires de

BRFI est présenté en tant qu’option stratégique prometteuse.

À notre connaissance, le seul article de recherche traitant explicitement la problématique de la conception de

modèles d’affaires pour le cas de l’industrie forestière est celui de (Caisse and Montreuil, 2007), où les auteurs

proposent une approche conceptuelle tétraédrique de conception de modèles d’affaires afin d’innover le

modèle d’affaires d’une compagnie en quête de transformation, et ce, en présentant un cas d’étude portant

d’une compagnie de fabrication de bois au Québec. L’outil proposé repose sur quatre pôles de conception :

les intervenants qui interagissent avec la compagnie, les offres représentant les interfaces entre la compagnie

et les intervenants, la création de valeur aux intervenants, et le caractère définissant la manière avec laquelle

la compagnie et les intervenants font affaire.

12

En analysant la revue de littérature présentée ci-dessus, nous observons que le concept de modèle d’affaires

est généralement traité sous deux angles différents. Dans la littérature orientée vers les sciences de gestion

(management), l’intérêt a été essentiellement porté sur la proposition de méthodologies conceptuelles

permettant aux entreprises d’identifier, concevoir et implémenter des modèles d’affaires compétitifs

((Osterwalder and Pigneur, 2010), (Nunes and Breene, 2011), (Johnson et al., 2008), (Govindarajan and

Trimble, 2011), (Osterwalder et al., 2005)). Bien qu’elles amènent de réelles contributions aux entreprises en

termes d’outils de management stratégique, ces approches ne s’attardent pas, en général, aux liens entre le

modèle d’affaires et les autres niveaux de décision tels que la définition d’une stratégie ou encore la

conception du réseau logistique.

D’autre part, les travaux de recherche s’intéressant à la conception des réseaux de création de valeur

s’intéressent principalement à développer des approches de conception stratégiques ayant comme finalité de

rendre le modèle d’affaires plus compétitif, sans toutefois détailler explicitement l’impact de telles approches

sur les composantes du modèle d’affaires considéré ((Caisse and Montreuil, 2007), (V. Chambost et al.,

2008), (Chambost et al., 2009)).

D’où vient l’intérêt de notre première contribution, qui consiste à proposer une approche d’aide à la décision

qui amène à la fois un cadre conceptuel pour réinventer le modèle d’affaires, ainsi qu’une méthodologie

intégrant cette transformation dans une séquence de décisions allant du plus haut niveau stratégique jusqu’au

réseau de création de valeur de la compagnie.

Le but de cette contribution est de développer une approche qui soit suffisamment conceptuelle pour poser les

fondements d’une transformation réussie, tout en amenant un outil pratique aux compagnies de P&P leur

permettant de traduire ces concepts à travers les différents niveaux de décision incluant la vision, la stratégie

le modèle d’affaires et le réseau de création de valeur.

1.3.2 Analyse de la profitabilité du modèle d’affaires de la BRFI

Dans un rapport discutant l’état actuel et les perspectives liées à l’industrie forestière au Canada (NRC, 2012),

des experts soulignent le poids économique important de cette industrie, et le rôle qu’elle détient dans le

développement d’une économie canadienne basée sur l’exploitation écoresponsable des ressources

naturelles et une proposition de valeur aussi bien durable que compétitive. L’étude présentée dans (NRC,

2012) discute, entre autres, la crise du secteur forestier canadien. La hausse du dollar canadien, la crise du

marché de l’immobilier aux États-Unis ainsi que l’émergence de compétiteurs à faible coûts, ont pesé

lourdement sur l’industrie forestière canadienne et ont engendré des pertes importantes durant ces dernières

13

années, ce qui s’est traduit par une nette détérioration des profits d’un nombre de secteurs, en particulier le

secteur de P&P.

Pour sortir de cette crise, plusieurs rapports et études perçoivent le développement d’une bioindustrie comme

l’une des solutions les plus prometteuses pour permettre au secteur forestier canadien de retrouver sa

compétitivité ((FPInnovations, 2011), (NRC, 2012), (FPAC, 2010), (FPInnovations and MRNF, 2009), (FPAC,

2011)). La transformation de l’industrie forestière en une bioindustrie passe par l’intégration de la biomasse

lignocellulosique1 en tant que source de création de valeur au sein des compagnies forestières, leur

permettant de diversifier leurs sources de revenus et d’accéder à de nouveaux marchés en dehors des

marchés conventionnels saturés.

Afin d’exploiter la biomasse d’une façon optimisée, le concept de bioraffinerie, représentant une usine

transformant de la biomasse en des bioproduits, tels que la bioénergie, les biocarburants et les produits

biochimiques, est de plus en plus étudié depuis quelques années, dans le but d’apporter des solutions

innovatrices quant à l’incertitude liée aux énergies fossiles, tout en amenant de nouvelles plateformes de

produits à haute valeur ajoutée pour un ensemble de marchés en phase de croissance.

La biomasse considérée dans une bioraffinerie pourrait regrouper les résidus forestiers, les résidus agricoles,

les résidus issus de l’industrie forestière, les cultures énergétiques qui sont des plantes cultivées spécialement

pour la production de l’énergie ou des bioproduits, ainsi que les déchets solides municipaux et urbains

(Bradley, 2010).

Pour pouvoir transformer cette biomasse, plusieurs technologies sont développées, ou sont en cours de

développement. Le degré de maturité de ces technologies varie entre des technologies au stade commercial

et d’autres qui sont encore au stade de projets pilotes (Bradley et al., 2009). Les auteurs de (de Wit et al.,

2010) modélisent la maturité des technologies de fabrication d’un nombre de bioproduits ainsi que les coûts

d’investissement et d’opération qui y sont associés. Les auteurs démontrent l’énorme potentiel de

développement technologique et de réduction des coûts associés à ces technologies, dans les années à venir,

favorisé par les incitations gouvernementales et une demande de marchés croissante d’ici 2030. Dans une

étude explorant le potentiel économique et environnemental de la production de la bioénergie et des

biocarburants, les auteurs de (Huang et al., 2009) soulignent l’avantage des bioraffineries lignocellulosiques

pour produire de l’éthanol, de l’électricité, de la chaleur, de la vapeur et possiblement d’autres biocarburants et

des produits chimiques, à partir de la biomasse lignocellulosique.

1 La lignocellulose est composée de lignine, d’hémicellulose et de cellulose en proportions variables. Elle est très

présente dans la paroi des cellules des végétaux, du bois et de la paille (Bradley, 2010).

14

L’intégration du concept de la bioraffinerie dans le modèle d’affaires des compagnies de P&P révèle un

énorme potentiel pour ce type d’entreprises qui sont considérées comme des bioraffineries

« conventionnelles » transformant le bois en produits de pâtes et papiers (Huang et al., 2009). Une compagnie

de P&P aurait ainsi les infrastructures de base et le réseau logistique adapté pour développer une nouvelle

plateforme de bioproduits, afin de diversifier ses marchés et retrouver la profitabilité, tout en contribuant à la

réduction des émissions de gaz à effet de serre (V. Chambost et al., 2008).

Une telle intégration a donné naissance à un nouveau concept de modèle d’affaires, appelé bioraffinerie

forestière intégrée ou BRFI. Le potentiel des BRFIs a été souligné à travers plusieurs travaux de recherche

((PwC, 2010a), (Stuart, 2006), (Pätäri et al., 2011), (Chambost et al., 2009), (Huang et al., 2009)). Le réseau

logistique conventionnel d’une entreprise de P&P est orienté vers le traitement et le transport des produits

forestiers, et jouit surtout d’un emplacement stratégique par rapport aux points d’approvisionnement de la

biomasse forestière. De plus, le processus de production du papier génère une multitude de résidus et de

sous-produits (liqueur noire, copeaux de bois, eaux usées, boues de papier, etc.) qui pourraient être valorisés

pour la fabrication de bioproduits.

Une telle transformation nécessite la revue du réseau de création de valeur des produits forestiers, et ce à

partir des fournisseurs, en passant par l’usine jusqu’aux consommateurs.

La Figure 1.3 illustre de façon macro et conceptuelle des avenues de transformation possibles de la biomasse

en bioénergie et en biocarburants de deuxième génération ((Bradley, 2010), (BIOCAP Canada Foundation,

2008), (Londo et al., 2008), (Wakker et al., 2005)). Cette figure représente graphiquement l’éventuel réseau de

création de valeur basé sur la BRFI. Un tel réseau inclut les fournisseurs des matières premières

conventionnelles telles que les copeaux de bois et l’énergie fossile, les nouveaux fournisseurs de biomasse,

les processus conventionnels de production des produits de pâtes et papiers, ainsi que plusieurs processus

possibles de transformation de biomasse en un ensemble de produits (incluant la bioénergie et les

biocarburants, allant de la chaleur, la vapeur et l’électricité jusqu’aux granules de bois, Diesel Fisher-Tropsch

(F-T), Gaz naturel synthétique (GNS), et Bioéthanol). Des co-produits, tels que la Naphta et la lignine,

pourraient être directement vendus aux marchés. L’activité conventionnelle de production de pâtes et papiers

génère un nombre de sous-produits et de résidus (tels que la liqueur noire et les boues de papier) qui

pourraient être utilisés pour alimenter l’activité de production de bioénergie et de biocarburants, ou encore

vendus en tant que co-produits. Les produits finis issus de l’activité conventionnelle et de l’ensemble des

technologies implantées serviraient un nombre de marchés incluant celui de produits de pâtes et papiers

davantage exigeant en termes de compétitivité et d’écoresponsabilité, et un ensemble de marchés de

15

bioproduits en croissance recherchant des alternatives aux énergies fossiles qui soient innovatrices et

économiquement viables.

17

Figure 1.3 Exemple d’un réseau de création de valeur d’une BRFI

18

La problématique liée à la transformation des compagnies forestières, en particulier les usines de P&P, en

bioraffineries intégrées attire de plus en plus de chercheurs dans le domaine de conception stratégique et de

la gestion des chaines logistiques. Le but commun de ces travaux en forte émergence est de proposer des

approches et des outils optimisant les décisions stratégiques et tactiques liées à cette transformation.

La littérature traitant cette problématique peut être divisée en deux grandes familles. D’une part, un nombre de

travaux se sont intéressés à la problématique de la conception de réseaux de création de valeurs des produits

forestiers intégrant la biomasse. D’autre part, un nombre croissant d’études s’est penché particulièrement sur

un concept prometteur permettant la transformation du secteur : la bioraffinerie forestière intégrée. Dans ce

qui suit, nous présentons une revue de littérature des principaux travaux appartenant à ces deux catégories.

1.3.2.1 Conception des réseaux de création de valeur des produits forestiers intégrant la biomasse

Étant une matière première présentant plusieurs particularités liées à la densité, la saisonnalité et le degré

d’humidité, la biomasse nécessite une gestion de chaine d’approvisionnement bien adaptée afin d’optimiser

son potentiel. Les auteurs de (Jenkins and Sutherland, 2009) analysent un nombre d’options liées à

l’acheminement de la biomasse forestière vers une installation de conversion en énergie. Ils considèrent trois

grandes étapes d’approvisionnement incluant la récolte, le transport, le stockage et le prétraitement. Dans

(Rentizelas et al., 2009), les auteurs étudient la chaine d’approvisionnement en biomasse pour le cas d’une

installation de cogénération d’électricité, de chauffage et de climatisation. Trois différents scénarios de

stockage sont évalués afin d’estimer le degré de séchage et la détérioration de la qualité de la biomasse

stockée.

Plusieurs travaux s’intéressent de près à la problématique de la conception des réseaux logistiques intégrant

la biomasse. Dans (Lakovou et al., 2010), les auteurs présentent une revue de synthèse sur les réseaux

logistiques transformant la biomasse en bioénergie. Les auteurs analysent l’état de développement des

technologies de conversion ainsi que les différents niveaux d’intégration de biomasse dans la gestion des

chaines logistiques intégrant la biomasse.

Les outils proposés font souvent coupler des décisions stratégiques liées à la localisation et la capacité des

sites de production, à des décisions tactiques liées aux flux de matières premières et produits finis, et ce afin

de mieux évaluer l’impact de la conception proposée. Un système d’aide à la décision est présenté dans

(Freppaz et al., 2004) permettant de décider des capacités et des localisations des installations de

cogénération, ainsi que de la quantité annuelle de biomasse forestière à acheminer aux sites de conversion et

la proportion d’électricité et de chaleur produite dans chaque installation. Dans (Ekşioğlu et al., 2009), un

modèle à nombres entiers mixtes est proposé permettant d’optimiser la localisation, le nombre et la capacité

19

des bioraffineries et des sites de collections, ainsi qu’un nombre de décisions concernant l’acheminement, le

stockage et le traitement de la biomasse et du biocarburant considérés. Le but étant d’optimiser la conception

de la chaine logistique considérant la production de bioéthanol à partir de quatre types de biomasse. En

couplant également les décisions stratégiques et les décisions tactiques liées à la conception de la chaine

logistique de production de bioéthanol, les auteurs de (Huang et al., 2010) apportent un modèle multi-périodes

où l’on peut agrandir la capacité d’une bioraffinerie déjà construite au cours des années, dans un horizon de

planification de vingt ans.

1.3.2.2 Le concept de bioraffinerie forestière intégrée (BRFI) dans le secteur de P&P Pour le cas des usines de P&P, la conjoncture économique difficile que vit le secteur depuis quelques années

a soutenu le développement d’une littérature récente ayant pour but d’analyser le potentiel des différentes

options offertes aux compagnies de P&P, notamment le concept de la BRFI.

Dans une étude portant sur le secteur de P&P canadien (Stuart, 2006), le concept de la BRFI est qualifié

comme étant la stratégie de survie pour un secteur en quête de modèle d’affaires innovateurs et compétitifs.

L’auteur avance qu’il est indispensable d’investir dans des produits à la fois économiquement et

écologiquement viables, tout en s’assurant d’une certaine sécurité en termes d’approvisionnement et de

marchés de distribution. Dans un travail complémentaire, considérant la BRFI en tant qu’option prometteuse

pour réussir la transformation du modèle d’affaires du secteur de P&P canadien (V. Chambost et al., 2008),

une approche stratégique de transformation à trois phases est proposée dans le but d’intégrer une nouvelle

plateforme de bioproduits, tout en abandonnant la fabrication de certains produits à faibles marges de profit.

Dans (Mansoornejad et al., 2010), une méthodologie hiérarchique est développée pour soutenir la

transformation d’une entreprise de P&P en une BRFI. La méthodologie présentée intègre, en ordre, la

conception de la plateforme des technologies et des produits à intégrer, l’intégration d’une flexibilité liée aux

capacités de production et aux proportions fabriquées de chaque produit, et enfin la revue de la conception de

la chaine logistique, où plusieurs alternatives d’expansion et d’acquisition sont évaluées, et ce en générant

différents scénarios reflétant la volatilité de la demande et des prix de marchés. Les auteurs de (Feng et al.,

2012) apportent un modèle pour l’optimisation du réseau logistique intégrant la biomasse, et ce pour décider

des sites de production à utiliser, de leurs localisations, des technologies, des capacités, ainsi que des

matières premières à s’approvisionner. Les bioraffineries à intégrer dans la structure du réseau considéré

pourraient être des scieries, des usines de P&P ou des sites autonomes de production de bioéthanol,

d’énergie ou de granules de bois. Le but est de maximiser la valeur des investissements à implanter.

L’analyse de la revue de littérature portant sur l’évaluation du potentiel de l’intégration des bioproduits, en

particulier la bioénergie et les biocarburants, au sein des compagnies forestières, révèle la spécialisation de la

portée des travaux cités. Une partie de la littérature s’est intéressée essentiellement à traiter les

20

problématiques liées à l’intégration de la biomasse dans les chaines d’approvisionnement des compagnies

forestières, en proposant des modèles optimisant cette intégration ((Jenkins and Sutherland, 2009),

(Rentizelas et al., 2009)). D’autres travaux se sont penchés sur la problématique de la conception de réseaux

logistiques intégrant les bioproduits afin d’aboutir à une conception optimale, en se limitant souvent à un seul

produit ((Freppaz et al., 2004), (Ekşioğlu et al., 2009), (Huang et al., 2010)).

D’autre part, la littérature portant sur l’analyse du potentiel des BRFIs pour le cas des compagnies de P&P

s’est principalement intéressée à proposer des approches stratégiques permettant aux compagnies d’assurer

une transition efficace, sans toutefois fournir d’outils mathématiques évaluant quantitativement la profitabilité

d’une telle transformation ((Stuart, 2006), (V. Chambost et al., 2008), (Mansoornejad et al., 2010)). Le seul

travail apportant un modèle mathématique afin d’évaluer le potentiel d’investir dans un nombre de bioproduits

((Feng et al., 2012)), considère seulement le Bioéthanol, la cogénération et les granules de bois dans un

problème d’optimisation de la conception du réseau logistique global. La considération d’un horizon de

planification de trois ans (dans (Feng et al., 2012)) ne permettait pas, toutefois, de tenir compte de l’évolution

technologique et économique liée aux investissements en bioproduits, jugés encore en début de phase de

croissance.

Nous pensons qu’il est ainsi indispensable de développer des outils d’aide à la décision permettant d’évaluer

le potentiel de l’intégration de la biomasse au sein des compagnies de P&P, en considérant l’ensemble de la

chaine de valeur allant des fournisseurs de matières premières jusqu’aux marchés .

En particulier, le potentiel des BRFIs, offrant une réelle opportunité aux compagnies de P&P pour diversifier

leurs sources de revenus, devrait être évalué aussi bien qualitativement que quantitativement sur un horizon à

long-terme afin de tenir compte des évolutions technologiques et économiques liées aux bioproduits. Le but

est de permettre aux décideurs au sein du secteur de P&P d’identifier les avenues de diversification les plus

prometteuses technologiquement et financièrement, tout en considérant une panoplie de matières premières,

de produits, et de marchés.

Ainsi, notre deuxième contribution consiste à amener aux compagnies de P&P une approche d’aide à la

décision basée sur la modélisation mathématique, leur permettant d’identifier les opportunités qui leur sont

offertes en termes de matières premières, de technologies, et de marchés, analyser en détail la profitabilité

associée à de telles intégrations, et en déceler les options les plus avantageuses. En considérant un horizon

de planification à long-terme, les tendances futures associées aux couts d’investissement, à la maturité

technologique, à la demande ainsi qu’aux prix de vente sur les marchés, sont intégrées explicitement dans

l’approche développée, dans le but de proposer des solutions qui tiennent compte des mutations qui

affecteraient l’environnement d’affaires du secteur dans les années à venir.

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1.3.3 Évaluation des stratégies de transformation des compagnies de P&P dans un environnement incertain

Tel que mentionné auparavant, les compagnies de P&P, secouées par une crise conjoncturelle difficile et par

un nombre de changements structurels, devraient entreprendre une mutation pour faire face à un

environnement d’affaires de plus en plus imprédictible et en mouvement (JAAKKO Pöyry consulting, 2005).

Une chose est sure : repenser les stratégies de base sera crucial pour ces compagnies, afin de se doter d’un

avantage concurrentiel capable d’assurer leur compétitivité. Une telle transformation pourrait amener

l’entreprise à remettre en question son offre de produits, ses relations avec ses consommateurs, les marchés

qu’elle dessert, etc. (PwC, 2010a).

Dans ce qui suit, nous présentons la littérature proposant différentes stratégies de transformation au secteur

de P&P, ainsi que les travaux considérant différentes approches pour intégrer l’incertitude dans les décisions

de transformation stratégique.

1.3.3.1 Les différentes avenues de transformation proposées Depuis quelques années, plusieurs travaux de recherche se sont intéressés à la problématique de

transformation des compagnies de P&P, en proposant des méthodologies pour évaluer différentes options

stratégiques potentielles. La bioraffinerie forestière intégrée est considérée comme étant une avenue

prometteuse pour l’industrie forestière, en particulier les compagnies de P&P. Les auteurs de (Feng et al.,

2012) proposent un modèle mathématique pour optimiser la conception d’un réseau de création de valeur des

produits forestiers intégrant la bioénergie. Les investissements considérés peuvent être intégrés dans des

scieries ou des usines de P&P déjà en place, ou implantés sur des sites de production autonome. Dans

(Pätäri et al., 2011), le potentiel stratégique de la BRFI pour une compagnie de P&P est analysé, en proposant

une approche stratégique afin d’analyser les opportunités d’affaires se présentant à ces compagnies et les

transformer en une source d’avantage concurrentiel.

D’autre part, un nombre d’études se sont penchées sur la mutation des marchés des produits P&P afin de

proposer des stratégies permettant aux compagnies de retrouver leur compétitivité. Dans (Frandina et al.,

2008), les principales tendances transformant la demande de différents marchés de P&P sont analysées, dans

le but de proposer des recommandations stratégiques d’investissements répondant aux nouvelles exigences

des consommateurs des produits de P&P. Les auteurs de (Marinova et al., 2010) discutent trois options

stratégiques qui permettraient aux compagnies de P&P d’améliorer leur rentabilité. La première étant

l’implantation des mesures d’efficacité énergétique permettant à l’entreprise d’optimiser ses coûts d’opération.

La deuxième option repose sur le concept de grappes industrielles regroupant des papetières afin de se

partager les ressources et optimiser leurs stratégies de collaboration. La troisième option discutée présente le

concept de bioraffinage incluant la valorisation des sous-produits issus de la production des produits de P&P,

22

tels que la lignine, la liqueur noire et les résidus de bois afin de fabriquer un nombre de produits de valeur

ajoutée tels que la bioénergie et les produits biochimiques. Dans une étude analysant les perspectives liées

au secteur de P&P au Québec (Ministère des Finances and MERN, 2000), les stratégies basées sur la

modernisation des processus de fabrication sont présentées comme cruciales pour les compagnies en

manque de compétitivité. Le rôle des subventions gouvernementales supportant les investissements à

considérer est mis en valeur.

1.3.3.2 La considération de l’incertitude dans les transformations stratégiques Quelle que soit la piste de transformation empruntée, les compagnies de P&P auraient à gérer un nombre

d’incertitudes associées aux matières premières, aux prix de l’énergie, aux politiques gouvernementales, aux

tendances des marchés, aux attitudes des consommateurs, etc. (UNECE/FAO, 2012).

Ces incertitudes sont traitées de différentes façons dans la littérature. De nombreux travaux portant sur

l’exploration du potentiel des bioraffineries et voulant analyser l’effet de l’incertitude sur les solutions

proposées, présentent des analyses de sensibilité afin d’explorer l’impact de varier certains paramètres sur les

décisions prises. En modélisant la compétitivité d’un ensemble de biocarburants considérant une évolution

technologique et des réductions de coût dans les années à venir, les auteurs de (de Wit et al., 2010) analysent

l’impact de varier certains paramètres du modèle proposé tels que le coût d’investissement, le timing

d’introduction au marché, et la courbe de maturité technologique sur les coûts de production et le potentiel

compétitif des biocarburants étudiés. Dans (Ekşioğlu et al., 2009), les auteurs proposent un modèle

mathématique optimisant la conception et la gestion d’un réseau logistique de bioraffinage intégrant le

bioéthanol, évaluent l’effet de varier les coûts logistiques liés au transport et à la récolte ainsi que les coûts

d’investissement sur les extrants du modèle tels que le coût de livraison du bioéthanol et la localisation des

site de production. Présentant un modèle mathématique à multi-étages optimisant l’ensemble des coûts sur la

totalité de la chaine de valeur de bioéthanol produit à partir de biomasse sur un horizon de planification donné,

les auteurs de (Huang et al., 2010) analysent l’effet de varier le coût de transport, la capacité de production, et

la disponibilité de la biomasse sur la conception de la chaine logistique et les coûts obtenus.

D’autre part, l’environnement d’affaires des compagnies de P&P de plus en plus instable et incertain, a suscité

l’intérêt d’un nombre de chercheurs quant à la planification par scénarios, afin d’évaluer l’impact qu’aurait

différentes tendances sur le potentiel d’un ensemble d’avenues de transformation. La planification par

scénarios étant une méthodologie permettant de concevoir un ensemble de scénarios plausibles basés sur

différentes tendances futures possibles et d’évaluer l’impact qu’aurait chaque scénario sur les options

stratégiques évaluées (Wright and Goodwin, 2009). Dans (Wetterlund et al., 2010), les auteurs proposent un

modèle mathématique déterminant le support politique financier requis pour rendre l’intégration de la

technologie de gazéification aux usines de P&P profitable. Le prix de l’énergie étant un facteur crucial dans la

23

profitabilité d’une telle technologie, différents scénarios futurs des prix d’énergie et des taxes sur émissions de

carbone sont considérés dans l’analyse. Les auteurs de (Szabó et al., 2009) introduisent un modèle global

pour l’industrie de P&P permettant d’analyser l’effet de différents scénarios futurs sur la demande en produits

finis, la consommation d’énergie et les émissions de carbone. Afin de concevoir les scénarios, différentes

tendances liées aux politiques environnementales et énergétiques sont modélisées. Un scénario « statut quo »

ainsi qu’un scénario à engagement climatique sont ainsi considérés comme cas de référence. En proposant

une approche par scénarios, les auteurs de (Mansoornejad et al., 2013) analysent différentes conceptions

logistiques intégrant deux processus de bioraffinage (thermochimique et biochimique) au sein d’une

compagnie de P&P. Différentes alternatives de réseaux logistiques allant des fournisseurs aux marchés sont

considérées. À l’issue du modèle mathématique développé afin de décider de l’alternative optimisant les

profits de l’entreprise, différents indicateurs de performance, incluant robustesse, flexibilité et profitabilité, sont

calculés pour chaque configuration de la bioraffinerie obtenue, et ce pour différents scénarios futurs

d’évolution des prix et des demandes sur les marchés.

Dans (Palma et al., 2010), une approche d’analyse par scénarios est proposée pour l’industrie forestière au

Canada dans le but d’amener une réflexion sur les stratégies à mettre en place pour permettre aux

compagnies forestières de se redresser. Afin d’évaluer potentiel de diverses options de changement, le retour

d’investissement pour un nombre de produits incluant les produits forestiers conventionnels ainsi qu’un

ensemble de bioproduits est estimé pour différents scénarios futurs affectant le secteur forestier Canadien.

Quatre scénarios sont proposés basés sur les tendances futures des prix de l’énergie, de carbone et de la

fibre forestière. Dans le premier scénario, la conjoncture économique difficile prendrait fin et les indices de prix

reviendraient graduellement aux niveaux de l’avant-crise. Dans le deuxième scénario, le contexte économique

global deviendrait de pus en plus difficile avec une multiplication des crises, amenant les indices des prix de

fibre et d’énergie à baisser. Dans le troisième scénario, un contexte de croissance économique engendrerait

une hausse de la demande et par conséquent des prix d’énergie et de fibre. Le quatrième scénario reposerait

sur l’émergence d’une économie globale de carbone entrainant une hausse des prix de carbone et

d’importantes pressions sociopolitiques quant à l’efficacité énergétique et les émissions de gaz à effet de

serre. L’intérêt de l’analyse est de mettre en exergue l’impact des incertitudes technologiques, économiques et

sociopolitiques sur le potentiel des options stratégiques proposées.

D’autres travaux de recherche proposent de développer des approches basées sur la programmation

stochastique, dans le but d’apporter des solutions robustes qui résisteraient aux incertitudes (voir (Higle, 2005)

pour une introduction à la programmation stochastique). Les auteurs de (Svensson and Berntsson, 2011)

présentent un modèle stochastique afin de décider des investissements futurs en bioénergie à intégrer au sein

des usines de P&P. Considérant un nombre de scénarios basés sur différentes tendances des marchés de

24

l’énergie, les solutions les plus robustes auraient la meilleure valeur actualisée nette espérée pour l’ensemble

des scénarios. Pour chaque scénario, les tendances affectant les marchés de l’énergie auraient différents

impacts sur le coût de développement des technologies analysées. Dans (Hytönen and Stuart, 2010), une

approche basée sur la simulation Monte Carlo est proposée afin d’intégrer les risques associés aux

investissements en biocarburants. En présentant une étude de cas portant sur une usine de production de

pâte Kraft, les incertitudes liées aux coûts des matières premières, aux coûts d’investissement en

biocarburants, et aux prix de marchés sont considérées. Les possibles développements futurs liés à ces

différents paramètres sont évalués afin d’identifier les technologies les plus prometteuses.

En s’intéressant à la problématique de conception des réseaux logistiques des biocarburants, les auteurs de

(Yueyue et al., 2012) présentent un modèle d’optimisation stochastique à multi-étages afin d’aboutir à une

conception optimisant les coûts d’investissement ainsi que les coûts d’opération, et ce en partant des sources

de matières premières jusqu’aux sites de demande d’énergie. En intégrant des décisions stratégiques

(localisation et capacité des sites de production et d’entreposage) et des décisions tactiques (flux des matières

premières et des produits finis), le but est de proposer une conception qui serait robuste face aux incertitudes

liées à la saisonnalité et à la variabilité des matières premières. Dans un travail amenant une nouvelle

approche d’optimisation des infrastructures intégrant les biocarburants (Huang and Pang, 2013), un modèle à

multi-objectifs basé sur la programmation stochastique est proposé pour évaluer la profitabilité des réseaux

logistiques intégrant les biocarburants ainsi que leur résilience face aux hasards naturels. Pour mesurer la

résilience d’une conception, quatre aspects sont à considérer : la robustesse, la rapidité, la redondance et la

créativité.

La revue de littérature exposée ci-dessus montre la diversité des avenues de transformation proposées au

secteur de P&P et des approches utilisées afin d’analyser les incertitudes liées à de telles transformations. En

fait, tandis qu’un nombre d’études plaident en faveur d’une transition vers un modèle d’affaires basé sur la

BRFI ((Pätäri et al., 2011), (Feng et al., 2012)), d’autres proposent une restructuration de l’activité

conventionnelle de production de pâtes et papiers, en passant par une modernisation des processus

conventionnels pour les rendre plus compétitifs ((Ministère des Finances and MERN 2000)), ou encore par

une innovation au niveau de l’offre de produits de pâtes et papiers en s’adaptant aux nouvelles tendances de

marchés ((Frandina et al., 2008)). D’autres travaux avancent que plusieurs options stratégiques pourraient

être considérées pour les compagnies de P&P allant de simples mesures d’efficacité énergétique jusqu’aux

stratégies de collaboration et à la diversification de la plateforme de produits ((Marinova et al., 2010)). Pour

tenir compte des incertitudes associées à ces différentes stratégies de transformation, plusieurs approches

sont proposées; allant des analyses de sensibilité ((de Wit et al., 2010), (Ekşioğlu et al., 2009), (Huang et al.,

2010)), en passant par la planification par scénarios ((Wright and Goodwin, 2009), (Wetterlund et al., 2010),

25

(Szabó et al., 2009), (Palma et al., 2010)), jusqu’à la programmation stochastique et l’optimisation robuste

((Svensson and Berntsson, 2011), (Hytönen and Stuart, 2010), (Yueyue et al., 2012), (Huang and Pang,

2013)).

Néanmoins, cette revue révèle un manque d’approches analysant explicitement plusieurs options stratégiques

tout en considérant les incertitudes qui y sont liées. Souvent, les travaux effectués se limitent à analyser une

seule option de transformation, telle que l’intégration de biocarburants ((de Wit et al., 2010), (Ekşioğlu et al.,

2009), (Huang et al., 2010), (Yueyue et al., 2012), (Huang and Pang, 2013)), ou encore de la gazéification de

biomasse (Wetterlund et al., 2010).

D’autre part, les études qui présentent des approches évaluant plusieurs stratégies de transformation en

considérant différents scénarios futurs de l’évolution de l’environnement d’affaires du secteur de P&P,

proposent des scénarios basés principalement sur l’évolution des prix d’énergie et de carbone sur les marchés

((Szabó et al., 2009), (Palma et al., 2010)).

Par ailleurs, la planification par scénarios serait un puissant outil au service des décideurs au sein du secteur

de P&P pour dresser un nombre d’images plausibles des possibles évolutions technologiques, économiques,

et sociopolitiques qui pourraient avoir lieu dans le secteur dans les années à venir. Ainsi, les approches

décisionnelles visant à identifier les stratégies de transformation les plus viables devraient intégrer une

analyse de scénarios approfondie pour bien conceptualiser les incertitudes associées à ces évolutions.

Dès lors, notre troisième contribution consiste à proposer une approche d’aide à la décision permettant

d’évaluer différentes options de transformations stratégiques, en considérant différents scénarios futurs

d’évolution de l’environnement d’affaires des compagnies de P&P. Outre la proposition d’une méthodologie

conceptuelle permettant d’identifier les stratégies potentielles qui s’offrent au secteur et de définir les

différentes tendances qui affecteraient le secteur dans les années à venir, nous présentons un modèle

mathématique permettant de tester la robustesse de ces différentes options face aux incertitudes qui y sont

associées.

Le but est de fournir aux compagnies de P&P un outil d’aide à la décision permettant de transformer les

opportunités qui s’offrent au secteur en des stratégies de transformation qui sauraient résister aux

nombreuses incertitudes technologiques, économiques, et sociopolitiques qui affecteraient sérieusement la

profitabilité de telles stratégies dans les prochaines années.

26

1.4 Méthodologie scientifique et contributions

Afin d’atteindre les objectifs de cette thèse, définis à l’issue de la présentation des différentes problématiques

(voir section 1.2.), nous proposons trois contributions dans le but d’amener de nouvelles approches d’aide à la

décision pour supporter la transformation des compagnies de pâtes et papiers.

Pour produire ces contributions, la méthodologie scientifique poursuivie est comme suit :

Formuler la problématique de recherche du travail.

Recenser les principaux travaux ayant proposé des éléments de réponses aux différents concepts

présentés dans la problématique de recherche.

Dégager les limites des travaux revus afin de délimiter un objectif spécifique de la contribution.

Présenter la méthodologie proposée pour répondre à l’objectif défini.

Cibler un cas d’étude permettant de tester la méthodologie proposée.

Présenter et développer une discussion autour des résultats obtenus.

Présenter une synthèse de l’apport ainsi que les limites de la méthodologie proposée, permettant de

proposer des pistes futures de recherche.

Dans ce qui suit, chacune des contributions proposées est brièvement expliquée.

Contribution 1 : « Une approche de décision à multi-niveaux pour la conception du modèle d’affaires de la

bioraffinerie forestière intégrée pour le cas des compagnies de pâtes et papiers ». Cette contribution propose

une méthodologie à six étapes pour supporter les compagnies de pâtes et papiers dans leur transformation de

modèles d’affaires :

Analyser les faiblesses ainsi que les forces du secteur de pâtes et papiers au Canada.

Identifier les opportunités technologiques, économiques et sociopolitiques se présentant aux

compagnies de pâtes et papiers.

Définir une vision stratégique présentant la direction générale dans laquelle la compagnie s’en va.

Identifier une stratégie de la compagnie traduisant la vision globale en des objectifs à long-terme.

27

Concevoir un modèle d’affaires permettant d’implémenter la stratégie définie à travers la proposition

de valeur, l’interface clients, la gestion des infrastructures et les aspects financiers.

