Research Paper:
Enterprise Digital Maturity Assessment Driven by Multi-Source Data: Based on the Entropy Weight Method and Skyline Algorithm
Hongqin Tang*,**
, Yang Shen*,**,
, and Jianping Zhu*,**
*School of Management, Xiamen University
No.422 Siming South Road, Siming District, Xiamen, Fujian 361005, China
**Data Mining Research Center, Xiamen University
No.422 Siming South Road, Siming District, Xiamen, Fujian 361005, China
Corresponding author
The rapid advancement of digitalization is reshaping multiple aspects of firms and transforming the nature of innovation and entrepreneurship. However, a mature solution to accurately measure the digitalization maturity of enterprises is lacking. To help firms better understand their digitalization competitiveness, this study examined Chinese listed companies and, drawing on publicly available multi-dimensional heterogeneous data, employed the skyline algorithm and entropy weight method to construct a scientific measure and evaluation of digitalization maturity. To assess the reliability and practical feasibility of the measurement, this study further conducted heterogeneity analyses across industries and regions in China based on the evaluation results. The findings indicated that firms with superior digitalization maturity were predominantly concentrated in industries that were highly sensitive to digital technologies, as well as in regions characterized by stronger resource endowments and more frequent knowledge exchanges. In contrast, the digital transformation of traditional industries, such as the real estate sector, and of the regions where these industries are concentrated remained relatively weak and required further strengthening. These findings provide significant implications for both policymakers and industry stakeholders.
Technical framework
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