Pathways and Empirical Analysis for Enhancing Corporate Working Capital Efficiency from a Fabric Supply Chain Collaboration Perspective

Efficient working capital management has become a critical challenge for textile enterprises operating in increasingly interconnected supply chain environments. This study develops a collaborative analytical framework that integrates supply chain coordination theory with working capital management to investigate the mechanisms through which information collaboration, logistics collaboration, and capital collaboration influence operational efficiency. A multidimensional evaluation system is established using entropy weighting to quantify collaboration levels, while Data Envelopment Analysis (DEA) and panel regression models are employed to assess working capital performance based on data from listed textile enterprises between 2018 and 2023. The empirical results demonstrate that all three collaboration dimensions significantly improve working capital efficiency, with information collaboration exerting the strongest effect, followed by logistics and capital collaboration. Moreover, interaction analysis reveals that coordinated implementation of the three dimensions generates substantial synergistic gains beyond their individual contributions. The proposed framework provides quantitative evidence for optimizing resource allocation and collaborative decisionmaking across supply chain networks. Beyond textile manufacturing, the methodology offers useful insights for digital industrial ecosystems and intelligent information exchange architectures, where efficient d ata c oordination a nd r esource s cheduling a re increasingly important for communication-intensive engineering systems and next-generation smart infrastructure.