摘 要

鮮少有科技如人工智慧（Artificial Intelligence, AI）般引發如此分歧的觀點：對部分人而言，它象徵希望；對另一些人而言，則引發質疑與冷漠。在對科技環繞未來的期待中，人們同時產生好奇感，然而，對於自主性、信任與控制等議題的不確定性與疲憊感亦隨之而來。當前，人工智慧已被廣泛應用於多個產業領域，尤以顧客體驗個人化與行銷策略發展最為顯著。然而，透過人工智慧所實現的個人化與情緒智慧（Emotional Intelligence, EI）之間的關聯，至今仍缺乏充分的學術探討。本文旨在分析人工智慧技術於行銷與顧客體驗個人化中的角色，並主張儘管人工智慧能夠提供對消費者行為的寶貴洞察，情緒智慧與人類的監督與介入仍是形塑真實且成功的行銷策略，以及創造令人滿意之顧客體驗的關鍵因素。

Abstract

Few technologies divide opinion like AI: it inspires hope in some and cynicism in others. While feelings of curiosity arise with aspirations for a future surrounded by technology, uncertainty and weariness are elicited, regarding autonomy, trust and control. Artificial Intelligence is now being integrated in multiple sectors, particularly in the sectors of customer experience personalization and marketing strategies development. However, the interconnection between personalization through artificial intelligence (AI) and emotional intelligence (EI) remains insufficiently researched. This paper analyzes AI-technology's role in marketing and customer experience personalization, arguing that while AI can provide valuable insights into consumer behavior, emotional intelligence and human supervision remains a crucial factor in creating authentic, successful marketing approaches and satisfactory customer experience.

Thesis Validation Letter i
Acknowledgements ii
摘 要 iii
Abstract iv
List of Tables vii
Term Definition and Abbreviations viii
Chapter 1 1
Introduction 1
Chapter 2 4
Literature Review 4
2.1 Introduction 4
2.2 AI Overview- Weak AI vs General AI 4
2.3 AI in Marketing 7
2.4 The AI Effect in Marketing Processes and Consumer Experience Personalization 9
2.5 Challenges of Implementing AI in Customer Experience 12
2.6 Theoretical Framework 14
2.6.1 Emotional Intelligence (EI) Theory 15
2.6.2 Artificial Intelligence under the Spectrum of Technology Acceptance Model (TAM) 17
2.6.3 Socio-Technical Systems Theory (STS)/ Human-AI Interaction Frame 20
2.7 Summary 24
Chapter 3 26
Research Methodology 26
3.1 Research Approach 26
3.2 Case Selection 27
3.3 Netflix Case 28
3.4 Facebook Case 30
3.5 Data collection 32
Chapter 4 34
Data Analysis 34
4.1 Secondary literature, Articles and Reports 34
4.2 Validity and Trustworthiness of the Analysis 36
4.3 Ethical Considerations for the Analysis 39
Chapter 5 41
Findings and Discussion 41
5.1 Introduction 41
5.2 Cross Case Thematic Findings 42
5.3 Netflix AI Integration 44
5.4 Algorithmic Regulation 44
5.5 Emotional Intelligence Implications 45
5.6 Ethical Challenges and Implications 47
5.7 Findings under the Lens of Theoretical Framework for Netflix 48
5.8 Facebook AI Integration 51
5.9 Algorithmic Regulations 51
5.10 Emotional Intelligence Implications 52
5.11 Ethical Challenges and Implications in the Context of Customer Experience 53
5.12 Findings under the Lens of Theoretical Framework for Facebook 54
5.13 Limitations 56
Chapter 6 58
Implications 58
6.1 Research Question and Confirmation of Proposition 58
6.2 Implications 59
6.2.1 Theoretical implications 59
6.2.2 Practical Implications 59
6.3 Summary 60
Conclusion 61
References 63

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