Valider la conception du modèle d’affaires en proposant des outils d’analyse quantitatifs et qualitatifs.

Contribution 2 : « Un cadre de travail basé sur un modèle mathématique pour évaluer le potentiel technico-

économique d’intégrer la bioénergie dans les usines de pâtes et papiers ». Cette contribution apporte une

méthodologie à quatre étapes pour identifier les investissements en bioénergie les plus prometteurs à intégrer

dans les usines de pâtes et papiers dans les années à venir:

Présélection d’un ensemble de configurations potentielles incluant les matières premières, les

technologies et les produits qui seraient adaptés au secteur Canadien de pâtes et papiers.

Construction d’une base de données pertinentes, à partir d’un nombre de rapports et d’études, et ce

pour collecter des données réalistes concernant la disponibilité de la biomasse, les coûts

d’investissement ainsi que les coûts d’opération des différentes technologies considérées, prix de

marchés, etc.

Développement d’un modèle mathématique à nombres entiers mixtes afin de maximiser la valeur

financière estimée des investissements en bioénergie à intégrer dans une usine de pâtes et papiers

sur un horizon de vingt ans.

Identification d’une feuille de route des investissements les plus prometteurs en bioénergie à intégrer

durant les vingt prochaines années, pour l’ensemble des données considérées. La feuille de route

renseigne sur le timing des investissements et d’éventuels ajouts de capacité de production pour les

technologies retenues.

Contribution 3 : « Une approche de modélisation par scénarios pour identifier des stratégies de

transformation robustes pour le cas des compagnies de pâtes et papiers ». Cette contribution présente une

méthodologie à quatre étapes dans le but d’identifier les avenues de transformation les plus prometteuses

pour les compagnies de pâtes et papiers qui sauraient résister aux incertitudes affectant l’environnement

d’affaires du secteur dans les années à venir.

Identifier un nombre de stratégies de transformation potentielles pour les compagnies de pâtes et

papiers au Canada.

28

Concevoir un nombre de scénarios futurs plausibles de l’environnement d’affaires des compagnies

de pâtes et papiers, en se basant sur les différentes évolutions des tendances économiques,

technologiques et sociopolitiques.

Développer un modèle mathématique permettant d’évaluer la valeur financière espérée de chacune

des stratégies sous les différents scénarios définis.

Proposer un nombre de recommandations quant aux stratégies de transformation les plus robustes

pour le secteur de pâtes et papiers au Canada.

1.5 Conclusion

À travers ce chapitre, nous avons introduit en détail la problématique générale traitée durant cette thèse. Afin

de traiter les différentes facettes de la problématique, trois contributions ont été clairement identifiées. Une

revue de littérature a été ensuite présentée relativement aux principaux travaux concernant la conception des

modèles d’affaires, l’analyse de la profitabilité des bioraffineries forestières intégrées, et l’évaluation des

stratégies de transformation en considérant un environnement d’affaires incertain du secteur de P&P. À l’issue

de chaque partie de la revue de littérature, les gaps entre ce qui a été déjà proposé et les objectifs

correspondants fixés pour cette thèse ont été clairement identifiés. Finalement, les trois contributions

proposées pour pallier aux gaps révélés, ainsi que les méthodologies qui y sont utilisées ont été exposées.

Les trois prochains chapitres représentent les trois contributions de cette thèse présentées sous forme

d’articles scientifiques.

29

Chapitre 2 Une approche de décision à multi-niveaux pour la conception du modèle d’affaires de la bioraffinerie forestière intégrée pour le cas des compagnies de pâtes et papiers

Cet article, intitulé « A multi-level decisional approach to design Integrated Forest Biorefinery business model

for pulp and paper companies », a pour auteurs Mahdi Machani, Mustapha Nourelfath et Sophie D’Amours. Il

a été soumis au journal « Long Range Planning » en Décembre 2013 (Facteur d’impact évalué à 3,667 en

2012). La version présentée dans cette thèse est identique à la version soumise.

31

Résumé

Affaiblies par le déclin des marchés conventionnels et la compétition à faible coût, les compagnies forestières

au Canada, en particulier les compagnies de pâtes et papiers, sont plus que jamais en manque de

compétitivité. Transformer le modèle d'affaires afin de réinventer la logique d'affaires de la compagnie est

considéré en tant qu'avenue prometteuse permettant aux compagnies de pâtes et papiers d'assurer leur

pérennité. Une telle transformation devrait être supportée par une vision définissant la direction générale de la

compagnie, une stratégie fixant les objectifs à long terme, ainsi qu'un plan d'affaires soutenant

l'implémentation du modèle d'affaires tout au long du réseau de création de valeur.

Une approche d'aide à la décision multi-niveaux est ainsi développée permettant aux compagnies de pâtes et

papiers de réinventer leurs modèles d'affaires. La bioraffinerie forestière intégrée, basée sur l'intégration de

bioproduits, est présentée comme modèle d'affaire prometteur permettant aux compagnies de pâtes et papiers

de surmonter la crise et s'adapter en continu aux mutations majeures affectant leur environnement d'affaires.

Afin d'aligner les différents niveaux de décision à une telle transition, la conception d'un nouveau modèle

d'affaires est intégré à une approche globale incluant la définition d'une vision commune, d'une stratégie, d'un

modèle d'affaires ainsi que d'un plan d'affaires. L'objectif est de proposer un cadre d'aide à la décision aux

preneurs de décisions au sein du secteur de pâtes et papiers, leur permettant d'appréhender les opportunités

et les défis associés à la transformation de leurs modèles d'affaires, et de passer à un modèle d'affaires

compétitif, tout en alignant les différents niveaux de décisions à cette transition.

32

Abstract

Faced with increasingly declining conventional markets and low-cost competition, Canadian forest companies,

particularly pulp and paper companies, are struggling to maintain their competitiveness, The design of a new

business model, reinventing the way the company does business, is seen as one of the most promising

avenues to provide a sustainable future to pulp and paper companies. Transforming the business model

should be supported by a vision outlining the general direction of the company, a clear strategy defining a set

of long-term objectives, and a business plan supporting the implementation of the business model through the

company value creation network.

Therefore, a multi-level decisional approach has been developed to design a new business model for pulp and

paper companies. The Integrated Forest Biorefinery business model, based on the integration of bioproducts

within the company product portfolio, has been suggested as an effective pathway to help these companies

overcome the crisis and continuously adapt to the major shifts affecting their business environment.

In order to align all the decision levels with such a transformation, the design of a new business model is

integrated with a holistic approach encompassing the definition of a common vision, a corporate strategy, the

business model itself, and a business plan. Our aim is to propose a decision-support framework for decision

makers in pulp and paper companies, allowing them to understand the opportunities and the challenges

associated with the transformation of the business model and move towards a competitive business while

aligning all the decision levels.

33

2.1 Introduction

The Canadian forest industry is confronted with serious challenges due to emerging low-cost competition, the

rising Canadian dollar and the declining demand for several conventional forest products (NRC, 2012). In

particular, pulp and paper (P&P) companies are experiencing a stalemate situation because of increasingly

saturated P&P markets and inefficient cost-structure, amplified by global competition and higher energy costs

(Marinova et al., 2010). More than ever, P&P companies are then seeking for viable solutions to overcome the

crisis and adapt to the major shifts affecting their competiveness.

Over the last decades, the companies that have successfully thrived in spite of successive crises in several

sectors, have fully grasped the hidden opportunities (Collins and Hansen, 2011). Forest sector stakeholders

should then identify and seize new opportunities to overcome the crisis and achieve a sustainable competitive

advantage. As for the Canadian forest industry, profiting from the growing global bioeconomy, based on

innovative and high value-added bioproducts, is conceived as one of the most promising opportunities for

forest companies to diversify their markets and hedge against conventional demand uncertainties

(Government of Canada, 2007). Bioproducts are high-value products extracted from several biomass types,

including forest and agriculture biomass, industrial residuals and urban waste residues. Bioproducts

encompass a variety of products including bioenergy (such as electricity, heat, and biofuels), biochemicals

(such as adhesives, pharmaceutical products and essential oils), and biocomposites (such as biopolymers and

nanocellulose) (Brunette, 2011). In fact, several Canadian forest companies, mainly P&P companies, have

already undertaken a range of efforts towards integrating bioproducts within their product portfolio. However,

the bioproducts considered are essentially bioenergy produced to meet internal energy needs (Bradley, 2010)

and there are still huge bioproduct-related market opportunities which are already largely unrealized (Sparling

et al., 2011). Moreover, when Canadian companies have sought to invest in bioproducts, they have mainly

focused on cost-saving strategies requiring little change to products and processes. Among the number of

firms producing bioproducts in Canada, bioenergy arrives in first position, while contributing only 3,5% to all

bioproduct gross revenues. Those companies investing in bioproducts have considered mainly Bioethanol,

which contributes 68% of total bioindustry revenues (Sparling et al., 2011). Yet, an increasing number of

practitioners claim that low-innovation strategies based only on operational cost restructuring and energy

efficiency would not be sufficient for struggling companies to achieve a long-term competitive advantage.

Value innovation, based on creating and delivering an innovative value proposition, would then be crucial for

those companies seeking sustainable transformation (Kim and Mauborgne, 2005b).

For Canadian forest companies, transforming their business models is seen as one of the most effective ways

to innovate their value, leading to a competitive and sustainable business ((CIFQ, 2010), (Marinova et al.,

2010), (Johnson et al., 2008), (Wising and Stuart, 2006)). Nevertheless, value innovation is only achieved

34

when all components of the value chains are aligned, including the buyers, the company itself and the

suppliers (Kim and Mauborgne, 2005b). As business models describe the relationship the company builds with

its different partners, involving suppliers and customers, throughout the value chain, designing a well-defined

business model would be vital for decision makers to successfully deliver that value innovation (Teece, 2010).

Furthermore, when the issues related to the transformation and implementation of business model are treated,

they are usually associated with a vision that defines the general direction of a company and a strategy to

achieve the sustainable competitive advantage ensuring that future vision ((CIFQ, 2010), (Government of

Canada, 2012a), (Smith et al., 2010)). Thus, transforming the business model needs to be integrated into a

holistic methodology involving the reinvention of the vision, the strategy as well as the issues related to the

implementation of the business model.

However, struggling companies, while generally convinced that value innovation is vital to thrive, lack design

tools to achieve that innovation (Kim and Mauborgne, 1999a). Therefore, there is a need to develop

approaches to guide these companies throughout the value innovation processes, leading to a competitive

business model. While all the decision levels, from the top strategic level to the value network level, are

aligned with that innovation. Regarding literature dealing with forest industry including P&P companies, all the

researches emphasising the integrated forest biorefinery business model, have assumed the viability of the

associated business model and have ignored business model design matters.

Our contribution is then to develop a decision-support approach helping Canadian P&P companies transform

their business models, while integrating all the strategic decision processes including vision, strategy, business

model and design of the value creation network. The proposed approach aims to allow companies to well

assess their current competitive position, identify the potential opportunities of value innovation, adapt the

different strategic decisional levels to maximise the defined value innovation, design a new business model

optimising the creation and delivery of that new value, and develop conceptual tools to validate and implement

the designed business model. The objective is to design a holistic approach that helps those companies

continually adapt to the economic, socio-political and technological challenges they are facing, in order to react

to the shifts occurring within their competitive environment as quickly as possible.

The remainder of the paper is organised as follows. In Section 2.2, we review the literature dealing with the

development of strategic decision support methodologies. In Section 2.3, we present a multi-level decisional

approach to design new business models in the case of the Canadian P&P companies. In conclusion, the

obtained results are discussed and future research avenues are presented.

35

2.2 Literature review

In this section, we review the contributions that have focused on developing methodologies to help companies

rethink a range of strategic decisions involving several decision levels from strategic vision to value creation

network in order to achieve a sustainable business. To well assess the literature dealing with these questions,

we have classified the reviewed contributions according to the following issues addressed: competitive position

analysing, identifying the opportunities to grasp, vision definition, strategy formulation, business model design,

business model validation, and business model implementation. When analysing the contributions proposing

conceptual frameworks and practical methodologies to rethink companies’ business models, the elements

presented above are developed or even mentioned on a recurring basis. We have then organised our literature

review around works focusing on these key elements. In Table 2.1, we present a survey of the main

contributions according to that classification.

When reviewing the literature, one should note the growing emphasis on proposing strategic decision support

approaches to allow companies to adapt to the major shifts they are facing. From presenting studies to

understand and manage the current challenges and identify the opportunities, to developing frameworks

evaluating the profitability of several transformation options, and through proposing a range of tools to help

stakeholders align the different decision levels with the planned transformation, theoreticians and practitioners

are increasingly addressing strategic issues about the most viable pathways to achieve a sustainable

business.

A number of reports have assessed the current competitive position of forest companies by pointing to their

strengths and weaknesses, and highlighting the opportunities to grasp, in order to identify successful ways of

change ((FPAC, 2010), (Wising and Stuart, 2006), (J. Benjamin et al., 2009), (Martel et al., 2005), (Towers et

al., 2007)). In addition, national task forces addressing the challenges of the forest industry have resulted in a

number of key assessments and a set of recommendations useful for identifying a new common vision for the

forest industry as well as a set of potential high value strategies. ((MRNF, 2012), (FPAC, 2011), (Biomass

Research and Development Technical Advisory Committee, 2007), (MRNF, 2008)). Other contributions have

focused on proposing a set of transformation strategies to allow forest companies to seize the opportunities

offered and achieve a competitive advantage ((Stuart, 2006), (Pätäri et al., 2011), (FPInnovations and MRNF,

2009)).

Business model, a conceptual tool to depict the way the company would do business (Osterwalder and

Pigneur, 2010), has been increasingly attracting the interest of researchers and practitioners as a powerful

decision-support approach to optimally manage how the company would create, deliver and capture value

while interacting with its different partners. However, all the works we have found, dealing with assessing and

36

designing tools to reinvent business models, mainly belong to the strategy and management literature ((Caisse

and Montreuil, 2007), (Osterwalder and Pigneur, 2010), (Magretta, 2002), (Johnson et al., 2008), (Osterwalder

et al., 2005), (Kim and Mauborgne, 1999a)). To our knowledge, there is no literature where business model

design methodologies are applied to economic issues related to forest industry. Such finding is confirmed in

(Teece, 2010), where the author argues that when it comes to economic literature, business models are

frequently mentioned but rarely analysed. In fact, a major part of the reviewed works dealing with integrated

forest biorefineries have mentioned the importance of business models and the need to design new business

models for the forest industry, but none of these works have developed clear approaches to design business

models. These contributions have focused on testing the profitability of such business models and proposing

decision-support tools to support their implementation. In fact, a few researches have suggested quantitative

approaches to assess and validate the profitability of integrated forest biorefinery business models, while

focusing on optimising a number of decisions about supply chain design including the choice of feedstock,

technologies, products, processes and plant locations, in order to maximise the financial value of bioproduct

integration ((Huang et al., 2009), (Mansoornejad et al., 2010), (Feng et al., 2012), (Martel et al., 2005), (Tay et

al., 2011)). Nevertheless, none of these works have tackled business model design issues.

Regarding the business model implementation phase, it has recently attracted a number of researchers. The

concept of business plan, a step in which the business model design is translated into concrete elements over

the supply chain, has been developed in ((Osterwalder and Pigneur, 2010), (Osterwalder et al., 2005)); As for

IFBR-related works, research efforts have been concentrated on developing strategic approaches to support

the implementation of IFBR business models((Stuart, 2006), (Chambost et al., 2009),(Moshkelani et al., 2013))

without, however, pointing out the link between the business model and its translation over the value creation

network involving the organisation structure and the processes.

The literature review raises the need for global approaches to transform business models, encompassing the

different strategic decision levels from competitive position analysis to business model implementation. The

contributions focusing on vision and strategy definition have just highlighted the importance of business model

innovation without providing tools to manage such an issue. Those treating business model implementation

strategies and efficiency-assessing approaches have assumed the effectiveness of the business model

considered, while ignoring design concerns. As for researches proposing decision-support methodologies to

help transform P&P companies into IFBRs, efforts have emphasised assessing the effectiveness of such a

transformation without discussing the design process issues of the associated business models.

This brings us to the main contribution of this paper: developing a holistic approach to support the

transformation of struggling forest companies, particularly the P&P companies, into competitive IFBRs, while

37

involving all the decision levels from the top strategic to the implementation level. We provide a set of tools to

design, validate and implement a new business model for P&P companies, supported by a global vision

underlining the future direction of the company and a clear strategy formulating the long-term objectives arising

from the vision and ensuring that the business model design would achieve a sustainable competitive

advantage. Our primary goal is to offer a decision-support methodology for decision-makers, helping them

assess the company’s competitive position, identify the potential opportunities to seize, transform the business

model to create an innovative value proposition from these opportunities, propose a set of tools to validate the

design and translate it into a business plan, and continually reiterate the whole process to adapt the company

to an increasingly changing environment.

38

Literature Competitive position analysing

Opportunities to grasp Vision definition Strategy

definition Business model

design

Business model

validation

Business model Implementation

X X (Martel et al.,

2005) X X

(Caisse and Montreuil, 2007) X

(Osterwalder et al., 2005) X X X

(Osterwalder and Pigneur, 2010) X X X

(Magretta, 2002) X X X (Chambost et al.,

2009) X X

(Moshkelani et al., 2013)

X X

(Biomass Research and Development

Technical Advisory

Committee, 2007)

X X

(FPAC, 2010) X X

(FPAC, 2011) X X X

(Stuart, 2006) X X X X (Wising and Stuart, 2006)

X X

(Towers et al., 2007) X

(FPInnovations and MRNF, 2009)

X X X

(MRNF, 2008) X X X X

(MRNF, 2012) X X X X

(Pätäri et al., 2011) X X X

39

(Johnson et al., 2008) X

(Kim and Mauborgne,

1999a) X

(Tay et al., 2011) X

(Feng et al., 2012) X (Huang et al.,

2009) X

(Mansoornejad et al., 2010) X

Tableau 2.1 Literature review on strategic decision support methodologies

40

2.3 The approach

The approach we present in this section (Figure 2.1), is a decision-support framework aiming to help

stakeholders transform their business models while considering an integrated methodology involving all the

decisional levels dealing with the design of business models. The objective of the developed approach is to

support the transformation of struggling companies into competitive companies that continually adapt to the

substantial shifts occurring within their competitive environment.

The first step of the approach is to analyse the current state of the company business environment by

assessing the existing strengths and weaknesses characterising the sector. After that, the second step is to

identify the opportunities to seize, by assessing a number of socio-political, economic, technological and

market-related incentives. These first two steps are essential to review the competitive position of a given

company in depth and underline the promising transformation avenues, thus helping the decision-makers

identify the successful pathways of change. The first step to achieve that sustainable transformation is to

define a global vision for the company highlighting its general direction and giving a snapshot of the projected

future image. The governmental vision and the forest industry stakeholders’ vision are crucial parameters to

consider when defining the company vision. Once a vision has been stated, a strategy should be expressed to

translate the vision into a set of long-term objectives and achieve a competitive advantage. The strategies of

the considered industry’s leaders should be reviewed to identify the best strategic practices to implement. To

underpin the implementation of the settled strategy, a new business model should be designed to optimise the

logic the company would create, deliver and to capture value. The business model would be an efficient way to

optimally manage the value proposition, the customer interface, the network configuration, as well as the

financial issues. The business model design would allow the company to thrive despite future turbulences

affecting its business environment. It should then be aligned with several driving forces, including

technological, economic, socio-political and market forces, affecting the competitiveness of the company. The

business model would support the implementation of the corporate strategy to successfully cope with these

future changes.

Before implementing the business model throughout the company value chain, a validation step is critical to

test the viability of the design without directly incurring the risks associated with implementation. We propose a

set of quantitative and qualitative analysis tools to help stakeholders simulate the efficiency of the designed

business model. At the end of this validation step, the design is validated if the analysis results meet the

decision makers’ requirements. Otherwise, the business model design should be reviewed. Even the strategy

and the vision could be revised, in order to align the business model with the design requirements.

41

After being implemented, the business model should be continuously adapted to future changes occurring

within the industry. Such a “closed-loop” process would be essential to allow the company to achieve a

sustainable value innovation that meets an increasingly changing business environment.

In this paper, the developed approach is applied to the case of the Canadian forest industry, particularly the

P&P sector. Our objective is to suggest a strategic decision-support methodology to help Canadian P&P

companies move towards a sustainable business.

42

Figure 2.1 Multi-level decisional approach to design business models

43

2.3.1 Current state analysis

The current state analysis of the Canadian forest industry, the P&P sector in particular, is an essential step

towards the transformation of the sector. During this step, we have assessed the weaknesses as well as the

strengths of the forest industry.

In Table 2.2, we summarise the two components of the conducted analysis.

Weaknesses Strengths

-Structural demand decline in some conventional forest products, such as newsprint and printing paper, due to substitution products (MRNF, 2012). - Cyclical demand decline in almost all conventional forest products including lumber, pulp and paper, due to a rising Canadian dollar, low-cost competition and high operating costs (FPInnovations, 2011). - Low capital returns for P&P sector, driving away investments (CIFQ, 2010). - Low P&P margin profits due to overcapacity and operational inefficiency (NRC, 2012). - Substantial employment decline (more than 30% in the last 10 years), principally in the P&P sector (NRC, 2012).

- High energy consumption for P&P sector (30% of the Canadian industry energy consumption), representing 25% of operating costs (Marinova et al., 2010). - High GHG emissions, representing 15% of total Canadian industry emissions (Martin et al., 2009). - The P&P sector is the largest water-consuming industry (Martin et al., 2009). - An obsolete business model due to low-value product portfolio and inefficient cost structure (CIFQ, 2010).

- Vast sustainably managed forests: Quebec is world leader regarding sustainable forest management practices, having 75% of its forests certified (MRNF, 2012). - High-quality universities and research centres providing innovation and technology transfer (MRNF, 2012). - Substantial amounts of available biomass which could be converted into high value products (Government of Canada, 2012b). - Highly-qualified labour (Government of Canada, 2012b). - Almost all Canadian P&P companies already convert a set of biomass sources into cogenerated electricity and steam, having then the adapted supply chain to use biomass (Stuart, 2006). -Canadian P&P companies have been reinventing their business models to adapt to ulterior changes, making them ready to transform again their way of doing business (MRNF, 2012).

Tableau 2.2 Strengths and weaknesses of the Canadian P&P sector

2.3.2 Opportunity spotting

Canadian forest companies, particularly the P&P companies, are confronted by serious challenges regarding

their competitiveness. As shown above, in Table 2.2, these challenges hide a number of weaknesses and

strengths that companies should manage to achieve a sustainable transformation.

Therefore, there is a need to transform the way the company does business, in order to further enhance the

strengths and eliminate the weaknesses. In fact, a major part of forest industry executives, mainly in mature

markets like in Canada, believe there is a need for fundamental change in the sector to remain competitive

(PwC, 2010a). Among the possible avenues for change, diversifying the product portfolio by integrating

44

bioproducts is considered as a promising opportunity to create new revenue sources and access a set of

growing markets ((MRNF, 2012), (FPAC, 2010))

To well assess the bioproduct-related opportunities for Canadian P&P companies, we have grouped them into

socio-political opportunities, technological opportunities, and economic opportunities.

2.3.2.1 Socio-political opportunities The forest industry contributes 12% to the Canadian manufacturing Gross Domestic Product (GDP) and

employs directly and indirectly nearly 600.000 persons (FPAC, 2012). Because of their considerable weight in

the Canadian economy, the Canadian government supports forest companies both financially and politically

and is helping them achieve a long-term competitive advantage. Governmental support actively promotes the

transformation of the forest sector to integrate bioproducts. A set of programs, such as Investments in Forest

Industry Transformation, Forest Innovation Program, and Pulp and Paper Green Transformation have been

launched to support the integration of new technologies to enhance the energy efficiency of the sector,

produce a set of high-value bioproducts, and access new markets ((Bradley, 2009), (Canadian Forest Service,

NRC, 2012)).

At the social level, investing in bioproducts represents a great opportunity for forest companies to enhance

their environmental image, as the forest industry is still perceived as a poor environmental performer (CIFQ,

2010). In fact, an increasing part of the community requires that forest companies further consider the

environment in their core strategies, in order to reduce their carbon footprint and offer eco-responsible

products. Bioproducts would then be a viable solution to address these new social challenges and transform

them into a source of competitive advantage.

2.3.2.2 Technological opportunities Bioproducts, ranging from cogenerated electricity, heat and steam to biochemicals, biofuels and biomaterials,

offer a huge opportunity for the Canadian forest industry to overcome its stalemate situation and achieve long-

term competitiveness (FPAC, 2010). In fact, integrating bioproducts within forest companies would be an

effective way to maximise economic results and employability for both conventional and new activities (FPAC,

2011).

In particular, bioenergy technologies to produce electricity, heat and biofuels would allow P&P companies to

meet their energy needs and diversify their revenue sources (FPAC, 2010).The viability of a number of these

technologies has already been proven, presenting an enormous growth potential in the coming years due to

governmental incentives and increasing demand (de Wit et al., 2010). Therefore, P&P companies should

45

consider this technological advent of bioproduct technologies as a promising way to remedy the structural

decline of an increasing number of conventional products.

2.3.2.3 Economic and market-related opportunities Bioproducts present a substantial opportunity for Canadian P&P companies to address issues related to

conventional saturated markets, These products offer a set of new growing markets that allow maximising the

value extracted from fibre (FPAC, 2011). Besides, there would be an increasing demand globally for

bioproducts, creating a competitive bioeconomy in which Canadian P&P companies should seize the

opportunities offered to maximise their share-markets (FPAC, 2010).

Integrating bioproducts within P&P companies would make it possible for them to diversify their revenue

sources by offering high-profit margin products and reduce their dependency on fossil energy. Furthermore,

government policies of financial support including carbon credits, incentives, and tax exemptions (Bradley,

2009) would offer substantial economic opportunities for P&P companies.

2.3.3 The need for change

The current state analysis has revealed a set of points of weakness as well as strengths for the P&P sector.

Assessing them creates a real motivation for fundamental change to allow P&P companies to thrive within the

crisis. As we have seen, there are a number of opportunities that P&P sector stakeholders should spot in order

to ensure not only short-term survival solutions, but also a durable competitive advantage through creating an

innovative value. In (Kim and Mauborgne, 2005b), an analytical tool has been developed, called “the four

action framework” aiming to explore how to maximise that value innovation. The proposed tool is about

assessing the factors affecting the company’s business environment and answering four key questions to help

the company survive the crisis and create an innovative value: Which factors should be eliminated? Which

factors should be reduced? Which factors should be raised? And which factors should be created?

By adapting this tool to the P&P sector, we exploit the results of the “current state analysis” and “opportunity

spotting” to respond to the four questions presented above, in order to ensure a competitive business (Figure

2.2).

2.3.3.1 Reduce A P&P company, aiming to be competitive, could reduce its mass-market strategy offering a few varieties of

substantial volume commodities to limited markets. Besides, it could reduce its low-margin-product offer to

current mature markets due to competition. The crowded current market space of P&P products forces

companies that are seeking to survive to further lower its cost structure and reduce its energy consumption, in

order to ensure an increasingly tight margin.

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2.3.3.2 Eliminate In order to be better adapt to the structural changes affecting the sector, the P&P company could consider

eliminating its non-profitable assets and get rid of its conventional manufacturing-centric culture which is based

on producing a variety of basic P&P products and selling them as commodities regardless the changes in

customers’ needs (Thorp, 2005).

2.3.3.3 Raise The P&P mill could increase its high-margin profit product offer to meet the customer need changes. The by-

products generated when producing P&P products, such as black liquor and paper sludge, could be further

valued by converting them to higher-value products. In addition, the P&P company should be agile regarding

the short-term shifts all along the supply chain by developing a flexible organisational structure to respond

efficiently to these changes. On the other hand, in order to face growing environmental requirements, the

company could strengthen its environmental implication by increasing its energy self-sufficiency and further

integrating the environmental issues, such as managing greenhouse gas emissions and greening the supply

chain.

2.3.3.4 Create To seize the technological and economic opportunities associated with bioproducts, the P&P company could

build a number of partnerships from outside the P&P sector (Chambost et al., 2009). These partners could be

vital to gain access to new markets for P&P companies such as chemical markets and energy markets, and to

take advantage of the expertise of technological partners to implement and distribute a set of high-value

bioenergy products. In fact, diversifying the product portfolio by adding bioenergy products would be beneficial

for the company to overcome the declining demand of conventional P&P products.

These new high-value products could serve a number of niche markets, which would overtake the mass

market of low-profit margin conventional P&P products. Accessing these niche markets would require a

fundamental shift in the way of dealing with customers, by moving from a manufacturing-centric thinking

towards a demand-driven culture (Thorp, 2005), where the emphasis is on meeting specific-need customers

and managing company resources to effectively respond to demand requirements.

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Figure 2.2 Perspectives for change using the four-action framework

By looking beyond the boundaries of the P&P sector, a P&P company aims to seize new growth opportunities

and create innovative value in order to move from saturated P&P mass markets to a set of growing niche

markets. When assessing the four required actions to achieve this value innovation, it is clear that P&P

companies should undergo a fundamental change from the top-strategic decision level to the operational value

network level. Furthermore, as this transformation would seriously affect the logic the company is creating and

delivering value, transforming the business model would be a vital step towards achieving that change.

That is why it would be crucial that the design process of the new business model should be integrated into a

holistic approach that involves all decisional levels starting by expressing the global vision, then working down

to the corporate strategy followed by depicting the principal components of the business model, and finally

outlining the most relevant business model implementation mechanisms.

Throughout the following subsections, we present in detail the different decision-level layers of the developed

approach.

2.3.4 Strategic vision

The strategic vision represents a snapshot of the company’s future serving as a guiding blueprint, which would

be easy to communicate to the customers, the shareholders and the employees (Kotter, 1995). Mainly, the

mission of defining a general vision for the company is to align all the incurred transformational actions in the

same direction.

For the forest industry, defining a strategic vision would be essential to be able to transform existing

opportunities into a sustainable competitive advantage. In the case of Canadian forest companies in particular,

48

a long-term vision should be developed rather than just remain limited to a number of short-term objectives

(Chambost et al., 2009). In fact, according to many academics and forest industry stakeholders, the stalemate

situation the forest industry is currently facing, could have been avoided if the forest companies had adapted

their vision the changing competitive environment in time (Senate Committees, 2011). The company’s

developed vision should then be well aligned with the vision of all actors dealing with the forest industry,

including the government and the major forest industry stakeholders.

As regards the government, a Canadian forest company vision should be aligned with the government’s

general direction in order to take advantage of supportive governmental policies as well as financial incentives.

In recent years, the Canadian government has been strongly supporting forest industry transformation by

providing several financial incentive programs and innovative regulations to reinvent the forest industry and

improve its environmental performance (Canadian Forest Service, NRC, 2012).

In Table 2.3, we present a number of federal programs undertaken for the forest industry during recent years.

Program Objectives

Aboriginal Forestry Initiative

Increasing the participation of aboriginal people in the Canadian economy and improving their economic outcomes

Expanding Market Opportunities Program Increasing market opportunities for the Canadian forest industry in both offshore and North American markets

Forest Communities Program Encouraging community-level partnerships to take advantage of emerging forest opportunities

Forest Innovation Program Supporting Research and Development in forest industry

Investments in Forest Industry Transformation Program

Supporting the Canadian forest companies in becoming more economically competitive and environmentally sustainable

Pulp and Paper Green Transformation Program Improving the environmental performance of the Canadian P&P sector

Tableau 2.3 Federal programs to support the Canadian forest industry

The programs presented above reveal the strategic vision the federal government defines for the Canadian

forest industry: A competitive Canadian forest industry economically as well as environmentally, allowing an

optimal implication of the local communities and maximising both the economic and social outcomes of the

forest industry transformation.

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At the provincial level, a set of nine guidelines have been developed to help the Quebec forest industry

overcome the crisis (MRNF, 2008). These strategic orientations aim to reinvent the way the provincial

government manages the forest industry by prioritising sustainable development and creating a competitive

industry in harmony with its environment and community. The general directions described throughout that

governmental report uncover a long-term provincial vision that translates the guidelines’ objectives: An

adapted and profitable Quebec forest industry, while integrating innovation and environmental concerns in its

core strategy.

This vision has been clearly expressed in the Quebec governmental report presenting the Quebec strategy for

2012-2017 to transform the Quebec forest industry (MRNF, 2012), by defining the three major components of

the presented vision: diversified, innovating and adapting.

On the forest industry level, several actors are moving towards integrating a bio-industry where forest

companies would take full advantage of the new opportunities that present the substantial biomass resources

available in Canada. This transformation would involve a product diversification including bioenergy,

biochemicals and biomaterials, while adapting the conventional activities to the changing markets by producing

innovative and ecofriendly forest products (FPAC, 2011). The Biopathway project, a multi-partner project

involving the Forest Products Association of Canada (FPAC), FPInnovations, Natural Resources Canada

(NRC) and a number of industrial experts and academics, aiming to explore the existing possibilities for the

Canadian forest industry and to assess the opportunities to ensure its long-term competitiveness (FPAC,

2010), have shown the economic, social and environmental potential of integrating the bioproducts into the

forest industry. The Biopathway project represents a strategic roadmap for the Canadian forest industry to

overcome declining markets and ensure long-term competitiveness. The roadmap would support the shift of

the forest industry from an energy-dependent and traditional industry, serving saturated markets, to an

innovative and energy-efficient industry oriented toward growing worldwide growing markets.

Therefore, there is already a trend among the different forest industry stakeholders to establish a common

future vision: An innovative and ecological bioindustry based on the integration of new bioproducts within the

conventional forest product portfolio, which would optimally grasp the new opportunities associated with the

new global bioeconomy.

The strategic vision of a forest company should be aligned with the visions of the different forest industry

stakeholders and their partners. In the case of a Canadian P&P company, the developed vision should be in

harmony with the governmental vision at both the federal and the provincial levels, as well as with the forest

industry stakeholders’ vision. Besides, as outlined above in the developed framework (Figure 2.1), the

company vision must translate the existing technological, economic and socio-political opportunities into a

50

future blueprint aiming to transform these opportunities into sustainable competitive advantage (see Figure

2.3).

Thus, we define the vision for a Canadian P&P company, aiming to specify a general direction, as follows: An

environmentally and economically competitive company, taking full advantage of the growing opportunities

associated with the bioproduct development, while optimally managing its conventional activity and maximising

the economic and social outcomes for the communities.

Figure 2.3 The P&P company vision

2.3.5 Strategy

According to (Porter, 1996), strategy is the creation of a unique and valuable position, involving a set of well-

fitted activities. It represents the logic the company would use to achieve the defined vision (Kotter, 1995).

51

For the developed approach in this paper, the strategy translates the future vision into a set of long-term

objectives to ensure a durable competitive advantage.

In order to well define an appropriate strategy for a given Canadian P&P company, we have reviewed in detail

the principal strategic features for the biggest P&P companies both in Canada and worldwide. The conducted

analyses have allowed us to reveal a number of common strategies, which have been implemented, to survive

the forest industry crisis. This step has been essential to understand why some companies thrive during such

an economic stalemate while others do not, and thereafter to identify the most promising strategies to achieve

a durable transformation.

