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Title: Energy performance contracting, risk factors, and policy implications : identification and analysis of risks based on the best-worst network method
Authors: Wang, Z
Xu, G
Lin, R 
Wang, H
Ren, J 
Issue Date: 1-Mar-2019
Source: Energy, 1 Mar. 2019, v. 170, p. 1-13
Abstract: The Energy Performance Contracting (EPC) industry in China faces many severe risks that hinder its development. This study aims at identifying the risk factors in China's EPC industry, developing a generic method for prioritizing these factors and identifying the key risk factors, and proposing some policy implications for China's decision-makers to draft effective measures and policies to promote the harmonious development of EPC industry in China. A total of 21 risk factors in five categories including external environmental risks, managerial and operational risks, financial and market risks, technical risks, and client risks are identified. A best-worst network (BWN) method was developed for ranking these risk factors based on the traditional Analytic Network Process (ANP) and the BW method. The results determined the BWN method were validated by ANP method, and the results determined by the BWN method were also compared with that determined by Analytic Hierarchy Process (AHP) method. According to the results, some policy implications have also been proposed for China's decision-makers.
Keywords: Analytic network process
Best-worst method
Energy performance contracting
Risk factors
Publisher: Elsevier Ltd
Journal: Energy 
ISSN: 0360-5442
EISSN: 1873-6785
DOI: 10.1016/j.energy.2018.12.140
Rights: © 2018 Elsevier Ltd. All rights reserved.
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Wang, Z., Xu, G., Lin, R., Wang, H., & Ren, J. (2019). Energy performance contracting, risk factors, and policy implications: Identification and analysis of risks based on the best-worst network method. Energy, 170, 1–13 is available at https://doi.org/10.1016/j.energy.2018.12.140.
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