Assessment of new energy industrial clusters: An MCDM approach using DEA and GEMS

Abstract

Industrial clusters play a pivotal role in securing competitive advantages and achieving national strategic objectives within the new energy sector. The assessment of new energy industrial clusters is crucial for sustaining their swift development. However, prior research has rarely addressed this domain. In this study, a Multi-Criterion Decision-Making (MCDM) approach is introduced for the assessment of new energy industrial clusters. This approach employs the Data Envelopment Analysis (DEA) super efficiency method alongside the Grounding-Enterprise-Market-Surrounding (GEMS) model to evaluate the efficiency and competitiveness of new energy industrial clusters, respectively. Subsequently, this approach categorizes new energy industrial clusters based on their efficiency and competitiveness scores. Clusters exhibiting similar scores in these areas are grouped together for the identification of key new energy industrial clusters. Ultimately, the selection of key new energy industrial clusters is performed based on varying criteria. A case study on the selection of prominent solar energy industrial clusters is presented to demonstrate the efficacy of the proposed approach. The findings indicate that this approach facilitates an effective selection process for key new energy industrial clusters.