Throughout the last two decades, the most common strategy in Canadian P&P companies has been a

process-oriented commodity strategy. The main features of this strategy are the manufacturing of standard

P&P products using standard processes and selling them as commodities to a number of standard markets

(Thorp, 2005). As conventional markets have been shrinking, the economies of scale generated when selling

substantial product volumes to substantial markets, have become a handicap because of the low flexibility that

is offered. To remedy that issue, an increasing number of academics and industrials support customer-

oriented innovation strategies, where P&P companies offer an innovative value proposition that meets the new

customer requirements and sell them in growing new market spaces ((Thorp, 2005), (Wising and Stuart,

2006), (Towers et al., 2007))

In the next subsection, we review in detail how the forest industry leaders in Canada and worldwide are

reinventing their strategies to meet the economic, social and environmental challenges.

2.3.5.1 The strategies of forest industry leaders In mature markets like in North America, the forest industry, particularly the P&P sector, has to deal with an

increasingly structural decline in several market segments. The emerging low-cost competition, the

technological shifts, and the increasing environmental pressures have profoundly affected conventional

markets, forcing companies to transform their strategies to survive (PwC, 2010a). About 63% of 49 CEOs,

from leading forest companies around the world interviewed by PriceWaterhouseCoopers2, confirm that they

are already reinventing their strategies. Besides, nearly a full quarter of the interviewed CEOs are convinced

that these changes will be fundamental (PwC, 2012).

In the top 100 global forest industry companies, in terms of revenues, ten Canadian forest companies are

listed (PwC, 2010b). Among them, we have decided to assess in depth the strategies of five companies,

2 PriceWaterhouseCoopers is the world's largest professional services firm

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producing P&P products, on the basis of their net earnings in 2010, 2011 (PwC, 2011). We have chosen the

company that has realised the best performance, as well as the company that made the worst operational

performance. Then we selected three companies whose operational profits fluctuate between loss and

earnings. The reason behind our choice is to evaluate how the financial performance of the company affects

its transformation strategy.

To well assess the selected companies, we have reviewed their visions in detail, their strategic structures, their

product portfolio and their principal partners, by referring to their Internet sites and their periodic reports. Such

an evaluation has been essential to retrieve common transformation strategic features for the case of the P&P

companies.

To identify the most common features of the selected Canadian P&P companies’ transformational strategies,

we have classified each strategy according to three parameters: The degree of innovation in the strategy, the

time-horizon of the strategy and finally whether the strategy is cost-driven or value-driven.

Regarding the degree of innovation, a strategy could range from one that is low innovation, by just making

incremental changes to the product portfolio and the served markets, to one that is high innovation and makes

disruptive changes to the company business to serve new customer and market needs (Nagji and Tuff, 2012).

For a low innovation strategy, the changes could include improving existing product properties such as the

environmental and quality certification, producing customised products to meet specific needs, and reducing

the fossil energy consumption by optimising the energy efficiency and increasing the use of cogeneration to

meet a part of the energy needs. In sum, there would be no major transformation in the products, the

processes and all-over supply chain. As for a high innovation strategy, the changes made would profoundly

affect the value creation network of the company. At the product level, there would be a substantial

diversification in the product portfolio by adding innovative forest products to meet changing customer needs

or new high-value products such as bioenergy and biomaterials to serve new growing markets. To

manufacture these products, a set of innovating processes would be implemented. For the energy needs,

there would be a fundamental transformation regarding the energy sources by aiming to substitute the

supplied fossil energy by on-site produced bioenergy and even become an energy supplier. These major

changes would require adapting the whole supply chain to optimally manage the transformation while

maintaining the conventional activities.

Regarding the time-horizon of the strategy, we consider short-term, mid-term and long-term strategies. Cost-

cutting measures, capacity reductions and shutdowns are considered as short-term strategies aiming to

maximise cash flows and ensure further financial flexibility without looking at long-term survival issues

(Rogers, 2011). Furthermore, we assume that reducing strategic actions aiming to improve the operational

53

performance of the company supply chain are considered as mid-term actions that target acquiring an

operationally efficient supply chain. Finally, mill modernisation, product portfolio diversification, and new

market access are considered as long-term strategic actions towards ensuring a sustainable business for the

company (Ministère des Finances and MERN, 2000) .

The third parameter that we have considered in classifying the transformation strategies for P&P companies is

whether the strategy is cost-driven or value-driven. A strategy that focuses on maximising the productivity and

the efficiency throughout the supply chain while minimising resources consumption to outperform the

competition is considered as a cost-driven strategy. On the other side, a strategy that emphasises creating a

new and superior value by continuously adapting to shifts in customer needs, rather than focusing on

outperforming the competition’s value proposition, is considered as a value-driven strategy (Kim and

Mauborgne, 1999b).

The companies we have analysed above have undertaken different strategic approaches to deal with the new

challenges they are facing. The driving forces defined above are used in different degrees within each

strategy. Moreover, to well define the different strategies, we consider that each strategy is composed of three

building blocks: corporate capabilities, customers and competition (Kim and Mauborgne, 1999b). When

formulating a strategy, each block should be clearly defined to achieve a sustainable competitive advantage.

Referring to the considered driving forces, we have been able to identify four major transformation strategies

that the assessed companies have undertaken to overcome the forest industry crisis (Figure 2.4). In each

strategy, we outline how the corporate capabilities, including the technologies, processes and products, are

managed, how the customers and the served markets are handled, and how the company deals with

competition.

2.3.5.2 Survival strategy It is based essentially on reducing production capacities and rationalising assets, to adapt to the decline of

demand in conventional markets. In this strategy, the company limits its offer to the conventional existing

portfolio of products, while making minor changes in their characteristics such as innovating design and

environmental certification. In parallel, that strategy aims to maintain the conventional markets by offering cost-

competitive products to face competition. On the environmental side, the company’s strategy principally

consists in reducing fossil energy consumption by producing cogenerated electricity and steam to meet a part

of the company’s energy needs. We then define the survival strategy as a cost-driven strategy, as it is based

on cost restructuring. In addition, it brings a low-innovation degree regarding company capabilities as the

product portfolio is slightly changed. Regarding the time frame, the survival strategy is considered as a short-

54

term strategic choice for the company, as it aims only to overcome the short-term financial problems without

suggesting sustainable solutions for the shifts occurring within the business environment of the company.

2.3.5.3 Operational efficiency strategy It complements the survival strategy. Besides capacity adjustment and assets rationalisation, the conventional

product portfolio is innovated by offering customised products and a set of superior forest products that meet

increasing customer requirements regarding quality and efficiency. That extended product offer aims to

expand the conventional forest product markets. In this strategy, the emphasis is on improving the operational

efficiency of the value creation network and implementing an effective supply chain management. The

improvements in supply chain operations and value proposition help the company offer a competitive offer

relative to the increasingly fierce competition. Concerning the energy needs, the operational efficiency strategy

would not be limited to meeting a part of the energy needs via cogeneration but would also support

diversification of bioenergy sources, in order to improve mill energy efficiency. Thus, this strategy is considered

as a mid-term strategy aiming to help the company overcome the crisis and obtain a lean operational structure.

The degree of innovation remains low in this strategy, as the changes wouldn't fundamentally transform the

company value proposition. Furthermore, the operational efficiency strategy, as its name suggests, is a cost-

driven strategy, though it brings some significant improvements to the value of the product portfolio.

2.3.5.4 Intra-industry diversification strategy It consists in diversifying the product portfolio by producing a set of new high-value forest products presenting

innovating features or using advanced technology materials. That product diversification helps the company

access new niches within the conventional forest product markets. Different revenue sources from a number of

small markets then overtake the traditional mass-market revenues. Therefore, such a strategy aims to

outperform the global competition within conventional P&P markets by offering a diversified product portfolio

encompassing innovative P&P products. Still, integrating innovative P&P products requires implementation of

disruptive technologies, which would deeply transform the value creation network of the company. Building

partnerships from inside the forest industry would then be essential to overcome the associated technological

barriers and enhance the design, the manufacturing and the commercialisation of such products.

The intra-industry diversification strategy is then a long-term strategy aiming to create new market spaces for

the P&P companies requiring innovative products. In addition, it presents a high degree of innovation, as it

requires the integration of new technologies and processes to diversify the product portfolio. Furthermore, the

intra-diversification strategy is considered as a value-driven strategy as it deeply transforms the company’s

value proposition by integrating a set of innovative P&P products and serving new markets.

55

2.3.5.5 Bioproduct-based diversification strategy It is based on the diversification of the product platform by integrating bioproducts such as biomaterials (NCC,

biocomposites) and bioenergy (biofuels, cogeneration) (FPAC, 2010). This diversification implies the

implementation of new technologies within the company to manufacture the bioproducts. The bioproduct-

based strategy is an inter-industry diversification strategy allowing the company to access new markets

beyond the conventional P&P markets, such as chemical market, fuel market, and construction market. Thus,

instead of competing with other P&P companies within saturated P&P markets, such a diversification allows

the company to access new market spaces making the conventional competition irrelevant (Kim and

Mauborgne, 1999a).

Still, there is a technological and economic risk associated with the manufacturing and the commercialisation

of a number of bioproducts. In this case, building partnerships with partners from outside the forest industry

such as oil industry, energy industry, and private and governmental research institutes, mitigates that risk and

helps P&P companies profit from the substantial growing opportunities associated with a bioproduct-based

value proposition (Chambost et al., 2009). Furthermore, bioenergy products would make it possible for

companies to acquire energy self-sufficiency by substituting the supplied energy such as natural gas and

electricity for on-site manufactured bioenergy such as synthetic gas, cogenerated electricity and steam, while

selling the excess part to outdoor customers.

The bioproduct-based strategy is then a long-term strategy as it helps P&P companies access new market

spaces to diversify their revenues beyond the competition within the P&P sector. That strategy lends a high

degree of innovation to the P&P company as the diversification of the product portfolio would be accompanied

by the implementation of innovative processes and technologies, as well as the reinvention of the supply chain

from the supplying sources to the served markets. Thus, the strategy described is value-driven as it would

transform the whole value creation network of the P&P company.

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Figure 2.4 Transformational strategies for Canadian forest companies

To overcome the crisis and achieve a sustainable competitive advantage, the Canadian P&P companies, have

to transform their strategies. In (PwC, 2010a), most of the interviewed CEO’s of companies operating in

mature markets such as Europe and North America consider bioenergy diversification as one of the most

promising transformation strategies to ensure their sustainability. Nevertheless, operational restructuring

strategies based on asset rationalisation and operational performance improvement, which, in this paper, we

called survival strategies and operational efficiency strategies, would be essential for those companies to

acquire an agile and flexible organisational structure before tackling diversification strategies (PwC, 2010a).

Furthermore, the Canadian government recognises the vitality of short-term operational restructuration

strategies to get the basics right for long-term transformation strategies (Government of Canada, 2012a).

Canadian P&P companies should then manage short-term and long-term strategies to successfully undertake

their transformation. As we have seen when analysing Canadian forest companies, those who are moving

towards long-term diversification strategies have already undertaken, in parallel, short-term operational

efficiency strategies. This finding is reinforced in (Nagji and Tuff, 2012), where it has been shown that

companies which have achieved successful transformation strategies have optimally managed three levels of

57

innovation: basic innovation where the competitiveness of the existing products improved to maintain the

conventional markets (survival strategy, operational efficiency strategy), adjacent innovation where the

product portfolio is expanded while serving conventional or adjacent markets (intra-industry diversification

strategy), and finally transformational innovation where new products are added to the product portfolio to

serve new markets beyond the conventional industry boundaries (inter-industry diversification strategy).

Nevertheless, the declining demand for several conventional P&P products as well as the emergence of low-

cost competition make short-term operational restructuring strategies insufficient to ensure a sustainable

competitive advantage for P&P companies (FPAC, 2011). Undertaking diversification strategies to create new

market spaces, would be vital to successfully reshape the sector (FPAC, 2010).

Furthermore, as highlighted in Figure 2.1, the new formulated strategy has to be aligned with the vision

defined. As the vision defined (see previous section) supports the transformation of conventional P&P

companies into environmentally and economically competitive companies, profiting from the growing

bioproduct-based opportunities, the bioproduct-based diversification strategy fits well with that vision. By

implementing such a strategy, the general direction outlined in the vision is translated into a set of long-term

objectives defining how the P&P company would manage its capabilities, customers and competition to

achieve a sustainable competitive advantage.

However, the uncertainties associated with the development of diversification strategies, particularly the

bioproduct-based diversification strategies, are still high due essentially to the lack of information regarding

profitability and the risks associated with strategy implementation (FPAC, 2010). Thus, to help P&P companies

evaluate the profitability of such strategies and understand the challenges of their implementation, the design

of a new business model, which represents the link between strategy formulation and business process

implementation, represents a vital step in the developed approach (Ammar, 2006). Indeed, according to almost

all Canada forest industry stakeholders, developing a new business model would be essential to achieve the

aimed strategic transformation for the sector (NRC, 2012).

As shown in Figure 2.1, a new business model would support the implementation of the formulated strategy,

while considering a set of driving forces affecting the business environment of the company. Thereby, the

strategic thinking about how the company would handle its capabilities, customers, and competition is

translated into a plan outlining the logic the company would manage its value proposition, the customer

interface, the infrastructure management and the financial aspects.

The next section is devoted to the design of the business model associated to the bioproduct-based

diversification strategy.

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2.3.6 Business model design

The business model describes the logic the company creates, delivers and captures the value (Osterwalder

and Pigneur, 2010).

While the strategy outlines the operating guidelines of a company to achieve a long-term competitive

advantage, the business model is the plan associated with that strategy to implement the organisational

structure, the processes and the systems.

As presented above in the previous section, the bioproduct-based diversification strategy is suggested as

being a promising transformation strategy to achieve the common vision initially defined. Among the different

available bioproducts to integrate within Canadian P&P companies, bioenergy products, encompassing a

range of bio-based products ranging from electricity and heat to a set of biofuels and biochemicals, would be a

viable pathway to achieve a sustainable business for those companies (FPAC, 2010).

Therefore, as highlighted in Figure 2.1, there is a need to link the different decisional levels including the

vision, the strategy, the business model, and the value network implementation level, in order to achieve a

successful transformation. We have listed these decisional levels according to three steps: the planning step

where the vision defines the general direction of the company and the strategy outlines the long-term

objectives to achieve that vision, the design step where the business model describes the logic the company

would earn money, and finally the implementation step where the organisational structure and the business

processes are established (Figure 2.5).

Figure 2.5 The three-step decisional levels

These three steps should all be reiterated in time to continually adapt the company to the increasingly

changing business environment. The business model then depends on a number of external factors that would

59

profoundly affect customer demand and even the need for the products offered (Osterwalder and Pigneur,

2010).

For every external factor, different evolution scenarios might occur in the future, which would lead to a set of

appropriate business models for every combination of factor levels. Therefore, to identify an appropriate

business model, we have to decide on the most plausible combination of scenarios. We have then defined four

external factors that would affect the business model design.

As we consider the bioenergy pathway, the impact of each external factor on the viability of bioenergy-based

diversification strategies is presented.

The technological factor: The development degree of bioenergy technologies is an essential factor in

the advent of bioenergy product diversification. Currently, the maturity degree of these technologies

varies between demonstration projects and commercial scale status (Bradley, 2009). If the bioenergy

technologies become commercially mature during the coming years, it will boost the implementation

of these technologies within P&P companies. Otherwise, the risk associated with bioenergy

investment will remain high, which would promote other diversification pathways such as biomaterials

or innovative P&P products.

The economic factor: The evolution of bioenergy investment costs would be a key factor to support

bioenergy diversification, since capital costs represent 35% to 50% of total bioenergy costs (IEA,

2011). The current investment costs are still high, presenting a serious barrier to the implementation

of bioenergy within P&P companies which are already experiencing financial difficulties. Thus, a

decline in investment costs would enhance the return on investment of bioenergy diversification.

Otherwise, the risk associated with the profitability of such investments would remain high, therefore

limiting bioenergy investments within P&P mills.

The socio-political factor: As a part of the existing bioenergy technologies is not yet commercially

mature and the investment costs are still high, the political regulations and the community

environmental pressure would be prominent in the development of bioenergy. On the one hand, the

governmental financial incentives and the bioenergy investment funds would reduce the financial risk

associated with bioenergy investments, thus helping P&P companies’ stakeholders take that step

(Bradley, 2010). On the other hand, the community could promote the integration of bioenergy

technologies within forest industry companies, since such an integration would imply the use of

biomass, a neutral carbon-cycle energy source (Johnson, 2009), and offer a set of ecofriendly

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products helping reduce P&P companies’ carbon footprint and promote their environmental image

(CIFQ, 2010).

The market factor: The growth of markets for bioenergy products would be crucial to the development

of bioenergy technologies within P&P companies (Sparling et al., 2011). In fact, if there were a

growing need for bioenergy products within large-scale markets such as energy market and chemical

market, it would represent a hedge for P&P companies against market entry risk. The development of

such markets would be essential for P&P companies seeking to diversify their revenue sources by

accessing new market spaces beyond the boundaries of conventional P&P saturated markets.

For each of these four factors, there could be different development trends. Moreover, for every possible

combination of these factors, there should be a corresponding future scenario (Figure 2.6). For each plausible

scenario, there would be an appropriate business model ensuring the competitiveness of the company within

that environment (Osterwalder and Pigneur, 2010).

Figure 2.6 A multi-scenario development for business model

2.3.6.1 The integrated forest biorefinery business model A number of reports have been expressed interest in scrutinising the future for the global and North American

forest industry ((FPInnovations, 2011), (FPAC, 2010), (Bradley, 2010), (Bradley, 2009), (PwC, 2012), (IEA,

2010)). One of the most common findings in these reports is that the bioenergy pathway for the forest industry,

particularly for P&P companies, would profit from political and social support to achieve the transformation of

this industry into a bioindustry, where companies would integrate the manufacturing of high value-added

bioproducts in their core strategies. What’s more, there would be huge market opportunities for bioenergy

products, which are supposed to grow during the coming years (FPAC, 2010). As for the technological and

economic potential, it has been shown in (de Wit et al., 2010) that there would be substantial development of

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bioenergy technologies as regards technological maturity and investment cost reduction, enhanced by

governmental incentives and increasing global demand.

Thus, the development of the bioenergy pathway, presented as a promising avenue to transform the Canadian

P&P sector, is considered as one of the most plausible scenarios to occur in the coming years.

The business model that is most appropriate to that scenario is what we have called the Integrated Forest

Biorefinery (IFBR) ((Stuart, 2006), (Thorp, 2005), (Chambost et al., 2009), (Huang et al., 2009), (van

Heiningen, 2006)). In Figure 2.7, we present the value creation network of a P&P company-based IFBR.

Figure 2.7 P&P company-based IFBR value creation network

An IFBR, in the case of a P&P company, would integrate bioenergy production to the conventional P&P

activity, by using supplied and plant-generated biomass and transform it into high-value bioenergy products.

The P&P activity would produce market-adapted and cost-efficient P&P products, and would generate a set of

co-products such as black liquor and paper sludge, which could be used to produce bioenergy. To produce

bioenergy products, several technologies could be considered in the IFBR, such as Fermentation to produce

Bioethanol, Pelletisation to produce Pellets, Pyrolysis to produce Pyrolysis Oil, Digestion to produce Biogas,

Cogeneration to produce Electricity, Heat and Steam, and Gasification to produce Synthetic Gas. Synthetic

Gas could be further processed to produce Fischer-Tropsch Diesel via Fischer-Tropsch-Synthesis technology,

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Synthetic Natural Gas via Methanation technology, or Methanol via Methanol-synthesis technology. The

company’s energy needs in natural gas, electricity, heat and steam could be fulfilled by bioenergy production,

allowing the IFBR to be energy self-sufficient.

The supplied biomass could be industrial residues from other forest mills like sawmills and P&P mills, including

chips that could be used for both P&P or bioenergy production, agricultural residues from farms, forest

residues generated by harvesting activity, or even urban waste residues from municipalities. The demand

markets would include, besides the conventional P&P market, a set of markets such as energy market,

chemical market, and power generation distributors.

2.3.6.2 The nine-block business model canvas To design the IFBR business model, we have used the nine-block business model decomposition introduced

in (Osterwalder and Pigneur, 2010) that aims to depict the way the company would do business. The nine

components of the business model could be grouped into four strategies.

Each of the four strategies may involve one or several business model components (Figure 2.8).

The market strategy: it controls the relationship between the company and the demand markets. It is

based on three elements: client segments where the different customer groups that the company

aims to serve are defined, client relationships that depict the kind of the relationship that the company

maintains with each customer segment, and communication channels that describe the way the

company delivers the created value to each customer segment.

The offer strategy: it presents the centrepiece of the business model and the reason why a customer

would choose to deal with that company. The offer strategy portrays the value proposition of the

company, which defines the value created for each customer segment to meet its specific needs.

The network strategy: it defines the configuration of the value creation network for the offered

products. It is composed of three elements: the key resources which represent the most important

physical, financial and human resources, helping the company create the value, the key activities

which involve the essential activities to optimise the operational structure of the company such as

supply chain management, and finally the key partners which present the most strategic collaborators

to reduce investment risks or to acquire specific resources or activities.

The profit strategy: it outlines the way the company generates money from its value proposition, as

well as how it manages its operating costs. The profit strategy is composed of two elements: the

revenue flows, which define how the company gets money from each customer segment, and which

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are the applied pricing mechanisms, and the cost structure which describes all operating expenses

incurred by the company in order to create and deliver the value proposition to the customers.

Figure 2.8 Business model canvas

2.3.6.3 Case study: The P&P company-based IFBR We have applied the nine-block business model decomposition in the case of a P&P company-based IFBR.

Several reports and research works treating the issue of integrating bioenergy into P&P companies ((MRNF,

2012), (FPInnovations, 2011), (FPAC, 2010), (Stuart, 2006), (Pätäri et al., 2011), (Bradley, 2010), (FPAC,

2011), (Wising and Stuart, 2006), (Bradley, 2009), (V Chambost et al., 2008)) have been useful to gather the

different elements composing the business model. The business model design has been an iterative process

of generating ideas; through which the different designed elements have been discussed and improved within

the research team in order to converge to a better design.

The question dealing with the starting element when designing business models has been discussed in

(Osterwalder and Pigneur, 2010) where the choice of one particular element among the developed nine

elements affects the design of the business model. The starting element drives the design of the other

elements. In our case, the IFBR business model is essentially based on a new value proposition, which is the

bioenergy integration. Then, based on the classification presented in (Osterwalder and Pigneur, 2010), the

IFBR business model is an offer-driven designed business model, where the new value proposition affects the

design of the eight remaining elements.

In the following, we propose a number of elements to design the nine business model components.

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a) ValuepropositionAdding new activities is considered as one of the most viable means to reinvent business models (Amit and

Zott, 2012). The developed IFBR business model is essentially based on a new value proposition: diversifying

the product portfolio by integrating bioenergy products. Besides conventional P&P products serving saturated

markets, the IFBR would offer a number of high-value bioenergy products for new growing markets (FPAC,

2011). Such a diversification would allow the company to generate new revenue sources and gain access to a

set of high-margin profit markets, beyond the boundaries of the P&P industry.

b) ClientsegmentsThe IFBR customers would be categorised in two groups: the P&P product customers composing mass

markets, and the bioenergy product customers composing a set of niche markets. These two customer

segments have different requirements: The P&P product customers claim innovative P&P products, which

would be both eco-efficient and cost-competitive.

As for the bioenergy product customers, they would require high-value products that would make it possible to

substitute fossil energy and offer a low environmental impact alternative. The challenge would then be to

maintain a saturated mass market as well as to gain market shares within growing niche-markets.

c) DistributionchannelsTo deliver the products to the customers, a company could deploy its own distribution network (direct mode),

exploit a partner distribution network (indirect mode), or implement a mixed distribution strategy combining the

two modes. For bioenergy products, building partnerships to deliver the products to the markets may be a key

factor to reduce the risk of accessing these markets (FPAC, 2011).

To implement an efficient distribution network, the different combinations should be well evaluated by

considering all related issues. The direct mode requires substantial investment, while allowing the company to

generate high profit margins and operate an agile supply chain close to the customers. On the other hand, the

indirect mode limits company profit margins but doesn’t require initial investments and, for the company,

avoids managing the distribution issues and the risks of penetrating such markets (Osterwalder and Pigneur,

2010).

d) CustomerrelationshipsThe IFBR relationship with its customers would be different for the two principal customer segments. For the

P&P product customers, the relationship would be essentially based on customer retention mechanisms and

revenue maximisation per customer, due to saturated P&P markets (Osterwalder and Pigneur, 2010). Forest

certification and the offer of ecofriendly products present one of the most efficient strategies to retain

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customers and even get access to niche P&P markets where the environmental criteria represent an essential

accessing condition (Chen et al., 2010).

For the bioproduct customers, where the markets are still in their early growth stage, the customer relationship

would consist in acquiring market shares. Partnerships and contracts could help the company gain market

shares and reduce the risk of market entry. Besides, the company implication within the local communities to

develop bioenergy projects would convince them of the social, economic and environmental benefits of

bioenergy integration within P&P companies and would represent a substantial marketing tool for bioenergy

product development (Mangoyana and Smith, 2011).

e) RevenueStreamsIn the case of the IFBR, the revenue streams would be mainly generated from both P&P products and

bioenergy products. That revenue source diversification represents a key factor in the IFBR business model,

as it would reduce the risk of investing in bioenergy by having different revenue sources. One of the most

important issues associated with revenue stream management is the pricing mechanism to set the market-

selling price of products (Osterwalder and Pigneur, 2010). For P&P products, the markets set the price, due

essentially to the low-cost competition. As for bioenergy products, the prices rely essentially on the fossil

energy product equivalents, by considering, for example, the ratio of their low heating values (NETL, 2009), or

by referring to the low heating value of a mix of fossil energy products (Okkonen and Suhonen, 2010).

f) KeyresourcesTo create value, the IFBR would require a set of physical, human and financial resources. For the physical

resources, besides the existing P&P manufacturing facilities, there would be a need for bioenergy technologies

to manufacture the bioenergy products. With respect to human resources, high-qualified human resources

would be required to support the reinvention of the company (BioTalent Canada, 2009). In (Rothwell et al.,

2011), the research & development people, engineers, laboratory technicians, and commercialisation staff, are

presented as being the key human resources to achieve such a bio-based transformation. As for the financial

resources, they would be essential to invest in bioenergy, which requires substantial financial funds, up to

several tens of millions of dollars (FPInnovations, 2011). The government contribution would be crucial to

provide financial support in the form of incentives and tax exemptions for companies aiming to invest in

bioenergy, in order to reduce the investment risks and help these companies take the plunge (Rothwell et al.,

2011).

g) KeyactivitiesFor the IFBR, the key activities would be manufacturing and supply chain management. Since the IFBR is

essentially based on integrating bioenergy products into the value proposition, manufacturing constitutes a

66

vital activity within the new business model. The production activity consists in manufacturing P&P products as

well as bioenergy products. It would be crucial to jointly manage the production for both product families, as

the P&P activity generates a set of co-products that could be converted into bioenergy products and the

bioenergy activity allows the mill to meet the energy needs of the P&P activity (Figure 2.7).

Besides, the management of feedstock and the distribution of the finished products represent key activities to

allow the company to optimise its supplying costs and deliver the right product at the right time in the right

place. The complexity of the logistic operations is considered to be one of the main barriers to bioenergy

integration within the forest companies (Lakovou et al., 2010). Therefore, a well defined supply chain

management jointly optimising the key activities from material supplying to product distribution would be

essential to successfully reinvent the business model.

h) KeypartnershipsBuilding partnerships would be crucial for the transformation of the P&P Company into an IFBR, in order to

reduce the investment risks and achieve a successful implementation (Chambost et al., 2009). In fact, there

are several uncertainties associated with bioenergy market development, requiring the establishment of

partnerships to hedge against these uncertainties and increase the chances of success (CIFQ, 2010). In

(Chambost et al., 2009), four principal categories of partnerships to build have been identified when

implementing integrated forest biorefineries. We have adapted and developed this classification to the case of

the proposed P&P company-based IFBR.

The supplying partnerships: they allow the company to ensure a steady availability of biomass to

hedge against the periodic fluctuations, and to minimise supplying costs due to economies of scale.

The commercial partnerships: they help the IFBRs enhance the commercialisation of the bioenergy

products and gain access to the associated markets. There are several sectors such as oil,

chemicals, automobile, aerospace and agriculture that could be strategic commercial partners for the

P&P companies to achieve their transformation (FPAC, 2011).

The technological partnerships: they accelerate company access to the bioenergy market by profiting

from the partners’ technological expertise in developing and implementing bioenergy technologies.

The IFBRs should also build partnerships with research and development organisms such as

universities, and private and public research organisms to assess the feasibility and profitability of

bioenergy investment (Rothwell et al., 2011).

The financial partnerships: they are vital to provide the required financial funds to invest in bioenergy.

The financial funds represent a key factor in the development of bioenergy within the P&P sector, as

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the lack of such funds represents one of the main barriers to the advent of bioenergy integration

within P&P companies (FPInnovations, 2011).

The government is currently the principal source of financing for bioenergy investments in the Canadian forest

industry. The remaining funds come essentially from private venture capital (Rothwell et al., 2011). Having a

clear business model highlighting the logic the company would create value and earn money would be a

substantial step to convince private capital to financially support the biotransformation of the sector.

In Figure 2.9, we illustrate the potential partnerships the IFBR could build throughout the value creation

network, from the research and development stage to the finished product distribution, in order to maximise its

chances for a successful transformation.

Figure 2.9 Potential partnerships for IFBR

i) CoststructureThe operating cost reduction remains a priority for most P&P companies to support their transformation into

IFBRs (PwC, 2010a). For the North American P&P companies, saturated markets and the highly competitive

environment they are facing make it essential to maintain a flexible and cost-efficient operational structure to

allow them to thrive.

The cost structure could be defined once the key activities, the key resources and the key partnerships have

been defined. In the case of the IFBR, the operating costs are associated with the supplying, manufacturing

and distribution activities (Figure 2.10). For the supplying activity, the costs would be principally feedstock

supplying. Regarding the manufacturing activity grouping the bioenergy and the P&P product manufacturing,

the operating costs are composed of fixed costs, such as the annualised investment costs and the fixed

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operating costs including staff remuneration and maintenance costs, and variable costs that mainly consist of

direct labour costs. As for the distribution costs, they include the finished product transportation costs as well

as the commercialisation-related costs.

Figure 2.10 Cost structure for the IFBR

In fact, optimising the process efficiency all along the IFBR supply chain would be crucial to achieve long-term

competitiveness, as the companies would not decide about feedstock and finished product prices, which would

be set by the market (PwC, 2010a).

In Figure 2.11, we summarise the entire nine elements described above that compose the IFBR business

model. The different elements we present aim to help P&P decision makers within P&P companies design an

efficient business model translating the formulated transformation strategy throughout the company value

chain.

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Figure 2.11 The business model canvas for a P&P company-based IFBR

2.3.7 Business model validation

Once the business model has been designed, its validation before being implemented is an important step that

aims to simulate the business model performance via a set of low-risk experiments, without exposing the

company to the real investment risks (Osterwalder et al., 2005). In (Magretta, 2002), the business model

development process is likened to the scientific method design process, in which one starts with a hypothesis,

tests it, and revises it when necessary.

The uncertainty associated with the viability of bioenergy investments is one of the main barriers to their

integration within the forest industry. Thus, simulating the business model would help anticipate its profitability

and possibly rectify the design before its implementation.

In the literature dealing with the design of business models, a few works have been interested in raising the

issue of simulating business models before implementation. Some studies have argued that testing viability is

an essential step when designing business models ((Osterwalder and Pigneur, 2010), (Magretta, 2002),

(Chesbrough, 2010)) without explicitly detailing that testing step.

To our knowledge, only two contributions have focused on developing explicit methods to simulate business

models before their implementation. In (McGrath and MacMillan, 1995), a five-step approach, called discovery-

driven planning, has been developed that allows modelling the economic profitability of a new business model,

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by formulating a set of hypotheses, testing their effect on the business model profitability, and adjusting them

according to the test results. In (Hamel, 2000), three criteria have been suggested to assess the potential of a

designed business model: efficiency which measures the profit margins relative to the operating costs,

uniqueness which evaluates the originality of the business model compared to those of competitors, and profit

accelerating which estimates the capacity of the business model to rapidly grasp the new market opportunities.

In this paper, we propose four performance indicators to test the potential of the designed business model

before its implementation. We distinguish the quantitative indicators, of which the measure is compared

relative to predefined thresholds, and the qualitative indicators, of which the measure depends on the

evaluation of the stakeholders. For the latter ones, the evaluation would be done by determining whether or

not the business model meets the required evaluation of that indicator.

2.3.7.1 Quantitative indicators The quantitative indicators that we have defined aim to assess the economic profitability as well as the

environmental impact of the P&P company-based IFBR business model. In fact, P&P companies should now

consider the environmental aspect when reinventing their business model to meet the growing social and

political requirements regarding fossil energy consumption and carbon emissions (Chaabane et al., 2012).

a) Netpresentvalue(NPV)It measures the long-term profitability of the IFBR, by evaluating the financial investment returns during a given

planning horizon. For T periods, the NPV is the sum of future discounted cash flows, taking into account the

investment costs and the operational profits, and the IFBR salvage value discounted at the end of the planning

horizon. The salvage value is the estimated financial value of the company, once the assets’ accounting

depreciation and the debts have been deduced (Equation 1).

(1)

Where

: Future periodic cash flow;

: Discount rate;

: Discounted salvage value estimated by the end of planning horizon.

NPV CFt

(1 r )t SVTt1

T

CFt

r

SVT

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If the obtained NPV is greater than the predefined threshold, the designed business model would likely be

profitable. Otherwise, the design process should be reviewed.

b) Greenhousegasemissionreduction(RGHG)It quantifies the environmental impact of the IFBR. In fact, several elements of the transformed business

model, such as the embedded bioenergy technologies, the network configuration as well as some built

partnerships would affect carbon emissions throughout the value creation network. The reduction rate of GHG

emissions, by a future period t, relative to the initial emissions of the conventional P&P company, is given by

equation 2.

(2)

Where

: GHG emissions of the IFBR over a given future period t;

: Initial GHG emissions of the conventional P&P company.

A reduction threshold could be set for a given term, aiming to allow the IFBR to meet the future environmental

requirements or to fulfil a predefined internal commitment. If the measure of the anticipated reduction rate

meets the required threshold, the business model would then be aligned with the environmental commitments

the company would face in the coming years. Otherwise, the environmental impact of the designed business

model has to be re-evaluated to further support the sustainable transformation of the company.

