Study On the Driving Mode of Production Factor Allocation on Regional Digital Transformation Under the Configuration Perspective
Year: 2025
Type: article
Abstract: To explore the different paths of regional digital transformation in China and understand its development mechanism, this paper employs the Fuzzy-set Qualitative Comparative Analysis (fsQCA) method. It examines 21 prefectural-level cities (or municipalities) with national high-tech zones in China's Yangtze River Delta (YRD) region using relevant data from 2022. The study investigates regional digital transformation from two aspects: the labour factor and the data element, based on six measures. The study finds that, firstly, none of the six single antecedents is necessary for a high level of regional digital transformation, but multi-factorial synergies can help achieve a high level of regional digital transformation. Secondly, after the group analysis, there are five configurations to achieve high-level regional digital transformation, which are divided into four paths according to the characteristics of the core variables, namely, the ‘talent development’ path, the ‘digitalisation of a diversified economic base’ path, the ‘public factor orientation’ path, and the ‘education and life integration’ path, The ‘public factor-oriented’ path and the ‘education and life integration’ path. Thirdly, the robustness of the grouping is tested by changing the consistency threshold, after which the grouping is still stable, indicating that the grouping results are reliable. Unlike existing econometric studies that focus on the impact of a single factor, this study reveals the multi-factor driving mechanism of regional digital transformation from a multi-path perspective. This paper provides new perspectives and methods for the theoretical study of regional digital transformation, as well as a more targeted theoretical basis for regional policymaking.
DOI: 10.54097/syb66791
Authors: Jialei Li, Huiran Guo
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4409621637