系统管理学报 ›› 2022, Vol. 31 ›› Issue (5): 893-909.DOI: 10.3969/j.issn.1005-2542.2022.05.007

• 大数据与信息管理 • 上一篇    下一篇

基于元分析的移动医疗持续使用意愿影响因素

李伊,刘人境   

  1. 西安交通大学管理学院,西安> 710049
  • 收稿日期:2020-07-27 修回日期:2021-05-25 出版日期:2022-09-28 发布日期:2022-10-07
  • 作者简介:李 伊(1991-),女,博士生。研究方向为移动医疗。
  • 基金资助:
    国家社会科学基金重大项目(18ZDA104)

Influencing Factors of Continuance Use Intention of Mobile Health Based on Meta Analysis

LI Yi,LIU Renjing   

  1. School of Management, Xi’an Jiaotong University, Xi’an 710049, China
  • Received:2020-07-27 Revised:2021-05-25 Online:2022-09-28 Published:2022-10-07

摘要: 基于30篇中外文献,以信息系统持续使用模型(ECM-IS)为基础,构建了包含个体感知因素与个体特征的综合研究框架。同时,采用元分析方法,探讨了用户持续使用意愿影响因素并分析了国家经济发展水平的调节效应。结果表明:信息系统持续使用模型各变量关系在移动医疗服务领域解释用户持续使用意图方面均得到了验证;个体感知因素与个人特征因素对用户满意度及持续使用意愿均有正向影响;除感知有用性与满意度、感知服务质量与满意度的关系而外,国家经济发展水平均显著调节模型中相关变量关系。所得结论一方面可以为后续研究提供理论参考,另一方面可以协助移动医疗服务提供商进一步了解用户行为,增强用户粘性,促进移动医疗服务持续发展。

关键词: 移动医疗, 持续使用意愿, 信息系统持续使用模型, 影响因素, 元分析

Abstract: Based on 30 related Chinese and foreign literatures, this paper developed a comprehensive research framework including individual perception factors and individual characteristics based on the information continuance (ECM-IS) model and used the meta-analysis method to examine the factors affecting the continuance use intention of mobile health service users, and the moderating effects of the national economy development. The results indicate that the relationships between variables in the ECM-IS model have been verified in explaining the continuance use intention of mobile health users. Both the individual perception factor and the individual characteristic factor have a positive influence to the continuance use intention of users. The moderator analysis confirms that the difference in economic development of different countries have specific moderating effects on the continuance use of mobile health services. These conclusions may provide theoretical reference for future research and practice.

Key words: mobile health, continuance use intention, information system, influencing factors, meta-analysis

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