研究生: |
蔡瓊儀 Tsai, Chiung-Yi |
---|---|
論文名稱: |
語音助理感知特質對用戶信任感與使用行為之影響 The Impact of Perceived Traits of Voice Assistants on Users’ Trust and Usage Behavior |
指導教授: |
蔡欣怡
Tsai, Hsin-Yi |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 電信管理研究所 Institute of Telecommunications Management |
論文出版年: | 2025 |
畢業學年度: | 113 |
語文別: | 中文 |
論文頁數: | 123 |
中文關鍵詞: | 智慧語音助理 、感知特質 、信任感 、使用行為 、人機互動 |
外文關鍵詞: | Smart Voice Assistant, Perceived Traits, Trust, Usage Behavior, Human-Computer Interaction |
相關次數: | 點閱:21 下載:17 |
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智慧語音助理(Smart Voice Assistants, SVAs)是運用人工智慧技術,透過語音與人類互動的軟體,近年來,語音助理已融入人們的日常生活。因此,理解驅動使用者互動的心理機制,對於優化設計與促進技術採用,具有重要意義。
本研究旨在探討使用者對語音助理所感知的特質,包括智慧、有趣與真誠,如何影響其信任感,進而影響後續的使用行為。有別於以往主要著重於科技接受模型的研究,本研究整合跨領域觀點,建構一個專為語音助理研究所設計的整體性模型。該模型納入信任、功利價值與享樂價值、感知風險,以及社會聯繫感等變項。研究透過線上問卷蒐集資料,並以結構方程模型(SEM)進行分析。
研究結果顯示,使用者感知語音助理特質能顯著提升其信任感,進而增強對語音助理的功能性與情感價值認知,降低感知風險,並提升社會聯繫感。這些因素綜合促進了使用者的滿意度、使用行為與持續使用意圖。此外,本研究也發現語音助理的性別與使用者所賦予的角色認知,會顯著影響其對語音助理特質的感知與互動行為。此結果進一步凸顯「電腦即社會行為者」(CASA)範式與社會實體理論(social entity theory)在人工智慧系統設計中的重要性。
本研究提供理論與實務上的雙重貢獻。結果指出,開發者除了強化語音助理的技術功能外,也應將社會性與人格特質納入設計,以提升使用者的信任感、滿意度與長期使用意願。
Smart voice assistants (SVAs), software that utilizes artificial intelligence to interact with human beings through spoken language, have become increasingly important in people’s daily lives. Therefore, understanding the psychological mechanisms driving user interaction has become essential to optimizing design and promoting adoption. This study examines how users’ perceived traits of SVAs—including intelligence, fun, and sincerity—affect trust and subsequent usage behavior. Unlike prior studies that mainly focused on technology acceptance models, this research integrates interdisciplinary perspectives to construct a holistic model tailored for voice assistant studies. The model incorporates trust, utilitarian and hedonic value, perceived risk, and social connectedness. Data were collected through an online survey and analyzed using structural equation modeling (SEM).
The results indicate that perceived traits significantly enhance user trust, which in turn strengthens perceptions of both functional and emotional value, reduces perceived risk, and increases social connectedness with SVAs. These factors collectively promote user satisfaction, actual usage, and continued usage intention. Moreover, this study finds that both the gender of an SVA and users’ role perceptions significantly influence how users perceive the assistant’s traits and interact with it. These findings further highlight the importance of the CASA (Computers Are Social Actors) paradigm and social entity theory in the design of AI systems.
This research offers both theoretical and practical contributions. It suggests that developers, in addition to enhancing technical functionality, should also incorporate social and personality-related traits into the design of voice assistants to strengthen user trust, satisfaction, and long-term engagement.
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