Multicriteria assessment of renewable energy sources under uncertainty: barriers to adoption

Tseng, M.-L., Ardaniah, V., Sujanto, R. Y., Fujii, M. and Lim, M. K. (2021) Multicriteria assessment of renewable energy sources under uncertainty: barriers to adoption. Technological Forecasting and Social Change, 171, 120937. (doi: 10.1016/j.techfore.2021.120937)

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Abstract

This study contributes by identifying a set of factors serving as barriers and facilitators to the adoption of renewable energy sources under uncertainty to provide an understanding of renewable energy sources in Indonesia. Previous studies have neglected to identify the factors serving as barriers to the adoption of renewable energy sources through contextual interrelationships and uncertainty. The attributes need to be assessed with multiple criteria, but contextual attributes have interrelationships and qualitative descriptions. Hence, this study applies the fuzzy Delphi method to arrive at a valid set of barriers to the adoption of renewable energy sources based on qualitative information and linguistic preferences. These qualitatively valid attributes are interrelated; hence, this study uses the fuzzy decision-making trial and evaluation laboratory method to visualize the interrelationships among attributes under uncertainty. This study compares the adoption of and barriers to the adoption of renewable energy sources. The results indicate that adoption is driven by technical capabilities and that the main barrier is technical analysis. In practice, the adoption criteria are institutional, policy and technical analysis aspects, and the main barriers to achieving sustainable electricity generation are development funding, licensing procedures, groundwater pollution and investment cost.

Item Type:Articles
Keywords:Fuzzy Delphi method, fuzzy decision-making trial and evaluation laboratory, renewable energy source adoption, renewable energy source barrier.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Lim, Professor Ming
Authors: Tseng, M.-L., Ardaniah, V., Sujanto, R. Y., Fujii, M., and Lim, M. K.
College/School:College of Social Sciences > Adam Smith Business School > Management
Journal Name:Technological Forecasting and Social Change
Publisher:Elsevier
ISSN:0040-1625
ISSN (Online):1873-5509
Published Online:17 June 2021

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