消費者與AI技術之間的實證研究：聊天機器人與生成式人工智慧

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題名	消費者與AI技術之間的實證研究：聊天機器人與生成式人工智慧 An Empirical Study between Consumers and AI Technology : Chatbots and Generative AI
作者	玎公明 Dinh, Cong Minh
貢獻者	朴星俊 Park, Sungjun (Steven) 玎公明 Dinh, Cong Minh
關鍵詞	人工智慧聊天機器人生成式人工智慧動機社會臨場感思維智能情感智能社會距離社會地位 artificial intelligence chatbot generative artificial intelligence motivations social presence thinking intelligence feeling intelligence social distance social status
日期	2024
上傳時間	2-Jan-2025 12:09:36 (UTC+8)
摘要	基於大數據、自然語言處理、雲端運算、機器學習、自然語言處理、電腦視覺、大型語言模型、機器學習及相關技術方面的進步，人工智慧（AI）的應用已愈來愈廣泛。由於AI的應用不斷滲透到消費者日常生活的各個方面，消費者對這些應用的依賴也逐漸增加。因此，無論是業界還是學術界，都需要了解促使消費者採用這些AI應用的因素。本論文則通過三個研究對美國受試者進行問卷研究來填補這些缺口。研究一以自我決定理論為基礎，通過探討享樂動機和功利動機如何影響社會臨場感，進而影響消費者對於AI聊天機器人之使用意圖。該研究還顯示，消費者的COVID-19恐懼會加強影響社會臨場感對使用意圖的影響。在生成式AI（GenAI）的背景下，研究二A和研究二B以社會相互依賴理論為基礎，探討GenAI的思維智能和情感智能如何透過預期成功影響消費者的使用意圖。研究二顯示，可以透過操弄消費者與GenAI關係間之社會距離來改變其對GenAI社會地位之認知。綜上所述，本研究的發現不僅對AI相關的文獻做出貢獻，而且還能為開發AI聊天機器人和GenAI的企業提供了有價值的實務建議。 Progress in big data, natural language processing, cloud computing, computer vision, large language models, machine learning, and related technologies has driven the widespread adoption of various artificial intelligence (AI) applications. As AI applications permeate many aspects of consumers’ everyday lives, their reliance on these applications also increases. Therefore, it is imperative to identify what motivates consumers to adopt these technologies. This dissertation addresses this question through three studies using survey data from U.S. participants. Grounded in self-determination theory, study 1 contributes to chatbot research by examining how different types of motivations, particularly intrinsic/hedonic and extrinsic/utilitarian, influence social presence, thereby shaping users’ adoption intentions. The study also reveals that fear arising from the COVID-19 pandemic heightened the influence of perceived social presence on adoption. In generative AI (GenAI) contexts, studies 2A and study 2B draw on social interdependence theory to investigate how thinking and feeling intelligence of GenAI drive consumers’ adoption intention, with anticipated success acting as a mediator. These two studies also advance consumer research by demonstrating that by manipulating social distance in consumer-GenAI relations, researcher can alter perceptions of GenAI’s superior social status. Together, these findings not only extend the relevant literature, but also provide practical insights for firms seeking to facilitate consumer adoption of AI-powered chatbots and GenAI.
