图书情报工作

图书情报工作 >

2024 , Vol. 68 >Issue 3: 49 - 58

DOI: https://doi.org/10.13266/j.issn.0252-3116.2024.03.005

情报研究

用户信息搜寻转移意向研究：从搜索引擎到生成式AI

  • 周涛 ,
  • 李松洮 ,
  • 邓胜利
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  • 1 杭州电子科技大学管理学院 杭州 310018;
    2 武汉大学信息管理学院 武汉 430072
周涛,教授,博士,博士生导师,E-mail:zhoutao@hdu.edu.cn;李松洮,硕士研究生;邓胜利,教授,博士,博士生导师。

收稿日期: 2023-07-12

  修回日期: 2023-09-26

  网络出版日期: 2024-02-23

基金资助

本文系国家自科基金项目“社会交互对用户参与社会化商务行为的作用机理研究”（项目编号：71771069）和国家社会科学基金项目“矛盾态度视角下社交媒体用户使用行为的演变与机理研究”（项目编号：22BTQ095）研究成果之一。

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Research on Users' Switching Intention of Information Seeking: From Search Engines to Generative AI

  • Zhou Tao ,
  • Li Songtao ,
  • Deng Shengli
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  • 1 School of Management, Hangzhou Dianzi University, Hangzhou 310018;
    2 School of Information Management, Wuhan University, Wuhan 430072

Received date: 2023-07-12

  Revised date: 2023-09-26

  Online published: 2024-02-23

Supported by

This work is supported by the Natural Science Foundation of China titled "The effect of social interaction on user participation in social commerce" (Grant No. 71771069) and the National Social Science Fund of China titled "The evolution and mechanism of social media user usage behavior from the ambivalence perspective" (Grant No. 22BTQ095).

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摘要

[目的/意义] 生成式AI的广泛应用将使得用户信息搜寻行为发生转移，这可能导致传统搜索引擎用户流失。因此，有必要研究用户信息搜寻转移的形成机理。[方法/过程] 基于推—拉—锚理论（PPM）构建研究模型，采用结构方程模型（ SEM）和模糊集定性比较分析（ fsQCA）进行数据分析。[结果/结论] 信息—任务低匹配、信息过载导致用户不满意，AIGC信息质量、感知交互性影响感知价值，用户不满意、感知价值、社会影响决定用户的转移意向。fsQCA识别了导致转移意向的3个组态。研究结果启示搜索服务商需提高信息—任务匹配度，降低信息过载和用户不满意来实现用户保持；另外一方面，生成式AI平台则需提高AIGC信息质量、交互性等，通过社会影响来吸引用户使用。

关键词： 生成式AI; 信息搜寻; 转移意向; PPM

本文引用格式

周涛 , 李松洮 , 邓胜利 . 用户信息搜寻转移意向研究：从搜索引擎到生成式AI[J]. 图书情报工作, 2024 , 68(3) : 49 -58 . DOI: 10.13266/j.issn.0252-3116.2024.03.005

Abstract

[Purpose/Significance] The wide application of generative AI will enable users’ switch of information seeking. This may lead to users’ defection from search engines. Thus, it is necessary to examine the formation mechanism of user’s switching intention. [Method/Process] This study adopted the push-pull-mooring (PPM) to develop the model and conducted data analysis with structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). [Result/Conclusion] Low information-task fit and information overload lead to user dissatisfaction, whereas AIGC information quality and perceived interactivity affect perceived value. Dissatisfaction, perceived value and social influence determine users’ switching intention. With fsQCA, it identifies three configurations leading to switching intention. The results imply that search service providers need to improve the information-task fit and reduce information overload and user dissatisfaction to retain users. On the other hand, generative AI platforms can improve AIGC information quality and interactivity, and leverage social influence to facilitate user usage.

Key words： generative AI; information seeking; switching intention; PPM

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