机构地区:[1]湘潭大学商学院,湖南湘潭411105 [2]南京大学工程管理学院,南京210093
出 处:《管理科学》2021年第2期56-68,共13页Journal of Management Science
基 金:教育部人文社会科学研究项目(19YJA630030);湖南省教育厅优秀青年项目(17B267);湖南省社会科学基金(17YBA369)。
摘 要:随着移动社交媒体的迅速发展,越来越多的人被紧密地嵌入一个相互影响的社会网络中,越来越多的用户开始关注并使用微信运动共享运动数据,并进行个人健康管理。因此,探讨用户运动行为在社会网络中的相互影响机制成为重要的研究课题。尽管已有研究探讨了微信运动对于用户运动行为的影响,但这些研究忽视了平台的排名机制以及性别差异和态度差异等个人因素在运动行为中的作用。依托微信运动平台,整合社会网络行为传染、社会支持、竞争机制、动机理论和用户行为的相关研究,从用户运动行为内在动机的视角,研究微信运动"步数排行榜"对用户运动行为的影响机制以及由于个人差异而造成的不同影响,在此基础上提出研究假设和模型。采用问卷调查方法收集752名使用计步软件用户的日平均步数和个人特征信息作为研究数据,运用倾向得分匹配法对数据和实证模型进行反事实估计分析。研究结果表明,微信运动"步数排行榜"对用户运动行为有显著的正向激励作用,参与排行榜时用户的运动行为比其不参与时更加积极。排名机制对不同运动态度和不同性别用户的影响存在差异,排行榜对运动态度积极和运动态度消极的用户均具有显著的激励作用,而对运动态度中性的用户并不具有显著影响;女性更容易受到排行榜的激励影响,且比男性用户更具显著性。研究结果扩展了关于社会网络中用户行为影响机制的研究,考虑了个人特征的调节作用,研究方法降低了选择性偏误带来的影响,结果更加准确;有利于用户更好地了解"步数排行榜"的价值和功能,帮助其更好地进行健康管理;并为电子健康社交服务平台的运营提供决策依据和借鉴。With the rapid development of mobile social media, an increasing number of people are closely embedded in an interactive social network. In addition, now more and more users are starting to pay attention to and use WeRun for sharing exercise data and doing personal health management. Therefore, it is an important research topic to explore the interaction mechanism of user′s exercise behavior in the social network. Although some scholars have studied the effect of WeRun on user′s exercise behavior, these studies ignored the role of the platform′s ranking mechanism and individual factors(gender and attitude differences) in exercise behavior.Relying on WeRun, we integrate the related researches of behavior contagion in social networks, social support, competition mechanism, motivation theory, as well as user behavior. From the perspective of intrinsic motivation of user′s exercise behavior, this research discusses the mechanism of the effects of WeRun′s "step ranking" on user′s exercise behavior and the differences caused by individual differences. On this basis, we put forward the research hypothesis and model. This study further used the questionnaire to collect the average daily step number and personal characteristic information of 752 network users as the research data, who used the pedometer software, and the propensity score matching(PSM) method to analyze the counterfactual estimation of the data and the empirical model.The results show that the WeRun′s "step ranking" has a significant positive incentive effect on user′s exercise behavior, and users who participate in the "step ranking" are more active than those who do not participate in. At the same time, it is found that the ranking mechanism has different effects on different genders and different exercise attitudes of users: the ranking has a significant incentive effect on users who have positive and negative exercise attitudes, but not on those who have neutral exercise attitudes;in addition, female users are more likely to be motivate
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