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Adoption of green electricity policies: Investigating the role of environmental attitudes via big data-driven search-queries

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  • Lee, Donghyun
  • Kim, Minki
  • Lee, Jungyoun

Abstract

Despite the rising influence of public opinion on government energy policy formulation and implementation, the roles of pro and/or anti-environmental attitudes among residents have not been empirically examined. To quantify time-varying environmental attitudes among local residents, we exploit geo-specific Google search-query data derived from Internet-based “big data” and verify through ordinary least squares regression outcomes regarding environmental behavior. For the purpose of drawing policy implications, we revisit decisions by state governments of the United States to adopt three well-known green electricity policies: renewable energy portfolio, net metering rules, and public benefit funds. As some states have not yet adopted some (or any) of these policies, unlike previous studies, we handle the issue by examining right-censored data and applying a duration-based econometric method called the accelerated failure time model. We found state residents’ environmental attitudes to have statistically significant roles, after controlling for other traditional time-varying policy adoption factors. Interestingly, the extent to which anti-environmental attitudes affect a state’s policy adoption differs across green energy policies, and knowing this can help a local government formulate better-tailored environmental policy. In particular, researchers can use our method of incorporating citizens’ environmental attitudes to discuss relevant issues in the field of energy policy.

Suggested Citation

  • Lee, Donghyun & Kim, Minki & Lee, Jungyoun, 2016. "Adoption of green electricity policies: Investigating the role of environmental attitudes via big data-driven search-queries," Energy Policy, Elsevier, vol. 90(C), pages 187-201.
  • Handle: RePEc:eee:enepol:v:90:y:2016:i:c:p:187-201
    DOI: 10.1016/j.enpol.2015.12.021
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    4. Wei, Jing & Zhong, Zewei & Chen, Haoran & Arango-Aramburo, Santiago & Zhao, Xiaoli, 2025. "Exploring green electricity certificate purchasing behavior via a laboratory experiment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 215(C).
    5. Peterson, Mark & Feldman, David, 2018. "Citizen preferences for possible energy policies at the national and state levels," Energy Policy, Elsevier, vol. 121(C), pages 80-91.
    6. Cui, Li & Chan, Hing Kai & Zhou, Yizhuo & Dai, Jing & Lim, Jia Jia, 2019. "Exploring critical factors of green business failure based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL)," Journal of Business Research, Elsevier, vol. 98(C), pages 450-461.
    7. Jody W. Lipford, 2025. "On the politics of constitutional law: an environmental case study of the role of politics and economics in constitutional appeals," Constitutional Political Economy, Springer, vol. 36(1), pages 80-94, March.
    8. Agnieszka Janik & Adam Ryszko & Marek Szafraniec, 2021. "Determinants of the EU Citizens’ Attitudes towards the European Energy Union Priorities," Energies, MDPI, vol. 14(17), pages 1-32, August.
    9. Justin Longo & Alan Rodney Dobell, 2018. "The Limits of Policy Analytics: Early Examples and the Emerging Boundary of Possibilities," Politics and Governance, Cogitatio Press, vol. 6(4), pages 5-17.
    10. Donghyun Lee & Suna Kang & Jungwoo Shin, 2017. "Using Deep Learning Techniques to Forecast Environmental Consumption Level," Sustainability, MDPI, vol. 9(10), pages 1-17, October.
    11. Kocak, Ece & Yilmaz, Kadri Gokhan & Tokucoglu, Tuba, 2026. "Behavioral intention towards green electricity consumption: An analysis in the context of behavioral reasoning theory," Energy Policy, Elsevier, vol. 209(PA).
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