以驅動和制約力量的觀點探討生成式AI聊天機器人擬人化對人機互動意願的影響

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劉冠妤(Kuan-Yu Liu) 查詢紙本館藏

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資訊管理學系

論文名稱

以驅動和制約力量的觀點探討生成式AI聊天機器人擬人化對人機互動意願的影響
(Exploring the Impact of Anthropomorphism of Generative AI Chatbots on Human-Computer Interaction Willingness from the Perspective of Driving and Restraining Forces)

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至系統瀏覽論文 (2029-7-8以後開放)

摘要(中)

生成式AI聊天機器人是目前極具商業潛力的顛覆性創新，由於生成式聊天機器人的崛起，讓人們對於人機互動的方式和體驗有了新的期待和挑戰。因此目前生成式AI成為各界相當熱門的討論和研究議題，然而目前仍較缺乏生成式AI聊天機器人對使用者態度和看法的量化研究。
故本研究進行實證研究，探討生成式AI聊天機器人擬人化特性對使用者互動意願的影響。以力場分析理論為基礎，考察了生成式AI聊天機器人擬人化特徵（同理心、適應性、感知溫暖）等驅動力因素和（溝通延遲和感知冷淡）等制約力因素對感知溝通品質（準確性、可靠性、能力）、使用者好感度和人機互動意願的影響，以及隱私擔憂在此應用背景下的調節效果。研究方法分為兩部分，第一部分欲了解大眾生成式AI使用經驗，第二部分透過情境實驗，了解作為行銷和娛樂用途之聊天機器人對話風格對使用者態度的影響。兩部份皆透過問卷調查將有效樣本資料進行結構方程模型的分析。研究結果顯示同理心、適應性和感知溫暖對消費者對聊天機器人的感知溝通品質產生正面影響，而溝通延遲和感知冷淡則會產生負面影響。整體而言，若使用者感受聊天機器人有較高的溝通品質，將對使用者好感度產生正面影響，進而有更高的人機互動意願。儘管隱私問題在我們提出的模型中沒有發揮調節作用，但結果也揭示了某些程度的隱私悖論。
研究提供了對於生成式AI聊天機器人擬人化特性及其對使用者影響的新洞察，並為企業利用生成式AI聊天機器人作為品牌行銷與顧客服務提供一些見解和指導方向，為後續學者和開發者提供了理論和實務建議。

摘要(英)

Generative AI chatbot is a highly disruptive innovation with significant commercial potential. The rise of generative chatbots has introduced new expectations and challenges regarding human-computer interaction. Consequently, generative AI has become a popular topic for discussion and research. However, there is still a lack of quantitative research on user attitudes and perceptions toward generative AI chatbots. This study conducts empirical research to explore the impact of anthropomorphic design in generative AI chatbots on users′ willingness to interact. Based on Force Field Theory, the study examines the driving factors such as the anthropomorphic characteristics of generative AI chatbot (empathy, adaptability, perceived warmth) and the restraining factors (communication delay, perceived coldness) on perceived communication quality (accuracy, credibility, competence), user likability, and willingness to interact. It also investigates the moderating effect of privacy concerns in this context. The research methodology is divided into two parts. The first part aims to understand the public′s experience with generative AI, while the second part uses situational experiments to understand the impact of chatbot communication styles for marketing and entertainment purposes on user attitudes. Both parts employ questionnaire surveys, with the collected data analyzed using structural equation modeling. The results indicate that empathy, adaptability, and perceived warmth positively influence consumers′ perceived communication quality with chatbots, whereas communication delay and perceived coldness have negative effects. Overall, higher perceived communication quality leads to increased user likability and greater willingness to interact with the chatbot. Although privacy concerns did not moderate the proposed model, the findings revealed a certain degree of privacy paradox.

This study provides new insights into the anthropomorphic characteristics of generative AI chatbots and their effects on users. It offers practical guidance for businesses using generative AI chatbots for branding and customer service, and provides theoretical and practical recommendations for future researchers and developers.

關鍵字(中)

★ 生成式AI聊天機器人
★ 擬人化
★ 力場分析理論
★ 感知溝通品質
★ 人機互動意願

關鍵字(英)

★ Generative AI chatbot
★ Anthropomorphism
★ Force field theory
★ Perceived communication quality
★ Willingness to interact

論文目次

摘要 i
Abstract ii
目錄 iv
圖目錄 vii
表目錄 viii
第一章、緒論 1
1.1研究背景與動機 1
1.2研究目的 3
1.3研究流程 4
第二章、文獻探討 5
2.1聊天機器人相關研究 5
2.2擬人化 (Anthropomorphism) 7
2.3驅動與制約觀點 9
2.4溝通品質 (Communication Quality) 10
2.5聊天機器人的資訊隱私擔憂 11
第三章、研究模型與假說 13
3.1研究架構 13
3.2研究假說 15
3.2.1擬人化(驅動因素)與感知溝通品質 15
3.2.2擬人化(制約因素)與感知溝通品質 17
3.2.3隱私擔憂的調節作用 18
3.2.4感知溝通品質與使用者好感度 19
3.2.5使用者好感度與人機互動意願 20
第四章、研究方法 21
4.1研究設計 21
4.2研究1 25
4.2.1前測 25
4.3研究2 28
4.3.1腳本情境設定 28
4.3.2聊天機器人與腳本設計 29
4.3.3腳本檢測 34
4.3.4前測 36
4.4資料分析方法 38
第五章、研究結果 39
5.1研究1 39
5.1.1樣本基本資料分析 39
5.1.2信度分析 41
5.1.3第一階段測量模型分析 42
5.1.4第二階段測量模型分析 47
5.1.5結構模型檢驗 52
5.1.6線上訪談 55
5.2研究2 58
5.2.1樣本基本資料分析 58
5.2.2信度分析 59
5.2.3收斂效度 59
5.2.4區別效度 63
5.2.5結構模型檢驗 66
5.2.6問答題結果 71
5.1.6線上訪談 72
第六章、結論與建議 75
6.1結果討論 75
6.1.1研究1 75
6.1.2研究2 77
6.2研究貢獻與建議 78
6.2.1理論意涵 78
6.2.2管理建議 79
6.3研究限制與未來方向 81
參考文獻 83
附錄一正式問卷 95
附錄二簡單斜率分析 107
附錄三中介效果分析 109
附錄四 f2解釋效果分析與Q2模型預測能力 111

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指導教授

許文錦(Wen-Chin Hsu)

審核日期

2024-7-10

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