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Exploring the Multiple Paths to Improve the Construction Level of Digital Government: Qualitative Comparative Analysis Based on the WSR Framework

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  • Shuguang Wang

    (School of Public Finance and Administration, Harbin University of Commerce, Harbin 150028, China)

  • Xuefu Sun

    (School of Public Finance and Administration, Harbin University of Commerce, Harbin 150028, China)

  • Shen Zhong

    (School of Finance, Harbin University of Commerce, Harbin 150028, China)

Abstract

The construction of digital government is an essential premise and foundation to improve a national governance system. Based on the Wuli–Shili–Renli (WSR) framework, this paper applies fuzzy-set qualitative comparative analysis (fsQCA) to data from 31 Chinese provinces to investigate how six conditional variables (information-infrastructure construction, organizational construction, financial support, digital-policy support, public demand, and digital talent) jointly affect the construction level of digital government (CDG). The results show that none of the six conditions is necessary for the CDG, and three paths exist to enhance the CDG. Information-infrastructure construction and digital-policy support play a more significant role in digital-government transformation than other variables. As a subjective and controllable approach, digital policy may significantly affect the CDG in the short term. Based on the findings above, we propose policy recommendations for strengthening the elements of coordination, enhancing the construction of information infrastructure in each province, and enhancing the digital-policy support system. This study provides a new research framework and theoretical perspective for improving global digital-government construction.

Suggested Citation

  • Shuguang Wang & Xuefu Sun & Shen Zhong, 2023. "Exploring the Multiple Paths to Improve the Construction Level of Digital Government: Qualitative Comparative Analysis Based on the WSR Framework," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9891-:d:1176140
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