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NIMBY-ism and green energy infrastructure: A strategic risk disclosure approach

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  • Yu, Liukai
  • Goh, Mark
  • Zheng, Junjun

Abstract

The resistance toward green energy infrastructure (GEI) often leads to a NIMBY (Not in My BackYard) event, and this can challenge green energy development. This paper proposes an approach for alleviating NIMBYism through strategic risk information disclosure. It involves the project developer of the GEI committing ex-ante (before risk investigation) to a signaling mechanism that strategically discloses informed signals about the risk of the GEI to the local community, who may hold heterogeneous risk priors and engage in preference-driven social learning within the community. For this, a signaling mechanism based on a network persuasion model coupled with communication learning dynamics is developed. Our results suggest that resident heterogeneity converge to divergent consensus unions (subgroups), manifesting a social stratification and segregation phenomenon in NIMBYism. The optimal signaling mechanism is a tiered threshold recommendation structure, setting tailored thresholds for each community subgroup that commits to recommending acceptance when the risk level investigated does not exceed the threshold. The effectiveness of strategic disclosure is moderated by the external benefits and the prior pessimism of the community. It may underperform or even fail under low compensation and GEI's positive externality when dealing with a conservative community. Segregation among the community subgroups is not necessarily unfavorable. Additionally, we make two extension analyses on private priors of the residents and differentiated compensation for the divergent unions. These findings can inform policy on crafting strategic risk disclosure to address NIMBYism in GEIs.

Suggested Citation

  • Yu, Liukai & Goh, Mark & Zheng, Junjun, 2026. "NIMBY-ism and green energy infrastructure: A strategic risk disclosure approach," Energy Economics, Elsevier, vol. 154(C).
  • Handle: RePEc:eee:eneeco:v:154:y:2026:i:c:s0140988325009466
    DOI: 10.1016/j.eneco.2025.109116
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