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描述	博士國立政治大學企業管理學系 109355511
資料來源	http://thesis.lib.nccu.edu.tw/record/#G0109355511
資料類型	thesis

dc.contributor.advisor	朴星俊	zh_TW
dc.contributor.advisor	Park, Sungjun (Steven)	en_US
dc.contributor.author (Authors)	玎公明	zh_TW
dc.contributor.author (Authors)	Dinh, Cong Minh	en_US
dc.creator (作者)	玎公明	zh_TW
dc.creator (作者)	Dinh, Cong Minh	en_US
dc.date (日期)	2024	en_US
dc.date.accessioned	2-Jan-2025 12:09:36 (UTC+8)	-
dc.date.available	2-Jan-2025 12:09:36 (UTC+8)	-
dc.date.issued (上傳時間)	2-Jan-2025 12:09:36 (UTC+8)	-
dc.identifier (Other Identifiers)	G0109355511	en_US
dc.identifier.uri (URI)	https://nccur.lib.nccu.edu.tw/handle/140.119/155011	-
dc.description (描述)	博士	zh_TW
dc.description (描述)	國立政治大學	zh_TW
dc.description (描述)	企業管理學系	zh_TW
dc.description (描述)	109355511	zh_TW
dc.description.abstract (摘要)	基於大數據、自然語言處理、雲端運算、機器學習、自然語言處理、電腦視覺、大型語言模型、機器學習及相關技術方面的進步，人工智慧（AI）的應用已愈來愈廣泛。由於AI的應用不斷滲透到消費者日常生活的各個方面，消費者對這些應用的依賴也逐漸增加。因此，無論是業界還是學術界，都需要了解促使消費者採用這些AI應用的因素。本論文則通過三個研究對美國受試者進行問卷研究來填補這些缺口。研究一以自我決定理論為基礎，通過探討享樂動機和功利動機如何影響社會臨場感，進而影響消費者對於AI聊天機器人之使用意圖。該研究還顯示，消費者的COVID-19恐懼會加強影響社會臨場感對使用意圖的影響。在生成式AI（GenAI）的背景下，研究二A和研究二B以社會相互依賴理論為基礎，探討GenAI的思維智能和情感智能如何透過預期成功影響消費者的使用意圖。研究二顯示，可以透過操弄消費者與GenAI關係間之社會距離來改變其對GenAI社會地位之認知。綜上所述，本研究的發現不僅對AI相關的文獻做出貢獻，而且還能為開發AI聊天機器人和GenAI的企業提供了有價值的實務建議。	zh_TW
dc.description.abstract (摘要)	Progress in big data, natural language processing, cloud computing, computer vision, large language models, machine learning, and related technologies has driven the widespread adoption of various artificial intelligence (AI) applications. As AI applications permeate many aspects of consumers’ everyday lives, their reliance on these applications also increases. Therefore, it is imperative to identify what motivates consumers to adopt these technologies. This dissertation addresses this question through three studies using survey data from U.S. participants. Grounded in self-determination theory, study 1 contributes to chatbot research by examining how different types of motivations, particularly intrinsic/hedonic and extrinsic/utilitarian, influence social presence, thereby shaping users’ adoption intentions. The study also reveals that fear arising from the COVID-19 pandemic heightened the influence of perceived social presence on adoption. In generative AI (GenAI) contexts, studies 2A and study 2B draw on social interdependence theory to investigate how thinking and feeling intelligence of GenAI drive consumers’ adoption intention, with anticipated success acting as a mediator. These two studies also advance consumer research by demonstrating that by manipulating social distance in consumer-GenAI relations, researcher can alter perceptions of GenAI’s superior social status. Together, these findings not only extend the relevant literature, but also provide practical insights for firms seeking to facilitate consumer adoption of AI-powered chatbots and GenAI.	en_US
dc.description.tableofcontents	TABLE OF CONTENT 摘要_____i ABSTRACT_____ii TABLE OF CONTENT_____iii LIST OF TABLES_____vii LIST OF FIGURES_____ix GENERAL INTRODUCTION_____1 STUDY 1_____4 1. Introduction_____4 2. Literature Review and Hypothesis Development_____6 2.1 A Review on Chatbots and Relevant Literature_____6 2.2 Consumer Motivations and Intention_____16 2.3 Consumer Motivations and Perceived Social Presence_____18 2.4 Perceived Social Presence and Intention_____20 2.5 COVID-19 Fear as a Moderator_____21 3. Methodology_____24 3.1 Data Collection and Sampling_____24 3.2 Measurements_____25 4. Results_____28 4.1 