2.3.7.2 Qualitative performance indicators The presented qualitative indicators help the stakeholders scrutinise the adaptability of the business model to

the changing business environment as well as its acceptability by the community. We believe that the

adaptability and the acceptability of the business model would be crucial criteria to ensure a sustainable

competitive advantage for the IFBR.

a) AdaptabilityIt assesses the capacity of the designed business model to adapt to the economic, technological and socio-

political changes that would occur within the P&P companies’ business environment during the coming years.

To remain competitive within a tough economic context, struggling companies should adapt their business

models at the right time to the changes occurring in technologies and markets (Bower and Christensen, 1995).

RGHGt 100%

GHGIFBRt GHGP&P

0

GHGP&P0

GHGIFBRt

GHGP&P0

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At the economic level, there would be several changes regarding market prices and demand levels for both

conventional and bioenergy products. The IFBR should be able to continuously adapt its business model to

these changes, in order to maintain a sustainable business.

With respect to the socio-political aspect, governmental legislations and community requirements would likely

change in the coming years regarding the environmental requirements and the financial and social incentives

to invest in bioenergy. The business model should be easily adapted to these major shifts, to transform them

into sources of competitive advantage.

As for the technological level, several bioenergy technologies would experience a substantial advent during

the next years, regarding the investment costs and the conversion yields (IEA, 2009). The IFBR business

model should then be flexible enough to invest in these technologies in the right capacity and at the right

moment.

Thus, the stakeholders should evaluate whether the business model would be easily adapted to the

technological, economic and social-political changes that would affect the P&P sector in the coming years.

b) AcceptabilityIt evaluates the social acceptability of the community concerning the developed business model. In the coming

years, the pressure of the community will be important, requiring eco-responsible products which would make

it possible to substitute fossil energy products and enhance the environmental commitment of the P&P sector

(Brunette, 2011). Thus, convincing the community about the environmental and economic advantages

associated with the IFBR business model would be essential for the transformation to be successful.

In Quebec, members of the civil community participate in redesigning forest management strategies in order to

meet the new environmental requirements. This participation remains insufficient and should be involved when

designing business strategies (Bouthillier and Roberge, 2007).

One of the reasons for the Quebec forest industry crisis is that the community no longer believes in the

environmental and social commitment of the forest industry (MRNF, 2008). Therefore, integrating the civil

community in the validation process of the designed business model would be profitable for P&P companies to

promote the environmental and social potential of the IFBR.

The four performance indicators described above would be crucial to simulate the viability of the IFBR

business model before its implementation. Once each indicator has been evaluated, two decisions could be

made: validating the business model design, or invalidating it.

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2.3.7.3 Invalidation If the evaluation of one or several performance indicators is considered unfavourable, reviewing the company’s

decisional choices is essential. The revision could be limited to reviewing one or several components of the

designed business model, changing some elements in the defined strategy, or even adjusting the strategic

vision (Figure 2.1).

This reviewing process could be repeated until the expected levels for the defined performance indicators have

been obtained, or a consensus reached among the stakeholders on the required performance levels for the

designed business model.

2.3.7.4 Validation If the indicators evaluation is positive, the designed business model is estimated as being viable and ready to

be implemented. In the implementation step, the business model would be transformed into a detailed

business plan (Osterwalder et al., 2005). The business plan translates the business model into concrete

elements including the organisational structure, the business processes, and the infrastructure and systems

(Osterwalder et al., 2005).

2.3.8 Continuos adaptation

After being implemented, the business model should undergo a continuous process of adaptation, which

includes revision and refinement (Morris et al., 2005). In fact, business models are considered as perishable

(Govindarajan and Trimble, 2011) and have to be reinvented after a period of time. As we have mentioned in

the “opportunity spotting” step of the developed approach, a number of external incentives (technological,

economic and sociopolitical) would emerge in the future, requiring an iterative transformation of the company

business model. The business model design approach should then consider a business model life cycle,

involving a closed loop of planning, design, validation, revision and adaptation (Figure 2.1).

The presented business model, the P&P company-based IFBR, is an example of that adaptation cycle, by

making it possible for P&P companies to offer an innovative value proposition by integrating bioenergy

products within the P&P mill product portfolio, therefore allowing the company to access new market spaces.

That value innovation would be crucial for the P&P sector to evolve towards a competitive business model.

Still, the business model reinvention process has to be continually adapted to the major shifts within the

company’s business environment, allowing it to achieve a sustainable business.

2.4 Conclusion

To overcome the economic stalemate, Canadian forest companies, particularly the P&P companies, are

seeking long-term solutions to regain their competitiveness. Value innovation is conceived as a viable avenue

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for those companies to diversify their revenues and create new market spaces. Bioproducts, especially

bioenergy products, are considered to be a promising pathway for P&P companies to achieve a sustainable

business.

The decision-support approach presented in this paper aims to propose a practical framework to help P&P

companies’ decision-makers to plan, design and implement a new business model underlining that value

innovation.

To successfully reinvent the P&P companies’ business model, a multi-level transformation process has been

developed to align all the decisional levels with the proposed new value, involving a global vision depicting the

general direction of the company, a strategy translating that vision into long-term objectives, and a business

plan ensuring an effective implementation of the designed business model.

Starting by analysing the competitive situation of P&P companies and identifying the potential opportunities for

change, a four-action framework has then been applied to define sources to create an innovative value for

those companies. Next, a series of analyses adapted to the Canadian P&P sector have been conducted to

identify a new vision as well as an adapted strategy to support the transformation. Through a scenario

analysis, the integrated forest biorefinery IFBR is identified as a promising business model for the most

plausible changes which would occur within the business environment of Canadian P&P companies. After that,

a nine-component business model canvas has been adapted to design a P&P company-based IFBR business

model. Before being implemented, a validation step, where a set of performance indicators have been

presented, has been suggested to simulate the viability of the designed business model without directly

incurring the implementation risks. Via a closed-loop adaptation process, the aim of the approach is to

continuously adapt the P&P companies’ business models to the major economic, socio-political and

technological shifts affecting the P&P competitive environment.

Our contribution has been to propose a decision-support framework to help P&P companies understand and

manage the challenges they are confronted with as well as the business opportunities that lie open to them,

and then adapt their different strategic levels to the future trends that would occur within their business

environment. Our primary goal has been to propose a set of strategic tools to support those companies in

reinventing their business models, in order to transform those opportunities into a source of sustainable value

innovation.

The P&P company-based IFBR business model is presented as a promising business model to respond to the

increasing challenges affecting the competitiveness of the P&P sector. Therefore, further analyses are

required to assess its long-term profitability while considering the future trends associated with such a

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transformation. In our future work, we will focus on developing a decision-support methodology to allow P&P

companies to achieve roadmap to a viable transformation.

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Chapitre 3 Un cadre de travail basé sur un modèle mathématique pour évaluer le potentiel technico-économique d’intégrer la bioénergie dans les usines de pâtes et papiers

Cet article, intitulé « A mathematically-based framework for evaluating the technical and economic potential of

integrating bioenergy production within pulp and paper mills », a pour auteurs Mahdi Machani, Mustapha

Nourelfath et Sophie D’Amours. Il a été soumis au journal « Biomass & Bioenergy » en Octobre 2012 (Facteur

d’impact évalué à 3,931 pour les cinq dernières années). Suite à une deuxième révision, l’article est accepté

avec modifications mineures concernant la longueur de l’article. Une version raccourcie a été soumise en

Novembre 2013 et est en attente pour la décision finale. La version présentée dans cette thèse est la version

complète (plus longue) incluant le modèle mathématique et la base de données.

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Résumé

Les compagnies de pâtes et papiers (P&P) au Canada envisagent la diversification de leur plateforme de

produits afin de survivre au déclin des marchés conventionnels et à la compétition à faible coût. Investir en

bioénergie est considéré en tant qu'option avantageuse pour soutenir la compétitivité du secteur.

Nous présentons alors une approche basée sur la programmation mathématique pour évaluer la profitabilité

d'intégrer la bioénergie à une usine de pâtes et papiers, tout en analysant les risques technico-économiques

qui y sont associés. L'usine, transformée ainsi en une bioraffinerie forestière intégrée (BRFI), pourrait produire

un ensemble de bioproduits obtenus à partir de la biomasse générée sur le site de production ou

approvisionnée de l'extérieur. L'activité de production de P&P génère un nombre de résidus tels que la liqueur

noire ou les boues papetières, qui pourraient être utilisés pour produire de la bioénergie. L'activité de

production de P&P devrait donc être bien gérée, en considérant la possibilité de mettre temporairement

l'activité à l'arrêt. Notre objectif est d'amener aux décideurs au sein du secteur forestier une approche d'aide à

la décision se basant sur la modélisation mathématique afin d'optimiser le réseau de création de valeur de la

BRFI, tout en optimisant la gestion de l'activité de production de P&P.

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Abstract

To overcome declining markets and low-cost competition, Canadian pulp and paper (P&P) mills are

considering the diversification of their product platform. Investing in bioenergy is emerging as a promising way

to boost the sector. In this paper, we present a mathematical programming approach to evaluate the

profitability of bioenergy investments in the case of a P&P mill, while assessing technical and associated

economic risks. The mill, called the integrated forest biorefinery (IFBR), could produce a set of high-value

bioproducts from biomass generated in the mill or supplied from outside. P&P activity generates residues,

such as black liquor and pulp sludge, which could be used to produce bioenergy. P&P activity should then be

well managed, by considering the possibility of temporarily stopping the production of P&P, while assuming the

costs associated with the shutdowns. The objective is to develop a mathematically-based approach for

investors and stakeholders, within the forest sector that aims to optimise the value creation network of the

IFBR and to maximise the profitability of future investments in bioenergy, while optimising the existing P&P

activity.

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3.1 Introduction

The increased value of the Canadian dollar, the US housing crisis and low-cost competition have led to

significant losses within the Canadian forest industry. Pulp and paper mills, in particular, are struggling to

maintain their competitiveness, due to reduced pulp and paper demand, increased competition from emerging

countries operating with low costs and the continued substitution of online media for paper based products

(Browne, 2011). Integrating new high added-value products is seen as one of the most viable solutions to

allow P&P mills to evolve towards a competitive business model by transforming a conventional mill to an

IFBR that, in addition to pulp and paper products, produces a wide range of products including electricity,

steam and biofuels, from biomass ((FPAC, 2010), (Stuart, 2006)).

Biomass is considered to be an abundant renewable resource that encompasses all organic materials of

vegetable or animal origin. It includes forest woody residues (forest harvesting residues and mill residues),

agricultural residues and municipal solid waste (Bradley, 2010).

P&P mills can take advantage of biomass by diversifying their revenues and reducing fossil energy

consumption. By using mill residues and supplied biomass, these mills could reduce and even supplant the

use of fossil energy by using biomass to fill the power, heat and steam needs of the mill, while diversifying their

product portfolio by integrating high-value bioenergy products. In addition, a major part of industrial biomass

residues comes from the P&P industry and forest management (Gregg and Smith, 2010), such as black liquor

and paper sludge, which provide near-zero cost raw materials (Jeffrey Benjamin et al., 2009). Converting

these residues into bioenergy products would not only help the company diversify its product portfolio, but also

reduce its waste disposal costs.

So, P&P mills already have an available logistical infrastructure and a set of generated residues for processing

biomass in order to produce higher-valued products (Stuart, 2006). This predisposition of P&P mills to host

bioenergy investments makes the integration of such investments more advantageous, in terms of investment

costs, than building a bioenergy stand-alone plant (Huang et al., 2009).

Biomass can be used to produce a set of high-value products including bioenergy, biomaterials and

biochemical products (FPInnovations, 2011). In this work, we are interested in the bioenergy pathway.

Bioenergy is a source of energy obtained from the decomposition process of organic materials in biomass, and

by the combustion of combustible materials released, which encompasses biofuels, power and heat (IEA,

2009). To produce bioenergy, a set of technologies is already available. In (Saidur et al., 2011), the principal

avenues to convert biomass into bioenergy are presented, including all available pathways to produce heat,

electricity and biofuels. The maturity of these technologies varies between commercial scale and pilot or

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demonstration projects (Bradley et al., 2009). In (de Wit et al., 2010), the degree of maturity of different

bioenergy technologies has been assessed, in terms of efficiency, investment and operational costs. The

authors have shown the enormous potential of technological development for bioenergy, and substantial cost

reduction, enhanced by government incentives and bioenergy increasing demand. Even for demonstration

scale technologies, their efficiencies have been proven and they would be ready for commercialisation

between 2010 and 2025 (IEA, 2009).

As our objective is to assess the viable bioenergy opportunities for investing, we only consider the bioenergy

technologies that are already commercialised or ready for commercialisation ((IPCC, 2011); (Bradley, 2010)).

The Canadian P&P mills should transform their business models in order to thrive while faced with the decline

of paper demand and uncertain status of fossil energy. The IFBR business model is seen as a promising

pathway to help those companies face the economic and market-related challenges. Environmental policies

and community pressure regarding greenhouse gas emissions could greatly affect the business model of the

P&P sector. Considered as big greenhouse gas emitters, P&P mills could be forced to seriously reduce their

emissions if political and social pressures increase. IFBR transformation would help P&P mills be well

prepared for eventual changes, as it contributes to the supplanting of fossil energy and reduces greenhouse

gases. On the other hand, as energy supplying represents almost a quarter of the P&P mill operational costs,

the uncertainty related to energy prices would be a major factor in operational profitability. By allowing the mill

to become energy self-sufficient, the IFBR may represent a viable solution and a hedge against the energy

market uncertainty. An IFBR, in the case of the P&P sector, would integrate bioenergy production into

conventional P&P activity by using supplied and plant-generated biomass and transforming it into high-value

bioenergy products. Fossil energy and power needs, as natural gas and electricity, could be supplied from

outside or satisfied internally by bioenergy production, allowing the IFBR to be energy self-sufficient.

Heat and electricity cogeneration is already a tradition in Canadian P&P mills. In 2009, more than 51% of the

thermal needs and 22% of the electricity needs of Canadian P&P mills were generated from biomass

cogeneration, which places the P&P sector as the first sector using biomass cogeneration in the whole of

Canada, with 31% of the total cogeneration capacity (Nyboer and Groves, 2012). Mill residues as black liquor

and on-site biomass residues are principally used to produce cogenerated electricity and heat, which is not

always the most valuable way to convert that biomass (FPInnovations, 2011). One of the advantages of

transforming P&P mills into IFBRs is to optimally balance the use of biomass between the different available

bioenergy pathways.

In Figure 3.1, we present the value creation network of a standard IFBR. The biomass supplied could be

industrial residues from other forest mills like sawmills and other P&P mills, including chips that could be used

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for both P&P or bioenergy production, agricultural residues from farms, forest residues generated by

harvesting activity, or even urban waste residues from municipalities. Chips are the only biomass source that

could be used to produce both P&P conventional products and bioenergy products. The other biomass

sources would be used to produce only bioenergy products. The technologies considered in the IFBR are

Fermentation to produce Bioethanol, Pelletization to produce Pellets, Pyrolysis to produce Pyrolysis Oil,

Digestion to produce Biogas, Cogeneration to produce Electricity and Steam, and Gasification to produce

Synthetic Gas. Synthetic Gas could be further processed to produce Fischer-Tropsch Diesel by Fischer-

Tropsch Synthesis technology, or to produce Synthetic Natural Gas by Methanation technology. We also

consider that P&P activity generates two by-products: Black Liquor and Paper Sludge issued from the pulping

process. These two by-products could be used to produce bioenergy. In addition, we consider the Lignin

residue, a by-product of Fermentation, and Naphtha, a by-product of F-T Synthesis. Lignin and Naphtha are

considered as co-products that could be sold to the chemical market (FPInnovations, 2011).

In Canada, bioenergy investment, particularly when integrated within the forest companies, is considered as

an avenue to help those companies thrive during the crisis (FPAC, 2010). An increasing number of forest

companies have been investing in pilot projects and even commercial plants to produce bioenergy (Bradley,

2010). Therefore, there is already a need to further explore the profitability of the bioenergy pathway, in order

to allow forest companies to profit from the increasing demand in bioenergy in the near future, which would be

much more than the available bioenergy capacities according to recent studies(IEA, 2010).

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Figure 3.1 IFBR value creation network

For the IFBR, the demand markets are, besides the conventional P&P market, the oil industry, chemical

industry, power generation distributors, etc. In this work we consider that these markets are the principal

consumers of the intermediate biofuels and chemicals that the IFBR could produce.

There is already a growing demand for bioenergy products in North America and Europe, which would be

further enhanced by technological development of bioenergy technologies allowing IFBRs to offer market-

competitive substitutes for fossil-based fuels and chemicals (IEA, 2011). Bioenergy supportive polices could

also actively contribute in driving the creation and development of a steady demand for bioenergy products

through regulation and quotas (IEA, 2011).

In order to reduce greenhouse gases and fossil energy dependence, the Canadian government has launched

a number of bioenergy incentive programs, such as carbon tax on fossil fuels, biofuel blending quotas and

bioenergy investment subsidies. However, some barriers still exist for bioenergy investments such as lack of

bioenergy-related data and the uncertainty about economic profitability and investment scale for bioenergy

(IEA, 2010).

Besides being eco-friendly, investments in bioenergy have to be economically viable to insure its durability.

Moreover, to support bioenergy development, financial analyses are essential, since capital costs represent

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35% to 50% of total bioenergy costs (IEA, 2011). Bioenergy investments require the mobilisation of important

financial funds, thus it would be essential to assess their profitability by considering all the incurred costs over

the entire value creation network and throughout long-term planning horizons (Martel et al., 2005).

As shown above, a set of bioenergy production technologies are available, different biomass sources could be

used, some bioenergy products could be processed to produce other bioenergy products, and the P&P activity

directly affects bioenergy production by its generated residues that could be used to produce bioenergy

products.

Our contribution in this work is to assess and decide on the following: Which technologies should be

embedded? What would the timing of embedding be? Which biomass sources should be used in each

technology? What would the production capacity of each technology be? And how could the P&P activity to

ensure an optimal synergy with bioenergy production be managed?

To answer these questions, we propose a mathematically-based framework, which aims to help stakeholders

in designing a value creation network for forest products integrating bioenergy, particularly in the case of P&P

mills. The output would be a road map for investments in bioenergy, maximising the financial value of the IFBR

over a long-term planning horizon while ensuring an optimal operating activity for the conventional P&P plant.

The remainder of the paper is organised as follows. In Section 3.2, we present a review of the principal

previous works done in biorefinery designing and integrating bioenergy into P&P mills. Section 3.3 is devoted

to a description of the methodology that we have undertaken to develop our mathematically-based framework.

In Section 3.4, we present the different components of our mathematical model. A summary and discussions

of the results are provided in Section 3.5. Finally, we conclude our work by discussing the overall results and

presenting suggestions for future research.

3.2 Literature Review

This section is structured as follows. First, we discuss the research works dealing with supply chain design

integrating bioenergy. Then, we review the literature focusing on the potential of integrating biomass and

producing bioenergy within P&P mills. A third subsection is devoted to a discussion of the gaps found in

pervious literature as well as to highlighting the contribution of the paper.

3.2.1 Supply chain design integrating bioenergy

Since the potential of biorefining has been proven as a promising strategy for the forest industry to diversify its

revenue sources and remain competitive ((FPInnovations, 2011), (Stuart, 2006), (V Chambost et al., 2008),

(Larson et al., 2006)), several research projects have studied the problem of integrating biomass into

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biorefining supply chains. In (Lakovou et al., 2010), the authors have presented a summary of the supply

chains transforming biomass into bioenergy and the different levels of integrating biomass in the supply chains

as biomass availability, harvesting site allocation and bioenergy plant location. In (Jenkins and Sutherland,

2009), the supply chain of biomass to a bioenergy plant has been studied. By considering several options in

each of the three supply stages, harvesting, transport and storage of biomass, the objective is to decide on the

optimal configuration of the supply chain, while considering the whole network. In (Rentizelas et al., 2009),

three different biomass storage scenarios have been compared to assess obtained biomass quality supplying

a cogeneration plant. Other papers have proposed decision support systems, for bioenergy supply chains, with

different optimisation objectives. The decision support tool developed in (Freppaz et al., 2004) aims to decide

the capacities and locations of a cogeneration plant and the biomass flows supplied in each period, in order to

meet the demand of a number of municipalities in electricity and heat, while minimising the investment and

operations costs. In (Frombo et al., 2009), a decision support optimisation module has been proposed to

design a value creation network of electricity and heat. By considering four different ways to produce electricity

and heat, and three different types of biomass, forest residues, agricultural residues and urban waste residues,

the performance of each network configuration is assessed. The objective is to decide the quantity of each

type of biomass supplied annually and the installed production capacity, while minimising the associated

logistic costs.

There are several works in the literature that have considered scenario simulation of different biorefinery

designs, to assess the profitability of investing in bioenergy ((Laser et al., 2009a), (Laser et al., 2009b)).

Nevertheless, few works exist that have considered mathematical approaches in designing biorefineries, while

integrating the strategic and the tactical levels. In (Ekşioğlu et al., 2009) a mixed integer-programming model

has been proposed, which optimises strategic decisions (location, number and capacities of plants and

collection sites) as well as tactical decisions (flows of biomass, quantity of bioethanol produced) for a

bioethanol logistic network. In a multi-period model (Huang et al., 2010), a set of strategic decisions have been

optimised, such as location and capacity of bioethanol plant, as well as a number of tactical decisions including

biomass supplied and flows of final products, while considering the possibility of adding ethanol production

capacity over the twenty-year planning horizon. The authors consider future changes for several parameters,

such as increasing bioethanol demand over the periods, and a capacity-dependent production cost.

In recent years, there has been an increasing awareness of the potential of integrating biomass into the P&P

mill supply chain in order to propose new high value-added products and regain their competitiveness. In the

following subsection, we review the major works dealing with this issue.

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3.2.2 IFBR potential for P&P mills

Biomass integration within the value creation network of P&P mills has recently attracted the interest of many

researchers and forest-industry strategy experts, in order to detect the root causes of the tough economic

situation of P&P companies, and to assess the economic and environmental potentials of IFBR, judged as

being one of the viable ways to ensure their competiveness (Stuart, 2006). In (Thorp, 2005), the limits of the

traditional business model of the U.S. P&P industry have been discussed, based on an economy-of-scale

production of P&P products and selling them as commodities. A new business model embracing the IFBR

concept could, if economical, offer to the forest industry companies a unique opportunity to create a

competitive advantage over both the conventional P&P companies and the conventional suppliers of fossil-

based chemicals and fuels. By creating a new value proposition integrating bioenergy products, P&P

companies could gain access to a set of growing markets requiring bio-based products to substitute for the

fossil-based products.

In Canada, there is growing interest in transforming P&P mills into IFBRs by exploring the integration of

bioenergy products into their core business, aiming to ensure more revenues from higher value-added

products, besides conventional P&P products (Rodden, 2008). Nevertheless, there are different risks

associated with that transformation, such as technical, economic and commercial risks, which should be

assessed and mitigated, while evolving to the new business model (Jeffrey Benjamin et al., 2009). Different

authors have developed strategic frameworks taking into account these risks in the conversion of P&P mills

into IFBRs. A three-phase strategic approach has been developed in (V Chambost et al., 2008) in order to

allow a step-by-step transition of the business model of the P&P mill, while mitigating the risks and maximising

the generated margins. In a complementary work (Mansoornejad et al., 2010), a hierarchical methodology has

been presented to support the product portfolio definition and technology selection strategies, while building

the IFBR supply chain design. A margins-based supply chain operating policy has been developed as the core

of this methodology. After addressing the challenges facing global P&P mills, a five-step dynamic strategic

framework for P&P mills has been developed in (Pätäri et al., 2011) to evolve towards a competitive business

model. The biorefinery strategy has been identified as one of the main emerging business opportunities,

allowing P&P mills to gain a sustainable competitive advantage.

While a number of papers have undertaken assessing the IFBR concept applied to P&P mills by developing

strategic frameworks, few works have tackled the transformation of P&P mills into IFBRs, by using modelling

methodologies in order to obtain an optimal supply chain design as an output. In (Huang et al., 2009), three

IFBR scenarios have been compared by developing process models for a pulp mill-based biorefinery. The only

bioenergy technology considered was the bioethanol production by a hemi-cellulose pre-extraction from wood

chips, which would be used to produce pulp after the extraction. In (Feng et al., 2012), a mathematical

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modelling approach has been developed to maximise the net present value of investments in bioenergy, over

a planning horizon of three years. The authors consider the whole forest product supply chain network, and the

bioenergy investments could be made within P&P mills, sawmills or even in stand-alone plants. The bioenergy

technologies considered have been pellets production, cogeneration, and bioethanol production. The objective

is to optimise the financial value of investments in bioenergy embedded in the first period of the planning

horizon.

There have been other works dealing with the financial performance of the transformation of P&P mills into

IFBRs. In (Consonni et al., 2009), the internal rate return of gasification-based technology integration within a

Kraft P&P mill has been obtained under two future energy-price scenarios. In (Moshkelani et al., 2013), the

economics of integrating lignin and hemicellulose extraction and biomass gasification technologies within the

P&P industry have been assessed, while developing an energy optimisation methodology to improve the

energy efficiency of the resulting IFBR. In (Phillips et al., 2013), three alternatives of integrating bioethanol

production with P&P production have been simulated, using a financial model to back-calculate the minimum

ethanol revenue required to ensure a predefined internal rate return to the investment.

3.2.3 Paper contribution

In recent years, there has been an increasing amount of literature on the design of supply chains integrating

bioenergy and a number of bioenergy-related issues have been addressed such as biomass supplying and

storage activities, bioenergy technology selection, location and capacity of the biorefining plant. In addition,

there have been a considerable number of contributions emphasising the need to transform the forest

companies’ value chains while developing strategic approaches to optimise that transformation and give the

forest decision-makers useful tools to achieve successful transformations.

Meanwhile, when evaluating the literature done regarding IFBR design and assessment of the bioenergy

investment potential for P&P mills, one should note the lack of works tackling the design of the entire value

creation networks integrating bioenergy. The works dealing with the biomass supplying chains considering

different biomass types, have demonstrated less interest in the bioenergy technology selection issues. The

literature tackling the technology selection issues has essentially focused on the plant level by simulating the

viability of different bioenergy processes without integrating the whole value chain. Most of the mathematical

models proposed to optimise the profitability of the whole supply chain design integrating bioenergy have not

considered all the possible avenues related to biomass sources, bioenergy technologies and demand markets.

We believe that mathematical modelling is a core element of any decision tool to support the transformation of

forest companies, as it brings a quantitative evaluation of the profitability of different transformation pathways.

However, to make it really advantageous over qualitative methods, the mathematical model should take into

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account the whole value network, while being integrated into a holistic transformation approach aiming to feed

the model with viable inputs and transform the numerical results into a useful decision-support method.

The objective of this paper is to propose a mathematically-based framework that integrates the strength of

mathematical modelling to supply viable numerical outputs, as well as the power of strategic approaches

providing a useful methodology to support the transition of forest companies, when considering bioenergy

investments.

Our contribution is then to develop a decision-support methodology, based on mathematical programming,

which helps forest stakeholders optimise the strategic design of a P&P company aiming to integrate bioenergy

investments, while considering different bioenergy technologies and different biomass sources in deciding on

the technologies to embed, the capacity options to add, and the timing of investment, over a long-term

planning horizon. The other originality of the present work is to build an optimal roadmap of bioenergy

investments for a set of given realistic data, over the planning horizon, while managing the P&P activity, in

order to maximise the financial value of the so called IFBR in an evolving future.

3.3 Methodology

In the previous section, a number of research works have been interested only in developing mathematical

models for designing IFBRs, while some other works have developed strategic approaches serving as

guidelines to transform P&P mills to IFBRs. For the reviewed mathematical models, we have noted a lack of

detailed analyses assessing the technical feasibility and the adaptability of the products and technologies

evaluated in the mathematical model, in the Canadian context, in Quebec particularly. Thus, our motivation is

to build a holistic approach that adapts mathematical modelling to the particular context of the Quebec P&P

mills and embraces both the qualitative and the quantitative aspects of the bioenergy supply chain design. The

qualitative aspect is covered by defining what we have called “initial pool”, in which we have pre-selected a

number of technologies, products, raw materials, as well as other supply chain components that fit the P&P

mill sector in Quebec. Therefore, the construction of a real database has been essential to ensure a viable

quantitative analysis through the model solving.

The methodology that we have undertaken, to develop the mathematically-based framework, encompasses

four principal steps: the initial pool definition, the real database construction, the mathematical model, and

finally the investments roadmap (Figure 3.2).

Our objective is not to limit our work to an abstract mathematical model, but rather to develop a

comprehensive approach highlighting the choices and the assumptions made in the model. Therefore, the aim

is not to discuss the optimal solution to a given data configuration, but rather to propose a decision-support

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framework helping P&P investors and stakeholders better understand the challenges facing P&P companies in

their transformation into IFBRs and recommend a useful methodology.

In the following, we detail the four steps of our methodology.

3.3.1 Initial pool definition

As mentioned in the first section, several configurations are available to transform the P&P mill into an IFBR.

There are different types of biomass that could be used, and several technologies, with different ranges of

conversion rates, which could transform each type of biomass into a number of bioenergy products. Thus,

several recipes are possible to produce a set of bioenergy products. A biomass type and a conversion rate

characterise each recipe. Only the proven recipes found in the literature are considered in this work

(Appendix A).

These different possible configurations make deciding on the right configuration an arduous task. Thus, in this

first step, our aim is to pre-select a set of feasible configurations by keeping the ones that are feasible for the

Canadian P&P mills. To perform this task efficiently, we have referred to the related reports and case studies

dealing with the Canadian context.

Therefore, we have chosen the biomass types that are available in Quebec and adapted for use in P&P mills.

We have then considered the industrial residues coming principally from sawmills such as chips and sawdust,

the agricultural residues coming from Quebec farms including wheat straws and corn stover, the forest

residues including harvesting roadside residues, barks and branches, and the municipal waste residues

including organic waste residues. At the level of the P&P mill, we have considered black liquor and paper

sludge as two by-products generated from P&P production activity (see Figure 3.1).

For bioenergy products and technologies, we have selected the technologies whose feasibility has been

proven in the North American context, particularly in the forest industry. For the bioenergy products that we

have considered, the conversion rate and the production cost are judged to be economically viable, and there

is already an increasing demand for them. Thus, the bioenergy production technologies we have considered

are Cogeneration, Pelletization, Fermentation, Digestion, Pyrolysis, Gasification, Methanation and F-T

Synthesis.

The choice of capacity options, for each technology, has been based on real embedded capacities in

integrated biorefineries in North America to make sure that the bioenergy capacities added really fit well with

the demand volume. We have also considered economies of scale for investment costs and production costs

based on real case studies (Tijmensen et al., 2002). The choice of the planning horizon, the financial horizon,

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the fiscal lifetime and the economic lifetime, has been carefully calibrated to be appropriate with the design of

such a value creation network.

The choice of the markets has been made to host the flows of bioenergy products. Therefore, the energy

market would be the destination of cogenerated electricity and a set of bioenergy products that could be used

to generate power and heat. The chemicals market would host the bioenergy products that could be used to

process chemical products to substitute fossil-based feedstock. Finally, the biofuel market would host the

bioenergy products that would replace the fossil-based fuels. Obviously, the conventional P&P market would

remain a principal destination for the conventional P&P products of the mill.

3.3.2 Relevant database construction

In order to obtain a useful decision-support methodology, it was essential to feed the optimisation model with

relevant-data parameters. Thus, we have collected and assessed data from government reports, multinational

organisation researches, specialised biomass magazines, and recent academic works. For several parameters

used in our mathematical model, we have found different values or future forecasts. We have constructed

intervals based on these values and we have used the average value of these intervals as inputs. The

collected data have allowed us to obtain realistic values for the different parameters of the model, including

biomass availability, biomass supplying cost, conversion rate, investment cost, operational cost, P&P activity

closing cost, electricity consumption, plant-gate product prices, the different demand estimations, as well as

the future trends for the parameters evolving over the planning horizon, in the case of a P&P mill based in

Quebec (see Appendix A).

For some parameters for which we have not found real values, we have used formulas to obtain them, such as

estimating some biofuel prices based on their lower heating value (NETL, 2009), or deducing the plant-gate

prices from market prices (USDE, 2011).

For other parameters, for which we have not been able to find real value or even a realistic estimation in the

literature, we have used an approximation while trying to make a realistic approximation as much as possible.

In order to estimate the future trend for the parameters that evolve over the periods, we have used several

reports publishing bioenergy development outlooks over the next decades ((IEA, 2009), (IPCC, 2011), (ORNL,

2011), (Hacatoglu et al., 2010)). For the future trends not found, we have used personal assumptions. To

estimate the demand of bioenergy products, for which we have not found any estimation in literature, we have

used random values where the lowest and highest considered capacity options have been used as interval

bounds for the generated random value. For the products and technologies, for which almost all the

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parameters should be approximated, we have decided not to consider them in the model. This was the case of

“Pyrolysis” technology.

Our objective, via a realistic database construction, is to obtain a realistic solution, which would really help the

forest industry decision makers optimise their decisions regarding the transformation of P&P mills in a

competitive IFBR.

3.3.3 Mathematical model

Once the real database was constructed, based on the best pre-selected configurations, we developed a

mixed integer-programming model, to maximise the financial value of the IFBR over the defined planning

horizon. Besides the standard costs included in supply chain design, such as cash-flow and annualised

investment cost, we have integrated more detailed financial analysis tools, like tax rate, depreciation, debts,

and the estimated residual value of the IFBR at the end of planning horizon. The objective of the mathematical

model is to maximise the objective function, described above, under a number of constraints to ensure feasible

solutions. The model developed represents the centrepiece of the methodology, since it connects the

qualitative step in which we have chosen the elements and the assumptions to consider in the design with the

quantitative output in order to obtain an investment roadmap. The next section is devoted to a description of

the mathematical model in detail.

3.3.4 The investments roadmap

The roadmap of investments is the principal output of the mathematical model. It prescribes the bioenergy

technologies to be embedded and the timing of capacity options added, during the planning horizon. To decide

on the most profitable investments, tactical decisions regarding raw material and finished product flows over

the planning periods are also made.

The obtained planning of long-term investments in bioenergy maximises the financial value of the developed

IFBR, by optimising the bioenergy production and the P&P activity. This planning takes into account the

evolution of several parameters over the periods of the planning horizon, such as biomass availability,

technologies maturity, bioenergy demand and energy market price. The obtained roadmap constitutes a first

strategic step to help stakeholders ensure a viable transition of a conventional P&P towards a profitable IBFR.

Obviously, only the decisions made for the first planning cycle would be implemented. The objective of such an

approach is to anticipate eventual changes in a technical and economic environment over a long planning

horizon, which allows decision-makers to be proactive in deciding investments in bioenergy.

A subsection will be dedicated to detailing the obtained roadmap in which we highlight and discuss the most

important results obtained.

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Figure 3.2 IFBR design methodology

3.4 Mathematical model

By considering a P&P mill, producing conventional P&P products, our purpose is to optimise the investment

timing in bioenergy products over a planning horizon H=20 years. The developed model aims to maximise the

financial value of the IFBR at the end of the planning horizon. Since investments in bioenergy require

substantial financial funds, we have performed a detailed financial analysis including accounting and fiscal

depreciation, tax rate, discount rate, salvage value and the debts at the end of H, besides the traditional

analysis, which includes operational and investments costs.

