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Renewable energy performance analysis using fuzzy dynamic directional distance function model under natural and managerial disposability

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  • Shabani, Mohadeseh
  • Kordrostami, Sohrab
  • Jahani Sayyad Noveiri, Monireh

Abstract

Addressing the dynamic performance aspects of processes and identifying the sources of inefficiency are key considerations for making informed decisions, especially in situations where imprecise data are available. This study aims to evaluate the performance of renewable energy using the Fuzzy Dynamic Directional Distance Function (FDDDF) model considering natural and managerial disposability for 34 OECD member countries. As a non-parametric methodology, Data Envelopment Analysis (DEA) is used to measure dynamic fuzzy environmental efficiencies of renewable energy through multiple fuzzy inputs and outputs. Using the proposed approach, optimistic, pessimistic and integrated renewable energy performances of entities with carry-overs are assessed for each period and generally. The empirical findings reveal that the proposed FDDDF approach has strong capability to discriminate the performance of renewable energy.

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  • Shabani, Mohadeseh & Kordrostami, Sohrab & Jahani Sayyad Noveiri, Monireh, 2023. "Renewable energy performance analysis using fuzzy dynamic directional distance function model under natural and managerial disposability," Applied Energy, Elsevier, vol. 352(C).
    • Handle: RePEc:eee:appene:v:352:y:2023:i:c:s0306261923013041
    DOI: 10.1016/j.apenergy.2023.121940
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    1. Li, Jiang & Wu, Hecheng & Zhu, Chen & Goh, Mark, 2024. "Evaluating and analyzing renewable energy performance in OECD countries under uncertainty: A robust DEA approach with common weights," Applied Energy, Elsevier, vol. 375(C).

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