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Energy transition dynamics: Does participatory modelling contribute to alignment among differing future world views?

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  • Bent Erik Bakken

Abstract

A large international classification, assurance, and advisory services company provides for an energy microcosm where two opposing energy camps project initiated were assumed to be present. This research applies a case study design to analyse the contribution of participatory modelling to align differing views of energy futures. The modelling process as an intervention in a pretest and posttest setting is outlined. The hypothesis that the organization contained differing world views among respectively renewable and Oil & Gas professionals was however only marginally supported. Similarly, a survey showed no effect of the modelling intervention. We discuss the role of modelling at societal and organizational levels and indicate that even if the modelling effort includes dozens of participants and frequent workshops, if the model effort is minor and marginal to the transformational issue, one cannot expect participatory modelling to contribute strongly to alignment to a new direction. We also argue that there might be limits to positive findings of impacts of participatory modelling efforts if the issues are of high complexity. Finally, we find that the potential self‐confirming bias of participatory modelling accounts argues for expanding measuring effects to encompass also those organizational members outside the core participants teams.

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  • Bent Erik Bakken, 2019. "Energy transition dynamics: Does participatory modelling contribute to alignment among differing future world views?," Systems Research and Behavioral Science, Wiley Blackwell, vol. 36(2), pages 184-196, March.
    • Handle: RePEc:bla:srbeha:v:36:y:2019:i:2:p:184-196
    DOI: 10.1002/sres.2578
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    Cited by:

    1. Ricciardi, Francesca & De Bernardi, Paola & Cantino, Valter, 2020. "System dynamics modeling as a circular process: The smart commons approach to impact management," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    2. Wang, Lianghu & Shao, Jun, 2024. "The energy saving effects of digital infrastructure construction: Empirical evidence from Chinese industry," Energy, Elsevier, vol. 294(C).
    3. Castilla-Rho, Juan & Kenny, Daniel, 2022. "What prevents the adoption of regenerative agriculture and what can we do about it? Lessons from a behaviorally-attuned Participatory Modelling exercise in Australia," OSF Preprints asxr2, Center for Open Science.
    4. Dolter, Brett, 2021. "Greening the Saskatchewan grid: A case study in deliberative energy modelling," Ecological Economics, Elsevier, vol. 183(C).
    5. Daniel C. Kenny & Juan Castilla-Rho, 2022. "No Stakeholder Is an Island: Human Barriers and Enablers in Participatory Environmental Modelling," Land, MDPI, vol. 11(3), pages 1-26, February.
    6. Zhang, Weike & Fan, Hongxia & Zhao, Qiwei, 2023. "Seeing green: How does digital infrastructure affect carbon emission intensity?," Energy Economics, Elsevier, vol. 127(PB).

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