To decide which technology to embed, which capacity option to add, and when to add that option, we have

had to optimise anticipated tactical decisions, in each period, including the quantity of biomass supplied, the

quantity of bioenergy products produced, the flows of bioenergy products and by-products within the IFBR and

to the demand markets, and the quantity of P&P products produced and shipped to the P&P market.

The financial value of the IFBR at the end of the horizon is the sum of the actualised financial cash flow and

the salvage value actualised at the end of H.

In this work, we consider a deterministic model with predetermined parameters which evolve over all the

periods of the planning horizon to take into account the technical and the economic evolution regarding the

bioenergy development, such as conversion rate, investment cost, production cost, and bioenergy demand.

The model aims to optimise the value creation network of forest products, including P&P products and

bioenergy products. The P&P activity and the bioenergy activity are interdependent, in the sense that P&P

activity generates a number of by-products, such as black liquor and paper sludge, which could be used to

generate bioenergy. On the other hand, some bioenergy products generated by the technology embedded,

such as electricity, steam and natural gas, could be used to fulfil the mill energy needs. Besides bioenergy

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products, a number of technologies generate some bioenergy by-products which could further be used in the

mill to generate bioenergy products or could be sold directly to the market.

Thus, during the planning horizon, we have to decide jointly about bioenergy activity and P&P activity. There

are two types of planning periods: A five-year period in which we decide about strategic investments in

bioenergy technologies. The choice of a five-year interval is due to the fact that the five-year period is widely

used in international reports to estimate the technical and economic change regarding bioenergy development

((IEA, 2010), (IPCC, 2011)). A one-year period is used to decide to keep running the P&P activity or not, while

assuming an operating cost and a closing cost. This one-year period is also used to anticipate a number of

tactical decisions regarding the product flows throughout the IFBR supply chain.

To assess well the profitability of the IFBR, we consider strategic costs including investment costs, accounting

and fiscal depreciation, debts and salvage value. In addition, we consider a number of operational costs

including supplying costs and production costs.

We consider a fixed discount rate to get actualised costs and revenues, in order to discount all future cash

flows and obtain their estimated present value.

3.4.1 Model assumptions

While developing the model, a number of assumptions are made:

Economies of scale have been considered for bioenergy investment costs and production costs. The

scaling factor has been set at 0.7 (Tijmensen et al., 2002). Thus, the production capacity installed is

inversely proportional to the unit investment and operation cots.

All the steam produced by cogeneration in the mill is used to fulfil mill steam needs. Thus the steam

flows are not included in the model. Only the electricity flows are considered.

All the space needed to embed potential bioenergy technologies is available. So, no space constraint

is added to the model.

For the bioenergy investments, the accounting depreciation as well as the fiscal depreciation, are split

linearly during the planning periods.

No additional investments are considered for the P&P activity. Furthermore, the studied pulp mill

initial assets are considered to be already completely depreciated.

95

The biomass supplying costs include transportation costs within 100 kilometres (Magdzinski, 2006).

Therefore, only the estimation of the biomass available within this distance is considered in the

model.

For each bioenergy product considered in the model, different production recipes are possible. Every

recipe is characterised by a biomass feedstock and a conversion rate.

The bioenergy investments are irreversible. Once embedded, a technology cannot be shut down

during the remaining periods of the planning horizon.

The P&P activity can be shut down, for one or several periods, if it is judged unprofitable by the model

while considering the estimated closing and restarting costs.

Some bioenergy products can be further processed and used as inputs to produce other bioenergy

products (see Appendix A).

A number of by-products generated from P&P activity and bioenergy production can be used as

inputs to produce bioenergy products or sold directly to the market as co-products.

The different parts of the model, including sets, parameters, decision variables, costs and revenues, objective

function and constraints, are presented in the following.

3.4.2 Sets

T : Number of periods;

1..H T : Planning horizon expressed in periods;

C : Number of cycles;

1..Cycles C : Planning horizon expressed in cycles;

RM : Set of raw materials (biomass);

INTP : Set of generated by-products;

FINP : Set of bioenergy products;

Options : Set of capacity options;

96

PP : Set of P&P (pulp and paper) products;

S : Set of biomass suppliers;

G : Set of bioenergy technologies;

M : Set of demand markets.

3.4.3 Parameters

FH : Financial horizon (period of repaying debts);

EL : Economic lifetime (period of accounting depreciation);

FL : Fiscal lifetime (period of fiscal depreciation);

LP : Number of periods in a planning cycle;

BG : A big number;

TR : Tax rate;

r : Discount rate (capital rate);

, ,i t nCSUP : Supplying cost of biomass i RM , in period t H , from supplier

n S ;

, ,i t nB : Quantity of biomass i RM , available in period t H , from a supplier

n S ;

cBd : Available budget in cycle c Cycles ;

, ,ELEC n ie : Electricity consumption per unit of capacity installed of technology

" "n G p to produce i FINP PP ;

FCP : Operating fixed cost of P&P activity;

97

, , ,i t j n : Conversion rate of i RM FINP INTP , in period t H , to

produce j FINP by technology n G ;

, ,o n cCA : Investment cost of implanting the option o O of the technology n G ,

in cycle c Cycles ;

pb : Closing cost of P&P activity" "p ;

,o nK : Capacity of the option o O of the technology n G ;

pcapP : Capacity installed of the P&P activity" "p ;

,i tCUP : Unit production cost of i INTP FINP PP , in period t H ;

,i j : Proportion of generating by-product i INTP by producing

j FINP PP ;

,i tP : Selling price (plant-gate price) of i INTP FINP PP , in period

t H ;

, ,i t md : Expected demand of i INTP FINP PP , in period t H , for a

demand market m M .

3.4.4 Decision variables

Binary variables

, ,o n cX =1 if the capacity option o O of the technology n G is added in cycle c Cycles , 0

otherwise.

,p tZ =1 if the P&P activity is operating in t H , 0 otherwise.

Continuous variables

98

, , , 'i t n nFB Flows of biomass i RM , in period t H , which are shipped from supplier n S to

technology 'n G ;

, , , 'i t n nFC Flows of by-products i INTP , in period t H , generated by the technologies

" "n G p to other technologies 'n G or market 'n M ;

, , , 'i t n nFFP Final product flows i FINP , in period t H , from technologies n G , to other

technologies ' " "n G p , or to the demand markets 'n M ;

, ,i t pQP Produced quantity of P&P products i PP , in period t H , by P&P activity " "p ;

, ,i t nQBio Produced quantity of bioenergy products i FINP , in period t H , by technologies

n G .

In Figure 3.3, we present a graph in which the decision variables are represented spatially over the IFBR

supply chain, from the suppliers to the markets.

99

Figure 3.3 Decision variables over the IFBR supply chain

3.4.5 Costs and Revenues

In this section, we present the different costs and revenues figuring in the objective function.

3.4.5.1 Actualised sales of P&P products

The actualised sales of P&P products are given by the product of the selling price, ,i tP , and the quantity

produced per period, , ,i t pQP , discounted using the discount rate r .

, , ,

,

.Re

1i t i t p

tt H i PP

P QPvPPAct

r

(1)

3.4.5.2 Actualised production cost of P&P products

The actualised production cost of P&P products is given by the product of the unit production cost, ,i tCUP ,

and the quantity produced per period, , ,i t pQP , discounted using the discount rate r .

, , ,

,

.Pr

1i t i t p

tt H i PP

CUP QPodCostPPAct

r

(2)

3.4.5.3 Actualised operating fixed cost of P&P activity The actualised operating fixed cost of P&P activity is equal to the operating fixed cost of P&P activity, FCP, if

the P&P activity is operating in that period ( ,p tZ =1), discounted using the discount rate r .

,.

1p t

tt H

FCP ZFixCostPPAct

r

(3)

3.4.5.4 Actualised closing cost of P&P activity

The actualised closing cost of P&P activity is equal to the closing cost in that period, pb , if the P&P activity is

not operating in that period ( ,p tZ =0), discounted using the discount rate r .

,. 1

1p p t

tt H

b ZClosCostPPAct

r

(4)

100

3.4.5.5 Actualised bioenergy sales revenues

The actualised bioenergy sales revenues are given by the product of the selling price, ,i tP , and the sum of

bioenergy product flows, from the different technologies to the markets, , , ,,

i t n mn G m M

FFP , discounted using

the discount rate r .

, , , ,,

,

.Re

1

i t i t n mn G m M

tt H i FINP

P FFP

vBioActr

(5)

3.4.5.6 Actualised co-products sales revenues

The actualised co-products sales revenues are given by the product of the selling price, ,i tP , and the sum of

co-products flows, from the different technologies including P&P activity to the markets, , , ,

" ",i t n m

n G p m M

FC

, discounted using the discount rate r .

, , , ," ",

,

.Re

1

i t i t n mn G p m M

tt H i INTP

P FC

vCoActr

(6)

3.4.5.7 Actualised bioenergy production costs The actualised production cost of bioenergy products is given by the product of the unit production cost,

,i tCUP , and the sum of quantities produced by all the embedded technologies per period, , ,i t nn G

Qbio ,

discounted using the discount rate r .

, , ,

,

.Pr

1

i t i t nn G

tt H i FINP

CUP QbioodCostBioAct

r

(7)

3.4.5.8 Actualised biomass supplying cost

The actualised supplying cost of biomass is given by the product of the unit supplying cost, , ,i t nCSUP , and

the sum of biomass flows to the different embedded technologies, , , , ''

i t n nn G

FB , discounted using the

discount rate r .

101

, , ' , , , ''

, ,

.

1

i t n i t n nn G

tt H n S i RM

CSUP FBRMCostBioAct

r

(8)

3.4.5.9 Actualised fiscal depreciation of bioenergy investments The actualised fiscal depreciation of bioenergy investments is equal to the sum of bioenergy investment costs,

for the technologies already embedded, CAo,n,i1. X

o,n,i1 Xo,n,i

nG,oO , annualised, over the planning

periods, by dividing it by the fiscal lifetime FL, over the planning horizon, and discounted using the discount

rate r .

DepFiscAct CA

o,n,i1. Xo,n,i1 X

o,n,i nG,oO

FL. 1 r tti .LP1

T

i0

C1

(9)

3.4.5.10 Accounting depreciation of bioenergy investments The accounting depreciation of bioenergy investments is equal to the sum of bioenergy investment costs, for

the technologies already embedded,

CAo,n,i1. X

o,n,i1 Xo,n,i

nG,oO , annualised by dividing it by the

economic lifetime EL, over the planning cycles.

DepAcc CA

o,n,i1. Xo,n,i1 X

o,n,i nG,oO

ELti .LP1

T

i0

C1

(10)

3.4.5.11 Total investment cost for bioenergy The total investment cost for bioenergy is equal to the sum of bioenergy investment costs, for the technologies

already embedded, over the planning cycles.

InvTot CAo,n,c. X

o,n,c Xo,n,c1

nG,oO,cC (11)

3.4.5.12 Investment cost considered over the periods of the planning horizon The investment cost for bioenergy, considered for the planning horizon, is equal to the sum of bioenergy

investment costs, for the technologies already embedded, CAo,n,i1. X

o,n,i1 Xo,n,i

nG,oO , which is

annualised, over the planning periods, by dividing it by the financial horizon FH, over the planning cycles.

102

InvHorizonCA

o,n,i1. Xo,n,i1 X

o,n,i nG,oO

FHti .LP1

T

i0

C1

(12)

3.4.5.13 Actualised investment cost considered over the periods of the planning horizon The investment cost for bioenergy, considered for the planning horizon, is equal to the sum of bioenergy

investment costs, for the technologies already embedded, CAo,n,i1. X

o,n,i1 Xo,n,i

nG,oO , which is

annualised, over the planning periods, by dividing it by the financial horizon FH, over the planning cycles, and

discounted using the discount rate.

InvHorizonAct CA

o,n,i1. Xo,n,i1 X

o,n,i nG,oO

FH . 1 r tti .LP1

T

i0

C1

(13)

3.4.5.14 IFBR debts in the end of the planning horizon The debts of the IFBR in the end of the planning horizon are equal to the total investment cost for the

bioenergy technologies InvCost, minus the investment cost for bioenergy incurred by the company over the

planning horizon, InvHorizon.

Debts InvTot InvHorizon (14)

3.4.5.15 Actualised net cash flow of the IFBR The actualised net cash flow of the IFBR, is equal to the sum of the actualised net operating profits of

bioenergy activity, the actualised net operating profits of the P&P activity, and the proportion of actualised

refundable fiscal depreciation .TR DepFiscAct , minus the actualised investment cost over the planning

horizon.

1 . Re Pr

+ 1 . Re Re Pr + .( )

NetCFAct TR vPPAct odCostPPAct FixCostPPAct ClosCostPPAct

TR vBioAct vCoAct odCostBioAct RMCostAct

TR DepFiscAct InvHorizonAct

(15)

103

3.4.5.16 Salvage value of the IFBR at the end of the planning horizon The salvage value of the IFBR, at the end of the planning horizon, is equal to the total investment cots for

bioenergy, InvTot , minus the accounting depreciation, DepAcc, minus the debts, Debts, actualised at the

period T, using the discount rate r.

1 T

InvTot DepAcc DebtsSVT

r

(16)

3.4.6 Objective function

The objective function is to maximise the sum of the actualised net cash flow of the IFBR, NetCFAct, and the

salvage value of the IFBR at the period T, SVT.

Max NetCFAct SVT (17)

3.4.7 Constraints

3.4.7.1 Availability of supplied biomass The flows of biomass residues FMP, which represent the raw materials RM used in the IFBR, cannot exceed

the quantity of biomass B available from suppliers S, in each period t.

, , , , , , ,i t m n i t mn G

FB B i RM m S t H

(18)

3.4.7.2 Logical constraint for non supplied biomass

If the biomass i RM is not used in period t by technology n G , the flows of this type of biomass to that

technology are equal to zero.

, , , , , , . , ,i t m n i t j nn S j FINP

FB BG i RM n G t H

(19)

3.4.7.3 Receipt production of bioenergy products The quantity produced of each bioenergy product i FINP , in each period t, depends on the conversion

rate of inputs consumed. These inputs could be supplied biomass (RM), by-products generated within the

IFBR (INTP), or even other bioenergy final products (FINP).

, , , , , , , , , , , , , ,, , " "

, , , , , ,,

. .

. 0 , ,

i t n j t i n j t m n j t i n j t m nj RM m S j INTP m G P

j t i n j t m nj FINP i m G n

QBio FB FC

FFP I FINP n G t H

(20)

104

3.4.7.4 Electricity flows equilibrium The quantity of electricity produced by cogeneration has to ensure the needs of other technologies and P&P

activity, in electricity, in each period t, depending on the capacities installed in the cycle associated with that

period, ( )c t .

' ', ,' ', ' ', , , , , ( ). . 0

' ', ,

ELEC t COG m ELEC m i o m o m c to O

FFP e K X

m G COG i FINP t H

(21)

' ', ,' ', ' ', , ,. . 0

' ', ,ELEC t COG p ELEC p i p p tFFP e capP Z

m G COG i PP t H

(22)

3.4.7.5 Bioenergy product flow equilibrium Each bioenergy product i FINP produced in each period t, is equal to the sum of its flows consumed in

other technologies and its flows shipped to the market

, , , , , , , ," "

0 , ,i t n i t n l i t n ml G n p m M

QBio FFP FFP i FINP n G t H

(23)

3.4.7.6 By-product availability from bioenergy and P&P products The flows of by-products available for selling (considered as co-products) or for use in other technologies are

generated according to a proportion, α, of the quantity of some bioenergy or P&P products.

, , , , , ,. 0 , ,i t n m i l l t nm G M l FINP

FC QBio i INTP n G t H

(24)

, , , , , ,. 0 ,i t p m i l l t pm G M l PP

FC QP i INTP t H

(25)

3.4.7.7 Capacity of production constraint for bioenergy products The quantity of bioenergy products produced in each period t, and its flows to other technologies and the

market, should not exceed the capacity of production installed in the cycle including that period, ( )c t .

, , , , , ( ). 0 , ,i t n o n o n c to O

QBio K X i FINP n G t H

(26)

, , , , , , ( ). . 0 , , " " ,i t n m o n o n c to O

FFP K X BG i FINP n G m G p M t H

(27)

105

3.4.7.8 Capacity of production constraints for P&P products The quantity of P&P products produced in each period t should not exceed the capacity installed in that period,

if the P&P activity is operating

, , ,. 0 ,i t p p p tQP capP Z i PP t H (28)

3.4.7.9 Investment irreversibility constraint If a technology has already been embedded, it remains embedded over the entire planning horizon.

, , , , 1 0 , ,o n c o n cX X n G o O c Cycles (29)

3.4.7.10 Budget availability constraint The investment cost per cycle cannot exceed a predefined budget

, , , , 1, ,

,. 0 o n c o n c

o n c cn G o O

X XCA Bd c Cycles

C

(30)

3.4.7.11 P&P demand constraint The P&P production, in each period, should not exceed the demand for these products in that period.

, , , , ,. 0 , ,i t p i t m p tm M

QP d Z i PP m M t H

(31)

3.4.7.12 Bioenergy product demand constraint The flows of bioenergy products shipped to the demand markets, in each period, should not exceed the

demand for these products in that period.

, , , , , , ,i t n m i t mn G

FFP d i FINP m M t H

(32)

3.4.7.13 Co-product demand constraint The flows of co-products shipped to the demand markets, in each period, should not exceed the demand for

these products in that period.

, , , , , , ,i t n m i t mn G

FC d i INTP m M t H

(33)

106

3.4.7.14 Non-negativity constraint

, ,

,

, , ,

, , ,

, , ,

, ,

, ,

0,1 , , ;

0,1 ;

0 , , , ;

0 , , " ", ;

0 , , , " " ;

0 , ;

0

o n c

p t

i t n m

i t n m

i t n m

i t p

i t n

X o O n G c Cycles

Z t H

FB i RM t H n S m G

FC i INTP t H n G p m G M

FFP i FINP t H n G m P G M

QP i PP t H

QBio i F

, , .INP t H n G (34)

3.5 Results and Discussion

The mathematical model has been implemented in CPLEX Optimisation Studio 12.3, on a 2.4 GHz dual-core

Intel Core i5 machine, with 4GB of RAM.

The data was implemented in an ACCESS database, linked to CPLEX. Similarly, the optimisation results have

been exported to an ACESS database to simplify the assessment of the output data. In Figure 3.4, we present

a graph that illustrates spatially the sets of the different nodes over the IFBR supply chain, comprising

suppliers, biomass types, bioenergy products, bioenergy co-products, P&P products, P&P by-products,

bioenergy technologies, P&P activity, and demand markets).

107

Figure 3.4 Sets and nodes over the IFBR supply chain

In Table 3.1, we present the time-related parameters values, including the planning horizon, the number of

periods, the number of planning cycles, the cycle length, the financial horizon, the fiscal lifetime, and the

economic lifetime.

Parameter Value Planning horizon 20 years

Number of periods 20 Number of cycles 4 Length of cycle 5 years

Financial horizon 20 years Fiscal lifetime 20 years

Economic lifetime 30 years

Tableau 3.1 Time-related parameters values

The optimal solution was found in less than 30 seconds, under the above configuration. The obtained IFBR

financial value reveals the substantial potential of integrating bioenergy production technologies within P&P

mills. By embedding gradually, over the planning horizon, an integrated forest biorefinery that produces

bioenergy products besides P&P conventional products, the investors could generate an actualised cash-flow

of $512.698 million and an estimated residual value of 79.332 $ million for the IFBR at the end of H, which

gives a total estimated financial value of $592.031 million. The investments made during the planning horizon

depend on the financial funds available over it. In our case, we assume that the stakeholders have financial

funds according to average available budgets found in the literature which allow the company to invest for

108

$789.68 million from which $631.48 million is repaid over the planning horizon. The remaining part, $158.198

million, would be considered as debts of the company. In Table 3.2, we summarise these financial results.

Cost/Revenue Value Total investment cost InvTot $789.68 million

Investment cost over H InvHorizon $631.48 million

Accounting depreciation over H DepAcc 420.98 million

Debts at the end of H = InvTot - InvHorizon 158.198 million

Actualized net cash flow NetCFAct $512.698 million

Salvage value at the end of H SVT $79.332 million

IFBR financial value = NetCFAct + SVT $592.031 million

Tableau 3.2 Summary of financial results

3.5.1 Bioenergy investment roadmap

As we have shown in Section 3.3, the primary goal of the mathematical model is to provide an optimal

roadmap of bioenergy investments during a 20-year planning horizon, aiming to maximise the financial value

of the IFBR while optimally managing the P&P conventional activity. In fact, the roadmap constitutes a

guideline prescribing the optimal pathway to transform a P&P mill into an IFBR.

Under the different assumptions made and the parameters values chosen in this developed model, the

technologies embedded over the planning horizon are: Digestion which produces Synthetic Natural Gas

(SNG1), Fermentation which produces Bioethanol (BE) and generates Lignin (LGN) as a by-product,

Cogeneration which produces Electricity (ELEC) and generates hot steam, as a by-product which is totally

used to fill the IFBR needs in steam, and Pelletisation which produces Pellets (GRAN). The IFBR continues to

produce Pulp to meet market demand. The pulping activity generates two principal by-products: Black Liquor

(BL) and Paper Sludge (PS), which will be used as inputs for bioenergy products.

For this case, the optimal road map for bioenergy investments is presented in Table 3.3. A grey cell means

that the option o O of the technology n G is embedded in cycle c Cycles . For example, the option

“Op3” of technology “Fermentation” is embedded in cycle “1”, with 90 million litres as bioethanol production

capacity per year. In cycle “4”, the option “Op1” is embedded, adding 30 million litres of bioethanol production

capacity for the IFBR, which generates a total bioethanol production capacity of 120 million litres per year. In

the same way, the option “Op2” of technology “Digestion” is embedded in cycle “1”, with 80 million cubic

metres as biogas production capacity. In cycle “3”, the option “Op1” is embedded, adding 40 million cubic

metres as biogas production capacity for the IFBR. For the “Pelletization” technology, the option “Op2” is

embedded in cycle “1” giving a pellet production capacity of 40 thousand tons as production capacity per year.

An additional 20 thousand tons capacity is embedded in cycle “3” by embedding the option “Op1.” To

109

principally fill the needs of the IFBR in power and sell the remaining part to the market, a 480 million kilowatt-

hours “Cogeneration” production capacity is embedded in cycle “1” by embedding the option “Op3”. An

additional 160 million kilowatt-hours’ production capacity is added in cycle “4”.

For the other bioenergy technologies considered in the model, including “Gasification”, “F-T synthesis” and

“Methanation”, they have been discarded from the optimal roadmap essentially for economic considerations. In

fact, biogas produced via “Digestion” was preferred over methane produced via “Gasification”+ “Methanation”

due to its lower investment cost and its use of a MSW, for whose use the company could be paid. For the F-T

diesel, its investment cost of almost three times higher than bioethanol amplified by its lower production yields

was a serious barrier preventing such investment.

The progressive embedding of bioenergy technologies, by adding capacities during the planning periods, is

explained by the increasing demand for bioenergy in the coming years combined to an improvement in

biomass conversion rates and lower bioenergy investments costs. Thus, it would be more profitable for the

IBFR to adapt progressively its bioenergy capacities to the demand and profit from technological and

economic maturity of bioenergy technologies, rather than implement all the bioenergy capacities in the

beginning of the planning horizon, which would generate higher investment costs and lower adaptability to the

market changes.

Tech Cycle1 Cycle2 Cycle3 Cycle4

Op1 Op2 Op3 Op1 Op2 Op3 Op1 Op2 Op3 Op1 Op2 Op3

Digestion 80.106

m3

80.106 m3

40.106

m3 80.106

m3

40.106 m3

80.106 m3

Fermentation 90. 106

liters

90. 106

liters

90. 106

liters

30. 106

liters

90. 106

liters

Cogeneration 480. 106

kwh

480. 106

kwh

480. 106

kwh

160. 106

kwh

480. 106

kwh

Pelletisation 40. 103

tons

40. 103

tons

20. 103

tons

40. 103

tons

20. 103

tons

40. 103

tons

Gasification

F-T

Methanation

Tableau 3.3 Roadmap of bioenergy investments

3.5.2 P&P operational roadmap

For the P&P activity, its optimal operating roadmap would be to shut down the P&P production for three

periods (1, 7 and 17) and keep it operational during the other periods of the planning horizon. For the

110

biorefinery, it would be financially more profitable to produce only bioenergy products during the P&P

shutdown periods.

This operational roadmap for the P&P activity generates revenues of $950.964 million with a total production

that costs more than $595.912 million including $20.587 million as shutdown cost, $208.068 million as fixed

operating costs and 367.257 million as production costs (Table 3.4).

Production cost ($) Fixed cost ($) Closing cost ($) Revenues ($) 367.257 million 208.068 million 20.587 million 950.964 million

Tableau 3.4 Operational financial summary of P&P activity over the planning horizon H

3.5.3 Feedstock and product flows

To decide which bioenergy technology to embed and what capacity option to add in each cycle, we have also

optimised tactical level decisions, made over all the periods of each cycle, by determining the biomass flows

supplied, the quantity of bioenergy and P&P products produced, as well as the flows of final products and by-

products within the IFBR and to the market.

By assessing the biomass used to produce bioenergy (Table 3.5), the quantity used is relatively small, when

considering the estimated available biomass over the planning horizon. Only 28.77 of the 71.22 million tons

available are used to produce bioenergy. Except for the urban waste residues (UWR), of which more than 17

of the 18 million available tons are used, essentially due to its negative supply cost, the use of other types of

biomass represents a low percentage of the available quantities. Particularly, only 1 million tons of more than

12.2 million tons of available waste process residues (WPR) are used. Their relatively higher conversion rate

has not been enough to cover their higher supply cost compared to the other biomass types. For the

agricultural residues (AR), 4.26 million tons of more than 24.8 million available tons have been used to

produce bioenergy. Similarly, over 6 millions tons of forest residues (FR), have been used out of a total of

more than 16 million available tons.

One important fact to notice is that, during most of the planning periods, all types of biomass are used to

produce energy. Diversifying its supplying sources allows the IFBR to manage uncertainty in biomass

availability and react better to demand variability.

To choose the best feedstock to produce a bioenergy product, the conversion rate and the supply cost are

essential parameters to make a decision about that choice. Biomass availability is not as important, since it

generally exceeds the bioenergy plant needs.

111

For example, “Cogeneration” technology is only fed with more than 4.1 million tons of FR from outside the mill.

The higher cogeneration conversion rate of the other possible feedstock, WPR, was not enough to balance its

higher supply cost compared to FR (see Appendix A). “Fermentaion” technology is the best example of

feedstock diversification to produce energy. Among the 6.15 million tons of supplied feedstock to produce

bioethanol, AR represented more than 4.26 million tons, essentially due their lower supply cost compared to

FR and WPR. Almost 886 thousand tons of FR and about 1 million tons of WPR ensured the remaining part.

The low rate of use of FR is due to its higher supply cost compared to AR, while the conversion rates are

almost the same for both (see Appendix A). For “Digestion” technology, more than 17.48 million tons of UWR,

were used to produce biogas. As for the “Pelletization” technology, more than 1 million tons of FR were used

to produce pellets. The other possible feedstock, WPR, was not used due to its higher supply cost comparing

to FR, while their conversion rates are quite similar (see Appendix A).

Flows of biomass per Technology (tons) Total

(tonne)

Available biomass

(tons) COG FER DIG PELL

AR 0 4 261 198.4 0 0 4 261 198.4 24 855 899

FR 4 105 457.45 885 960.7 0 1 028 627.28 6 020 045.43 16 119 761.3

UWR 0 0 17 486 895.7 0 17 486 895.7 18 029 657.6

WPR 0 1 008 469.6 0 0 1 008 469.6 12 221 169.1

Total (tonne) 4 105 457.45 6 155 628.7 17 486 895.7 1 028 627.28 28 776 609.13 71 226 487

Tableau 3.5 Biomass supplied over planning horizon H

For the bioenergy investments made over the planning horizon, the capacities installed allow the IFBR to meet

a major part of the estimated bioenergy market demand (Table 3.6 and Table 3.7).

For example, bioethanol (BE) production (more than 1776 million litres) satisfies most of the demand (more

than 1796 million litres). The relatively high investment costs of “Fermentation” technology are recouped by the

estimated increasing market price of bioethanol. The same goes for pellet “GRAN” production, where nearly

614 thousand tons of produced pellets meet a major part of more than 858.663 thousand tons of market

demand. The wood pellets are one of the most profitable bioenergy products to invest in, since the investment

costs are relatively low compared to the other bioenergy investment options, while the increasing market

demand would maintain competitive market prices. Electricity (ELEC) production meets the power needs of

the mill, where the major produced part feeds the power needs of the P&P activity, exceeding 6734 million

kilowatt-hours. The remaining part of the electricity production (more than 1163 million kilowatt-hours) is sold

112

to the market (Table 3.7). The electricity sold represents a small amount relative to the nearly 9344 million

kilowatt-hours’ market demand. That incapacity of cogenerated electricity to be competitive outside the plant-

gate is due essentially to low electricity market prices in Quebec. As for synthetic natural gas (SNG1), the gap

of 500 million m3 between the production (more than 1928 million cubic metres) and the demand (more than

2515 million cubic metres) can be explained by the additional large amount of funds required to add more

production capacity for the Digestion technology.

Product Technology Total production Total demand

P&P P&P 2 053 042.8 tons 2 420 835 tons

BE FER 1 776 231 990 Liters 1 796 104 170 Liters

ELEC COG 9 407 411 580 Kwh 9 344 377 900 Kwh

GRAN PELL 613 851.96 tons 858 663.55 tons

SNG1 DIG 1 928 240 050 m3 2 515 893 600 m3

Tableau 3.6 P&P and bioenergy production over the planning horizon H

Product IFBR Market Total demand

ELEC (Kwh) DIG FER PELL P&P

1 163 798 646 9 344 377 900 755 873 200 752 296 100 468 867.7 6 734 975 000

BE (Liters) 0 1 776 231 990 1 796 104 170

GRAN (tons) 0 613 851,96 858 663,55

SNG1 (m3) 0 1 928 240 050 2 515 893 600

Tableau 3.7 Flows of final products within the IFBR and to the market over the planning horizon H

For the by-products, the P&P generated by-products, black liquor (BL) and paper sludge (PS), are only used

as inputs to produce bioenergy (Table 3.8). More than 3.49 million tons of produced BL are used in

“Cogeneration” to produce electricity. As for PS, nearly 222 thousand tons are used to produce biogas via

“Digestion”. Due to their zero production cost, it should be more profitable to convert PS and BL to high value

bioenergy products rather than sell them directly to the market and use externally supplied biomass. For lignin

(LGN,) its estimated market demand (nearly 725 tons) is totally met by the available generated quantity (Table

3.8). In the model we consider, LGN could only be sold to market as a co-product. As a by-product of

bioethanol production, it represents a viable way to support the investment return of bioethanol investment.

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Product Co-product IFBR Market Total demand

P&P BL (tons) COG

0 0 3 490 172.6

P&P PS (tons) DIG

0 0 221 730.91

Bioethanol LGN (kg) 0 724 438.4 724 438.4

Tableau 3.8 Co-products flows within the IFBR and to the market over the planning horizon H

3.5.3.1 Operational financial summary The operational financial summary of the IFBR over the planning horizon shows significant profitability by

integrating bioenergy production into the P&P activity. The revenues generated from bioenergy products and

co-products would be more than $1.472 billion, which comfortably covers the $251.746 million supplying

biomass and the nearly $465 million operations and maintenance (O&M) costs (Table 3.9).

Biomass supplying cost ($) O&M cost ($) Revenues ($)

251 746 800 464 377 400 1 472 040 000

Tableau 3.9 Operational costs and revenues summary over the planning horizon H

3.5.4 Discussion

The obtained results clearly show the substantial potential of integrating bioenergy into P&P mills, for the data

used and adapted to the Quebec P&P sector. The mathematically-based framework developed in this paper,

has allowed us to assess several bioenergy investment scenarios, while considering their interaction with P&P

activity through a set of by-products, such as black liquor and paper sludge, that could be used to produce

bioenergy products. In the case of Quebec P&P mills, the case-study results have shown that the best strategy

to transform a mill into an IFBR would be to invest in a set of bioenergy products and use diverse biomass

sources. Therefore, one of the most important findings of this work is that bioenergy integration within the P&P

sector should ensure a diversity of bioenergy options, in order to hedge against market changes and demand

uncertainty. To get a durable competitive advantage, a number of niche markets would then overtake the mass

market for P&P products.

From another perspective, the estimated 20-year snapshot of the developed IFBR, given by the roadmap,

confirms the need to optimally manage P&P activity while investing in bioenergy. As shown in the results, it

would be more profitable for the IFBR to continue to produce conventional P&P products in most of the

planning periods, while progressively integrating the bioenergy products. The IFBR could then profit from the

increasing demand for bioenergy while ensuring diverse revenue sources by producing both conventional

forest products and bioenergy.

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Nevertheless, the financial potential of the bioenergy investments shown in this section remains sensitive to

the dataset used in the model. Even if the future trends we have used for several parameters are plausible, a

range of uncertainties related to energy prices, market trends and governmental policies could seriously affect

these trends. Then, a number of model parameters such as bioenergy investment and operation costs,

biomass supplying costs and bioenergy market prices and demands could evolve much differently relative to

the considered base scenario. In the following, we analyse the impact of such eventual uncertainties

3.5.5 Sensitivity analysis

To further evaluate the impact of the uncertainties related to most critical parameters on the design and the

profitability of the IFBR, we have conducted a sensitivity analysis in which three different future scenarios have

been considered. In the first scenario, we consider that the technologies of Gasification, F-T synthesis, and

Methanation would experience a higher technological and market-related development relative to the other

bioenergy technologies. The objective of this scenario is to assess the impact of higher government incentives

and market-driven demand on promoting such technologies. On the other hand, other bioenergy technologies

such as Pelletization and Cogeneration that are already considered as mature bioenergy technologies would

slightly profit from technological and market-related development during the planning horizon. In this scenario,

we consider that biomass supplying costs would increase by 30% during the next twenty years due essentially

to a growing bioenergy demand.

In the second scenario, we consider that the bioenergy market would stagnate during the next twenty years. In

this scenario, the substantial technological and economic development considered in the base-trend scenario

would not occur due to insufficient governmental incentives and unstructured bioenergy market demand. The

technological development of bioenergy technologies would be low compared to the base-trend scenario,

implying slight improvements regarding conversion rates and investment costs.

In the third scenario, we consider that the energy costs would considerably decrease over the coming years,

which would negatively impact the bioenergy product markets. Consequently, there would be no further

technological developments for bioenergy technologies, and the operational costs would even slightly increase

due to higher salary charges. In this scenario, biomass-supplying costs would decrease by 20% in the next

twenty years because of the significant decline (- 50% over the planning horizon) in market demand and prices

of bioenergy products. The details of the sensitivity analysis are presented in Appendix B.

