2024  VOLUME 4  ISSUE 1

RESEARCH ARTICLE

Growth analysis of new-energy enterprises in China: A grey possibility degree clustering model for panel data

AUTHOR

Yanhua Liang, Li Zhang, Hongjuan Lu

ABSTRACT

Growth clustering analysis of new-energy enterprises is an important reference for decision-makers. This study proposes a novel grey clustering model based on the grey probability function from both absolute and incremental perspectives. The model was applied to the cluster analysis of 117 listed new-energy enterprises in China between 2017 and 2021. The results of the grey clustering analysis showed that the proposed model can classify these listed new-energy enterprises into three categories from both absolute and incremental perspectives. In the crossover grey clustering table of the two perspectives, there were 58 new-energy listed enterprises on the diagonal, which belonged to the same level of grey clustering and had growth consistency in both perspectives. Based on the classification, the characteristics of the clusters were analyzed and different development proposals were made accordingly. The study is not only innovative in its clustering methodology, but also contributes to the sustainable development of the new-energy industry by providing decision-makers with reference information on cluster analysis.

KEYWORDS

New energy; Growth; Grey possibility degree; Grey clustering

DOWNLOAD FULL ARTICLE