人工智慧的角色策略：客戶、公司、與股東觀點

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研究生：	阮何長安 Nguyen, Thanh Tuan
論文名稱：	人工智慧的角色策略：客戶、公司、與股東觀點 ARTIFICIAL INTELLIGENCE STRATEGIC ROLES: PERSPECTIVES FROM CUSTOMERS, FIRMS, AND SHAREHOLDERS
指導教授：	許裴舫 Hsu, Pei-Fang
口試委員:	Shmueli, Galit Shmueli, Galit Ray, Soumya Ray, Soumya Teo, Thompson Teo, Thompson Nishant, Rohit Nishant, Rohit
學位類別：	博士 Doctor
系所名稱：	科技管理學院 - 服務科學研究所 Institute of Service Science
論文出版年：	2021
畢業學年度：	109
語文別：	英文
論文頁數：	176
中文關鍵詞：	人工智能、人工智能、信息系統、預言、商業價值、定性比較分析
外文關鍵詞：	artificial intelligence, artificial intelligence, qualitative comparative analysis, QCA, prediction, IT adoption
相關次數：	點閱：6 下載：1
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人工智能 (AI) 被認為可以為客戶、公司和其他利益相關者（即股東）提供多種好處。考慮到最近人工智能的前景和期望，過去研究並沒有從不同利益相關者的角度充分調查人工智能的潛在結果。本論文包括三章，研究目的是了解人工智能如何為不同利益相關者（包括客戶、公司和股東）帶來獲益。第 1 章通過服務主導邏輯和歸因理論著眼於自助服務技術（作為流程自動化/認知參與 AI），闡明客戶在什麼情況下選擇與公司共同創造或共同破壞價值。第 2 章提出了一個研究議程，從公司的角度，預測誰將為免費增值服務（作為認知洞察 AI）付費。第三章從股東的角度，考察了三種人工智能類型（流程自動化人工智能、認知洞察人工智能、認知參與人工智能）如何與公司特徵，相互影響市場反應。

Artificial Intelligence (AI) is believed to offer several benefits to both customers, firms, and other stakeholders (i.e., shareholders). Considering the recent hype and expectations of AI, IS research has insufficiently investigated the potential outcomes of AI from the perspectives of different stakeholders. The current thesis that includes three chapters, embarked on a research project with the aim of understanding how AI benefits are reaped from different stakeholders’ interests, including Customers, Firms, and Shareholders. Chapter 1 looks at Self-service technology (as a Process Automation/ Cognitive Engagement AI) through Service-Dominant Logic and attribution theory, illuminating in what contexts, customers choose to co-create or co-destruct value with service firms. Chapter 2 proposes a research agenda to conduct resource-wise predictions of who will pay for freemium service (as a Cognitive Insight AI) from the firm’s point of view. Chapter 3 examines the interdependent effect of three AI types (Process Automation AI, Cognitive Insight AI, Cognitive Engagement AI) and firm’s characteristics on the market reaction outcome from the perspective of shareholders.

Dissertation Introduction    1

CHAPTER 1: Process Automation and Cognitive Engagement AI from a Customer’s Perspective: The Value Co-Creation and Co-Destruction in Self-Service Technology    7

Abstract    7
Introduction    8
Prior studies in SST    10
Theoretical Foundation    13
1 Value Co-Creation    13
2 Value-In-Context    15
3 Value Co-Destruction    16
Conceptual Model    18
1 SST service context    18
1.1. Resource Misuse    18
1.2. Service Failure    19
2 Value-in-context: Perceived Severity    20
3 In-process co-creation versus In-process co-destruction    22
4 Behavioral intention: Retaining SST and Retaining Firm    24
Methodology    25
1 Data    25
2 Constructs’ Operationalization    27
Data Analysis Results    29
Discussion    32
1 Theoretical contribution    33
2 Managerial insights    34
Conclusion    37



CHAPTER 2: Cognitive Insight AI from a Firm’s Perspective: Theory-based Prediction from survey studies for SAAS Firms    39

Abstract    39
Introduction    40
Literature Review    43
1 Theory-driven survey-based studies    43
2 Data-driven Prediction    46
3 Theory-based Prediction    48
Methodology    48
1 Data Source    48
2. Detailed Prediction Process    49
2.1 Goal definition    50
2.2 Study design and data collection    50
2.3 Data preparation    52
2.4 Data Dimension Reduction    53
2.5 Choice of variables    55
2.6 Choice of methods    58
2.7 Model evaluation, validation and selection    59
Prediction Results    62
1. Theory-based prediction results    62
2.  Data-driven prediction results    64
Robustness Checks    66
1.  Machine Learning    66
2.  Poisson Regression    68
Discussion    71
1 Research Implications    71
2. Managerial Implications    75
2.1. Maximizing revenues    76
2.2 Increase community vitality    77
2.3 Balancing revenues and community vitality.    78
2.4. The resource-constrained SaaS providers    79
2.5. Saving resources on prediction process    80
3. Limitation and further research    81
Conclusion    82



CHAPTER 3: AI Strategic Roles from Shareholder’s Perspective: When Do AI Announcements Generate Positive and Negative Market Reaction?    83

Abstract    83
Introduction    84
Theoretical Background    88
1 IT Strategic Role Framework    88
2. Organizational Characteristics    93
Methodology    95
1. Data    95
2. Crisp-set Qualitative Comparative Analysis (csQCA)    100
2.1 Methodological Motivation    100
2.2 csQCA procedures    102
3. Variable Operationalization and Calibration    106
3.1 Outcome Variable: CARs    107
3.2 AI Capability Variables: Process Automation, Cognitive Insight, Cognitive Engagement    109
3.3 Organizational characteristics    110
Results    112
1. Configurations for Positive Market Reaction    114
2. Configurations for Negative Market Reaction    118
Robustness Analysis    120
1. Logistic Regression    121
2. Decision Tree    121
3. csQCA with control variables    122
4. csQCA with Time factor    126
Discussion    127
1. Research and Managerial Implications    128
1.1 Research Implications    128
1.2 Managerial Implications    131
2. Limitations and Future Research Directions    132
Conclusion    133


Concluding Remarks    134


References    138


Appendix A: Literature Review on SST    166
Appendix B: Constructs and Measurement Items    169
Appendix C: Theory-based prediction variables    170
Appendix D: Data-driven prediction variables    171
Appendix E: Details of the four Logistic Regression Models    173
Appendix F: Data categorization Examples    174
Appendix G: Industry-breakdown    175
Appendix H: Consistency and Coverage in csQCA    176


                                

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