Abstract
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.
Highlights
Explicit appraisal of three dimensions in sustainability—environment, society, and economy—is the key to transitioning toward a renewable energy-based society [1,2]
Recent extension of life cycle assessment (LCA) into life cycle sustainability assessment (LCSA) [5] provides a good opportunity to understand the importance of the decision support framework
We focused our attention to preference construction in decisions made regarding renewable energies
Summary
Explicit appraisal of three dimensions in sustainability—environment, society, and economy—is the key to transitioning toward a renewable energy-based society [1,2]. The social dimension has increased the importance in the assessment of energy technologies recently [3]. Economic sustainability should not be neglected in establishing a sustainable society, because profitable technologies for utilizing renewables are the foundation for sustainable transition. In operationalizing the assessment of sustainability, a decision support framework plays an important role [4]. Recent extension of life cycle assessment (LCA) into life cycle sustainability assessment (LCSA) [5] provides a good opportunity to understand the importance of the decision support framework. The relationship between decision analysis and LCA has already been discussed [6,7,8], the use of LCSA necessitates indicator-based assessment covering environmental, social, and economic pillars throughout entire supply chains. The plurality of indicators as development goals is important in designing regional energy strategies, as well as the plurality of alternative scenarios under multiple stakeholders [9]
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