IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v138y2020ics0301421520300021.html
   My bibliography  Save this article

When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles

Author

Listed:
  • Hidayatno, Akhmad
  • Jafino, Bramka Arga
  • Setiawan, Andri D.
  • Purwanto, Widodo Wahyu

Abstract

Natural gas vehicles (NGV) face significant adoption barriers in Jakarta. Therefore, a successful transition requires measures from the government. Owing to the high cost of transition policies, the efficacy of these policies must be analyzed to identify the most effective policy. The implementation of transition policies, however, could dynamically influence people's perception and behavior, which then changes the landscape of adoption barriers. Furthermore, even a seemingly successful policy may fail when a certain pathway of uncertainties emerges in the future. To address these concerns, we integrated agent-based modeling, exploratory modeling, and diffusion of innovation theory into the exploratory model-based diffusion analysis approach. This approach evaluates the policy's performance, explores changes in the relative importance of different adoption barriers, and identifies policy vulnerabilities, i.e., scenarios leading to policy failures. We tested this approach on four NGV transition policies targeting three adoption barriers. We found that the importance of adoption barriers and the critical uncertainties upon the implemented policies. The social–behavioral barrier predominates under current conditions, whereas the economic factor becomes more relevant when all policies are executed. Understanding the changes in adoption barriers and policy vulnerabilities will help decision-makers to prepare additional measures that ensure a successful transition.

Suggested Citation

  • Hidayatno, Akhmad & Jafino, Bramka Arga & Setiawan, Andri D. & Purwanto, Widodo Wahyu, 2020. "When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles," Energy Policy, Elsevier, vol. 138(C).
  • Handle: RePEc:eee:enepol:v:138:y:2020:i:c:s0301421520300021
    DOI: 10.1016/j.enpol.2020.111239
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421520300021
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2020.111239?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. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    2. Kwakkel, Jan H. & Pruyt, Erik, 2013. "Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 419-431.
    3. Köhler, Jonathan & Whitmarsh, Lorraine & Nykvist, Björn & Schilperoord, Michel & Bergman, Noam & Haxeltine, Alex, 2009. "A transitions model for sustainable mobility," Ecological Economics, Elsevier, vol. 68(12), pages 2985-2995, October.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    6. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    7. Julie Rozenberg & Céline Guivarch & Robert Lempert & Stéphane Hallegatte, 2014. "Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation," Climatic Change, Springer, vol. 122(3), pages 509-522, February.
    8. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    9. Robert J. Lempert & David G. Groves & Steven W. Popper & Steve C. Bankes, 2006. "A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios," Management Science, INFORMS, vol. 52(4), pages 514-528, April.
    10. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    11. Eker, Sibel & van Daalen, Els, 2015. "A model-based analysis of biomethane production in the Netherlands and the effectiveness of the subsidization policy under uncertainty," Energy Policy, Elsevier, vol. 82(C), pages 178-196.
    12. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    13. Sierzchula, William & Bakker, Sjoerd & Maat, Kees & van Wee, Bert, 2014. "The influence of financial incentives and other socio-economic factors on electric vehicle adoption," Energy Policy, Elsevier, vol. 68(C), pages 183-194.
    14. Sebastiaan Greeven & Oscar Kraan & Emile Chappin & Jan H. Kwakkel, 2016. "The Emergence of Climate Change Mitigation Action by Society: An Agent-Based Scenario Discovery Study," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(3), pages 1-9.
    15. Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
    16. Noam Bergman & Alex Haxeltine & Lorraine Whitmarsh & Jonathan Köhler & Michel Schilperoord & Jan Rotmans, 2008. "Modelling Socio-Technical Transition Patterns and Pathways," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-7.
    17. Martino Tran & David Banister & Justin D. K. Bishop & Malcolm D. McCulloch, 2012. "Realizing the electric-vehicle revolution," Nature Climate Change, Nature, vol. 2(5), pages 328-333, May.
    18. Wolf, Ingo & Schröder, Tobias & Neumann, Jochen & de Haan, Gerhard, 2015. "Changing minds about electric cars: An empirically grounded agent-based modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 269-285.
    19. Walker, Warren E. & Rahman, S. Adnan & Cave, Jonathan, 2001. "Adaptive policies, policy analysis, and policy-making," European Journal of Operational Research, Elsevier, vol. 128(2), pages 282-289, January.
    20. Wander Jager, Marco A. Janssen, Charles Viek, 2001. "Experimentation with household dynamics: the consumat approach," International Journal of Sustainable Development, Inderscience Enterprises Ltd, vol. 4(1), pages 90-100.
    21. Noori, Mehdi & Tatari, Omer, 2016. "Development of an agent-based model for regional market penetration projections of electric vehicles in the United States," Energy, Elsevier, vol. 96(C), pages 215-230.
    22. Faber, Albert & Valente, Marco & Janssen, Peter, 2010. "Exploring domestic micro-cogeneration in the Netherlands: An agent-based demand model for technology diffusion," Energy Policy, Elsevier, vol. 38(6), pages 2763-2775, June.
    23. Erahman, Qodri Febrilian & Purwanto, Widodo Wahyu & Sudibandriyo, Mahmud & Hidayatno, Akhmad, 2016. "An assessment of Indonesia's energy security index and comparison with seventy countries," Energy, Elsevier, vol. 111(C), pages 364-376.
    24. Reddy, Sudhakar & Painuly, J.P, 2004. "Diffusion of renewable energy technologies—barriers and stakeholders’ perspectives," Renewable Energy, Elsevier, vol. 29(9), pages 1431-1447.
    25. Eppstein, Margaret J. & Grover, David K. & Marshall, Jeffrey S. & Rizzo, Donna M., 2011. "An agent-based model to study market penetration of plug-in hybrid electric vehicles," Energy Policy, Elsevier, vol. 39(6), pages 3789-3802, June.
    26. Marco A. Janssen & Wander Jager, 1999. "An Integrated Approach to Simulating Behavioural Processes: a Case Study of the Lock-in of Consumption Patterns," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(2), pages 1-2.
    27. Ascough, J.C. & Maier, H.R. & Ravalico, J.K. & Strudley, M.W., 2008. "Future research challenges for incorporation of uncertainty in environmental and ecological decision-making," Ecological Modelling, Elsevier, vol. 219(3), pages 383-399.
    28. Jonathan Köhler & Fjalar de Haan & Georg Holtz & Klaus Kubeczko & Enayat Moallemi & George Papachristos & Emile Chappin, 2018. "Modelling Sustainability Transitions: An Assessment of Approaches and Challenges," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(1), pages 1-8.
    29. Warren E. Walker & Vincent A. W. J. Marchau & Jan H. Kwakkel, 2013. "Uncertainty in the Framework of Policy Analysis," International Series in Operations Research & Management Science, in: Wil A. H. Thissen & Warren E. Walker (ed.), Public Policy Analysis, edition 127, chapter 0, pages 215-261, Springer.
    30. Moallemi, Enayat A. & de Haan, Fjalar & Kwakkel, Jan & Aye, Lu, 2017. "Narrative-informed exploratory analysis of energy transition pathways: A case study of India's electricity sector," Energy Policy, Elsevier, vol. 110(C), pages 271-287.
    31. Vanessa Schweizer, 2018. "A few scenarios still do not fit all," Nature Climate Change, Nature, vol. 8(5), pages 361-362, 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. Ishengoma, Esther K. & Gabriel, Genoveva, 2021. "Factors influencing the payment of costs of converting oil-to CNG-fuelled cars in a market dominated by used-cars," Energy Policy, Elsevier, vol. 156(C).
    2. Naimeh Mohammadi & Hamid Mostofi & Hans-Liudger Dienel, 2023. "Policy Chain of Energy Transition from Economic and Innovative Perspectives: Conceptual Framework and Consistency Analysis," Sustainability, MDPI, vol. 15(17), pages 1-27, August.

