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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃明蕙(Ming-Hui Huang) | |
| dc.contributor.author | Chiong Wei Thia | en |
| dc.contributor.author | 程章偉 | zh_TW |
| dc.date.accessioned | 2021-06-16T16:13:35Z | - |
| dc.date.available | 2020-06-09 | |
| dc.date.copyright | 2020-06-09 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-05-28 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/62883 | - |
| dc.description.abstract | AI is getting more pervasive in the business context across the world. Survey results have shown that 47% of the companies have implemented at least one AI capability in their business processes in the year 2018; an increase of almost 27% compared to the preceding year. Even so, most of them are incapable of quantifying the impact of these investments and measuring return is a problem. In addition, companies that have not yet adopted AI in their respective organization at scale or in a core facet of their business are unsure of a business case for AI implementation. These stakeholders are lacking of a standardized methodology to justify the value that AI could possibly bring about for them.
Thus, this paper aims to evaluate the impact of AI on 17 business KPIs across three digitization levels. The relationship between business KPIs and ROI of AI was examined as well leading to the development of the AIRI Measurement Model and its framework at the later stage of this study. Statistical tools such Mean Value Ranking, One Sample t-test and Spearman’s Rank Correlation Coefficient test were conducted on 120 samples to validate the five hypotheses made in this study. Generalizing the results gathered, this research has proven that AI is able to improve business KPIs which are deemed to be highly important to the companies. Coupled with the AIRI Measurement Model, it would potentially help to boost the AI Value and Perception and consequently, increasing AI adoption rate in the process. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T16:13:35Z (GMT). No. of bitstreams: 1 ntu-109-R07749042-1.pdf: 3631733 bytes, checksum: da3c1d596e314096fd1ce26e0ac8801b (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | Master Thesis Certification by Oral Defense Committee i
Acknowledgement ii Abstract iii Table of Contents iv List of Figures ix List of Tables xii List of Abbreviations xvi CHAPTER 1: INTRODUCTION 1 1.1 Background 1 1.2 AI in Modern Business Context 2 1.3 AI Adoption for Business from Singapore and Taiwan Context 4 1.3.1 AI Adoption in Singapore 4 1.3.2 AI Adoption in Taiwan 5 1.4 Research Problem 7 1.5 Research Aims and Objectives 9 1.6 Research Hypothesis 10 1.7 Research Scope 11 1.8 Research Methodology 12 1.9 Structure of Thesis 13 CHAPTER 2: LITERATURE REVIEW I – ARTIFICIAL INTELLIGENCE (AI) 16 2.1 Overview of Chapter 16 2.2 Definitions 16 2.3 AI in Depth 17 2.3.1 AI at Different Level of Intelligence 19 2.3.2 Technologies behind AI 22 2.4 Application of AI across Business Functions 25 2.5 Benefits of AI 28 2.6 Enablers of AI 31 2.6.1 Advancement of IT Infrastructure and Computer Technology 31 2.6.2 Increasing Awareness for AI Implementation 32 2.7 Barriers to Implementation of AI 34 2.8 Chapter Summary 35 CHAPTER 3: LITERATURE REVIEW II – RETURN ON INVESTMENT (ROI) OF ARTIFICIAL INTELLIGENCE (AI) WITHIN BUSINESSES 36 3.1 Overview of Chapter 36 3.2 ROI in General 36 3.3 Challenges to determine ROI of AI Adoption 38 3.4 Recommended ways to determine ROI of AI Adoption 39 3.4.1 Estimation of ROI for ML and DS Projects 39 3.4.2 ROI of AI Bot (ROAI) 41 3.4.3 ROI of AI Applications in Human Resource (HR) 43 3.5 Relationship between ROI of AI and Business KPIs 45 3.6 Chapter Summary 47 CHAPTER 4: LITERATURE REVIEW III – THE KEY PERFORMANCE INDICATORS (KPIS) ACROSS BUSINESSES 48 4.1 Overview of Chapter 48 4.2 Definition of KPIs 48 4.3 Business KPIs vs Low-level KPIs 49 4.3.1 Business KPIs 49 4.3.2 Low-level KPIs 50 4.4 Four Perspectives of developing KPIs 51 4.4.1 Financial Perspectives 52 4.4.2 Customer Perspectives 53 4.4.3 Internal Business