工作研究

中国省级政府数据开放平台利用水平的组态效应研究——基于NCA与fsQCA的实证分析

  • 黄如花 ,
  • 吴应强 ,
  • 李白杨
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  • 1 武汉大学信息管理学院 武汉 430072;
    2 南京大学数据管理创新研究中心 苏州 215163
黄如花,武汉大学图书馆副馆长,教授,博士;吴应强,博士研究生,通信作者,E-mail:wuyingqiangemail@126.com;李白杨,助理教授,博士。

收稿日期: 2023-10-19

  修回日期: 2024-01-19

  网络出版日期: 2024-06-04

基金资助

本文系国家社会科学基金重大项目“我国政府信息公开到数据开放的理论创新与实践路径研究”(项目编号:22&ZD329)研究成果之一。

Research on the Configuration Effect of the Utilization Level of China’s Provincial Open Government Data Platform: Empirical Analysis Based on NCA and fsQCA

  • Huang Ruhua ,
  • Wu Yingqiang ,
  • Li Baiyang
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  • 1 School of Information Management, Wuhan University, Wuhan 430072;
    2 Research Institute for Data Management Innovation, Nanjing University, Suzhou 215163

Received date: 2023-10-19

  Revised date: 2024-01-19

  Online published: 2024-06-04

Supported by

This work is supported by the major project of the National Social Science Fund of China titled “Theoretical Innovation and Practical Path of Government Information Disclosure to Open Government Data in China” (Grant No. 22&ZD329).

摘要

[目的/意义]政府数据开放平台是政府数据在线访问及获取的载体,如何提升平台利用水平是促进政府数据开放共享发展面临的重要问题。[方法/过程]以我国16个省级政府数据开放平台作为研究对象,采用TOE理论框架并引入必要条件分析方法(NCA)与模糊集定性比较分析法(fsQCA),分析必要和充分两类因果关系,探究影响我国省级政府数据开放平台利用水平的关键因素和有效路径。[结果/结论]研究发现,不存在影响省级政府数据开放平台利用水平的单个必要非充分条件,数据资源建设水平、数据平台建设水平和组织准备度三个前因变量是影响政府数据开放平台利用水平的关键因素。采用组态视角发现了产生省级政府数据开放平台高利用水平的4种条件组态模式,并将其总结为政府主导逻辑下数据资源与平台建设驱动型、需求响应下依托财政资源的资源与环境驱动型、财政助力下依托平台建设的组织与环境驱动型、政府主导逻辑下依托数据资源的环境驱动型。

本文引用格式

黄如花 , 吴应强 , 李白杨 . 中国省级政府数据开放平台利用水平的组态效应研究——基于NCA与fsQCA的实证分析[J]. 图书情报工作, 2024 , 68(10) : 66 -80 . DOI: 10.13266/j.issn.0252-3116.2024.10.007

Abstract

[Purpose/Significance] The open government data platform is a carrier for online access and acquisition of government data. How to improve the utilization level of the platform is an important issue for the promotion of open government data. [Method/Process] Taking 16 provincial open government data platforms in China as research objects, it adopted the TOE framework and the necessary condition analysis method, NCA and fsQCA, analyzed the two types of causality, necessary and sufficient, to explore the key factors and effective paths that affect the utilization level of China’s provincial open government data platforms. [Result/Conclusion] The study finds that there is no single necessary non-sufficient condition that affects the utilization level of provincial open government data platform, and that three antecedent variables, namely, data resource construction level, data construction level and organizational readiness, are the key factors of that. From the grouping perspective, it concludes four conditional grouping patterns that generate high utilization levels of provincial open government data platforms, that is, data technology and platform construction driven under government-led logic, technology and environment driven under demand response relying on financial resources, organization and environment driven under financial assistance relying on platform construction, and environment driven under government-led logic relying on data technology.

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