农业图书情报学报 ›› 2024, Vol. 36 ›› Issue (8): 82-95.doi: 10.13998/j.cnki.issn1002-1248.24-0444

• 研究论文 • 上一篇    下一篇

基于SEM和fsQCA的虚拟兴趣社区用户信息采纳的影响因素研究

韩龙1, 郭晋成1, 鲁羿廷2, 周群1()   

  1. 1. 中国农业大学 图书馆,北京 100083
    2. 天津师范大学 管理学院,天津 300382
  • 收稿日期:2024-07-07 出版日期:2024-08-05 发布日期:2024-12-13
  • 通讯作者: 周群
  • 作者简介:

    韩龙(2000- ),男,硕士研究生,研究方向为信息行为

    郭晋成(2002- ),男,硕士研究生,研究方向为信息行为

    鲁羿廷(2000- ),女,硕士研究生,研究方向为信息计量与评价

  • 基金资助:
    中央高校基本科研业务费“‘双一流’涉农高校期刊学术影响力综合评价研究”(2024TC004)

Factors Influencing User Information Adoption in Virtual Communities of Interest: A Study Based on SEM and fsQCA

Long HAN1, Jincheng GUO1, Yiting LU2, Qun ZHOU1()   

  1. 1. Library, China Agricultural University, Beijing 100193
    2. School of Management, Tianjin Normal University, Tianjin 300382
  • Received:2024-07-07 Online:2024-08-05 Published:2024-12-13
  • Contact: Qun ZHOU

摘要:

[目的/意义] 虚拟兴趣社区资源聚合、深度交流、互动性强等特点使其成为用户利用信息决策的重要信息来源,探究虚拟兴趣社区用户信息采纳的影响因素及其作用机理,有助于满足用户信息需求,优化社区管理与服务。 [方法/过程] 以信息生态理论为分析框架,构建虚拟兴趣社区用户信息采纳的影响因素研究模型,利用结构方程模型(SEM)和模糊集定性比较分析(fsQCA)方法对影响路径和前因构型进行实证分析。 [结果/结论] SEM结果表明,信息质量、情感支持、社区认同、社区意见领袖参与、社区内容互动对用户信息采纳意愿有显著正向影响;信息源可信度和平台易用性对用户信息采纳意愿无显著影响。fsQCA分析发现,用户信息采纳意愿的前因构型有两种模式,信任驱动型与体验促进型,共6条组态路径,结果与SEM分析存在差异,显示其能够揭示复杂的决策环境中多因素相互作用的价值。

关键词: 虚拟兴趣社区, 信息采纳, 信息生态理论, 结构方程模型, 模糊集定性比较分析

Abstract:

[Purpose/Significance] Virtual communities of interest have rapidly become key sources of information that significantly influence users' decision making. Characterized by resource aggregation, active exchanges, and high interactivity, these communities foster a unique environment that encourages strong user engagement. Understanding the factors that influence information adoption in these settings is essential to meeting user needs and enhancing community management and services. Unlike traditional information contexts, virtual communities emphasize user trust, emotional support, and community identity, which are critical in shaping how users perceive and adopt information. This study aims to deepen the theoretical understanding of information adoption in virtual communities of interest by incorporating information ecology theory and applying both structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). This dual-method approach enables in-depth analysis of individual factors and reveals complex configurations that influence adoption behaviors, providing insights that go beyond what SEM alone can provide. [Method/Process] The research model is based on information ecology theory, which provides a holistic framework that captures the dynamic interplay between factors such as information quality, user support systems, community structures, and platform features. This theory is particularly suited to the study of virtual communities, where multiple interdependent factors create a unique decision-making environment. SEM is used to assess linear relationships between variables, evaluating the influence of information quality, emotional support, community identity, opinion leader participation, content interaction, source credibility, and platform usability on users' information adoption intentions. As a complement to SEM, fsQCA is used to explore configurations of multiple factors, identify pathways through which these factors collectively shape adoption intentions, and capture complex causal relationships that SEM does not address. [Results/Conclusions] The SEM analysis shows that information quality, emotional support, community identity, active participation of opinion leaders, and content interaction significantly increase users' adoption intentions, while information source credibility and platform usability do not. These findings suggest that community-driven aspects may be more important to users in this context than traditional credibility indicators. The fsQCA results further identify two primary modes that drive adoption intentions: a trust-driven mode, where adoption is supported by trust-related factors, and an experience-promoting mode, which focuses on user engagement within the community. Together, these modes comprise six distinct configurations, suggesting that users' adoption intentions are influenced by combinations of factors rather than isolated variables. This study thus highlights the unique value of fsQCA in uncovering the complex interplay of factors in virtual communities and providing detailed insights into user behavior. Future research could explore cultural differences in adoption behaviors and additional factors influencing user engagement in different types of virtual communities.

Key words: virtualcommunity of interest, information adoption, information ecology theory, structural equation modeling, fuzzy-set qualitative comparative analysis

中图分类号:  G252

引用本文

韩龙, 郭晋成, 鲁羿廷, 周群. 基于SEM和fsQCA的虚拟兴趣社区用户信息采纳的影响因素研究[J]. 农业图书情报学报, 2024, 36(8): 82-95.

Long HAN, Jincheng GUO, Yiting LU, Qun ZHOU. Factors Influencing User Information Adoption in Virtual Communities of Interest: A Study Based on SEM and fsQCA[J]. Journal of Library and Information Science in Agriculture, 2024, 36(8): 82-95.