供应链
链条(单位)
转化(遗传学)
业务
数字化转型
产业组织
过程管理
计算机科学
营销
化学
万维网
天文
生物化学
基因
物理
作者
Zhang Xia,Ruifeng Liang,Yun Chen
标识
DOI:10.1108/scm-11-2024-0772
摘要
Purpose This study aims to examine how the digital transformation of chain-leading enterprises, i.e. key players within the industrial chain, affects supply chain efficiency. It defines screening criteria for these enterprises using three data indicators and conducts an analysis based on textual data from Chinese listed companies between 2010 and 2022. Design/methodology/approach Based on the theoretical foundation of the research, this paper proposes a theoretical hypothesis model and establishes a benchmark regression equation to study the impact of digital transformation on supply chain efficiency. The study uses panel data from 465 Chinese enterprises. Findings The results indicate that the digital transformation of leading enterprises in the industrial chain significantly improves supply chain efficiency. In this paper, an instrumental variable method is used to mitigate endogeneity and a series of robustness tests to confirm the validity of the findings. The impact path analysis reveals that the leading enterprises in the industrial chain can enhance efficiency by reducing financing cost, increasing operational efficiency and lowering the concentration level of the supply chain. Furthermore, the heterogeneity analysis demonstrates that the digital transformation of state-owned leading enterprises in the industrial chain and low-tech sector leaders have a more prominent effect on supply chain efficiency. Originality/value First, this paper enriches the research on digital transformation, and the method of extracting keywords through big data text analysis can better quantify the degree of digital transformation of the sample. Second, this paper provides empirical evidence of the impact of digital transformation on the supply chain efficiency of chain-leading enterprises. Third, it enriches existing research on chain leaders, particularly regarding their digital transformation and offers new insights into the quantitative screening of such enterprises.
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