IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v138y2017icp563-574.html
   My bibliography  Save this article

Managing technology performance risk in the strategic design of biomass-based supply chains for energy in the transport sector

Author

Listed:
  • d'Amore, Federico
  • Bezzo, Fabrizio

Abstract

Biomass has long been considered one of the most promising feedstock as an alternative primary source to substitute traditional fuels in the transport sectors. However, both biomass intrinsic variability and the fact that several conversion technologies have not reached full maturity make the economic assessment of the production system performance rather difficult. This paper proposes a quantitative approach for the strategic design and optimisation of biomass-based supply chains under uncertainty on technology conversion efficiency. The methodology is based on regret theory and allows quantifying both risk and regret with respect to benchmark economic outputs. A Mixed Integer Linear Programming is employed to represent and optimise the profitability of a multi-echelon, multi-period and spatially explicit biomass-based supply chain for bioethanol and bioelectricity production where several conversion technologies are simultaneously taken into account. The modelling framework includes biomass cultivation, transport, conversion, distribution and final usage in alternative fuel vehicles (running either on bioethanol or bioelectricity). Results demonstrate how the methodology can help policy-makers and investors assessing technological options according to their risk aversion attitude.

Suggested Citation

  • d'Amore, Federico & Bezzo, Fabrizio, 2017. "Managing technology performance risk in the strategic design of biomass-based supply chains for energy in the transport sector," Energy, Elsevier, vol. 138(C), pages 563-574.
    • Handle: RePEc:eee:energy:v:138:y:2017:i:c:p:563-574
    DOI: 10.1016/j.energy.2017.07.074
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217312501
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.07.074?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ahmed, Sajjad & Elsholkami, Mohamed & Elkamel, Ali & Du, Juan & Ydstie, Erik B. & Douglas, Peter L., 2014. "Financial risk management for new technology integration in energy planning under uncertainty," Applied Energy, Elsevier, vol. 128(C), pages 75-81.
    2. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-824, December.
    3. Nooraie, S. Vahid & Mellat Parast, Mahour, 2015. "A multi-objective approach to supply chain risk management: Integrating visibility with supply and demand risk," International Journal of Production Economics, Elsevier, vol. 161(C), pages 192-200.
    4. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    5. Han Bleichrodt & Peter P. Wakker, 2015. "Regret Theory: A Bold Alternative to the Alternatives," Economic Journal, Royal Economic Society, vol. 0(583), pages 493-532, March.
    6. Arnold, Uwe & Yildiz, Özgür, 2015. "Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach," Renewable Energy, Elsevier, vol. 77(C), pages 227-239.
    7. Bedoui, Rihab & Hamdi, Haykel, 2015. "Option-implied risk aversion estimation," The Journal of Economic Asymmetries, Elsevier, vol. 12(2), pages 142-152.
    8. Khatiwada, Dilip & Leduc, Sylvain & Silveira, Semida & McCallum, Ian, 2016. "Optimizing ethanol and bioelectricity production in sugarcane biorefineries in Brazil," Renewable Energy, Elsevier, vol. 85(C), pages 371-386.
    9. Bartunek, Kenneth S & Chowdhury, Mustafa, 1997. "Implied Risk Aversion Parameter from Option Prices," The Financial Review, Eastern Finance Association, vol. 32(1), pages 107-124, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yoichiro Fujii & Hajime Murakami & Yutaka Nakamura & Kazuhisa Takemura, 2023. "Multiattribute regret: theory and experimental study," Theory and Decision, Springer, vol. 95(4), pages 623-662, November.
    2. Emerson Melo, 2021. "Learning in Random Utility Models Via Online Decision Problems," Papers 2112.10993, arXiv.org, revised Aug 2022.
    3. Etelvina Stefani Chavez & Gastón Milanesi & Gabriela Pesce, 2021. "Aversión al riesgo implícita en los precios de mercado de diferentes activos financieros de Argentina," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-23, Enero - M.
    4. Fang Liu, 2021. "Regret theory under fear of the unknown," Papers 2108.01825, arXiv.org.
    5. Gollier, Christian, 2016. "Explaining rank-dependent utility with regret and rejoicing," IDEI Working Papers 863, Institut d'Économie Industrielle (IDEI), Toulouse.
    6. Enrico Diecidue & Haim Levy & Moshe Levy, 2020. "Probability Dominance," The Review of Economics and Statistics, MIT Press, vol. 102(5), pages 1006-1020, December.
    7. Zheng, Jiakun, 2021. "Willingness to pay for reductions in health risks under anticipated regret," Journal of Health Economics, Elsevier, vol. 78(C).
    8. Emmanuelle GABILLON, 2020. "When choosing is painful: anticipated regret and psychological opportunity cost," Bordeaux Economics Working Papers 2020-04, Bordeaux School of Economics (BSE).
    9. Paolo Guasoni & Gur Huberman & Dan Ren, 2020. "Shortfall aversion," Mathematical Finance, Wiley Blackwell, vol. 30(3), pages 869-920, July.
    10. Zhuzhu Zhou, 2024. "Ranking blame," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(2), pages 403-441, September.
    11. Doruk Iris, 2017. "Representation and Social Regret in Risk-Taking," Working Papers 1701, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    12. Klaus Wälde, 2016. "Emotion Research in Economics," CESifo Working Paper Series 5982, CESifo.
    13. Jiakun Zheng, 2021. "Willingness to pay for reductions in health risks under anticipated regret," Post-Print hal-04227414, HAL.
    14. Bonanno, Giacomo, 2022. "Minimax regret with imperfect ex-post knowledge of the state," Research in Economics, Elsevier, vol. 76(4), pages 403-412.
    15. Bertrand, Philippe & Prigent, Jean-luc, 2019. "On the optimality of path-dependent structured funds: The cost of standardization," European Journal of Operational Research, Elsevier, vol. 277(1), pages 333-350.
    16. Herweg, Fabian & Müller, Daniel, 2021. "A comparison of regret theory and salience theory for decisions under risk," Journal of Economic Theory, Elsevier, vol. 193(C).
    17. Armantier, Olivier & Foncel, Jérôme & Treich, Nicolas, 2023. "Insurance and portfolio decisions: Two sides of the same coin?," Journal of Financial Economics, Elsevier, vol. 148(3), pages 201-219.
    18. Ang, Dionysius & Diecidue, Enrico & Dewitte, Siegfried, 2022. "To deliberate or not? The effects of anticipated regret and deliberation on willingness-to-pay," Journal of Business Research, Elsevier, vol. 151(C), pages 563-578.
    19. Guo, Xu & Wong, Wing-Keung & Xu, Qunfang & Zhu, Xuehu, 2015. "Production and hedging decisions under regret aversion," Economic Modelling, Elsevier, vol. 51(C), pages 153-158.
    20. Doruk İriş & Jungmin Lee & Alessandro Tavoni, 2019. "Delegation and Public Pressure in a Threshold Public Goods Game," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 1331-1353, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:138:y:2017:i:c:p:563-574. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.