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Preference Construction Processes for Renewable Energies: Assessing the Influence of Sustainability Information and Decision Support Methods

1
Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, 3-1-3 Kannondai, Tsukuba, Ibaraki 305-8604, Japan
2
Graduate School of Environment and Information Sciences, Yokohama National University, 79-7 Tokiwadai, Hodogaya-ku, Yokohama 240-8501, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Gurkan Kumbaroglu
Sustainability 2016, 8(11), 1114; https://doi.org/10.3390/su8111114
Received: 25 July 2016 / Revised: 26 September 2016 / Accepted: 28 October 2016 / Published: 1 November 2016
(This article belongs to the Section Economic, Business and Management Aspects of Sustainability)
Sustainability information and decision support can be two important driving forces for making sustainable transitions in society. However, not enough knowledge is available on the effectiveness of these two factors. Here, we conducted an experimental study to support the hypotheses that acquisition of sustainability information and use of decision support methods consistently construct preferences for renewable power generation technologies that use solar power, wind power, small-scale hydroelectric power, geothermal power, wood biomass, or biogas as energy sources. The sustainability information was prepared using a renewable energy-focused input-output model of Japan and contained life cycle greenhouse gas emissions, electricity generation costs, and job creation. We measured rank-ordered preferences in the following four steps in experimental workshops conducted for municipal officials: provision of (1) energy-source names; (2) sustainability information; (3) additional explanation of public value; and (4) knowledge and techniques about multi-attribute value functions. The degree of changes in preference orders was evaluated using Spearman’s rank correlation coefficient. The consistency of rank-ordered preferences among participants was determined by using the maximum eigenvalue for the coefficient matrix. The results show: (1) the individual preferences evolved drastically in response to the sustainability information and the decision support method; and (2) the rank-ordered preferences were more consistent during the preference construction processes. These results indicate that provision of sustainability information, coupled with decision support methods, is effective for decision making regarding renewable energies. View Full-Text
Keywords: renewable energy sources; preference construction; multiple criteria decision analysis; life cycle assessment; sustainability assessment renewable energy sources; preference construction; multiple criteria decision analysis; life cycle assessment; sustainability assessment
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Hayashi, K.; Hondo, H.; Moriizumi, Y. Preference Construction Processes for Renewable Energies: Assessing the Influence of Sustainability Information and Decision Support Methods. Sustainability 2016, 8, 1114.

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