IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v195y2009i1p296-306.html
   My bibliography  Save this article

Modeling technology adoptions for sustainable development under increasing returns, uncertainty, and heterogeneous agents

Author

Listed:
  • Ma, T.
  • Grubler, A.
  • Nakamori, Y.

Abstract

This paper presents a stylized model of technology adoptions for sustainable development under the three potentially most important "stylized facts": increasing returns to adoption, uncertainty, and heterogeneous agents following diverse technology development and adoption strategies. The stylized model deals with three technologies and two heterogeneous agents: a risk-taking one and a risk-averse one. Interactions between the two agents include trade in resources and goods, and technological spillover (free riding and technology trade). With the two heterogeneous agents, we run optimizations to minimize their aggregated costs in order to find out what rational behaviors are under different assumptions if the two agents are somehow cooperative. By considering uncertain carbon taxes, the model also addresses environmental issues as potential driving forces for technology adoptions.

Suggested Citation

  • Ma, T. & Grubler, A. & Nakamori, Y., 2009. "Modeling technology adoptions for sustainable development under increasing returns, uncertainty, and heterogeneous agents," European Journal of Operational Research, Elsevier, vol. 195(1), pages 296-306, May.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:1:p:296-306
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(08)00165-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Messner, S. & Golodnikov, A. & Gritsevskii, A., 1996. "A stochastic version of the dynamic linear programming model MESSAGE III," Energy, Elsevier, vol. 21(9), pages 775-784.
    2. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    3. Watanabe, Chihiro, 1995. "Identification of the role of renewable energy," Renewable Energy, Elsevier, vol. 6(3), pages 237-274.
    4. Grubler, Arnulf & Messner, Sabine, 1998. "Technological change and the timing of mitigation measures," Energy Economics, Elsevier, vol. 20(5-6), pages 495-512, December.
    5. William D. Nordhaus, 1973. "The Allocation of Energy Resources," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 4(3), pages 529-576.
    6. Freeman, Chris, 1994. "The Economics of Technical Change," Cambridge Journal of Economics, Oxford University Press, vol. 18(5), pages 463-514, October.
    7. Ma, Tieju & Nakamori, Yoshiteru, 2005. "Agent-based modeling on technological innovation as an evolutionary process," European Journal of Operational Research, Elsevier, vol. 166(3), pages 741-755, November.
    8. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Huayi & Ma, Tieju, 2021. "Technology adoption and carbon emissions with dynamic trading among heterogeneous agents," Energy Economics, Elsevier, vol. 99(C).
    2. Wen Li & Tong Zhou & Qiang Mei & Xiangyang Liu & Muhammad Imran, 2023. "Evolution of micro and small enterprises’ work safety behavior in high-risk industries," Small Business Economics, Springer, vol. 60(1), pages 85-104, January.
    3. Tieju Ma, 2010. "Coping with Uncertainties in Technological Learning," Management Science, INFORMS, vol. 56(1), pages 192-201, January.
    4. Tom Savage & Antonio del Rio Chanona & Gbemi Oluleye, 2023. "Robust Market Potential Assessment: Designing optimal policies for low-carbon technology adoption in an increasingly uncertain world," Papers 2304.10203, arXiv.org.
    5. Guo, Shu & Choi, Tsan-Ming & Chung, Sai-Ho, 2022. "Self-design fun: Should 3D printing be employed in mass customization operations?," European Journal of Operational Research, Elsevier, vol. 299(3), pages 883-897.
    6. Zhang, Qiao & Zhang, Jianxiong & Zaccour, Georges & Tang, Wansheng, 2018. "Strategic technology licensing in a supply chain," European Journal of Operational Research, Elsevier, vol. 267(1), pages 162-175.
    7. Chenhao Fang & Tieju Ma, 2021. "Technology adoption with carbon emission trading mechanism: modeling with heterogeneous agents and uncertain carbon price," Annals of Operations Research, Springer, vol. 300(2), pages 577-600, May.
    8. J. Farmer & Cameron Hepburn & Penny Mealy & Alexander Teytelboym, 2015. "A Third Wave in the Economics of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 329-357, October.
    9. C. Wilson & A. Grubler & N. Bauer & V. Krey & K. Riahi, 2013. "Future capacity growth of energy technologies: are scenarios consistent with historical evidence?," Climatic Change, Springer, vol. 118(2), pages 381-395, May.
    10. Grzegorz Drozdowski, 2021. "Economic Calculus Qua an Instrument to Support Sustainable Development under Increasing Risk," JRFM, MDPI, vol. 14(1), pages 1-12, January.
    11. Ozer, Muammer, 2011. "Understanding the impacts of product knowledge and product type on the accuracy of intentions-based new product predictions," European Journal of Operational Research, Elsevier, vol. 211(2), pages 359-369, June.
    12. Fleiter, Tobias & Worrell, Ernst & Eichhammer, Wolfgang, 2011. "Barriers to energy efficiency in industrial bottom-up energy demand models--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3099-3111, August.
    13. Ma, Tieju & Chen, Huayi, 2015. "Adoption of an emerging infrastructure with uncertain technological learning and spatial reconfiguration," European Journal of Operational Research, Elsevier, vol. 243(3), pages 995-1003.
    14. Chen, Huayi & Zhou, P., 2019. "Modeling systematic technology adoption: Can one calibrated representative agent represent heterogeneous agents?," Omega, Elsevier, vol. 89(C), pages 257-270.
    15. Chi, Chunjie & Ma, Tieju & Zhu, Bing, 2012. "Towards a low-carbon economy: Coping with technological bifurcations with a carbon tax," Energy Economics, Elsevier, vol. 34(6), pages 2081-2088.
    16. Chen, Huayi & Ma, Tieju, 2014. "Technology adoption with limited foresight and uncertain technological learning," European Journal of Operational Research, Elsevier, vol. 239(1), pages 266-275.

