博碩士論文 110423058 詳細資訊




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姓名 李宜駿(I-Chun Lee)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 影響組織人工智慧準備度的因素: TOE 模型和資訊科技警覺留神
(Factors Affecting AI-Readiness in Organization: The TOE Model and IT Mindfulness)
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摘要(中) 人工智慧之研究與應用的快速增長為組織帶來了機會和挑戰,自 2015 年以來人工
智慧相關的出版刊物增長了 2.5 倍,超過 80%的公司表示未來可能會導入人工智慧。人
工智慧的多樣性和複雜性使組織必須全面了解並選擇合適的技術。組織變革準備度理論
強調了成功導入人工智慧所需的準備工作,而人工智慧的導入需要更高的技術專業知識
和資源。本研究旨在探討影響人工智慧準備度的因素,並使用技術-組織-環境(TOE)模
型和創新擴散(DOI)理論,以及研究資訊科技警覺留神在人工智慧準備度中的作用。資
訊科技警覺留神作為一個具有四個維度的動態特質,影響著組織的人工智慧準備度並對
導入人工智慧至關重要。研究目標包括檢驗 TOE 因素對人工智慧準備度的正向影響,並
將資訊科技警覺留神納入 TOE 模型中。本研究旨在為人工智慧導入過程提供方針,並有
助於理解影響人工智慧準備度的因素。回答這些研究問題將有助於更深入地了解組織中
人工智慧導入所面臨的挑戰和機會。
摘要(英) The rapid growth of Artificial Intelligence (AI) research and adoption offers opportunities
and challenges for organizations, with AI publications increasing 2.5 times since 2015 and over
80% of companies likely to incorporate AI. The diverse scope and complexity of AI require
organizations to develop a thorough understanding and select suitable technologies.
Organizational Readiness for Change theory highlights the importance of preparedness for
successful AI adoption, which demands higher technical expertise and resources. This study
aims to explore factors influencing AI adoption using the Technology-OrganizationEnvironment (TOE) model and the Diffusion of Innovation (DOI) theory and examine the role
of organizational mindfulness in AI-readiness. IT mindfulness, a dynamic trait with four
dimensions, is essential for successful AI adoption. The research objectives involve examining
the positive effects of TOE factors on AI readiness, integrating IT Mindfulness into the TOE
framework, and identifying the components of organizational readiness for AI. The study aims
to provide guidance for the AI adoption process and contribute to the understanding of factors
influencing AI readiness. Addressing these research questions will contribute to a deeper
understanding of the challenges and opportunities associated with AI adoption in organizations.
關鍵字(中) ★ 人工智慧
★ 導入
★ 技術-組織-環境模型
★ 創新擴散
★ 訊科技警覺留神
關鍵字(英) ★ Artificial Intelligence
★ Adoption
★ Technology-Organization-Environment Model
★ Diffusion of Innovation
★ IT Mindfulness
論文目次 摘要 i
Abstract ii
致謝 iii
Contents iii
List of Figures vi
List of Tables vii
1. Introduction 1
1.1 Research Background and Motivations 1
1.2 Research Objectives and Questions 4
2、Literature review 5
2.1 Mindfulness 5
2.1.1 Individual Mindfulness 5
2.1.2 Organizational Mindfulness 5
2.1.3 IT Mindfulness 6
2.2 Artificial Intelligence in Organization 9
2.2.1 Innovation and Technology Adoption 10
2.2.2 Organizational Readiness for Change 10
3. Research Framework and Hypotheses 13
3.1. Research Framework 13
3.2. Research Hypotheses 15
3.2.1. Effect of Technological Readiness on AI-readiness 15
3.2.2. Effect of Organizational Readiness on AI-readiness 16
3.2.3. Effect of Environmental Readiness on AI-readiness 17
3.2.4. Effect of IT Mindfulness on AI-readiness 18
4. Research Methodology 21
4.1 Sample Selection and Data Collection 21
4.2 Operationalization of Constructs 21
4.2.1 IT Mindfulness 23
4.2.2 Relative Advantage 24
4.2.3 Compatibility 25
4.2.4 Top Management Support 26
4.2.5 Competitive Pressure 27
4.2.6 Favorable Government Regulations 27
4.2.7 AI-readiness 28
4.3 Control Variables 29
4.4 Marker Variables 30
4.5 Research Procedures 31
