Research on big data-driven public services in China: a visualized bibliometric analysis

IF 2.4 3区 社会学 Q1 POLITICAL SCIENCE
Zhiqiang Xia, Xingyu Yan, Xiaoyong Yang
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引用次数: 4

Abstract

Abstract The gradual establishment of systematic, equalized, and standardized basic public services has drawn attention of the academic community to the mismatch between supply-demand, and public dissatisfaction. Big-data-driven public services innovatively attempt to solve these problems, and reflect the theoretical essence of the process by which big data can empower the responsiveness of governments. In this study, we adopted the theoretical frameworks of ‘diversified needs–selective responses’, ‘risk shocks–forward-looking responses’, and ‘forward-looking predictions–creative responses’. We propose that big data-driven public services should respond not only to present needs but also to social risks and future needs. Therefore, it is imperative to review the status, problems, and future directions of big data-driven public service research in China. This study uses bibliometric visualization analysis on data from research projects, monographs, and journal publications. The results reveal that the main research topics are basic theoretical issues, service-oriented government development guided by big data strategies, practical innovation of public services in the context of smart governance, and the effective supply of big data-driven public services. Previous studies suffered from weak theoretical reflection and construction, lacked relevant institutions, had less fine-grained and fragmented technical support, and lacked foresight and guidance. Attention should be paid to normative theories and institutions in big data-driven public services to ensure that these services are more targeted and prospective; creative research should be conducted. The systematic summarization of the current state of research and reflections on prospective and creative research trends will provide new ideas regarding future research directions.
中国大数据驱动的公共服务研究:可视化文献计量分析
摘要逐步建立系统化、均等化、规范化的基本公共服务,引起了学术界对供需不匹配和公众不满的关注。大数据驱动的公共服务创新性地试图解决这些问题,并反映了大数据增强政府响应能力的理论本质。在这项研究中,我们采用了“多样化需求-选择性反应”、“风险冲击-前瞻性反应”和“前瞻性预测-创造性反应”的理论框架。我们建议,大数据驱动的公共服务不仅应满足当前需求,还应满足社会风险和未来需求。因此,有必要回顾中国大数据驱动公共服务研究的现状、问题和未来方向。本研究对研究项目、专著和期刊出版物的数据进行了文献计量可视化分析。研究结果表明,主要研究主题是基础理论问题、大数据战略指导下的服务型政府发展、智慧治理背景下的公共服务实践创新以及大数据驱动的公共服务的有效供给。以往的研究理论反思和构建薄弱,缺乏相关制度,技术支撑不够精细和碎片化,缺乏前瞻性和指导性。应关注大数据驱动公共服务中的规范性理论和制度,以确保这些服务更有针对性和前瞻性;应该进行创造性的研究。系统总结研究现状,反思前瞻性和创造性的研究趋势,将为未来的研究方向提供新的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.40
自引率
6.70%
发文量
9
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