Evaluating the financial performance of companies from the perspective of fund procurement and application: New strategy cross efficiency network data envelopment analysis models

Abstract

To the best of our knowledge, no study adopts network data envelopment analysis (DEA) models to evaluate financial performance of companies. Not accounting for the inner structure of fund flow tends to obtain inappropriate conclusions, thereby being problematic. To overcome the problem, this study proposes a new network structure to unify fund procurement and application. Furthermore, this study proposes an extended framework to detect various inefficiency sources. The framework contains coupling-related indexes (for relationship between stages), efficiency Gini coefficient (for technology inequality) and relative weight indicators (for relative priority analysis). Furthermore, this study proposes new strategy network DEA models to improve efficiency. Such work cannot be found in the existing studies. Empirically, this study focuses on China's companies of clean energy industry from 2013 to 2021. The main conclusions are summarized as follows. First, China's companies experience an overall progress in efficiency with an annual growth rate of 2.75%. The overall progress is mainly driven by fund application stage. Meanwhile, there exists considerable heterogeneity across stages, groups and companies. Second, as for sector priority, fund procurement gains more importance than fund application. Finally, policy makers require well-tailored strategies that may help to improve efficiency or other efficiency-related measures.