Resilience evaluation model of photovoltaic industry chain based on grey-entropy-catastrophe progression method: a case study of Jiangsu province

Abstract

Purpose

The purpose of this study is to establish a grey-entropy-catastrophe progression method (CPM) model to assess the photovoltaic (PV) industry chain resilience of Jiangsu Province in China.

Design/methodology/approach

First, we designed the resilience evaluation index system of such a chain from two aspects: the external environment and internal conditions. We then constructed a PV industry chain resilience evaluation model based on the grey-entropy-CPM. Finally, the feasibility and applicability of the proposed model were verified via an empirical case study analysis of Jiangsu Province in China.

Findings

As of the end of 2022, the resilience level of its PV industry chain is medium-high resilience, which indicates a high degree of adaptability to the current unpredictable and competitive market, and can respond to the uncertain impact of changes in conditions effectively and in a timely manner.

Practical implications

The construction of this model can provide reference ideas for related enterprises in the PV industry to analyze the resilience level of the industrial chain and solve the problem of industrial chain resilience.

Originality/value

Firstly, an analysis of the entire industrial chain structure of the PV industry, combined with its unique characteristics is needed to design a PV industry chain resilience evaluation index system. Second, grey relational analysis (GRA) and the entropy method were adopted to improve the importance of ranking the indicators in the evaluation of the CPM, and a resilience evaluation model based on grey-entropy-CPM was constructed.