Process Perspectives 54 4.4.4 Organizational Learning and Growth Perspectives 55 4.5 Other KPIs to consider 55 4.5.1 Risk Management 56 4.5.2 Health and Safety Management 56 4.6 Chapter Summary 57 CHAPTER 5: RESEARCH METHODOLOGY 59 5.1 Overview of Chapter 59 5.2 Overall Research Design 59 5.3 Data Collection Methods and Aims 62 5.3.1 Survey Questionnaire 62 5.3.1.1 Survey Questionnaire Design 63 5.3.1.2 Sampling 65 5.3.2 Interviews 65 5.4 Data Analysis Methodology 66 5.4.1 Descriptive Analysis 68 5.4.2 Mean Value Ranking 68 5.4.3 One-Sample t-test 69 5.4.4 Spearman’s Rank Correlation Coefficient 70 5.4.5 Weight Factor 70 5.5 Chapter Summary 71 CHAPTER 6: DEMOGRAPHICS OF RESPONDENTS AND INTERVIEWEES 72 6.1 Overview of Chapter 72 6.2 Survey Questionnaire Response 72 6.2.1 Profile of Respondents 75 6.2.2 Profile of Respondents’ Companies 77 6.3 Interviews 79 6.3.1 Profile of Interviewee 80 6.4 Chapter Summary 80 CHAPTER 7: RESEARCH ANALYSIS 81 7.1 Overview of Chapter 81 7.2 High Digitization Industries 81 7.2.1 Ranking of Importance of KPIs 81 7.2.2 AI’s Impact on Business KPIs across High Digitization Industries 84 7.2.3 AI’s Overall Impact on Business KPIs across High Digitization Industries 88 7.2.4 Overall Conclusion for High Digitization Industries 89 7.3 Medium Digitization Industries 89 7.3.1 Ranking of Importance of KPIs 90 7.3.2 AI’s Impact on Business KPIs across Medium Digitization Industries 92 7.3.3 AI’s Overall Impact on Business KPIs across Medium Digitization Industries 95 7.3.4 Overall Conclusion for Medium Digitization Industries 95 7.4 Low Digitization Industries 96 7.4.1 Ranking of Importance of KPIs 96 7.4.2 AI’s Impact on Business KPIs across Low Digitization Industries 99 7.4.3 AI’s Overall Impact on Business KPIs across Low Digitization Industries 102 7.4.4 Overall Conclusion for Low Digitization Industries 102 7.5 Overall Impact of AI on Business KPIs 103 7.5.1 Ranking of Importance of KPIs 103 7.5.2 AI’s Impact on Business KPIs in Overall 105 7.5.3 AI’s Overall Impact on Business KPIs 108 7.5.4 Overall Conclusion 108 7.6 Relationship between Business KPIs and ROI of AI 110 7.6.1 Contributions to ROI of AI 110 7.7 Key Points from the Interview 113 7.7.1 Interviewee’s Experiences with AI 113 7.7.2 Company’s Implementation of AI 114 7.7.3 Key Barriers to Implementation of AI 115 7.7.4 ROI of AI 116 7.7.5 Opinions Pertaining to the Impact of AI on Business KPIs 116 7.7.6 Views Regarding the Future Prospects of AI 117 7.8 Chapter Summary 118 CHAPTER 8: PROPOSED MODEL AND FRAMEWORK 120 8.1 Overview of Chapter 120 8.2 AI ROI Index (AIRI) 120 8.3 Proposed Framework 122 8.3.1 Decision Making 123 8.3.2 AI Implementation 124 8.3.3 AI Assessment 124 8.4 Validation of Framework 127 8.5 Chapter Summary 128 CHAPTER 9: CONCLUSIONS AND RECOMMENDATIONS 129 9.1 Review of Aims and Objectives 129 9.2 Summary of Research Analysis 130 9.3 Summary of Research Deliverables 130 9.4 Limitations of Research 131 9.5 Recommendations for Future Studies 132 Bibliography 133 Appendix A 139 Appendix B 150 | |
| dc.language.iso | en | |
| dc.subject | 人工智慧 | zh_TW |
| dc.subject | 投資報酬率 | zh_TW |
| dc.subject | Key Performance Indicators (KPIs) | en |
| dc.subject | AI ROI Index (AIRI) | en |
| dc.subject | Artificial Intelligence (AI) | en |
| dc.subject | Return on Investment (ROI) | en |
| dc.title | 人工智慧的投資報酬率 - 探討人工智慧的導入對關鍵績效指標的影響 | zh_TW |
| dc.title | Return on Investment (ROI) of Artificial Intelligence (AI) – Impact of AI on Business Key Performance Indicators (KPIs) | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 王存國(T.G. Wang Eric),張瑋倫(Wei-Lun Chang) | |
| dc.subject.keyword | 人工智慧,投資報酬率, | zh_TW |
| dc.subject.keyword | Artificial Intelligence (AI),Key Performance Indicators (KPIs),Return on Investment (ROI),AI ROI Index (AIRI), | en |
| dc.relation.page | 151 | |
| dc.identifier.doi | 10.6342/NTU202000842 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-05-29 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 企業管理碩士專班 | zh_TW |
| 顯示於系所單位： | 管理學院企業管理專班(Global MBA) | |
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