In Table 3.10, the bioenergy investment roadmaps and a summary of financial results are presented for each

scenario, including the base-trend scenario.

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Total investment

Actualised cash-flow (A)

Salvage value (B)

Financial value

(A+ B)

Total investment

Actualised cash-flow (A)

Salvage value (B)

Financial value

(A+ B)

$789.68 million $512.69 million $79.33 million

$592.03 million

$823.11 million $413.67 million

$84.58 million

$498.25 million

Total investment

Actualised cash-flow (A)

Salvage value (B)

Financial value

(A+ B)

Total investment

Actualised cash-flow (A)

Salvage value (B)

Financial value

(A+ B)

$648.57 million $361.27 million $74.98 million

$436.25 million $574.57 million $109.02

million $65.68 million

$174.70 million

Tableau 3.10 Sensitivity analysis results

When evaluating the sensitivity analysis results, the bioenergy technologies show a variable financial

performance for the different scenarios considered. In Scenario 1, because of the higher technological and

market-related development for gasification-based bioenergy technologies (“F-T synthesis”, “Gasification”, and

“Methanation”) relative to the other technologies, it would be profitable to invest in “Gasification” and “F-T

synthesis”. Still, for the data we have used, such a development would not be enough to make “Methanation”

embedding profitable for the IFBR. In fact, it would be more profitable to produce “biogas” via “Digestion”

rather than “Methanation” due essentially to the higher investment and operation costs of “Methanation”. There

would be almost no changes in the investment roadmap for the other bioenergy technologies. Nevertheless,

the IFBR financial value, estimated at $498.25 million, would be about $100 million less than the base-trend

116

scenario, while the investment costs are quite similar for both scenarios. In Scenario 2, the market and

technological stagnation considered would not highly affect the profitability of the bioenergy investments

embedded in the base-trend scenario. However, there would be no further capacity embedding for

“Fermentation”, “Pelletisation” and “Cogeneration” during the planning horizon. In this scenario, it would be

more profitable for the IFBR to embed the bioenergy technologies in the beginning of the planning horizon to

maximise its bioenergy market share. “Digestion” is the only technology that would be progressively embedded

during the planning horizon. Its higher investment costs relative to the other technologies embedded makes its

progressive integration more advantageous regarding the IFBR financial statement. Thus, under the current

market conditions coupled with slight technological improvements, bioenergy embedding would remain a

profitable transition for the data used, with a financial value estimated at $436.25 million for a total of $648.57

million as investment costs. In Scenario 3, the decline in demand and market prices for bioenergy products

coupled with a technological stagnation, compared to the current status, would highly affect the profitability of

the IFBR transition. Even if the bioenergy investment roadmap is very similar to that of Scenario 2 (except for

“Fermentation” where the capacity option embedded is just the one-third that of the other scenarios), the

actualised cash flow is estimated at only $109.02 million over the planning horizon. The financial value

estimated at $174.70 million, by the end of the 20-year planning horizon, might not be enough to convince

decision-makers to invest a total of $574.57 million in bioenergy technologies.

The third scenario considered confirms the need for real governmental support in the coming years to enhance

the creation of a thriving bioenergy market and improve the competitiveness of bioenergy products.

Particularly, if fossil energy prices decrease during the coming years, the profitability of bioenergy investments

would greatly depend on government incentives and GHG emission reduction programs to help forest

companies get into bioenergy investments.

An important fact to notice about the conducted sensitivity analysis is that the profitability of the “bio-transition”

for forest companies would rely heavily on creating a durable market environment, in order to ensure a market

demand as well as a competitive selling price for bioenergy products. Governments would play a key role in

promoting the creation of such a market by establishing supportive programs through tax exemptions,

bioenergy quotas, emission credits and financial incentives to convince forest stakeholders and bioenergy

technology manufacturers to make the leap. Furthermore, establishing close and durable collaborations

between forest companies aiming to get into bioenergy, biomass suppliers and bioenergy consumers would be

essential to reduce the high uncertainties related to such investments and create a steady and competitive

market. Thus, even if the case study results as well as the sensitivity analysis findings show the financial

potential of integrating bioenergy technologies within the P&P companies, one should note the vulnerability of

117

such outcomes to the data used about the current bioenergy market status and the future projections for

technological and market-related developments.

By using this mathematically-based approach, our main objective is then to provide an assessment method for

the forest industry stakeholders, particularly those of the P&P sector, to help them gain a clearer vision about

the economically and technically viable bioenergy pathways in the coming years as well as a better

understanding of the most serious challenges the sector would face to ensure the profitability of this “bio-

transition”.

3.6 Conclusions

The “integrated forest biorefinery” concept, IFBR, is presented as a promising opportunity for Canadian pulp

and paper mills, to overcome the present crisis and evolve towards a competitive business model. In this

paper, we have developed a mathematical approach aiming to obtain an optimal roadmap for investments in

bioenergy, for the data used, considering a set of possible bioenergy investments, while managing their

synergy with the pulp and paper activity. The bioenergy roadmap presents a multi-period investment plan

giving a snapshot of the IFBR transformation strategy over the planning periods.

To well assess the potential of that transformation, we have presented a four-step methodology; embracing

both the qualitative and quantitative aspects of bioenergy supply-chain design. The design approach has led to

a decision-support approach, which would help forest industry stakeholders in designing long-term and

competitive business models.

The developed mathematically-based framework has been initiated by a qualitative study adapted to the

Canadian forest industry context. A real database was constructed to feed the model with a set of parameters

reflecting the reality of the Canadian pulp and paper sector, which would be useful to assess ulterior bioenergy

investments. A detailed financial analysis, mostly ignored in supply-chain design optimisation, was integrated

into the developed model, which complements the strategic and operational costs traditionally integrated in

such analyses.

The results of the study adapted to the Quebec pulp and paper mill sector have shown that it would be

financially profitable to invest, over a 20-year planning horizon, in a number of bioenergy technologies

including bioethanol, biogas, pellets and cogeneration, while managing the operation of the pulp and paper

activity. Still, other bioenergy technologies, such as gasification, F-T synthesis, and methanation have not

been considered as profitable for the IFBR, essentially due to their high investment costs compared to their

technological maturity. This finding is confirmed through a sensitivity analysis, where a higher technological

and market-related development of gasification-based technologies over the other bioenergy technologies has

118

made them profitable for the IFBR considered. Government financial incentives and strategic alliances within

the forest industry could boost the implementation of these technologies during the coming years.

The obtained solution output reveals the substantial financial potential of the transformation of a pulp and

paper mill into an IFBR, considering a dynamic planning horizon, economically, technically and commercially.

Nevertheless, the investment roadmap depends on a prefixed scenario of the parameters evolution over the

planning horizon. Our next step, is to develop a scenario tree-based model, where each branch represents an

evolution scenario for these parameters, in order to explicitly consider technical, economic and commercial

uncertainties related to such long-term investments.

3.7 Appendix

3.7.1 Appendix A: Model database

The database has been built using real data from reports and studies as well personal assumptions, in the

case of unavailable data.

Parameters Index Values References

Fiscal lifetime FL 20 years (FPInnovations, 2011)

Financial

horizon FH 20 years (FPInnovations, 2011)

Economic

lifetime EL 30 years

(Raymond Chabot Grant

Thornton, 2006)

Tax rate TR 30% (FPInnovations, 2011)

Length of

planning

horizon

T 20 years (FPInnovations, 2011)

Number of

periods per

cycle

LP 5 years (IEA, 2011)

Capital rate r 5% (IEA, 2011)

Operation

fixed cost of

P&P activity

FCP $20 million (FPInnovations, 2011), personal

assumption

119

Closing cost of

P&P activity b $10 million

(FPInnovations, 2011)

, personal assumption

By-product

rate

α

α(Black

Liquor) 1.7 dt/t of P&P (Larson et al., 2006)

α (Paper

Sludge)

0.2t/t of P&P

(1.7 million of tons for 8 million tons of produced

pulp)

(Rodrigue, 2010)

(MRNF, 2009)

α (Naphtha) 0.195l/l of F-T diesel (FPInnovations, 2011)

α (Lignin) 0.4 10-3 t/l of ethanol (IEA, 2011)

Supply cost

CSUP

Forest

Residues

FR

66 to 82$/dt (FPInnovations, 2011)

Agricultural

Residues

AR

40 to 90$/dt

(Magdzinski, 2006)

Wood process

residues

WPR

70 to 90$/dt

Urban waste

residues

UWR

-30 to 0$/t

Biomass

availability

B

FR (106 dt/y)

From 19.5 to 32.5 in

CA 0,64(*)

(Mabee et al., 2006)

6.4 in Qc (Gouvernement du Québec,

2008)

AR (106 dt/y) 5.3 to 14 in CA

So, 10 as average 1(*) (Wright and Goodwin, 2009)

WPR (106

dt/y) 4 to 5 in CA 0.5(*) (Mabee et al., 2006)

UWR (106 t/y) 7 in QC 0.7(*) (ENERKEM, 2011)

120

(*) We assume that:

- The biomass available in QC is about 20% of the total biomass

available in Canada.

- The IFBR has access to 10% of the amount of biomass available in QC

Personal assumption

Future trend From +1 to +4% annually (ORNL, 2011)

Conversion

rate

ρ

Technologies

Output Inputs Values References

CHP

Cogeneration

(Electricity)

FR 740 kwh to 1100

kwh/dt (FPInnovations, 2011)

BL 1200 kwh/dt (Larson et al., 2006)

WPR 1020 kwh/dt (http://www.alfagy.com, 2012)

Biogas (SNG1, SNG2) 35% (Pirlot, 2011)

Fermentation

(Bioethanol)

WPR 340L/dt (IPCC, 2011)

FR 280-300L/dt (FPInnovations, 2011)

AR 250-290L/dt (Wakker et al., 2005)

Digestion

(SNG1)

PS 200m3/dt (Skene, 2011)

MSW 100m3/t (ENEFIBIO, 2006)

Gasification

(Syn. Gas)

AR, FR 600-650 m3/dt (Wakker et al., 2005)

BL 480-500 m3/dt (Wakker et al., 2005)

Gasification

+

Methanation

(SNG 2)

AR, FR 245-290 m3/dt (Hacatoglu et al., 2010)

Gasification

+

F-T synthesis

(F-T diesel)

AR, FR 235 l/dt (FPInnovations, 2011)

Pelletisation

(Pellets) WPR, FR 0.55 t/dt (Brodeur et al., 2008)

121

Future trend +15% by 2030

So, +0.7%/year over 20 years (Hacatoglu et al., 2010)

Investment

costs

Products Values References

Electricity 3750$/kwe (FPInnovations, 2011)

Bioethanol From 169 to $315 million for 200 106 l/Y (FPInnovations, 2011)

F-T diesel

(F-T

Synthesis)

$403 million for 180. 106

l/Y (gasification+ F-T

synthesis)

(*) We assume that the F-T

synthesis investment cost is

equal to the investment cost

for gasification

(*) $200 million for

180. 106 l/Y for F-T

synthesis

(FPInnovations, 2011)

(Wakker et al., 2005)

Pellets $320 000 for 2700 t/Y (PelHeat, 2012)

Syn.gas

(Gasification) $200 million for 486. 106 m3 (Wakker et al., 2005)

SNG1

(Digestion) 2$/m3 (approximation) (ENERKEM, 2012)

SNG 2

(Methanation)

$230 million for 180. 103 m3/Y (*)

(*) We assume that the methanation investment cost is

equal to the investment cost for gasification

(Hacatoglu et al., 2010)

(Wakker et al., 2005)

Economies of

scale Scaling factor (R=0.7) (Tijmensen et al., 2002)

Future trend From 2010 to 2030: -30%

So -8.5% per cycle of 5 years

(IPCC, 2011)

Production

costs

(Operations)

Products Values References

Pulp 318$/t (FPInnovations, 2011)

Electricity 0.03$ to 0.065$/kwh (IPCC, 2011)

Bioethanol 0.15 to 0.3$/L (FPInnovations, 2011)

122

SNG1 0.026$/m3 (ENEFIBIO, 2006)

F-T diesel

$72 million for 180. 106l/Y (Gasification+F-T

synthesis)

So, 0.2$/L (*)

(*) We assume that the operational costs for

gasification and F-T synthesis are equal)

(FPInnovations, 2011)

Syn.gas 0.07$/m3

SNG2 0.07$/m3

Pellets 65$/t (PelHeat, 2012)

Future trend From 2010 to 2030: -20 to -30%

So, -1.1% to -1.8% annually

(IPCC, 2011)

Electricity

consumption

per technology

(Kwh/unit)

Technologies Values References

Bioenergy

technologies

1.14Kwh/m3 . SNG2 produced

(gasification+methanation)

Because of lack of data, we have used this data fo all

technologies

(Hacatoglu et al., 2010)

P&P activity 3047.5 Kwh/t produced (OEE, 2006)

Capacity

options

(We assume a

set of 3

possible

P&P

2007:an average of 142.6.

103 t

2008: an average of 120.8.

103 t

130. 103 t/year (MRNF, 2009)

123

options per

technology)

Cogeneration

From 20 to 50 103 kw

(typical capacities in P&P

mills in Canada)

20. 103 kw

40. 103 kw

60. 103 kw

(Hacatoglu et al., 2010)

Pelletisation

From 20. 103 to 120. 103 t/y

as typical capacities in

Canada

20. 103 t/y

40. 103 t/y

60. 103 t/y

(Brodeur et al., 2008)

Fermentation

36. 106 l/Y

30. 106 l/Y

60. 106 l/Y

90. 106 l/Y

(ENERKEM, 2012)

Gasification

+F-T synthesis 30. 106 l /Y

30. 106 l /Y

60. 106 l /Y

90. 106 l /Y

(USDE, 2012)

Gasification

160. 106 m3/Y

320. 106 m3/Y

480. 106 m3/Y Personal assumptions by

referring to real biorefinery

capacities Methanation 40. 106 m3/Y

80. 106 m3/Y

120. 106 m3/Y

Digestion

Market price

$/unit

Products Values References

Ethanol 0.65$/L (plant gate price) (FPInnovations, 2011)

F-T diesel 0.8$/L (plant gate price) (FPInnovations, 2011)

Kraft pulp 750$/t (We consider 500 to 1000$/t due to market

uncertainty)

(FPInnovations, 2011)

124

Lignin From 168 to 750$/t (FPInnovations, 2011)

Pellets From 160 to 190$/t (“http://www.pellet.org/markets,”

2012)

Electricity 0.106 $/kwh (January 2012 pricing) (Hydro-Québec, 2012)

Naptha 0.55$/L (FPInnovations, 2011)

Future trend +20 to +50% by 2030. So, from +0.9% to +2 %

annualy

(IPCC, 2011)

Biofuel price

estimation

from fossil

fuel price (for

non available

biofuel price

data)

.biobio fossil

fossil

LHVRSP RSPLHV

⎛ ⎞= ⎜ ⎟⎜ ⎟⎝ ⎠

(NETL, 2009)

Expected

demand

(For non

available data,

we used the

option

capacities as

bounds)

Products Values References

Ethanol

43-130. 106 l/y (*)

(*)We assume that the IFBR could have access to 10-

30% of bioethanol market in Qc. We have estimated

the bioethanol market to about 5% of gasoline

demand in Qc (8704. 106 l as average for the past 5

years)

(FPInnovations, 2011)

125

Lignin

(0.4kg/L

ethanol)

Estimated as 40% of ethanol market:17. 103 -50. 103

t/y

F-T diesel

9 -26. 106 l/Y (*)

(*)We assume that the IFBR could have access to 10-

30% of biodiesel market in Qc. We have estimated the

F-T diesel market to about 2% of diesel demand in Qc

(4422. 106 l as average for the past 5 years)

Naphta

(0.195L/L F-T

diesel)

Estimated as 20% of F-T market: 1.8. 106 to 5. 106 l/y

Personal assumptions based on

capacity options that we have

considered

Syn.gas Random values from 160. 106 m3/y to 480. 106 m3/y

SNG2 Random values from 40. 106 m3/y to 120. 106 m3/y

SNG1 Random values from 40. 106 m3/y to 120. 106 m3/y

Pellets Random values from 20. 103 t/y to 60. 103 t/y

Electricity Random values from 160. 106 kwh/y to 480. 106

kwh/y

Pulp

130. 103 t/y

We assume a -1 to -2% future trend annually due to

structural change in pulp demand

Future trend Market share

for Biofuels

+30% to 50% by 2030

So,+1.3 to 2% annually

(IEA, 2009)

126

3.7.2 Appendix B: Sensitivity analysis

Parameter Product Base

trend

Values for the sensitivity

analysis

SC1 SC2 SC3

Supplying cost All 0% +30% 0% -20%

Conversion rate

F-T

+15% for

all

technologies

+20%

+5% for all

technologies

0% for all

technologies

METH +20%

GAZ +20%

PELL +5%

COG +5%

FER +10%

DIG +10%

Production cost

F-T diesel

-20% to -

30%

-30%

0% +10%

Ethanol -10%

Syn. Gas -30%

SNG1 -10%

SNG2 -30%

Electricity -5%

Pellets -5%

Investment cost

F-T

-30% for all

technologies

-50%

-10% for all

bioenergy

technologies

0% for all

technologies

METH -50%

GAZ -50%

PELL -10%

COG -10%

FER -20%

DIG -20%

Bioenergy demand

F-T diesel +30 to

+50%

for all

bioenergy

products

+50%

0% for all

bioenergy

products

-50% for all

bioenergy

products

Naphtha +50%

Ethanol +20%

Lignin +20%

Syn. Gas +50%

SNG1/SNG2 +50%

127

Pellets +10%

Electricity +10%

Bioenergy price

F-T diesel

+20 to 50%

for all

bioenergy

products

+50%

0% for all

bioenergy

products

-50% for all

bioenergy

products

Naphta +50%

Ethanol +20%

Lignin +20%

Syn. Gas +50%

SNG1/SNG2 +50%

Pellets +10%

Electricity +10%

129

Chapitre 4 Une approche de modélisation par scénarios pour identifier des stratégies de transformation robustes pour le cas des compagnies de pâtes et papiers

Cet article, intitulé « A scenario-based modelling approach to identify robust transformation strategies for pulp and

paper companies », a pour auteurs Mahdi Machani, Mustapha Nourelfath et Sophie D’Amours. Il a été soumis à

« International Journal of Production Economics » en janvier 2013 (Facteur d’impact évalué à 2,594 durant les cinq

dernières années). La version présentée dans cette thèse est identique à la version soumise.

131

Résumé

La dernière décennie a été particulièrement rude pour les compagnies de pâtes et papiers au Canada. La hausse du

dollar canadien, la compétition à faible coût et le déclin d'un nombre de marchés conventionnels ont engendré

plusieurs restructurations et fermetures d'usines. Ainsi, entreprendre une stratégie de transformation revêt, plus que

jamais, une importance cruciale pour ces compagnies afin de survivre à la crise et assurer un avantage concurrentiel

durable. Plusieurs avenues de transformation pourraient être considérées en allant de la modernisation des

processus de production jusqu'à la diversification de la plateforme de produits et de marchés. L'environnement

d'affaires des compagnies de pâtes et papiers, de plus en plus imprédictible et instable, rend les décisions

stratégiques de transformation un exercice complexe.

Notre objectif est ainsi de proposer aux décideurs au sein du secteur de pâtes et papiers des outils leur permettant

d'identifier les stratégies de transformation les plus profitables qui sauraient résister aux tendances majeures

affectant la compétitivité des compagnies. Une approche de modélisation par scénarios est présentée afin d'évaluer

un nombre d'options de transformation stratégiques sous différents scénarios futurs d'évolution, et d'identifier les

options les plus robustes. Un modèle mathématique est développé pour évaluer la profitabilité de chacune des

stratégies de transformation considérées, et ce sous différents scénarios futurs plausibles d'évolution de

l'environnement d'affaires du secteur.

Investir en des bioproduits de haute valeur ajoutée, tels que le Bioéthanol, est présenté en tant qu'avenue de

transformation avantageuse. De même, intégrer des produits de pâtes et papiers innovateurs tels que les emballages

à fibre moulée pourrait être une option prometteuse à considérer au sein d'une stratégie de diversification multi-

produits.

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Abstract

Canadian pulp and paper companies have been experiencing hard times during the last decade. The rising Canadian

dollar, low-cost competition and the decline in number of conventional markets have led to several restructuring

projects and shutdowns among pulp and paper mills. Setting up a transformation strategy is considered vital for those

companies to overcome the crisis and achieve a sustainable competitive advantage. Several transformation pathways

could be undertaken, ranging from process modernisation to product portfolio and market diversification. The

increasingly volatile business environment makes strategic decisions a tough task.

Our objective is then to help decision makers, within the pulp and paper industry, identify profitable transformation

strategies that would resist the major driving forces affecting the companies’ competitiveness. A scenario-based

modelling approach is presented to evaluate a set of transformation strategies under different trend-based future

scenarios and to identify the most robust strategic options, allowing a given pulp and paper company to meet the

future challenges. A mathematical model is developed to evaluate the profitability of each transformation strategy

under different plausible future scenarios. Investing in high-value bioproducts such as Bioethanol is suggested as a

viable transformation pathway. Opting for innovative pulp and paper products such moulded fibre packaging would be

a promising strategy to consider within a multi-product diversification pathway.

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4.1 Introduction

Over the last years, Canadian forest companies have been struggling to maintain their competitiveness within an

increasingly competitive business environment due to saturated markets, low-cost competition and tighter profit

margins (FPInnovations, 2011). Canadian pulp and paper (P&P) companies in particular, have been severely affected

by such an economic stalemate because of structural decline in a number of conventional P&P products and an

inefficient cost structure amplified by the rise of the Canadian dollar and higher energy costs ((MRNF, 2012),

(Marinova et al., 2010)).

A growing number of industrials and researchers have been outlining the need to transform P&P companies to

address the new challenges they are confronted with ((PwC, 2010a), (MRNF, 2012), (Marinova et al., 2010), (Pätäri

et al., 2011), (Mansoornejad et al., 2010), (Feng et al., 2012), (Frandina et al., 2008), (Wising and Stuart, 2006),

(NSERC, 2013), (Machani et al., 2013), (Machani et al., 2014), (Dansereau et al., 2012)). The transformation avenues

claimed in these works range from cost structure optimisation and modernising the manufacturing processes via

integrating innovative P&P products, to integrating new end uses for fibre-based products. Nevertheless, there is

consensus on the need to rethink the basic strategies, involving products, customers and markets (PwC, 2010a), to

help P&P companies thrive in the crisis.

In Canada, P&P companies are increasingly aware of the need to reinvent themselves and adapt to the major shifts

they are facing. The Canadian government has undertaken a series of programs to support the transformation of

forest companies, particularly the P&P companies, to allow them to manage the structural and the conjectural decline

in major conventional P&P markets. The purpose of such programs is to support the companies’ efforts to improve

their manufacturing processes, by extracting more value from fibre by integrating new technologies and products,

diversifying their markets, and improving the efficiency and the sustainability of the supply chain management (NRC,

2012).

However, to fully grasp the opportunities associated with the different strategic pathways available, P&P companies

should consider the uncertainties associated with such transformation avenues. In fact, uncertainties related to forest

raw materials, energy prices, governmental policies, market trends and consumer behaviours would seriously affect

the competitiveness of Canadian P&P companies during the next years (UNECE/FAO, 2012). Companies should

then take into account these uncertainties when setting up new strategies to achieve a sustainable competitive

advantage.

Moreover, predicting how these driving factors will evolve in the future is quite a complicated task. When dealing with

such an unpredictable and changing environment, scenario planning, a tool to design a set of plausible future trends

(Schoemaker, 1995), represents a useful method to evaluate a number of strategic options while incorporating the

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uncertainties into a number of plausible future scenarios (Wright and Goodwin, 2009). Thus, scenario planning would

help identify robust strategies, which could represent strategies that would resist the uncertainties related to the

political, technological and economic shifts affecting the business environment of P&P companies.

Canadian P&P companies then need practical decision-making approaches to help them better understand the

challenges they are confronted with, identify the plausible future trends that would affect their competitiveness, and

identify the most successful strategic pathways to undertake within an increasingly changing environment.

Our contribution is to develop a decision-support approach to identify the most robust strategic options offered for

Canadian P&P companies, in order to successfully cope with the challenges and hedge against the future

uncertainties. Based on scenario planning, our objective is to evaluate how each proposed strategy would behave

under different future trend-based scenarios. To well evaluate the profitability of each strategy, an optimisation

mathematical model is developed to evaluate the financial performance of the P&P company when implementing

such a strategy. The objective is to provide the P&P sector decision makers with a useful framework to reshape their

strategic thinking and come up with robust transformation strategies that explicitly consider the socio-political,

technological and economic uncertainties related to the P&P companies’ business environment.

The remainder of the paper is organised as follows. In Section 4.2, we present a review of the principal previous

works done in scenario planning and scenario-based strategic design, particularly in the case of P&P companies.

Section 4.3 presents in detail the methodology developed to design robust transformation strategies for P&P

companies. A case study is presented to support the methodology. In Section 4.4, we present the results obtained for

the case study and we discuss the most promising transformation strategies. Finally, in Section 4.5 we conclude by

summarising the contribution of the paper and suggesting future research.

4.2 Literature review

We first discuss the research works dealing with scenario planning issues, particularly those applied to P&P

companies. Then, we review the literature developing scenario-based strategic design. A third subsection highlights

the research gaps found, and the contribution of the paper.

4.2.1 Scenario planning

P&P companies, particularly in mature markets such as Europe and North America, have been facing global

challenges due to structural changes coupled with a conjectural crisis affecting the P&P sector. The P&P companies’

business environment is becoming more and more unpredictable and rapidly changing (JAAKKO Pöyry consulting,

2005). Under such uncertainty, scenario planning, a disciplined method for imaging a range of possible futures

(Schoemaker, 1995), has gained practitioners and researchers interest as a thinking tool to evaluate the effectiveness

of long-term decisions, while explicitly considering the uncertainties related to the opportunities and the risks that

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could affect the competitiveness of companies (Palma et al., 2010). A growing number of papers have dealt with

scenario planning as a powerful decision-making tool to anticipate and manage future changes under high

unpredictability ((Wright and Goodwin, 2009), (Schoemaker, 1995), (Goodwin and Wright, 2001), (Heijden, 2005),

(Lindgren and Bandhold, 2003), (McKinsey & Company, 2013), (PwC, 2009), (Mahmoud et al., 2009), (Postma and

Liebl, 2005)).

Shell was the first company to introduce the scenario planning technique as a strategic tool to hedge against oil

market uncertainties and develop effective management strategies (Wack, 1985). Four trend-based scenarios have

been developed to anticipate major shifts affecting oil markets. Several research works have been interested in

developing systematic approaches to build a range of plausible future scenarios, while highlighting useful methods

and thinking principles aiming to conceptualise the scenario design process ((Schoemaker, 1995), (Lindgren and

Bandhold, 2003), (Ogilvy and Schwartz, 2004), (Kosow and Gaßner, 2008)),

In the forest industry, particularly in the P&P sector, an increasing number of researchers have been developing

scenarios to anticipate and manage the major shifts occurring in the coming years within the companies’ business

environment. A review of future-oriented studies at the European level, presents a number of trend-based scenarios

for the European forest industry and how they would impact the choice of policies and strategies to optimally address

the forest industry needs (Pelli, 2008). In a wider context, a world model of the P&P industry is developed in (Szabó et

al., 2009), to assess how different environmental, energy, and future climate trends would affect energy consumption

and carbon emissions within P&P mills. Three trend-based scenarios are built to simulate the impact of the different

carbon-constrained and energy efficiency policies considered on the development of the P&P industry. In (Leberle,

2011), two innovative development scenarios are presented for P&P companies to help them anticipate and

understand the future challenges. The first scenario is based on the development of efficient and modern P&P

products, while the second is based on the development of new end uses for fibre-based products.

4.2.2 Scenario-based strategic design

To overcome the present crisis, Canadian P&P companies have to review their strategies to meet the increasingly

changing customer requirements and profit from new market-related opportunities ((FPAC, 2010), (Pätäri et al.,

2011), (Thorp, 2005), (Wising and Stuart, 2006)). A number of papers deal with the identification of promising

transformation pathways for P&P companies to achieve a sustainable competitive advantage ((PwC, 2010a), (FPAC,

2010), (Machani et al., 2014), (Kivimaa and Kautto, 2010)). In (Pätäri et al., 2011), a dynamic framework is presented

aiming to identify successful strategic options for P&P companies to seize the offered opportunities related to the

growing markets, while managing the risks associated with such a transformation.

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Scenario planning has been proposed in the literature, in order to develop strategic options that could effectively

respond to various uncontrollable changes in the future ((Noori and Chen, 2003), (Pillkahn, 2007), (Ram et al., 2011)).

However, few works have presented scenario-based frameworks to assess the value and the robustness of various

strategic options, as cited in (Ram and Montibeller, 2013).

Combining Multi-Criteria Decision Analysis (MCDA), a method supporting the evaluation of the performance of

strategies, with scenario planning, has been widely used to propose conceptual frameworks aiming to evaluate

various strategic options while considering future uncertainties; see for example (Ram et al., 2011). In (Goodwin and

Wright, 2001), a multi-attribute value function, based on a subjective 100-0 value scoring, is integrated into a

scenario-based framework to evaluate the robustness of different strategies. Similar frameworks have been

proposed, based on multi-attribute scoring functions, to assess the impact of different scenarios on each strategy

proposed ((Ram et al., 2011), (Ram and Montibeller, 2013), (Montibeller et al., 2006), (Zinkevičiūte, 2007),

(Schroeder and Lambert, 2011), (Karvetski et al., 2011)).

Regarding the P&P industry, few works have been interested in developing scenario-based approaches to evaluate

the robustness of one or several strategic options; i.e. their ability to resist various uncertainties. In (Mansoornejad et

al., 2013), the authors present a scenario-based approach to assess different P&P supply chain configurations

integrating biorefining processes. A mathematical model is developed to decide on the optimal alternative, while

considering several market trend-based scenarios. Two supply chain performance metrics including robustness and

flexibility are measured for each alternative. In (Palma et al., 2010), four future scenarios are developed for the

Canadian forest industry based on future trends regarding energy, carbon and fibre prices. In each scenario, the

investment return of a set of conventional forest products, as well as of innovative fibre-based bioproducts, is

estimated. The objective is to analyse how different future pathways would impact the effectiveness of any adopted

strategy within Canadian forest companies.

Based on stochastic programming, a scenario-based approach is presented in (Svensson et al., 2009) to estimate the

expected net present value of a number of energy efficiency investments, in the case of a P&P mill, under uncertain

energy and carbon market conditions. In (Svensson and Berntsson, 2011), a similar methodology is proposed to

assess the profitability of investments in cogeneration, lignin separation and carbon capture, while considering,

besides uncertain energy market, future uncertainties related to the development in investment costs and proven

functionality for the technologies considered.

4.2.3 Paper contribution

In recent years, there has been an increasing awareness, among researchers and practitioners, of the need to

consider uncertainties within the volatile and uncontrollable business environment of the P&P sector. A growing

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amount of literature has highlighted the effectiveness of scenario-based approaches to anticipate the major

technological, socio-political and economic shifts that would affect the competitiveness of P&P companies.

Researchers have been increasingly interested in evaluating various strategic options to transform these companies,

while considering various future trends reshaping the P&P sector.

Nevertheless, the literature of the previous subsections shows that few papers have developed scenario-based

approaches to explicitly evaluate both the profitability and the robustness of different strategic options, particularly in

the case of P&P companies. Papers presenting scenario-based frameworks to evaluate the robustness as well as the

financial performance of a number of strategic options have only considered limited trend-based scenarios, such as

energy market-related trends in (Svensson et al., 2009), market price trends in (Palma et al., 2010), and technological

development trends in (Svensson and Berntsson, 2011). Furthermore, the papers focusing on evaluating the

profitability of different strategic pathways to transform P&P companies, have only considered a single development

scenario ((Feng et al., 2012), (Machani et al., 2013)).

Our contribution is then to develop a decision-support approach to evaluate the profitability of diverse transformation

strategies, in the case of Canadian P&P companies, while explicitly considering the uncertainties related to the major

shifts affecting their business environment, in order to ensure a robust output. A set of trend-based scenarios is

developed for generating plausible business environments for the P&P companies. A mathematical model, involving a

detailed financial analysis, is used to assess and optimise the financial performance of each strategic option under

the different scenarios proposed.

The objective is then to suggest a scenario-based modelling approach aiming to propose a number of potential

transformation strategies for Canadian P&P companies, generate a set of plausible scenarios based on the major

shifts within the driving forces affecting their competitiveness, evaluate the effectiveness of each strategy under the

different scenarios, and come up with a number of recommendations that would help decision makers identify the

most robust transformation pathways allowing P&P companies to achieve a sustainable competitive advantage. In the

following, we present in detail the approach developed.

4.3 Methodology: A four-step approach

In this section, we propose a four-step approach based on scenario planning (Figure 4.1). The first step of the

approach, “Strategy identification”, is about proposing a number of transformation strategies. In this step, different

transformation strategies are identified in order to develop a long-term competitive advantage. The next step,

“Scenario design”, aims to design a number of plausible scenarios based on different future trends occurring within

the business environment of a Canadian P&P company. To well model the future scenarios, the main driving forces

leading the competitiveness of the company are identified. Then, a number of scenarios are designed based on the

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different future trends affecting the major driving forces. The objective of the third step, “Strategy/Scenario

evaluation”, is to evaluate the profitability of each strategy proposed under the different scenarios generated. A

mathematical model is developed to assess the long-term financial profitability of each strategy considering different

future trend-based scenarios. Finally, the fourth step, “Strategy selection”, is about presenting the most profitable and

robust transformation strategies for a given Canadian P&P company. Based on a case study, the main objective of

this step is to formulate a number of recommendations for P&P sector decision makers to help them decide on the

most profitable and robust pathways to achieve a successful transformation for Canadian P&P companies.

Figure 4.1 A four-step methodology to design robust transformation strategies for P&P companies

In the following, we present in detail the four steps of the scenario-based approach we have developed in this work, to

identify the most promising transformation strategies, for a given Canadian P&P company.

4.3.1 Identifying a number of transformation strategies

The structural decline of a number of conventional markets coupled with a tough low-cost competition point to the

need to reshape the sector to meet future challenges. In a recent series of in-depth interviews with a number of

executives from the 100 biggest forest companies in the world (PwC, 2010a), there has been consensus on the

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necessity to transform the forest industry, particularly the P&P sector, in order to thrive within the crisis. To undertake

a successful transformation, almost all the executives stress the need to change their companies’ strategies. Three

strategic options have been outlined as the most necessary for the transformation. The first strategy concerns

rationalising production capacities and refining the company business model. It is seen as vital to “getting the basics

right” before tackling future transformations. The second strategy is based on process innovation and efficient use of

raw materials. It aims to improve the company’s cost structure and help it offer cost-competitive products. The third

strategy is about “deriving the most value from every tree”. Creating new revenue streams, resulting from an

alternative use for fibre and biomass to produce high value-added products, such as bioenergy and sustainable forest

products, may allow forest companies to maximise their value proposition and position themselves as sustainable

actors.

