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Influence of Safety Risk Perception on Post-Fukushima Generation Mix and its Policy Implications in Japan

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  • Akiko Iimura
  • Jeffrey Scott Cross

Abstract

Four years after the Fukushima nuclear power plant accident, a future portfolio of the electrical power generation mix was finally and officially determined by the Japanese Government. Opposition to nuclear power generation remains high in the Japanese public to accept the need for nuclear power given the potential for a nuclear accident in the future. In this paper, we introduce an Analytical Hierarchy Process model to evaluate the influence of two opposing risk perceptions relating to public opinion versus scientific risk measures related to the electrical generation mix. This study revealed that opposing viewpoints on safety results in choosing different generation mixes. It should be noted that the public in large chooses the nuclear-free preference that actually results in a higher number of human fatalities in the energy sector because of the statistically low accident rate in the nuclear energy generation sector, which is contrary to public sentiment in Japan.

Suggested Citation

  • Akiko Iimura & Jeffrey Scott Cross, 2016. "Influence of Safety Risk Perception on Post-Fukushima Generation Mix and its Policy Implications in Japan," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 3(3), pages 518-532, September.
    • Handle: RePEc:bla:asiaps:v:3:y:2016:i:3:p:518-532
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    References listed on IDEAS

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    1. Hong, Sanghyun & Bradshaw, Corey J.A. & Brook, Barry W., 2013. "Evaluating options for the future energy mix of Japan after the Fukushima nuclear crisis," Energy Policy, Elsevier, vol. 56(C), pages 418-424.
    2. Hamalainen, Raimo P., 1990. "A decision aid in the public debate on nuclear power," European Journal of Operational Research, Elsevier, vol. 48(1), pages 66-76, September.
    3. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    4. Lee, Seong Kon & Yoon, Yong Jin & Kim, Jong Wook, 2007. "A study on making a long-term improvement in the national energy efficiency and GHG control plans by the AHP approach," Energy Policy, Elsevier, vol. 35(5), pages 2862-2868, May.
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