文献类型：期刊文献

中文题名：基于自动逻辑行动者属性模型的在线医生团队社会影响机理研究

英文题名：Research on Social Influencing Mechanism of Online Doctor Teams Based on Auto-Logistic Actor Attribute Model

作者：刘璇[1];迟晓彤[1];范静[2]

机构：[1]华东理工大学商学院管理科学与工程系;[2]北京外国语大学国际商学院

年份：2021

卷号：18

期号：12

起止页码：1830

中文期刊名：管理学报

外文期刊名：Chinese Journal of Management

收录：CSTPCD;;国家哲学社会科学学术期刊数据库;北大核心:【北大核心2020】；CSSCI:【CSSCI2021_2022】；

基金：国家自然科学基金资助项目(71971082,71573022);上海市“科技创新行动计划”软科学研究领域重点资助项目(19692106700)。

语种：中文

中文关键词：在线医生团队;传染效应;医院网络;知识网络;行动者属性模型

外文关键词：online doctor teams;contagion effect;hospital network;knowledge network;ALAAM model

摘要：从社会影响视角,运用自动逻辑行动者属性模型,对好大夫在线平台中900位医生进行建模,综合考虑网络结构效应和行动者属性效应,分别构建医院网络和知识网络中医生加入在线医生团队的决策行为的传染效应模型。研究表明:两个网络中行动者属性效应对医生加入团队行为的影响基本相同,其中,决策资本和在线声誉更高的医生更有可能加入医生团队,职称的影响为负向;两个网络的网络结构对因变量的影响有所不同,基于相似专业知识背景的网络传染效应相对于基于工作关系的传染效应,更有助于促进在线医生团队这一新型服务模式的发展。
This study investigated the diffusion mechanism of online doctor teams from social influencing perspectives,based on the platform“haodf.com”,900 doctors were chosen as the research sample,and the auto-logistic actor attribute model(ALAAM)was used to construct the contagiousness effect model.To explore the factors that affect doctors’decision in joining the online doctor team,the study comprehensively consider the network structure effect and the actor attribute effect,so the contagiousness effect model were constructed and the social influence were analyzed in two different networks,hospital network and knowledge network.The research results show that the effect of the actor’s attributes in the two networks has a similar influence mechanism on the behavior of doctors joining the teams.Doctors with higher decision capital and online reputation are more likely to join the team while the influence of professional title is negative.The network structure of the two networks has different effects on the dependent variable.The contagion effect of networks based on similar professional knowledge backgrounds contributes more to the development of online doctor teams compared with the contagion effect based on offline connections.