In (Machani et al., 2014), we have identified four strategies that a number of the biggest forest companies in Canada

and worldwide have either been implementing or identifying to deal with the crisis. The first strategy, “Survival

strategy”, is based on rationalising company assets to align its production capacities with declining conventional

markets. The second strategy, “Operational efficiency strategy”, is based on implementing efficient supply chain

management by optimising operation costs and improving the energy efficiency of the plant. The third strategy, “Intra-

industry diversification strategy”, consists in diversifying the product portfolio by integrating innovative fibre-based

products to meet the new requirements of forest-products customers regarding sustainability and innovation. The

fourth strategy, “Bioproduct-based diversification strategy”, consists in integrating high value-added bioproducts to the

company product portfolio, such as biomaterials and bioenergy.

Based on the two works described above (i.e., (PwC, 2010a) and (Machani et al., 2014)), we propose three

transformation strategies for Canadian P&P companies, aiming to help them achieve a long-term competitive

advantage: the operational efficiency strategy, the intra-diversification strategy and the inter-diversification strategy.

4.3.1.1 Operational efficiency strategy This strategy is based on improving the supply chain efficiency of the company, involving raw material supplying,

product manufacturing and distribution. The objective is to offer cost-efficient products by optimising the operational

cost structure. In this work, we consider the modernisation of P&P processes as the central element of the operational

efficiency strategy. In fact, process modernisation is seen as one of the most viable ways to improve the efficiency of

P&P companies (Ministère des Finances and MERN, 2000). The modernisation mainly ensures considerable

operation cost reduction, more efficient energy consumption, and a better use of raw material. No product

diversification is considered in this strategy, as the main effort is to offer more cost-competitive existing P&P products.

On the market side, the strategy aims to retain the P&P conventional markets share without looking for market

diversification.

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4.3.1.2 Intra-diversification strategy The intra-diversification strategy is based on integrating innovative P&P products within the P&P product portfolio. It

aims to diversify company revenue streams by offering a set of new P&P product grades that meets the new

requirements of customers regarding sustainability and innovation. The objective is to integrate a set of innovative

end-use and sustainable P&P products to allow P&P companies to access a number of niche markets within

conventional P&P markets. Moulded Fibre Packaging (MFP) including intelligent and customised packages, is

considered as a promising avenue to offer an innovative end use for traditional fibre-based products, besides being

an advantageous sustainable solution to replace plastic packaging (Pätäri et al., 2011). In recent years, a number of

reports have outlined the huge opportunities related to integrating MFP within P&P companies to help them overcome

the crisis and offer sustainable as well as cost-competitive packaging solutions for customers (NSERC, 2013),

(Kivimaa and Kautto, 2010), (Government of Canada, 2013), (Government of Canada, 2012c), (Williams, 2013)).

4.3.1.3 Inter-diversification strategy The inter-diversification strategy is based on integrating a set of high value-added products within the P&P product

portfolio to access new markets beyond the traditional bounds of the P&P industry. The objective is to diversify the

revenue streams of P&P companies by offering new products meeting the demand of a set of growing markets that

requires innovative and sustainable fibre-based solutions. The bioproducts, encompassing a large variety of biomass-

based products, such as bioenergy (electricity, heat, and biofuels), biochemicals (adhesives, pharmaceutical

products, and essential oils), and biocomposites (biopolymers and nanocellulose) (Brunette, 2011), represent huge

market opportunities for P&P companies that are still unexplored (Sparling et al., 2011). Therefore, in this work, we

consider a bioproduct-based diversification strategy as a promising pathway to gain access to markets beyond the

borders of the saturated conventional P&P markets. The chemical market, the energy market and the biofuel market

are examples of markets offering great opportunities for P&P companies to obtain market shares by producing fibre-

based bioproducts (FPAC, 2011), which would be able to bring a set of economically and environmentally attractive

solutions to displace fossil energy consumption.

In Table 4.1, we summarise the main features of the three transformation strategies considered in this work.

Strategy Main features

Operational efficiency strategy

- P&P manufacturing processes modernisation - No product portfolio diversification - P&P Conventional market share retention

Intra-diversification strategy

- P&P technology innovation - Innovative end use P&P product diversification - New niche market access within the P&P markets (intra-

industry)

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Inter-diversification strategy

- Bioproduct technology innovation - High value-added bioproduct diversification - New market share access beyond the P&P markets (inter-

industries)

Tableau 4.1 Summary of the transformation strategies considered

4.3.2 Scenario design

This step consists in generating a set of plausible scenarios. To meet the future challenges, a Canadian P&P

company has to adapt to possible shifts within its business environment. To model these shifts, we consider a number

of future trend-based scenarios describing different plausible future trends that would affect the business environment

for a given Canadian P&P company. To adequately characterise each scenario, we consider four driving forces that

would govern the evolution of the company business environment.

4.3.2.1 Driving forces The driving forces considered are technological development, governmental policies, consumer behaviour and

markets. We consider that modelling the different future trends for such factors is a valuable step in the proposed

methodology. Instead of just proposing a set of different values to illustrate the uncertainties, building realistic trends

based on a multi-faceted environment has allowed us to generate a set of plausible “stories” depicting as realistically

as possible how the companies’ environment might evolve in the coming years.

Obviously, the drivers considered in this work would be much more complex to model in real world. In the meantime,

the objective of modelling these driving forces is mainly to simplify the design of different future business

environments for a given Canadian P&P company.

a) TechnologicaldevelopmentIt represents how the different technologies considered in the strategies proposed might evolve during the next years.

Therefore, the technological drivers outline how the P&P manufacturing technologies, the MFP manufacturing

technologies as well as the bioproduct manufacturing technologies would change in terms of production yields,

operating and investment costs. Thus, a higher development for a given technology would enhance its profitability

and promote its integration within the companies.

b) ConsumerbehaviourIt describes how the consumer might behave regarding the different features of the value proposition that the market

will offer. We assume that the consumer would consider cost, innovation and sustainability to various degrees when

deciding about the willingness to pay for a product or not (Thompson et al., 2010). Thus, a consumer could only seek

a cost-efficient product without being concerned about its innovative end uses or its sustainability. On the other hand,

there could be an increasing number of innovation-driven and/or sustainability-driven consumers who would be willing

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to pay a premium for sustainable and/or innovative products (Frandina et al., 2008). Therefore, in the coming years,

consumer behaviour would seriously shape the demand structure for conventional and innovative P&P products as

well as for bioproducts.

c) GovernmentalpoliciesGovernmental policies could play a key role in supporting the transformation of the Canadian P&P companies. The

support could be either political by setting up a set of measures such as imposition quotas for emissions and

bioenergy use, or financial by providing financial incentives for companies to help them improve their

competitiveness. In recent years, a number of supportive programs have been set up on both the federal and

provincial levels in Canada to help forest companies, particularly P&P mills, thrive within the crisis (Bradley, 2010). To

undertake a given transformation strategy, Canadian P&P companies need a set of political as well as financial

incentives to help them overcome the barriers related to the need for the capital required to achieve such a

transformation. Therefore, governmental policies could be critical in making a transformation pathway more financially

attractive than others for P&P companies.

d) MarketsMarkets represent a vital driver for shaping the business environment of P&P companies. In fact, the demand for

conventional, innovative P&P products or bioproducts will be a crucial factor in P&P companies’ decision makers

deciding whether or not to invest in a given transformation strategy. A greater demand for a product should, in

general, enhance its financial viability. Furthermore, market energy prices represent a key factor in the profitability of

several transformation avenues offered for the Canadian P&P companies. Higher energy prices would result in higher

operating costs for P&P products, while enhancing the profit margins of several products that displace the use of

fossil energy-based products such as bioenergy, biofuels and fibre packaging. On the other hand, low energy prices

would represent a serious barrier to the profitability of fossil energy displacing solutions, while allowing P&P

companies to reduce their operating costs.

As shown above, several forces would drive the changes that would occur within the business environment of

Canadian P&P companies. The technological, political, social and market-related drivers would be interconnected via

a set of complex mechanisms, which are beyond the scope of this paper. However, such an interconnection would

result in different future trends outlining a number of plausible scenarios (Schoemaker, 1995). In each scenario, the

different driving forces would contribute to create a specific business environment for a given P&P company. In each

business environment, we consider that a set of parameters might evolve differently, such as supplying costs,

investment and operation costs, production conversion rates, market demand and prices.

In the following, we present the scenarios considered, based on different future trends for the presented driving

forces.

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4.3.3 Scenarios

A scenario can be defined as a consistent view of what the future might turn out to be (Lindgren and Bandhold, 2003).

Designing a number of scenarios does not aim at predicting the future but rather to represent a snapshot of different

future outcomes. Therefore, based on different plausible combinations assumed for the driving forces discussed

above, four trend-based scenarios have been created.

To model the different trends for the four driving forces considered, we assume that two key factors would govern the

driving forces: Cost and Environment. In fact, companies’ inefficient cost structure is one of the main causes of the

P&P sector crisis. Our hypothesis is that the P&P companies’ business environment would evolve either to a cost-

driven environment where the emphasis is on products, technologies and policies offering cost-effective solutions, or

to a value-driven environment where we assume the advent of innovative solutions, policies and social trends

supporting the offering of new end uses to substitute conventional products.

As for the environmental factor, due to its high energy consumption, the P&P sector would be highly affected by

environmental trends regarding carbon emission issues and efficient energy uses.

On one side, we then consider that the P&P sector business environment would evolve to a low-environmental

commitment environment, where there would be no serious mechanisms to undertake a change towards a

sustainable environment: the efforts would be limited to scattered projects to reduce carbon emissions and improve

energy efficiency. On the other side, we consider a high environmental-commitment environment, where the driving

forces would evolve towards a green model integrating environmental concerns in the core strategies of the different

forest industry stakeholders.

Based on the different trends presented above, we then consider four different trend-based scenarios. In the

following, the main features of the four scenarios are presented. For each scenario, the future trends for the four

driving forces considered are portrayed in detail.

4.3.3.1 Scenario 1: Cost-driven/Low environmental commitment scenario In Scenario 1, the emphasis would be on products, technologies and strategies based on cost efficiency.

Environmental concerns would remain a second-class issue relative to economic matters. Regarding technological

development, there would be high development of modern cost-efficient P&P processes allowing companies to offer

cost-effective products. On the other side, the technological development for innovative technologies offering

sustainable and/or innovative end use would be low. In this scenario, the consumer would require more cost-efficient

products. Furthermore, no consumer would be willing to pay a premium for sustainable or innovative products. As for

governmental policies, the government would support cost-efficient processes and product development while being

slightly involved regarding sustainable issues. On the market side, conventional P&P markets would recover from the

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conjectural crisis. Moreover, there would be no high development for innovative and sustainable products. In this

scenario, we assume that energy prices would remain fair due principally to low environmental commitment.

4.3.3.2 Scenario 2: Cost-driven/High environmental commitment scenario In Scenario 2, the business environment would be cost-driven while experiencing a high environmental commitment.

For technological development, there would be high development for cost-efficient technologies as well as for

sustainable technologies, which would be cost-efficient. Thus, only technologies not requiring substantial investment

funds would experience high development such as energy-efficient technologies. Regarding consumer behaviour,

consumers would require products that would be cost-efficient as well as eco-friendly. We consider that consumers

would be willing to pay a premium for sustainable products, which would, however, be limited by the cost-driven trend.

As for governmental policies, there would be political and financial support for the advent of sustainable products and

technologies, which provide cost-effective solutions. Energy-efficiency transformation avenues would then be

prioritized in the governmental policies. Concerning market trends, the high environmental commitment considered in

this scenario would limit the recovery of conventional P&P markets while boosting the development of fossil energy

substitute markets. Moreover, we assume that energy prices would be high due to higher environmental restrictions.

4.3.3.3 Scenario 3: Value-driven/ low environmental commitment scenario In Scenario 3, the emphasis would be on value-driven innovation while the environmental concern would be low. On

the technological side, there would be a high development of innovative-driven technologies offering new end uses for

fibre-based products. On the other side, the development of highly efficient P&P processes would be limited by the

value-driven trend. Regarding consumer behaviour, there would be an increasing demand for innovative products

while not seriously considering the environmental issues. Consumers would then be willing to pay a premium for

innovative fibre-based products. On the governmental side, there would be financial and political support for value-

driven innovation to develop innovative technologies and products, while slightly supporting sustainable efforts. As for

the market trends, the recovery for conventional P&P markets would be partial, due to value-driven market trends,

which would rather promote market growth for innovative fibre-based P&P products. We assume that energy prices

would remain fair in this scenario due to low environmental commitment.

4.3.3.4 Scenario 4: Value-driven/ high environmental commitment scenario In this scenario, the business environment would evolve towards a value-driven and high environmental-commitment

environment. Regarding technological development, there would be a high development for innovative and

sustainable technologies fostering high value-added and eco-friendly products. On the other side, this scenario would

limit the development of highly efficient P&P processes. Concerning consumer behaviour, there would be a trend

towards requiring innovative and sustainable products. Consumers would then be willing to pay a premium for those

products. On the governmental side, there would be financial and political support to promote the development of

sustainable and innovative products and technologies. As for market trends, there would be a growing market

145

demand for sustainable and high value-added products promoting the advent of a bioeconomy, which would be based

on ecofriendly and innovative end uses for fibre-based products. In such a scenario, the energy prices would be high

due to sustainability restrictions.

In Figure 4.2, the main features of the four trend-based scenarios are presented.

Figure 4.2 Future trend-based scenarios for Canadian P&P companies’ business environment

4.3.4 Strategy/Scenario evaluation

The strategy/scenario evaluation is a centrepiece step in the approach developed, as it aims to assess the profitability

of the strategies formulated under the different scenarios generated.

In fact, for a given Canadian P&P company, the proposed transformation strategies are: modernisation of P&P

processes, innovative P&P diversification strategy and bioproduct-based diversification strategy. So, in addition to the

conventional Wood chips converted into P&P products, a P&P mill could convert a number of raw materials into

different fibre-based products such as recycled paper to produce moulded fibre packaging and forest residues to

produce bioproducts. By diversifying its product portfolio or modernising its manufacturing processes, the P&P

146

company could access a set of growing markets including increasingly demanding P&P markets, innovative P&P

product markets, and bioproduct markets. In Figure 4.3, we illustrate graphically a typical P&P mill value network

integrating these different transformation avenues.

Figure 4.3 The P&P company value creation network integrating the considered strategic options

4.3.5 Mathematical Model

To evaluate the profitability of the strategies considered under different future trend-based scenarios, a mathematical

model is proposed. The objective of such a model is to anticipate how each of three transformation strategies would

perform during the next years (twenty-year planning horizon) under each of the four possible scenarios considered.

In all the transformation strategies, the conventional activity of the P&P company, producing P&P products, would be

maintained. This activity should optimally be managed during the planning horizon to adapt to market changes.

To quantify the performance of each strategic option, an objective function, maximising the estimated financial value

of the company by the end of the planning horizon, is defined. Therefore, the mathematical model aims to optimise,

for each strategy, a number of decisions over the planning horizon, involving the timing and capacity of eventual

investments, the flows of raw materials as well as the flows of manufactured products towards the markets.

147

Two planning periods have been considered in the model: a five-year planning period in which we make the strategic

decisions concerning the timing and the capacity of the investments. The reason for choosing a five-year period is to

define a time-frame that would be long enough to consider the future shifts that would affect the profitability of such

investments (IPCC, 2011). A one-year planning period has been used to anticipate a number of tactical decisions

regarding product flows throughout the company supply chain. The planning horizon is then divided into four five-year

cycles, which are in turn divided into one-year periods.

To well evaluate the profitability of the different investments, a detailed financial analysis has been included, by

considering cash flows, annualised investments costs, tax rate, depreciation, debts, and salvage value by the end of

the planning horizon. We consider a fixed discount rate to get actualised costs and revenues, in order to discount all

future cash flows and obtain their estimated net present value. The estimated financial value of the company,

encompassing those different financial assessment tools, is maximised under a number of procurement,

manufacturing, distribution and logical constraints to ensure feasible solutions.

As the objective of the mathematical model is to assess the profitability of the different transformation strategies under

the different scenarios, the expected financial value, obtained from the average of the financial values for all the

scenarios, as well as the variation in performance of each strategy according to the scenario considered, are two

essential metrics to measure in order to evaluate the robustness of each strategic option.

In the following, we present the assumptions made in this model, the sets and parameters used, the decision

variables to optimise, the objective function as well as the different costs and revenues composing the objective

function, and the constraints considered.

4.3.5.1 Assumptions To simplify the modelling, without affecting its main purpose, the following assumptions have been made:

The electricity and steam needs of the P&P mill considered have already been met via the cogeneration of plant-

generated biomass residues such as black liquor and chip residues.

All the space needed to implement potential investments is available. Thus, no space constraint is considered in

the model.

For the embedded investments, the accounting depreciation, as well as the fiscal depreciation, have been split

linearly during the planning periods.

The investments are irreversible. Once embedded, a technology cannot be shut down during the remaining

periods of the planning horizon.

148

Except for the modernisation strategy where the P&P mill assets are modernised, the conventional P&P assets

are considered to have already completely depreciated.

The needs for raw materials that could be supplied in the different strategies are considered to be available.

Thus, no raw material availability constraint is introduced in the model.

The financial funds required for the investments are considered to be available. So, there is no constraint on

budget availability.

4.3.5.2 Sets S: Set of plausible future scenarios;

T : Number of periods;

C: Number of cycles;

HT 1,2,...,T : Planning horizon expressed in periods;

HC 1,2,...,C : Planning horizon expressed in cycles;

RM : Set of raw materials;

FP: Set of finished products;

O : Set of capacity options;

TG : Set of technologies.

4.3.5.3 Parameters : Financial horizon (period of paying debts);

: Economic lifetime (period of accounting depreciation);

: Fiscal lifetime (period of fiscal depreciation);

: A big number;

: Tax rate;

: Discount rate;

FH

EL

FL

M

TR

r

149

: Supplying cost of biomass , in period , under scenario ;

: Unit production cost of , in period , under scenario ;

: Conversion rate of , in period , to produce , under

scenario ;

: Investment cost of implementing the option of the technology , in

cycle , under scenario ;

: Capacity of the option of the technology ;

: Selling price (plant-gate price) of , in period , under scenario

;

: Expected demand of , in period , under scenario ;

4.3.5.4 Decision variables

=1 if the capacity option of the technology is added in cycle , 0 otherwise;

Flows of raw material , shipped in period , to technology ;

Flows of final product , shipped in period form technology to the market.

4.3.5.5 Objective function The objective function is about maximising the sum of the discounted net cash flows of the company, , and the

estimated salvage value of the company assets at the end of the planning horizon, .

In the following, we present the costs and revenues expressed within the objective function.

a) DiscountedrawmaterialsupplyingcostFor each scenario , the actualised raw material supplying cost is given by the product of the unit supplying

cost, , and the sum of raw material flows to the different embedded technologies, , discounted

using the discount rate r.

SCi ,t ,s i RM t HT sS

PCi ,t ,s i FP t HT sS

i ,t , j ,s i RM t HT j FP

sS

ICo,i ,c,s oO i TG

cHC sS

Ko,i oO i TG

Pi ,t ,s i FP t HT

sS

di ,t ,s i FP t HT sS

Yo,i ,c oO i TG cHC

FRMi ,t , j i RM t HT j TG

FFPi ,t , j i FP t HT j TG

CF

SV

sS

SCi ,t ,s FRMi ,t , jjTG

150

RMCs

SCi ,t ,s. FRM

i ,t , jjTG1 r ttHT ,iRM

(1)

b) DiscountedoperatingcostsFor each scenario , the actualised operating cost is given by the product of the unit production cost, ,

and the sum of manufactured product flows from the different embedded technologies, , discounted

using the discount rate r.

(2)

c) TotalinvestmentcostFor each scenario , the investment cost is the sum of the investment costs for the technologies options

embedded over the planning cycles.

, , 1, , , 1 , ,

, , 0, 1.s o i c s o i c o i c

i TG o O c C

I IC Y Y

(3)

d) DiscountedinvestmentcostovertheplanninghorizonFor each scenario , the discounted investment cost over the planning horizon is equal to the actualised

investment cost, annualised over the planning periods, by dividing it by the financial horizon FH.

, , 1, , , 1, , , ,1. 1 ,

0

.

. 1

T

o j i s o j i s o j i sCt i LP j TG o O

s ti

IC Y Y

IHFH r

(4)

e) DiscountedfiscaldepreciationoftechnologiesinvestmentsFor each scenario , the discounted fiscal depreciation over the planning horizon is equal to the actualised

investment cost, annualised over the planning periods, by dividing it by the financial lifetime FL.

sS PCi ,t ,s

FFPi ,t , jjTG

OCs PCi ,t ,s. FFPi ,t , j

jTG

1 r ttHT ,iFP

sS

sS

sS

151

, , 1, , , 1, , , ,1. 1 ,

0

.

. 1

T

o j i s o j i s o j i sCt i LP j TG o O

s ti

IC Y Y

FDFL r

(5)

f) Accountingdepreciationoftechnologiesinvestments For each scenario , the accounting depreciation over the planning horizon is equal to the investment cost,

annualised over the planning periods, by dividing it by the economic lifetime EL.

, , 1, , , 1, , , ,1. 1 ,

0

.T

o j i s o j i s o j i sCt i LP j TG o O

si

IC Y Y

ADEL

(6)

g) DebtsattheendoftheplanninghorizonFor each scenario , the debts of the company by the end of the planning horizon are equal to the total

investment cost, , minus the investment cost incurred by the company during the planning horizon, .

(7)

h) DiscountednetcashflowsovertheplanninghorizonFor each scenario , the total actualised net cash flows are equal to the sum of the actualised net operating

profits, which are obtained by subtracting the operating costs, , and the raw material supplying costs, ,

from the selling revenues, , and the proportion of actualised refundable fiscal depreciation, , minus the

actualised investment cost over the planning horizon, .

(8)

i) SalvagevalueofthecompanyassetsattheendoftheplanninghorizonFor each scenario , the salvage value of the company by the end of the planning horizon, discounted at the

period T, is equal to the total investment cost, , minus the accounting depreciation of the company assets by the

end of the planning horizon, , minus the debts of the company, .

(9)

sS

sS

I s IHs

Ds I s IHs

sS

OCs RMCs

RVs TR.DFs

IHs

CFs 1TR . RVs RMCs OCs TR.DFs IHs

sS

I s

ADs Ds

SVs I s ADs Ds

1 r T

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j) TheexpectedfinancialvalueofthecompanyFor each scenario , the expected financial value of the company is equal to the sum of the actualised cash

flows, , and the actualised salvage value, .

(10)

To take into account all the scenarios considered, the objective function, aiming to maximise the financial value of the

investments, is expressed as follows

(11)

Where

is the expectation of the estimated financial values for all the scenarios.

is the probability for scenario to occur.

4.3.5.6 Constraints

a) ProductionReceiptconstraintThe quantity produced and shipped for each final product, , in each period , depends on the

conversion recipe of the different raw materials used, which is expressed as a function of the conversion rate

and the raw material flows .

(12)

b) ProductioncapacityconstraintThe quantity of the shipped products , in each period , should not exceed the capacity installed of

each technology .

, , , , ,. , , i t j o j o j c to O

FFP K Y i FP t HT j TG

(13)

c) InvestmentirreversibilityconstraintIf an option capacity of a technology is embedded in a cycle , it remains embedded over the

entire planning horizon.

sS

CFs SVs

FVs CFs SVs

Max E(FV) ps.FVs

sS

E FV

ps sS

j FP t HT

i ,t , j ,s

FRMi ,t ,k

FFPj ,t ,k i ,t , j ,s.FRMi ,t ,k j FP,t HT,kTG,sS

iRM

i FP t HT

j TG

oO i TG cHC

153

(14)

d) MarketdemandconstraintThe flows of each final product shipped to the market should not exceed the market demand for that

product in each period .

(15)

e) Non‐negativityconstraint

(16)

4.4 Case-study: A Kraft pulp mill

To obtain viable results, we propose a case study inspired by a Canadian Kraft pulp mill. The reason for choosing

Kraft pulp is that it is a good example of a P&P conventional product that has been affected by the conjectural crisis

within the P&P sector during the last decade.

Regarding the transformation strategies, we have chosen moulded fibre packaging (MFP) as an example of an intra-

diversification strategy. For the bioproduct-based diversification strategy, we have chosen Bioethanol manufacturing,

as an avenue to assess its profitability. Bioethanol is considered to be a promising bioproduct-based avenue to

diversify the product portfolio of P&P companies ((Huang et al., 2009), (Ekşioğlu et al., 2009), (Huang et al., 2010),

(Feng et al., 2012), (Machani et al., 2013)).

4.4.1 Future trends for model parameters under the different scenarios

In this section, we present the future trends for the parameters used in the mathematical model under the different

scenarios considered. As shown in Figure 4.2, technological development, consumer behaviour, governmental policy

and market development would evolve differently for each scenario.

We assume that each model parameter, changing over the planning horizon, would principally rely on the future

trends of one or several factors considered in each scenario.

To model the future trends for the different parameters, we consider a series of trends ranging from very high decline

to very high growth, during the planning horizon, as follows:

Yo,i ,c Yo,i ,c1 0 i TG, oO, cHC

i FP

t HT

FFPi ,t , jjTG di ,t ,s iFP, t HT , s S

Yi ,o,c 0,1 oO, i TG,cHC;

FRMi ,t , j 0 i RM ,t HT, j TG;

FFPi ,t , j 0 i FP,t HT, j TG.

154

- - - : Very high decline

- - : High decline

- : Fair decline

0 : No change

+ : Fair growth

+ + : High growth

+ + + : Very high growth

Thus, a model parameter, having a future trend equal to (- - -), would experience very high decline over the

considered planning horizon relative to its current value. On the other side, a model parameter, having a future trend

equal to (+ + +), would experience very high growth over the considered planning horizon relative to its current value.

To obtain an estimated future trend for a parameter model, we sum the future trends of the different factors assumed

to affect its evolution during the planning horizon.

For example, for a model parameter A (production cost), under scenario S, depending on the influence of factors B

(technological development) and C (market development), where the future trends would be respectively (- -) and (+),

its resulting future trend is obtained by summing (- -) and (+), which gives (-). To standardise the trends, we set as

limits for the future trends, a very high decline (- - -) as a minimum and a very high growth (+ + +) as a maximum. If,

for example, a high decline in factor A (- -) and factor B (- -), would give a resulting trend equal to a very high decline

(- - -) and not (- - - -).

Obviously, the future evolution of each changing parameter considered in the model would be much more

complicated in the real world than just relying on the influence of two or three factors. Our objective is to simplify the

modeling of the different scenarios generated to help the decision makers explore a set of plausible changes, without

claiming to predict these changes.

In Appendix A, we present the obtained future trends for the model parameters evolving during the planning horizon.

The results are grouped according to the products considered in each of the strategies proposed.

To transform the future trends for the different model parameters, detailed above, into useful data to feed the

mathematical model, we have collected real data from several reports and research works highlighting some future

trends for one or several parameters used in the model. We have then extrapolated that dataset to foresee the

remaining future trends. In case of lack of data, we have made a number of realistic assumptions and extrapolations

155

to predict the needed future trends (see Appendix B). A realistic database has then been built to feed the model with

viable data, in order to obtain reliable results to discuss.

4.5 Results and Discussion

The mathematical model has been implemented in CPLEX Optimisation Studio 12.3, on a 2.4 GHz dual-core Intel

Core i5 machine, with 4GB of RAM. The data has been implemented in an ACCESS database, linked to CPLEX.

Similarly, the optimisation results have been exported to an ACESS database to simplify the assessment of the output

data.

We have tested each strategy under four different scenarios to evaluate its robustness when facing future

uncertainties. As it is difficult to determine the probability of occurring for each of the four scenarios proposed, we

assume that they would all have the same probability to occur in the coming years. Therefore, we have used a what-

if-analysis to resolve the mathematical model. We have then assessed the three transformation strategies under each

of the four scenarios considered.

In Table 4.2, we present a summary of the principal financial results obtained for each strategy under the different

scenarios considered. The financial results presented include the cash flows, the estimated investment salvage value

at the end of the planning horizon, the investment cost of the embedded technologies, and the estimated financial

value of the company by the end of the planning horizon. To well assess the robustness of each strategy proposed,

we have added a fifth scenario representing the average financial results for each strategy based on the financial

results of all the scenarios considered.

Furthermore, a min-max regret criterion; often used in robustness analysis to obtain robust decisions to hedge against

uncertain data (see (Aissi et al., 2009)), has been used to obtain the strategy that minimises the maximum deviation

“regret” over all possible scenarios, between that strategy’s profit and the optimal strategy profit for the corresponding

scenario.

For every strategy i , its regret, ,i sR , under a scenario s S , is defined as *, ,i s i s sR FV FV , where ,i sFV is

the estimated financial value of strategy i under scenario s , and *sFV is the optimal strategy’s financial value under

the scenario s . Therefore, the maximum regret of each strategy i is defined as ,max maxi i ss SR R . The most

robust strategy is the strategy having the lowest maxR .

The financial performance, FV , obtained for each of the three strategies varies significantly with the scenarios

considered. To measure this variability, we have calculated the coefficient of variation CV for the FV of a strategy i,

where:

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;

S is the set of scenarios considered;

is the financial value of a strategy i under a given scenario s;

is the average financial value of a strategy i considering all the scenarios;

is the standard deviation of the financial value for a strategy i for the average financial

value considering all the scenarios.

Therefore, the CV measures, in percentage, the amplitude of the variability of the financial performance of a given

strategy regarding the average performance. So, the higher the CV is, for a strategy, the more sensitive the financial

performance of the latter would be to future changes occurring within the competitive environment of a P&P company.

For Strategy 1 (ST1), considering the integration of Bioethanol (BE) within the P&P mill, the estimated financial value

varies from more than $64.5 million under Scenario 4 (SC4) to about $119.9 million under Scenario 3 (SC3), giving an

average financial value estimated at more than $93.4 million with a CV equal to 31%. Paradoxically, the lowest

estimated financial value obtained for ST1 corresponds to the highest investment cash flow of BE, estimated at more

than $100.2 million. This is mainly due to the fact that, in SC4, the estimated financial value of the company would be

profoundly affected by the considerable losses within P&P activity due to increasingly declining pulp markets and low-

cost competition, which would generate a negative P&P cash flow estimated at about -$51.4 million over the next 20

years. Indeed, the financial performance of conventional P&P activity would highly depend on future trends affecting

the P&P sector during the planning horizon. The estimated P&P cash flows would vary between about $ -51.4 million

(SC4) and more than $76.3 million (SC1), giving an elevated CV equal to 452%. The market-related conditions

associated with P&P prices and market demand would be two major parameters driving the performance of the P&P

sector during the next years.

As for Strategy 2 (ST2), considering the integration of Moulded Fibre Packaging (MFP) within the P&P mill, the

estimated financial value oscillates between about $ - 25 million (SC4) to more than $91 million (SC1), giving a high

CV equal to 129% with more than $36.7 million as an average estimated financial value. Although the cash flows for

the MFP investment would be positive for all the scenarios (varying between more than $13.1 million under SC1 to

about $34.3 million under SC2), it would not be enough to cover the important losses, estimated at about -$51.4

CVFV , i

FVi ,s FVi 2

Ss1

S

FVi

100%

FVi ,s

FVi

FVi ,s FVi 2

Ss1

S

157

million, within the P&P activity, under SC4.The average cash flows for MFP investments, estimated at about $23.6

million, although presenting a high investment return rate relative to the $12.5 million of investment costs, could not

be interesting enough for investors. In fact, MFP manufacturing is already considered as a mature technology. The

increasing low-cost competition considered in almost all the scenarios would seriously limit a high-volume production

capacity within a Canadian P&P mill. At this investment capacity scale, investing in MFP could just support a multi-

product diversification strategy to hedge against the structural market decline within the P&P sector. This explains the

fact that the variation trend for the estimated financial value of the company, when considering ST2 as a

transformation strategy, mainly depends on the financial performance of the P&P activity. In fact, the highest financial

value of the company is obtained underSC1 (about $91.1 million), which corresponds to the highest obtained P&P

cash flows under the different scenarios, while the lowest financial value is obtained under SC4 (about - $25 million),

which corresponds to the lowest obtained P&P cash flows under the different scenarios.

The third transformation strategy, ST3, based on the modernisation of the P&P plant, would be profitable if the P&P

sector recovered from the conjectural crisis (SC1 and SC2) or was affected less severely by the demand decline and

the low-cost competition during the planning horizon (SC3). In fact, modernisation would be the most profitable option

for the P&P company considered, under SC1, among all the transformation strategies proposed, with a financial value

estimated at more than $174.1 million. The estimated financial value would drop to $85.6 million if the recovery was

only partial (SC2). In SC3, where the P&P sector crisis will continue, but at a slower rate during the next 20 years, the

modernization strategy would remain profitable with a financial value estimated at more than $60.7 million. However,

if the P&P sector conjectural crisis continued at the same decreasing rate (SC4), the modernisation would not be

enough to offset the operational losses caused by progressively declining demand and low-cost competition, giving a

financial value estimated at about -$29.4 million. The considerable variability in the financial performance of the

modernisation strategy is shown in the high value of the CV (130%), which is the highest variability between all CV’s

of the investment cash flows for the three transformation strategies considered.

An important insight to note is that, although there is great variability in the financial performance of the transformation

strategies under the different scenarios, the timing and value of the investments would remain almost the same for all

the scenarios. For ST1, the timing of investing in BE during the planning horizon has slightly changed under the

different scenarios, giving a CV equal to 1%. As for ST2 and ST3, the CV’s are equal to 0%. In fact, for the ST1 and

ST2, both diversification strategies, it would be more profitable to invest in the beginning of the planning horizon to

fully take advantage of the market opportunities related to BE and MFP. The slight variability in the timing of capacity

adding for BE would be caused by the different future trends associated with the market-related and the socio-political

incentives. For MFP, the increasing competition considered in almost all scenarios would limit a progressive

embedding of such a technology. Investing in the beginning of the planning horizon would be preferred to maximise

the company market share.