    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. Steinmann, Patrick & Auping, Willem L. & Kwakkel, Jan H., 2020. "Behavior-based scenario discovery using time series clustering," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    2. Hesselink, Laurens X.W. & Chappin, Emile J.L., 2019. "Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 29-41.
    3. Evangelos Panos & Stavroula Margelou, 2019. "Long-Term Solar Photovoltaics Penetration in Single- and Two-Family Houses in Switzerland," Energies, MDPI, vol. 12(13), pages 1-33, June.
    4. Arias-Gaviria, Jessica & Larsen, Erik R. & Arango-Aramburo, Santiago, 2018. "Understanding the future of Seawater Air Conditioning in the Caribbean: A simulation approach," Utilities Policy, Elsevier, vol. 53(C), pages 73-83.
    5. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2018. "IRPsim: A techno-socio-economic energy system model vision for business strategy assessment at municipal level," Contributions of the Institute for Infrastructure and Resources Management 02/2018, University of Leipzig, Institute for Infrastructure and Resources Management.
    6. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Robust decision making and Epoch–Era analysis: A comparison of two robustness frameworks for decision-making under uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    7. Arias-Gaviria, Jessica & Carvajal-Quintero, Sandra Ximena & Arango-Aramburo, Santiago, 2019. "Understanding dynamics and policy for renewable energy diffusion in Colombia," Renewable Energy, Elsevier, vol. 139(C), pages 1111-1119.
    8. Wolf, Ingo & Schröder, Tobias & Neumann, Jochen & de Haan, Gerhard, 2015. "Changing minds about electric cars: An empirically grounded agent-based modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 269-285.
    9. Mehdizadeh, Milad & Nordfjaern, Trond & Klöckner, Christian A., 2022. "A systematic review of the agent-based modelling/simulation paradigm in mobility transition," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    11. Kwakkel, J.H. & Cunningham, S.C., 2016. "Improving scenario discovery by bagging random boxes," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 124-134.
    12. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    13. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    14. Auping, Willem L. & Pruyt, Erik & de Jong, Sijbren & Kwakkel, Jan H., 2016. "The geopolitical impact of the shale revolution: Exploring consequences on energy prices and rentier states," Energy Policy, Elsevier, vol. 98(C), pages 390-399.
    15. Luciano Raso & Jan Kwakkel & Jos Timmermans, 2019. "Assessing the Capacity of Adaptive Policy Pathways to Adapt on Time by Mapping Trigger Values to Their Outcomes," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    16. Zhang, Cen & Schmöcker, Jan-Dirk & Kuwahara, Masahiro & Nakamura, Toshiyuki & Uno, Nobuhiro, 2020. "A diffusion model for estimating adoption patterns of a one-way carsharing system in its initial years," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 135-150.
    17. Liu, Xueying & Madlener, Reinhard, 2021. "The sky is the limit: Assessing aircraft market diffusion with agent-based modeling," Journal of Air Transport Management, Elsevier, vol. 96(C).
    18. Busch, Jonathan & Roelich, Katy & Bale, Catherine S.E. & Knoeri, Christof, 2017. "Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks," Energy Policy, Elsevier, vol. 100(C), pages 170-180.
    19. Eker, Sibel & van Daalen, Els, 2015. "A model-based analysis of biomethane production in the Netherlands and the effectiveness of the subsidization policy under uncertainty," Energy Policy, Elsevier, vol. 82(C), pages 178-196.
    20. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.

    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:enepol:v:138:y:2020:i:c:s0301421520300021. 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/enpol .

    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.