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论文编号：	15323
作者编号：	2120223807
上传时间：	2025/6/5 13:58:43
中文题目：	在线社区个人投资者信息采纳行为影响因素研究——以雪球社区为例
英文题目：	Factors Influencing Individual Investors'''' Information Adoption in Online Communities: Evidence from Snowball Community
指导老师：	李月琳
中文关键字：	在线社区；雪球社区；个人投资者；信息采纳
英文关键字：	Online communities; Snowball Community; Individual investors; Information adoption
中文摘要：	随着互联网与在线社区的快速发展，个人投资者逐渐依赖在线平台获取和采纳投资信息。然而，在线社区中信息质量参差、用户行为复杂，如何有效促进信息采纳行为成为理论与实践的重要议题。本研究以雪球社区为例，聚焦个人投资者信息采纳行为的影响因素，结合信息采纳模型（IAM）与技术接受与统一使用模型（UTAUT），构建“绩效期望、努力期望、社会影响、信息质量、促进条件、个体特征”多因素理论模型，旨在揭示在线社区中个人投资者信息采纳行为的影响因素及内在机制。 研究采用混合研究方法，首先通过半结构化深度访谈进行质性分析，通过对访谈结果程序化编码，提取潜在影响因素，形成研究假设。而后基于质性研究结果和已有问卷，开发调查问卷，并针对收回的286份有效问卷，运用结构方程模型和单因素方差分析验证模型及假设。研究发现努力期望与信息质量是影响用户信息采纳意愿的核心因素；社会影响通过社区氛围与群体观点间接驱动信息采纳行为；促进条件直接作用于采纳行为；个体特征因素调节作用整体来看不显著，但其中的风险偏好因素对信息质量与采纳意愿细分维度存在调节作用。 研究基于UTAUT模型与信息采纳模型，构建了在线社区中个人投资者信息采纳行为影响因素模型，最终根据研究结论，有针对性地提出雪球社区未来运营过程中如何优化信息筛选机制、引入AI导航系统、升级个性化推荐算法的建议，并呼吁投资者提升信息验证能力与独立思考意识，为平台功能改进与用户决策效率提升提出可操作建议，具有一定的理论和现实意义。图3幅，表17个，参考文献46篇。
英文摘要：	With the rapid development of the internet and online communities,individual investors increasingly rely on online platforms to acquire and adopt investment-related information. However, the uneven quality of information and complex user behaviors in online communities pose significant challenges,making it a critical theoretical and practical issue to effectively facilitate information adoption behaviors. Taking the Snowball Community as a case study, this research focuses on the influencing factors of individual investors’ information adoption behaviors. By integrating the Information Adoption Model (IAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), a multi-factor theoretical framework is constructed, encompassing performance expectancy, effort expectancy, social influence, information quality, facilitating conditions, and individual characteristics, aiming to uncover the determinants and underlying mechanisms of information adoption behaviors in online communities. This study employs a mixed-methods approach. First, qualitative analysis was conducted through semi-structured in-depth interviews, with procedural coding of interview data to extract potential influencing factors and formulate research hypotheses. Subsequently, based on qualitative findings and established questionnaires, a 33-item survey was developed. Using 286 valid responses, structural equation modeling (SEM) and one-way ANOVA were applied to test the hypotheses. The results reveal that effort expectancy and information quality are core factors influencing adoption intention. Social influence indirectly drives adoption behaviors through community atmosphere and group consensus, while facilitating conditions directly affect adoption behaviors. Although individual characteristics showed no significant overall impact, risk preference exhibited a moderating effect on the relationship between information quality and adoption intention. By integrating UTAUT and IAM, this study proposes a theoretical model for understanding individual investors’ information adoption behaviors in online communities. Practical recommendations include optimizing Snowball Community’s information filtering mechanisms, introducing AI navigation systems, enhancing personalized recommendation algorithms, and advocating for investors to improve information verification capabilities and independent thinking. These insights offer actionable guidance for platform optimization and user decision-making efficiency. This paper includes 3 Figures, 17 Tables, 46 References.
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