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Strategies Scenarios Investment Cash flow

(a)

P&P Cash flow (b)

Salvage value (c)

Financial value

(a + b + c)

Investment Cost

Strategy 1 (BE)

SC1 $26 723 730 $76 359 290 $13 133 420 $116 216 400 $134 662 500

SC2 $54 484 530 $4 250 923 $14 322 050 $73 057 500 $133 504 000

SC3 $88 317 350 $17 266 930 $14 322 050 $119 906 300 $133 504 000

SC4 $100 211 700 -$51 454 100 $15 824 970 $64 582 620 $136 453 500

AVG SC $67 434 328 $11 605 761 $14 400 623 $93 440 705 $134 531 000

CV 49% 452% 8% 31% 1%

Strategy 2 (MFP)

SC1 $13 198 480 $76 359 290 $1 570 373 $91 128 140 $12 500 000

SC2 $34 269 270 $4 250 923 $1 570 373 $40 090 560 $12 500 000

SC3 $22 106 280 $17 266 930 $1 570 373 $40 943 590 $12 500 000

SC4 $24 908 100 -$51 454 100 $1 570 373 -$24 975 630 $12 500 000

AVG SC $23 620 533 $11 605 761 $1 570 373 $36 796 665 $12 500 000

CV 37% 452% 0% 129% 0%

Strategy 3 (Moder- nisation)

SC1 $165 964 100 $8 165 939 $174 130 100 $65 000 000

SC2 $77 511 660 $8 165 939 $85 677 590 $65 000 000

SC3 $52 626 940 $8 165 939 $60 792 870 $65 000 000

SC4 -$37 644 660 $8 165 939 -$29 478 720 $65 000 000

AVG SC $64 614 510 $8 165 939 $72 780 460 $65 000 000

CV 130% 0% 115% 0%

Tableau 4.2 Financial summary for the transformation strategies under the scenarios

The financial results presented in Table 4.2 show significant variability regarding the profitability of the strategies

proposed under the different scenarios considered. A transformation strategy could be the most profitable under a

given scenario as well as the worst strategic option to undertake under another scenario. This is the case of the

modernisation strategy (ST3), which is the most profitable strategy under SC1 and SC2, while being the worst

strategy under SC4.

In SC1 and SC2, the recovery of conventional P&P markets from the conjectural crisis coupled with a high

technological development of cost-efficient P&P manufacturing technologies and a community requiring more cost-

efficient products would enhance the profitability of the modernisation strategy (ST3). In these scenarios, BE and

MFP would both present promising avenues for the considered P&P company to diversify its product portfolio. Still, in

SC1, the lack of governmental policies promoting sustainable and innovative transformation as well as the

unwillingness of consumers to pay a premium for innovative and sustainable products, would limit the profitability of

investing in those products.

In SC2, high energy prices considered as well as the political and social incentives to support the sustainable

products would enhance the profitability of diversification strategies. However, the considerable decline in the

operational performance of the P&P activity due to higher energy costs, growing low-cost competition and a slower

159

market recovery compared to SC1, would limit the profitability of the proposed diversification strategies under SC2.

This explains why the modernisation strategy would remain the most profitable strategic avenue in SC2, in terms of

the estimated financial value of the company, as it would allow the P&P company to offer more cost-competitive and

energy-efficient P&P products.

In SC3, governmental policies supporting innovative transformation as well as willingness of consumers to pay a

premium for innovative products would boost the profitability of investing in BE, considered as an innovative way for

the Canadian forest industry to substitute fossil-based products. This explains why investing in BE (ST1) would be the

most profitable strategy in SC3. The modernisation strategy (ST3) would still be a profitable transformation strategy,

although shrinking P&P markets and decreasing profit margins would considerably affect its effectiveness compared

to SC1 and SC2.

In SC4, high environmental concerns and value-driven innovation would drive the business environment of the

considered P&P company. In this scenario, the high technological development of innovative and sustainable

technologies coupled with a socio-political will to transform the P&P sector into a major player within a competitive

bioeconomy, would enhance the development of market demand for BE and MFP. However, the increasingly mature

packaging markets, considered in SC4, would affect the financial performance of investing in MFP, as we consider

that the demand for recycled paper would increase supplying costs, and competition would tighten the profit margins

for the final products. P&P conventional markets would continue to decline, which would generate important losses

within P&P activity. Thus, investing in MFP (ST2) would not be enough to cover those losses, which explains the

negative financial value for ST2 in SC4 (about $-25 million). Even the modernisation strategy (ST3) would not be

effective to make the P&P company profitable, as the operational cost reductions would not be enough to cover the

important operation fixed costs required to run the P&P plant. This explains the negative financial value obtained for

ST3, estimated at about $-29.4 million. For ST1, based on investing in BE, there would be a great opportunity for

Canadian P&P companies to profit from fast growing bioenergy markets supported by political and social incentives.

The higher energy prices considered in SC4, and the willingness of consumers to pay more for innovative and

sustainable products would greatly contribute to the profitability of such a diversification strategy. In SC4, ST1 would

be the only profitable transformation strategy with a financial value estimated at more than $64.5 million.

In sum, the profitability of the transformation strategies considered would heavily rely on the future trends affecting the

competitive environment of Canadian P&P companies. As presented above and summarised in Figure 4.4, a strategy

could be highly profitable in one scenario while being ineffective in another. ST1, based on investing in BE, is the only

transformation strategy that would be profitable under all the scenarios considered. ST3, based on modernising the

P&P plant would be the most profitable strategic option in SC1 and SC2, while being the worst option in SC4 if the

conjectural crisis, affecting conventional P&P products such as Kraft pulp, persisted during the next 20 years. As for

160

ST2, based on investing in MFP, it could be a promising way, although not the most profitable one, to diversify the

revenue sources of Canadian P&P companies. However, the increasing low-cost competition and supplying costs

considered in almost all scenarios would affect its profitability, particularly in SC4, when it would not be enough to

cover the important losses affecting the P&P activity.

When considering the average of the estimated financial values for all the scenarios (Figure 4.4), investing in BE

would be the most robust option to transform the P&P company considered, with an average financial value estimated

at more than $93.4 million. Modernising the P&P plant, with an average financial value estimated at more than $72.7

million, would also be a promising way to help P&P companies optimise their operational costs, mainly when we

assume that the P&P market will recover from the conjectural crisis in the coming years. Nevertheless, modernisation

would not be effective if the conventional P&P markets continue to shrink during the next years. Finally, with about

$36.8 million as an average estimated financial value, investing in MFP would be an effective diversification strategy

to help P&P companies diversify their revenue sources. However, market-related pressures caused by competition

and increasing demand for recycled paper would considerably limit its financial performance. Creating a sustainable

demand for large-volume production by building long-term partnerships or offering innovative packaging solutions to

create market niches could be a viable way to further improve the profitability of such a diversification strategy. For

example, customised and intelligent packaging are seen as promising strategic avenues for P&P companies to create

new market spaces (PwC, 2010a).

Such findings are confirmed by the min-max regret criterion analysis summarised in Table 4.3, where we present the

min-max regret criteria for each strategy under the different scenarios considered. In fact, a strategy having a min-

max regret equal to zero under a scenario s is an optimal strategy under that scenario. The higher the criterion is for a

strategy, the higher the regret (the loss) would be for the investors. Thus, strategy 1 (ST1), based on Bioethanol

embedding into the Kraft pulp mill, would be the most robust strategy to invest in, as it offers the lowest maximum

regret (Rmax=57 913 700 $). On the other side, Kraft pulp manufacturing process modernisation, defined as strategy

2 (ST2) presents the highest regret criterion (Rmax=94 061 340 $). It confirms the finding stating that modernising the

pulping processes would be a profitable but risky strategy, particularly if pulp markets would continue to decline in the

next years.

Scenarios ST1 (BE) ST2 (MFP) ST3 (Modernisation)

SC1 57 913 700 $ 83 001 960 $ 0 $

SC2 12 620 090 $ 45 587 030 $ 0 $

SC3 0 $ 78 962 710 $ 59 113 430 $

SC4 0 $ 89 558 250 $ 94 061 340 $

Rmax 57 913 700 $ 89 558 250 $ 94 061 340 $

161

Tableau 4.3 Summary of min-max regret criterion analysis

Figure 4.4 Estimated financial values for the different transformation strategies under all the scenarios considered

As we have shown above, the operational performance of the P&P activity would highly affect the profitability of the

transformation strategies proposed. In Figure 4.5, we present the cash flows of the different products considered,

under the different scenarios. For MFP, for example, although its generated cash flows would be positive in SC4

(more than $24.9 million), it would not be enough to cover the important losses within the P&P activity (about $-

51.4million as cash flows). Another important finding shown in Figure 4.5 is that modernising the P&P plant (ST3)

would be profitable only if the cash flows of the non-modernised P&P plant were positive. In fact, ST3 would be

financially viable only if the P&P markets recovered from the conjectural crisis that the sector has been facing during

recent years. That would be the case in SC1, SC2, and even in SC3 where the conventional markets would slightly

decrease compared to the declining rate during the last ten years. In SC4, where the cash flows for non-modernised

P&P plant is estimated at about $-51.4million, modernisation would improve the financial performance of the company

but would not be enough to make P&P activity profitable, with a cash flow estimated at $-37.6 million.

By analysing the average cash flows of the different products under the different scenarios, Bioethanol diversification

and modernisation are the most promising strategic options to transform the P&P company considered with average

20-year cash flows respectively estimated at more than 67.4 and 64.6 million dollars. Nevertheless, under SC4,

modernising the P&P plant would not be effective to make the company financially profitable. In this scenario,

diversifying the product portfolio, by investing in bioenergy products or innovative P&P products would be effective to

ensure the competitiveness of the P&P company.

162

The cash flow analysis that we present in Figure 4.5 suggests that it could be more profitable for the P&P company to

shut down the P&P plant temporarily if the market demand was not sufficient to cover the operational fixed costs. In

that case, integrated technologies to produce bioenergy and innovative P&P products would be a promising option to

ensure a profitable financial performance. Nevertheless, further analyses would be needed to integrate explicitly the

shutdown-related costs and to optimally manage P&P activity during the planning horizon periods.

Figure 4.5 Estimated cash flows for the different transformation strategies under all the scenarios considered

The case study reveals the robustness of investing in Bioethanol as a viable bioproduct-based diversification strategy

to transform a given Canadian P&P company. While it would not be the most profitable transformation strategy in two

of the four scenarios presented (Figure 4.4), investing in Bioethanol is the only strategy that would be profitable in all

the scenarios considered. Furthermore, it represents the most profitable strategic option, in terms of average

estimated financial value and presents the lowest regret over all scenarios considered making it a conservative

option. Regarding the modernisation of the P&P plant, the variability in its financial performance suggests that the

decision makers should be aware of the risks associated with the viability of such a transformation strategy, mainly if

conventional P&P markets continue to shrink in the coming years. Its regret criterion, almost twice the value obtained

for Bioethanol diversification, reveals the high risks associated with such a strategy. Thus, modernising the plant

could be a viable way to optimise the operational costs of the company and help it offer cost-competitive products,

without necessarily being considered as a sufficient strategic option to ensure the long-term competitiveness of the

company.

As for the financial results of investing in MFP, they mainly pave the way for further analyses to test the financial

viability of investing in a set of competitive P&P specialty products, which constitute together a profitable

163

diversification strategy based on low investment requirements. MFP products for example could be embedded within

the P&P mill in addition to other innovative and specialised fibre packaging products, in order to access a set of niche

markets requiring innovative fibre-based substitutes for fossil-based packaging products.

4.6 Conclusion

Canadian P&P companies should rethink their strategies to successfully meet the challenges they are facing. As they

are dealing with an increasingly changing and unpredictable business environment, they have to explicitly consider a

range of economic, social, political and technological uncertainties when designing new strategies.

Scenario planning, a powerful decision-making tool aiming to image a set of plausible different futures, is considered

as a promising approach to manage such uncertainties when evaluating the viability of long-term decisions.

Therefore, integrating scenario planning into strategic design would be effective to help decision makers define robust

strategies that would resist the major shifts affecting the competitiveness of the P&P industry in the coming years.

We have then developed a decision-support framework based on scenario planning to propose, evaluate and identify

robust transformation strategies for Canadian P&P companies. Firstly, we have outlined three potential transformation

strategies that could help these companies profit from current opportunities and achieve a competitive advantage.

Ranging from modernising the conventional P&P manufacturing processes, to looking outside the borders of P&P

markets by integrating high value-added bioproducts, through accessing a number of growing niche P&P markets by

offering innovative fibre-based products, these strategies are considered, a priori, as different promising

transformation pathways to allow P&P companies to thrive in the crisis. Secondly, we have generated four trend-

based scenarios considering different plausible trends within the major shifts in environmental concerns and value

innovation, assumed to be two key driving forces that would shape the future development of P&P companies’

business environment. The four scenarios considered are intended to anticipate the influence of environmental and

innovation issues on technological development, consumer behaviour, governmental policies and market

development. Then, we have developed a mathematical model, based on mixed integer programming, to evaluate the

long-term profitability of each strategic option proposed under the different scenarios considered. A detailed financial

analysis has been included taking into account depreciation, salvage value, and discount rate, in order to propose a

realistic tool to assess the estimated net present value of the investments made within each strategy.

A case study, based on a realistic dataset, considering the case of a typical Canadian Kraft pulp mill, has been

presented to evaluate the robustness of modernising the Kraft pulp manufacturing processes, the integration of

Moulded Fibre Packaging, and the integration of bioethanol manufacturing technology.

The results obtained from the case study, show the potential of investing in Bioethanol as a robust transformation

strategy to allow Canadian P&P companies to achieve a competitive advantage. In particular, under scenarios

164

considering high environmental commitment and a value-driven business environment, integrating bioproducts such

as Bioethanol would be a viable option to diversify the revenues of the given P&P company and hedge against the

eventual increasing decline within conventional P&P markets. Even under scenarios assuming market recovery for

conventional P&P products such as Kraft pulp, bioethanol investments would profit from the steady future

development of already existing political and market pressures requiring innovative substitutes for fossil-based energy

products. The low regret criterion of bioethanol diversification, compared to the two other strategies, makes it a

conservative transformation avenue. As for modernising the P&P manufacturing processes, the case study has

revealed that such a strategy would be effective in ensuring the competitiveness of Canadian P&P companies by

optimising their cost structure and allowing them to offer cost-effective products. However, the effectiveness of

modernisation would heavily rely on the assumed recovery of conventional P&P markets such as Kraft pulp. Under

scenarios assuming continuously shrinking conventional P&P markets, modernising P&P manufacturing processes

would fail to retain Canadian P&P companies’ market shares within progressively declining markets and low-cost

competition. The min-max regret analysis presented confirms the high investment risks related to such a strategy. As

for Moulded Fibre Packaging (MFP), the results show that it would be a robust option to invest in, as its estimated

cash flows would be positive in all scenarios considered. However, as a diversification strategy, investing in MFP

would not be sufficient to achieve a sustainable competitive advantage for Canadian P&P companies, especially

under scenarios assuming fierce global competition for packaging products, because of a low and even negative

estimated net present value in almost all scenarios. Nevertheless, the high investment return rate for MFP suggests

that its integration within a diversified portfolio of innovative specialty packaging products would ensure steady

revenues from a set of growing markets requiring innovative fibre-based substitutes for fossil-based products.

Therefore, via the case study presented in this paper, our aim is mainly to help the P&P sector decision makers

understand the influence of different future scenarios on different strategic decisions considered. Our primary goal is

not to point out the most profitable strategy, but rather to propose a decision-support framework aiming to identify the

most promising pathways to consider when reinventing the strategies of Canadian P&P companies. The findings

obtained from the case study constitute a promising first strategic step towards implementing robust strategies that

would allow Canadian P&P companies to stand out from the competition and achieve a competitive value proposition.

To build on the results presented in this work, considering multi-product diversification strategies, such as a bioenergy

diversification strategy, or a specialty P&P diversification strategy, or even a mixture of specialty P&P and innovative

bio-based product diversification strategy, would be an interesting next research step after this work, in order to

evaluate how such strategies would behave within an increasingly changing business environment.

165

4.7 Appendix

4.7.1 Appendix A: Model parameters’ future trends

In this section, we present in detail how we have built the different trends of the model parameters for each scenario

considered.

4.7.1.1 Kraft pulp Kraft pulp manufacturing process modernisation is the intra-diversification strategy that we have considered in the

case study.

For Kraft pulp, the parameters that would evolve differently under each scenario are production cost (with and without

modernisation), modernisation investment cost, conversion rate (with and without modernisation), market demand

and market price. Each of these parameters depends on one or several factors, which would evolve differently under

each scenario.

To abbreviate the text, we present only how we have obtained the estimated future trend for the production cost in the

case of modernisation strategy. In fact, we consider that Kraft pulp production cost would depend on energy prices

(as energy represents about 25% of the operating costs), technological development (as the modernisation would

improve the efficiency of the Kraft pup manufacturing process), and governmental incentives (as the government

would be an important player in promoting or not the development and the investment in Kraft pulp innovative

technologies). In Scenario 1, for example, we consider that energy prices would fairly increase Kraft pulp production

cost (+), due to the low-environmental commitment in Scenario 1. Moreover, technological development would highly

decrease Kraft pulp production cost (- -), due to the cost-driven environment. On the governmental side, the

governmental incentives would decrease Kraft pulp production cost (-), due to its financial support in promoting the

modernisation of P&P manufacturing processes via, for example, tax exemptions and carbon offsets. By summing the

future trends of these three factors, the production cost, in the case of modernisation, would highly decrease (- -)

under Scenario 1. However, in Scenario 4, we consider that energy prices would very highly increase the operating

costs (+ + +), due to high environmental restrictions and value-driven requirements. Technological development

would slightly decrease Kraft pulp operating costs (-) due to the value-driven requirements regarding technological

development, which would favour innovative technology development over conventional P&P technologies. For the

same reason, the governmental incentives would be almost nonexistent (0) to promote the modernisation of such

conventional processes. Thus, Kraft pulp production cost would considerably increase in this scenario (+ +), being

mainly affected by increasing energy prices.

In the same way, Kraft pulp production cost, in the case of modernisation, would be estimated to decrease over the

planning horizon under Scenario 2 (-), and would experience no change under Scenario 3 (0).

166

In Table 4.4, all the future trends’ model parameters related to Kraft pulp are detailed, for each of the four scenarios. K

raft

pulp

Parameters Scenario 1 Scenario 2 Scenario 3 Scenario 4

Production cost With modernisation

- - - 0 + +

Energy prices + + + + + + + Technology development - - - - - - Governmental incentives - - 0 0

Production cost without modernisation

+ + + + + + +

Energy prices + + + + + + +

Investment cost for modernisation

- - - - - - - -

Technology development - - - - - - Governmental incentives - - 0 0

Conversion rate without modernisation

++ + + +

Manufacturing process development

++ + + +

Conversion rate with modernisation

+ + + + + + + + + +

Technology development + + + + + + + + + +

Market demand + + + - - - Consumer behaviour + 0 - - -

Governmental incentives + + 0 0

Market price - - - - - - - - Market demand + + + - - -

Low-cost Competition - - - - - - - -

Tableau 4.4 Kraft pulp model parameters' future trends

4.7.1.2 Moulded Fibre Packaging (MFP) MFP integration is the intra-diversification strategy that we have considered in the case study.

For MFP, the parameters that would evolve differently under each scenario are production cost, investment cost,

conversion rate, market demand and market price. Each of these parameters depends on one or several factors that

would evolve differently under the different scenarios. As we have explained above for Kraft pulp, the different future

trends for the parameters related to MFP are obtained by summing the future trends for the factors affecting their

evolution. In Table 4.5, all the future trends’ model parameters related to MFP are detailed, for each of the four

scenarios.

167

Mou

lded

Fib

re P

acka

ging

Parameters Scenario 1 Scenario 2 Scenario 3 Scenario 4

Production cost 0 - - - - Energy prices + + + + + + +

Technology development - - - - - - - Governmental incentives 0 - - - -

Investment cost - - - - - - - - Technology development - - - - - - - Governmental incentives 0 - - - -

Conversion rate + + + + + + + Technology development + + + + + + +

Market demand + + + + + + + + + Consumer behaviour + + + + + + + Supportive policies 0 + + + +

Market price 0 + + 0 + Market demand + + + + + + + +

Low-cost Competition - - - - -

Tableau 4.5 MFP model parameters' future trends

4.7.1.3 Bioethanol Bioethanol integration is the inter-diversification strategy that we have considered in the case study.

For Bioethanol, the parameters that would evolve differently under each scenario are production cost, investment

cost, conversion rate, market demand and market price. Each of these parameters depends on one or several factors

that would evolve differently under the different scenarios. As we have explained above for Kraft pulp and MFP, the

different future trends for the parameters related to Bioethanol are obtained by summing the future trends for the

factors affecting their evolution. In Table 4.6, all the future trends’ model parameters related to Bioethanol are

detailed, for each of the four scenarios.

Bio

etha

nol

Parameters Scenario 1 Scenario 2 Scenario 3 Scenario 4

Production cost - - - - - - - - - Technology development - - - - - - - Governmental incentives 0 - - - -

Investment cost - - - - - - - - - Technology development - - - - - - - Governmental incentives 0 - - - -

Conversion rate + + + + + + + Technology development + + + + + + +

Market demand + + + + + + + + Consumer behaviour + + + + + Supportive policies 0 + + +

Market price + + + + + + + +

168

Market demand + + + + + + + + Energy prices + + + + + + +

Tableau 4.6 Bioethanol model parameters' future trends

4.7.1.4 Forest residues For forest residues, their supplying cost would evolve differently under the different scenarios considered. We assume

that forest residues’ supplying cost depends on the market demand for bioenergy as well for pulp, and on the

supplying management development. In Scenario 1, for example, we assume that the bioenergy market demand

would increase (+) due to a steady growth of bioenergy markets. Moreover, the recovery from the conjectural crisis for

the P&P sector would increase the demand for pulp and generated forest residues, which would highly decrease the

supplying cost of forest residues (- -). Regarding forest residues’ supply management, we assume that future

development in forest operations, due to a cost-driven environment, would decrease forest residue supplying cost (-).

By summing these different future trends, the forest residues’ supplying cost would be expected to highly decrease

during the next years (- -). In Scenario 4, the high demand for bioenergy products, to meet increasing environmental

and value-driven requirements, would highly increase the demand for forest residues and thus their supplying cost (+

+ +). The increasing decline in conventional P&P markets would result in a scarcity in available forest residues, which

would highly increase their supplying cost (+ +). As for the supplying management development, it would contribute,

as in Scenario 1, in reducing the supplying cost for forest residues (-). All these trends would result in a very high

increase in forest residues’ supplying cost (+ + +). In Table 4.7, the four future trends for forest residues’ supplying

cost are detailed.

Fore

st

resi

dues

Parameters Scenario 1 Scenario 2 Scenario 3 Scenario 4

Supplying cost - - 0 + + + + +

Bioenergy Market demand + + + + + + + +

Pulp market demand - - - + + +

Supplying management development

- - - -

Tableau 4.7 Forest residues’ supplying cost future trends

4.7.1.5 Wood chips For Wood chips, their supplying cost would evolve differently under the different scenarios considered. We assume

that the Wood chips supplying cost depends on the market demand for bioenergy as well for pulp, and on the

supplying management development. As we have explained above for Forest residues, the different future trends for

Wood chips’ supplying cost are obtained by summing the future trends for the factors affecting their evolution. In

Table 4.8, the four future trends for Wood chips’ supplying cost are detailed.

169

W

ood

chip

s Parameters Scenario 1 Scenario 2 Scenario 3 Scenario 4

Supplying cost + + + + 0 0

Bioenergy Market demand + + + + + + + +

Pulp market demand + + + - - -

Supplying management development

- - - -

Tableau 4.8 Wood chips’ supplying cost future trends

4.7.1.6 Recycled paper For Recycled paper, its supplying cost would evolve differently under the different scenarios considered. We assume

that the Recycled paper supplying cost depends on the market demand for moulded pulp as well for pulp. As we have

explained above for Forest residues and Wood chips, the different future trends for Recycled paper supplying cost are

obtained by summing the future trends for the factors affecting its evolution. In Table 4.9, the four future trends for

Recycled paper supplying cost are detailed.

Rec

ycle

d pa

per

Parameters Scenario 1 Scenario 2 Scenario 3 Scenario 4

Supplying cost - + + + + + + +

Moulded pulp demand + + + + + + + +

Paper market demand - - - + + +

Tableau 4.9 Recycled paper supplying cost future trends

170

4.7.2 Appendix B: Model database

In the following table, we present the data used in the mathematical model to evaluate the different transformation strategies.

Parameters Current value Future trend ( )

S1 S2 S3 S4

20 (FPInnovations, 2011)

N.A

4

20

30

20

1010

30%

5%

100$/dt(FPInnovations, 2011) +10% +10% 0% 0%

70$/t (RECYC-QUÉBEC, 2013) -5% +10% +10% +15%

76$/dt(FPInnovations, 2011) -10% 0% +10% +15%

Var 398$/t (Browne, 2011) +10% +20% +10% +30%

Fixed 15 M$ pour 130kt/year N.A

Modernised

Var 386$/t (-3% p/r Kraft pulp) -20% -10% 0% +20%

Fixed 15 M$ pour 130kt/year ((FAO, 1984),

(FPInnovations, 2011)) N.A

Var 278$/t (-30%p/r Kraft pulp)

0% -10% -20% -10% Fixed 92$/t for 130kt/year (-20% p/r Kraft pulp)

% / 20years

T

C

FH

EL

FL

M

TR

r

SCi ,t ,s

"WC"

"RP"

"FR"

PCi ,t ,s

"KP"

"KP"

"MFP"

171

0.3$/L (FPInnovations, 2011) -20% -15% -25%(IPCC, 2011) -25% (IPCC,

2011) -30%

0.77t/ t (Kramer et al., 2009) +5% +10% +10% +10%

280 L /dt (FPInnovations, 2011) +10% +10% +20% +30%

0.42t/t (Shaun L. Turriff, 2011) +10% +5% +5% +5%

Modernised

0.52t/t (+25% p/r Kraft pulp) +20% +20% +10% +10%

340 L/dt (IPCC, 2011) +10% +10% +20% +30%

(unit/y)

130 kt (MRNF, 2009) N.A

50kt 100kt 150kt N.A

30ML 60 ML 90ML N.A

(M$)

Modernised 65

-20% -20% -10% -10% 500$/t(MRNF, 2000)

12.5 25 45

-10% -15% -15% -20% 300$/t

47.25 94.5 141.75

-15% -25%(IPCC, 2011) -25% (IPCC,

2011) -30%

1.575$/L (FPInnovations, 2011)

880$ (Average based on 52 weeks) (RNC, 2013)

-5%(UNECE/FAO,

2012) -15% -15% -30%

500$/t(UFP Technologies, 2013) 0% +20% 0% +10%

0.65$/L (FPInnovations, 2011) +4% (EIA, 2009) +20% +20% +43% (EIA,

2009)

100kt (Estimated to 75% of total capacity)

+40% (Reverse trend of

2000-2010) +10% -10% -48%

"BE"

i ,t , j ,s

"RP" "MFP"

"FR" "BE"

"WC"

"KP"

"KP"

"BE"

Ko,i

"Op1" "Op2" "Op3"

"PP"

"MF"

"FER"

ICo,i ,c,s

"Op1" "Op2" "Op3"

"KP"

"MF"

"FER"

Pi ,t ,s

"KP"

"MFP"

"BE"

di ,t ,s "KP"

172

(FAO, 2013)

65 kt (Estimated to 50% of Kraft pulp demand) +10% +20% +20%

+32% (current growing

trend)(FAO, 2013)

60 ML in QC (20% of 300ML in QC) (Site de la première

ministre du Québec, 2007)

+20% (current trend) (FPAC,

2011) +30% +30% +40%

0, 25 (Personal assumption)

0.25 N.A N.A N.A

0, 25 (Personal assumption) N.A 0.25 N.A N.A

0, 25 (Personal assumption) N.A N.A 0.25 N.A

0, 25 (Personal assumption) N.A N.A N.A 0.25

"MFP"

"BE"

ps

"S1"

"S2 "

"S3 "

"S4 "

173

Chapitre 5 Conclusion générale et perspectives

174

Tout au long de cette thèse, nous nous sommes intéressés à la problématique de la transformation de

l’industrie forestière, en particulier les compagnies de pâtes et papiers. Les changements structurels ainsi que

la conjoncture difficile affectant le secteur de pâtes et papiers ont rendu inévitable le développement de

nouvelles approches d’aide à la décision afin d’appréhender les nouvelles réalités des marchés et permettre

aux compagnies de se doter d’outils stratégiques assurant une transformation profitable vers un modèle

d’affaires compétitif.

Ainsi, nous avons développé un nombre d’approches permettant aux décideurs au sein du secteur de pâtes et

papiers de réinventer leurs modèles d’affaires, d’aligner les différents niveaux de décision à cette

transformation, d’optimiser les réseaux de création de valeur qui y sont associés, ainsi que d’identifier les

avenues de transformation les plus prometteuses dans un environnement d’affaires évolutif et incertain.

En combinant des outils de recherche opérationnelle, notamment la modélisation mathématique et la

programmation à nombres entiers mixtes, avec différents concepts de planification et de gestion stratégiques,

tels que les stratégies et les modèles d’affaires, nous avons proposé des méthodologies pratiques dans le but

de supporter le processus de transformation des compagnies de pâtes et papiers.

Dans la première contribution, nous avons présenté une approche à multi-niveaux pour supporter la

planification, la conception et la validation d’un nouveau modèle d’affaires pour les compagnies de pâtes et

papiers. Afin d’aligner les différents niveaux de décision à l’innovation apportée par le modèle d’affaires, une

nouvelle vision décrivant la direction générale de la compagnie a été définie. Une stratégie permettant de

traduire cette vision en un avantage concurrentiel a été proposée. Un canevas à neuf blocs a été adapté pour

le cas d’une compagnie de pâtes et papiers afin d’illustrer la conception d’un nouveau modèle d’affaires basé

sur le concept de la bioraffinerie forestière intégrée. Finalement, un ensemble d’indicateurs qualitatifs et

quantitatifs ont été proposés pour valider la conception présentée. Le modèle d’affaires proposé dans cette

contribution, s’avère à priori un concept prometteur pour le secteur de pâtes et papiers.

Lors de la deuxième contribution, nous avons développé une méthodologie basée sur la modélisation

mathématique afin d’évaluer quantitativement le potentiel d’intégrer la bioénergie au sein des usines de pâtes

et papiers. En présélectionnant un nombre de matières premières, de technologies et de produits adaptés au

contexte Québécois, nous avons construit une base de données pertinentes rassemblant des données

réalistes sur les coûts d’approvisionnement des matières premières, les coûts d’investissement des

technologies à implanter, les coûts d’opération pour les produits considérés, les prix de vente des produits finis

et des co-produits sur les différents marchés, ainsi que sur les tendances d’évolution future pour les différents

paramètres considérés. Nous avons ensuite développé un modèle mathématique à nombres entiers mixtes

afin de décider des technologies de production de bioénergie les plus profitables à intégrer, leur séquence

175

d’investissement et d’ajout de capacité, tout en optimisant conjointement l’activité conventionnelle de

production de pâtes et papiers, et ce sur un horizon de vingt ans. En considérant une étude de cas présentant

une usine de production de pâte Kraft, nous avons proposé une feuille de route optimale des investissements

en bioénergie à intégrer au sein d’une usine de pâtes et papiers durant les vingt prochaines années. Une

analyse de sensibilité nous a permis d’amener une réflexion quant à l’impact des tendances technologiques,

économiques et sociopolitiques futures sur le potentiel d’une telle intégration.

Dans la troisième contribution, nous avons apporté une approche de modélisation par scénarios pour identifier

les stratégies de transformation les plus robustes pour le secteur de pâtes et papiers. Nous avons commencé

par identifier trois familles de stratégies de transformation incluant la modernisation des processus de

production de pâtes et papiers, l’intégration de produits de pâtes et papiers innovateurs, et l’intégration de

bioproduits. Nous avons ensuite généré quatre scénarios futurs d’évolution de l’environnement d’affaires des

compagnies de pâtes et papiers, et ce à partir des différentes tendances technologiques, économiques et

sociopolitiques considérées dans les années à venir. Afin d’évaluer la profitabilité de chacune des stratégies

pour les différents scénarios définis, nous avons développé un modèle mathématique à nombres entiers

mixtes pour optimiser l’implémentation de la stratégie sur un horizon de vingt ans. Les résultats obtenus à

l’issue de l’étude de cas, présentant une usine à pâte Kraft, révèlent l’impact important des différents

scénarios futurs sur la profitabilité des options de transformation.

Les trois contributions proposées apportent de nouvelles approches d’aide à la décision pour accompagner la

transformation des compagnies de pâtes et papiers. Les résultats obtenus, bien que leur validité soit limitée

aux études de cas considérées, amènent de nouvelles réflexions sur les options stratégiques les plus

prometteuses pour le secteur et constituent des premières étapes de valeur pour des études plus

approfondies.

Les approches et méthodologies présentées dans cette thèse, bien qu’elles soient appliquées au secteur de

pâtes et papiers au Canada, pourraient être remodelées pour les adapter à d’autres secteurs industriels,

notamment celui de l’industrie forestière tels que le secteur du bois d’œuvre, dont les marchés subissent des

changements majeurs depuis plusieurs années. De façon générale, les développements autour des

bioproduits, biocarburants et bioénergies, offrent des opportunités de transformation aux secteurs capables

d’intégrer des activités de bioraffinage (exemple : agriculture, pétrole, valorisation des résidus, etc.). Les

fondements méthodologiques de cette thèse pourraient aussi influencer la façon dont la conception des

chaines de valeur est soutenue par les spécialistes de la logistique et de l’optimisation. L’intégration des

processus de réflexion stratégique, d’une conception basée sur un plan d’investissement stratégique et

176

l’intégration d’une stratégie de gestion du risque sont les principaux apports de cette thèse aux méthodologies

reconnues dans la littérature et utilisées par les gestionnaires.

Par ailleurs, les résultats obtenus à travers les différentes contributions ont révélé l’impact majeur des

tendances environnementales sur les différents niveaux de décision. Durant cette thèse, nous nous sommes

limités à évaluer l’impact global de telles tendances sur la planification et la gestion stratégiques pour le cas

des compagnies de pâtes et papiers. Dans les trois contributions, l’engagement environnemental des

politiques gouvernementales, des stratégies d’entreprises et du développement technologique a fortement

affecté le potentiel des pistes de transformations évaluées. Néanmoins, d’autres éléments tels que la bourse

de carbone, les crédits ou taxes sur émissions des gaz à effet de serre, non considérées explicitement dans

ce travail, auraient probablement un impact majeur sur la profitabilité des compagnies forestières dans les

années à venir. Ainsi, développer des outils d’aide à la décision évaluant en détail l’impact de tels concepts

sur la transformation de ces compagnies apporterait surement une contribution de valeur à de telles

approches décisionnelles. Des méthodologies basées sur des modèles mathématiques pourraient être

développées pour optimiser à la fois les profits économiques et environnementaux liés à telle ou telle

transformation. Afin de tenir compte explicitement de ces différentes dimensions, des modèles multi-objectifs

optimisant à la fois les coûts logistiques, les émissions de gaz à effet de serre, et les coûts ou/et les profits

environnementaux engendrés, amèneraient de nouvelles réflexions sur l’impact du choix d’une stratégie de

transformation sur la compagnie. D’autre part, différents mécanismes gouvernementaux basés sur les

subventions « vertes », la création et la régulation de marchés de carbone, ou encore les exemptions de

taxes, pourraient être intégrés dans des approches décisionnelles pour identifier les politiques les plus

prometteuses supportant une transformation efficace du secteur.

177

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