To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors a...To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.展开更多
总结国内外图书馆移动用户行为的研究现状,为面向个性化信息服务的图书馆移动用户行为分析模型设计提供参考。采用理论研究与模型分析相结合的方法,从数据采集、数据处理与数据应用三方面研究用户行为动作序列和用户行为特征之间的关系...总结国内外图书馆移动用户行为的研究现状,为面向个性化信息服务的图书馆移动用户行为分析模型设计提供参考。采用理论研究与模型分析相结合的方法,从数据采集、数据处理与数据应用三方面研究用户行为动作序列和用户行为特征之间的关系。以前端操作行为与后端业务数据库相结合的方式定义和表示图书馆移动用户在i OS App、Android App与Web页面上与产品UI的隐形反馈行为,采集移动用户客户端基础信息字段、用户行为相关字段、配置Flume 3个方面数据,引入时间维度、用户维度、部门维度、资源维度、行为维度、入口渠道6个维度进行数据仓库层面的建模,从用户行为序列预测与用户兴趣引导两步实现数据应用。展开更多
文摘To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.
文摘总结国内外图书馆移动用户行为的研究现状,为面向个性化信息服务的图书馆移动用户行为分析模型设计提供参考。采用理论研究与模型分析相结合的方法,从数据采集、数据处理与数据应用三方面研究用户行为动作序列和用户行为特征之间的关系。以前端操作行为与后端业务数据库相结合的方式定义和表示图书馆移动用户在i OS App、Android App与Web页面上与产品UI的隐形反馈行为,采集移动用户客户端基础信息字段、用户行为相关字段、配置Flume 3个方面数据,引入时间维度、用户维度、部门维度、资源维度、行为维度、入口渠道6个维度进行数据仓库层面的建模,从用户行为序列预测与用户兴趣引导两步实现数据应用。
