高校学术用户信息搜寻转移行为影响因素
Factors Influencing the Information Seeking Transfer Behavior of Academic Users in Colleges and Universities
邱均平 1宓秦泽 2徐中阳 2张廷勇 2李松洮2
作者信息
- 1. 杭州电子科技大学管理学院;杭州电子科技大学中国科教评价研究院;杭州电子科技大学中国科教评价研究院
- 2. 杭州电子科技大学管理学院
- 折叠
摘要
AIGC技术使高校学术用户在搜索学术信息时从学术网站向AIGC平台转移,为学术网站带来了挑战,分析用户信息搜寻转移行为的影响因素至关重要.文章基于PPM模型构建用户信息搜寻转移行为的影响因素模型,运用结构方程模型(SEM)与模糊集定性比较分析(fsQCA)相结合的混合方法分析417份有效数据.研究表明:推力因素(感知不方便性、感知焦虑)和拉力因素(准确度、感知定价优势)显著正向影响用户的转移意向,锚定因素(习惯)显著负向影响用户的转移意向,且具有同时负向调节推力因素和拉力因素的作用.fsQCA结果还揭示两条触发用户信息搜寻转移行为的路径,即"感知不方便性""感知焦虑"是触发用户发生转移的关键影响因素.对此,学术网站管理者应引入新兴技术,提升用户体验;加强机构合作,优化品质价格;关注用户习惯,增强用户黏性.
Abstract
AIGC technology is shifting university academic users from academic websites to AICG platforms,which poses challenges for academic websites.Therefore,it is crucial to analyze the influencing factors of university users'information seeking transfer behavior.The study develops a model of factors influencing university users'information seeking transfer behavior based on the PPM model and analyzes 417 valid data using used a mixed method of structural equation modeling(SEM)and fuzzy set qualitative comparative analysis(fsQCA).The study shows that push factors(perceived inconvenience,perceived anxiety)and pull factors(accuracy,perceived price advantage)significantly and positively influence users'swifting intention,and the anchoring factor(habit)significantly and negatively influences users'swifting intention and has the effect of negatively moderating both push and pull factors.The fsQCA-based results also reveal two pathways that trigger users'information seeking transfer behavior,with"perceived inconvenience"and"perceived anxiety"being the key factors that trigger users'transfer behavior.In this regard,academic website managers should introduce new technologies to improve user experience,strengthen institutional cooperation to optimize quality and price,and pay attention to user habits to enhance user stickiness.
关键词
学术网站/AIGC/高校学术用户/转移行为/PPM模型Key words
academic websites/AIGC/university academic users/switching behavior/PPM model引用本文复制引用
出版年
2024
NETL
NSTL
万方数据