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信息内容特征对移动医疗APP用户推荐行为的影响及作用路径分析
引用本文:陈远,张磊,张敏. 信息内容特征对移动医疗APP用户推荐行为的影响及作用路径分析[J]. 现代情报, 2019, 39(6): 38-47. DOI: 10.3969/j.issn.1008-0821.2019.06.005
作者姓名:陈远  张磊  张敏
作者单位:1. 武汉大学信息资源研究中心, 湖北 武汉 430072;2. 武汉大学信息管理学院, 湖北 武汉 430072
基金项目:教育部人文社会科学研究规划基金项目"在线健康社区用户知识共享行为的间歇性中辍现象研究:基于信息生态链的分析视角"(项目编号:18YJA870016);教育部世界一流学科"图书情报与数据科学"项目;武汉大学自主科研项目(人文社会科学)"70后"学者学术发展计划专题项目"数字人文和语义挖掘"。
摘    要:[目的/意义]旨在探究信息内容特征对移动医疗APP用户推荐行为的影响和作用路径,提炼出对运营和管理具有积极意义的意见和方法。[方法/过程]以精细加工可能性模型为理论框架,通过整合信息系统成功模型和口碑营销经典理论的相关因素,构建出"中心信息内容特征——自我推荐"以及"边缘信息内容特征——从众推荐"两条作用路径,并聚焦感知需求的调节作用提出假设并构建研究模型。实证研究采用"日志追踪实验+调查问卷"的方式收集来自移动医疗APP用户的288份数据,利用SmartPLS2.0对模型进行检验。[结果/结论]信息质量、服务质量、系统质量正向影响自我推荐意愿;APP认知声誉、医生认知声誉、医院认知声誉正向影响从众推荐意愿;感知需求正向调节自我推荐意愿对推荐行为的影响,而从众推荐意愿对推荐行为的影响不具有显著调节作用。

关 键 词:信息内容特征  推荐行为  移动医疗APP  作用路径

Analysis of the Impact and Action Path of Information Content Characteristics on Users' Recommender Behaviors in Mobile Health Applications
Chen Yuan,Zhang Lei,Zhang Min. Analysis of the Impact and Action Path of Information Content Characteristics on Users' Recommender Behaviors in Mobile Health Applications[J]. , 2019, 39(6): 38-47. DOI: 10.3969/j.issn.1008-0821.2019.06.005
Authors:Chen Yuan  Zhang Lei  Zhang Min
Affiliation:1. Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China;2. School of Information Management, Wuhan University, Wuhan 430072, China
Abstract:[Purpose/Significance]This paper aimed to explore the impact and action path of information content characteristics on users' recommender behaviors in mobile health applications,and to draw up opinions and suggestions which have positive significance for operations and management.[Method/Process]Taking the the ELM model as the theoretical framework,and by integrating the revelant factors of Information System Success Models and Word Of Mouth Marketing,this article constructed two action paths:central information content characteristics to self-recommendation and edge information content characteristics to conformity-recommendation,and focused on the moderating effect of perceived needs to propose hypotheses and construct research models.The empirical research used the log tracking experiment and questionnaire to obtian 288 valid data from mobile health APP users and test model with SmartPLS2.0.[Result/Conclusion]Information quality,service quality and system quality positively influenced users' self-recommendation intention;Cognitive reputation of applications,cognitive reputation of doctor and cognitive reputation of hospital positively influenced users' conformity-recommendation intention;Perceived information needed positively moderates the relationship between the self-recommendation intention and recommender behaviors,and did not moderate the relationship between the conformity-recommendation intention and recommender behaviors.
Keywords:information content characteristic  recommender behaviors  mobile health applications  action path  
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