    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. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    2. Stavins, Robert & Jaffe, Adam & Newell, Richard, 2000. "Technological Change and the Environment," Working Paper Series rwp00-002, Harvard University, John F. Kennedy School of Government.
    3. Chen, Huayi & Ma, Tieju, 2017. "Optimizing systematic technology adoption with heterogeneous agents," European Journal of Operational Research, Elsevier, vol. 257(1), pages 287-296.
    4. Ma, Tieju & Nakamori, Yoshiteru, 2009. "Modeling technological change in energy systems – From optimization to agent-based modeling," Energy, Elsevier, vol. 34(7), pages 873-879.
    5. Jin, Wei & Zhang, ZhongXiang, 2014. "Explaining the Slow Pace of Energy Technological Innovation Why Market Conditions Matter?," Energy: Resources and Markets 165758, Fondazione Eni Enrico Mattei (FEEM).
    6. Chi, Chunjie & Ma, Tieju & Zhu, Bing, 2012. "Towards a low-carbon economy: Coping with technological bifurcations with a carbon tax," Energy Economics, Elsevier, vol. 34(6), pages 2081-2088.
    7. Leo Wangler, 2010. "Renewables and Innovation - Empirical Assessment and Theoretical Considerations," Jena Economics Research Papers 2010-002, Friedrich-Schiller-University Jena.
    8. Jaffe, Adam B. & Newell, Richard G. & Stavins, Robert N., 2003. "Chapter 11 Technological change and the environment," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 1, chapter 11, pages 461-516, Elsevier.
    9. Rosendahl, Knut Einar, 2004. "Cost-effective environmental policy: implications of induced technological change," Journal of Environmental Economics and Management, Elsevier, vol. 48(3), pages 1099-1121, November.
    10. Vogt-Schilb, Adrien & Hallegatte, Stephane & de Gouvello Christophe, 2014. "Long-term mitigation strategies and marginal abatement cost curves : a case study on Brazil," Policy Research Working Paper Series 6808, The World Bank.
    11. Kverndokk, Snorre & Rosendahl, Knut Einar & Rutherford, Thomas F., 2004. "Climate policies and induced technological change: Impacts and timing of technology subsidies," Memorandum 05/2004, Oslo University, Department of Economics.
    12. Adrien Vogt-Schilb & St�phane Hallegatte & Christophe de Gouvello, 2015. "Marginal abatement cost curves and the quality of emission reductions: a case study on Brazil," Climate Policy, Taylor & Francis Journals, vol. 15(6), pages 703-723, November.
    13. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    14. Chen, Huayi & Ma, Tieju, 2021. "Technology adoption and carbon emissions with dynamic trading among heterogeneous agents," Energy Economics, Elsevier, vol. 99(C).
    15. F. Knobloch & J. -F. Mercure, 2016. "The behavioural aspect of green technology investments: a general positive model in the context of heterogeneous agents," Papers 1603.06888, arXiv.org.
    16. Taminiau, Yvette, 2006. "Beyond known uncertainties: Interventions at the fuel-engine interface," Research Policy, Elsevier, vol. 35(2), pages 247-265, March.
    17. Jean-François Mercure, 2015. "An age structured demographic theory of technological change," Journal of Evolutionary Economics, Springer, vol. 25(4), pages 787-820, September.
    18. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
    19. Iyer, Gokul & Hultman, Nathan & Eom, Jiyong & McJeon, Haewon & Patel, Pralit & Clarke, Leon, 2015. "Diffusion of low-carbon technologies and the feasibility of long-term climate targets," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 103-118.
    20. Blandine Laperche & Nadine Levratto, 2012. "The Emergence of Ecological Opportunities and Firms’ Behaviour," Chapters, in: Blandine Laperche & Nadine Levratto & Dimitri Uzunidis (ed.), Crisis, Innovation and Sustainable Development, chapter 2, Edward Elgar Publishing.

    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:ejores:v:195:y:2009:i:1:p:296-306. 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.elsevier.com/locate/eor .

    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.