数字乡村背景下农村社区健康信息服务内容供给优先序研究
Research on the Priority Order of Health Information Service in Rural Community in Digital Village Construction
洪闯 1李中明1
作者信息
- 1. 湘潭大学公共管理学院 湘潭 411105
- 折叠
摘要
[目的/意义]从用户需求视角深入剖析农村社区居民健康信息服务内容体系并厘清其供给优先顺序,对于助力数字乡村建设、提升农村社区居民健康水平具有重要的理论意义与实践指导价值.[方法/过程]在系统梳理相关文献的基础上,结合数字乡村建设的现实需要,通过半结构访谈与专家咨询等方式确立28项农村社区健康信息服务项目并设计调查问卷搜集数据,综合运用Kano模型、混合类分析、Better-Worse满意度指数分析与熵权Topsis方法识别农村社区健康信息服务内容的所属类型并量化其优先序.[结果/结论]研究发现农村社区居民对于健康信息服务内容的需求呈现出层次化特征,涵盖期望型服务8项,魅力型服务8项,无差异服务6项,混合型服务6项.农村社区在推进数字乡村建设进程中应根据不同的需求类型和优先序优化健康信息服务内容,推动服务适切性、满意度与整体效能的提升.
Abstract
[Purpose/Significance]This paper carries out an in-depth analysis of health information services and its supply priority for rural community residents from the perspective of user needs.It is of great theoretical significance and practical guiding value for the digital village construction and the residents health level.[Method/Process]On the basis of relevant literature review and the practical needs of digital village construction,this paper listed 28 health information service items through semi-structured interview and expert consultation,and designed questionnaires to collect data accordingly.Then,it used Kano model,mixed class analysis,Better-Worse satisfac-tion index analysis and entropy weight Topsis to identify the types of rural community health information services and quantify their priorities.[Result/Conclusion]The results show that rural residents'need for health information services presented hierarchical characteristics,including 8 expected services,8 attractive services,6 mixed services and 6 undifferentiated services.In the process of the digital village construction,rural communities should optimize the health information services according to different need and their priorities,and enhance the service appropriate-ness,satisfaction and overall efficiency.
关键词
数字乡村/农村社区居民/健康信息服务/Kano模型/熵权TopsisKey words
digital village/rural community residents/health information service/Kano model/entropy weight Topsis引用本文复制引用
基金项目
国家社会科学基金青年项目(22CTQ023)
出版年
2024
NETL
NSTL
万方数据