Descriptive Statistics_____28 4.2 Common Method Bias (CMB)_____30 4.3 Measurement Model_____31 4.4 Structural Model_____34 4.5 Moderation Analysis_____36 4.6 Post-Hoc Mediation Analysis_____37 4.7 Summary of Findings in Study 1_____38 5. Discussion for Study 1_____39 5.1 Theoretical Contributions_____39 5.2 Managerial Implications_____41 5.3 Limitations and Future Research Directions_____42 STUDY 2_____43 6. Introduction_____44 7. Literature Review_____46 7.1 Generative AI (GenAI)_____46 7.1.1 Overview of GenAI_____46 7.1.2 Recent Findings on GenAI_____48 7.2 Thinking Intelligence and Feeling Intelligence_____67 7.3 Social Interdependence Theory (SIT)_____69 8. Hypotheses Development_____71 8.1 Thinking Intelligence and Feeling Intelligence_____71 8.2 Thinking Intelligence, Feeling Intelligence, and Intention to Use_____72 8.3 Intention to Use and Actual Behavior_____73 8.4 The Mediating Role of Anticipated Success_____75 8.5 Social Distance as a Way to Prime Subjective Social Status_____77 8.6 The Moderating Role of Subjective Social Status_____79 9. Overview of Studies_____82 10. Study 2A_____83 10.1. Objectives_____83 10.2. Method_____84 10.2.1 Data Collection and Sampling_____84 10.2.2 Survey Design and Procedure_____85 10.2.3 Measurements_____86 10.3 Results_____89 10.3.1 Demographic Profiles_____89 10.3.2 Manipulation Check_____91 10.3.3 Effect of Social Distance on Subjective Social Status_____92 10.3.4 Regression Analyses_____94 10.3.5 Exploratory Moderation Analyses_____95 10.4 Discussion for Study 2A_____96 11. Study 2B_____97 11.1 Objectives_____97 11.2 Method_____98 11.2.1 Data Collection and Sampling_____98 11.2.2 Survey Design and Procedure_____99 11.2.3 Measurements_____100 11.2.4 Common Method Bias (CMB)_____103 11.3. Results_____105 11.3.1 Demographic Profiles_____105 11.3.2 Manipulation Check_____107 11.3.3 Effect of Social Distance on Subjective Social Status_____108 11.3.4 Assumption of a Cooperative Consumer-GenAI Relationship_____110 11.3.5 Regression Analyses_____111 11.3.6 Measurement Model_____112 11.3.7 Structural Model_____115 11.3.8 Logistic Regression_____117 11.3.9 Mediation Analyses_____118 11.3.10 Multigroup SEM_____119 11.3. Discussion for Study 2B_____123 12. Summary of Findings in Study 2_____125 13. General Discussion for Study 2_____126 13.1 Theoretical Contributions_____126 13.2 Practical Implications_____128 13.3 Limitations and Future Research Directions_____129 REFERENCES_____132 APPENDIX A_____167 APPENDIX B_____176 APPENDIX C_____192 APPENDIX D_____204 APPENDIX E_____223	zh_TW
dc.format.extent	4654330 bytes	-
dc.format.mimetype	application/pdf	-
dc.source.uri (資料來源)	http://thesis.lib.nccu.edu.tw/record/#G0109355511	en_US
dc.subject (關鍵詞)	人工智慧	zh_TW
dc.subject (關鍵詞)	聊天機器人	zh_TW
dc.subject (關鍵詞)	生成式人工智慧	zh_TW
dc.subject (關鍵詞)	動機	zh_TW
dc.subject (關鍵詞)	社會臨場感	zh_TW
dc.subject (關鍵詞)	思維智能	zh_TW
dc.subject (關鍵詞)	情感智能	zh_TW
dc.subject (關鍵詞)	社會距離	zh_TW
dc.subject (關鍵詞)	社會地位	zh_TW
dc.subject (關鍵詞)	artificial intelligence	en_US
dc.subject (關鍵詞)	chatbot	en_US
dc.subject (關鍵詞)	generative artificial intelligence	en_US
dc.subject (關鍵詞)	motivations	en_US
dc.subject (關鍵詞)	social presence	en_US
dc.subject (關鍵詞)	thinking intelligence	en_US
dc.subject (關鍵詞)	feeling intelligence	en_US
dc.subject (關鍵詞)	social distance	en_US
dc.subject (關鍵詞)	social status	en_US
dc.title (題名)	消費者與AI技術之間的實證研究：聊天機器人與生成式人工智慧	zh_TW
dc.title (題名)	An Empirical Study between Consumers and AI Technology : Chatbots and Generative AI	en_US
dc.type (資料類型)	thesis	en_US
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