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An integrated decision-making model for sustainable photovoltaic module supplier selection based on combined weight and cumulative prospect theory

Author:
Wu, Yunna, Ke, Yiming, Xu, Chuanbo, Li, Lingwenying
Source:
Energy 2019 v.181 pp. 1235-1251
ISSN:
0360-5442
Subject:
case studies, decision making, entropy, expert opinion, models, product quality, profits and margins, risk, solar collectors
Abstract:
Scientifically selecting the optimal sustainable photovoltaic module supplier can not only reduce investment costs but also increase generation profits, which is highly valued by decision-makers. However, some deficiencies such as information loss, weight deviation and the lack of psychological characteristic analysis lie in the present supplier selection studies, which greatly weakens the evaluation accuracy. To fill such gap, a novel decision framework under mixed information environment is proposed. First, triangular intuitionistic fuzzy numbers are adopted to depict the fuzziness and hesitancy of expert knowledge, which avoids information distortion. Then, under the consideration of logic importance and decision-making contribution, an approach combining the analytic hierarchy process and the entropy theory is used to compute index importance, which makes full use of expert experience and information content amount. Subsequently, the cumulative prospect theory is introduced to rank alternatives with the assumptions of bounded rationality and risk preference. Finally, a case study is conducted based on the proposed framework. Results show that product quality attributes, especially photoelectric conversion efficiency, degradation rate and environmental adaptability, are the primary considerations in the issue. Since environmental measures vary widely among suppliers and own a relatively high weight, they may become the core competitiveness of sustainable suppliers. Besides, the sensitivity analysis demonstrates that psychological characteristics like reference dependence and loss aversion greatly affect the ranking.
Agid:
6475047