5. Data Analysis and Result 32
5.1 Response Rate 32
5.2 Descriptive Statistics 33
5.3 Measurement Model 37
5.3.1 Examination of Second-Order Construct 37
5.3.2 Reliability and Validity 39
5.3.3 Common Method Bias 45
5.4 Structural Model 47
5.4.1. Assessing Structural Model 47
5.4.2. PLS Results of Hypothesis Testing 48
5.4.3 Robustness Analysis 49
6. Conclusions 51
6.1 Findings and Discussions 51
6.2. Theoretical Contributions and Managerial Implications 54
6.3. Limitations and Future Research 56
Reference 58
Appendix A 65
參考文獻 Aboelmaged, M. G. (2014). Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. International Journal of Information Management, 34(5), 639-651.
Al-Dmour, R. (2014). An integration model for identifying the determinants of the adoption and implementation level of HRIS applications and Its effectiveness in business organisations in Jordan.
Alshawi, M. (2007). Rethinking IT in Construction and Engineering: Organisational Readiness. Taylor & Francis.
Alsheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. PACIS, 4, 231-245.
Alsheibani, S., Messom, C., & Cheung, Y. (2020). Re-thinking the competitive landscape of artificial intelligence.
Armenakis, A. A., Harris, S. G., & Mossholder, K. W. (1993). Creating readiness for organizational change. Human Relations, 46(6), 681-703.
Baier, L., Jöhren, F., & Seebacher, S. (2019). Challenges in the Deployment and Operation of Machine Learning in Practice. ECIS, Vol. 1.
Baker, J. (2012). The technology–organization–environment framework. Information Systems Theory: Explaining and Predicting Our Digital Society, Vol. 1, 231-245.
Brown, K. W., Ryan, R. M., & Creswell, J. D. (2007). Mindfulness: Theoretical foundations and evidence for its salutary effects. Psychological Inquiry, 18(4), 211-237.
Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlstrom, P., Henke, N., & Trench, M. (2017). Artificial intelligence: The next digital frontier? McKinsey and Company Global Institute.
Chen, X., Chang-Richards, A., Ling, F. Y. Y., Yiu, T. W., Pelosi, A., & Yang, N. (2023). Developing a readiness model and a self-assessment tool for adopting digital technologies in construction organizations. Building Research & Information, 51(3), 241-256.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34(3), 555-590.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
De Souzabido, D., & Da Silva, D. (2019). SMARTPLS 3: SPECIFICATION, ESTIMATION, EVALUATION AND REPORTING. Administração: Ensino e Pesquisa–RAEP, 20(2), 465-514.
Dennis, A. R., Fuller, R. M., & Valacich, J. S. (2008). Media, tasks, and communication processes: A theory of media synchronicity. MIS Quarterly, 575-600.
DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 147-160.
Duan, X., Deng, H., & Corbitt, B. (2010). A critical analysis of e-market adoption in Australian small and medium sized enterprises.
Fast, E., & Horvitz, E. (2017). Long-term trends in the public perception of artificial intelligence. Proceedings of the AAAI conference on artificial intelligence, Vol. 31, No. 1
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Fraher, A. L., Branicki, L. J., & Grint, K. (2017). Mindfulness in action: Discovering how US Navy Seals build capacity for mindfulness in high-reliability organizations (HROs). Academy of Management Discoveries, 3(3), 239-261.
Ghobakhloo, M., Arias‐Aranda, D., & Benitez‐Amado, J. (2011). Adoption of e‐commerce applications in SMEs. Industrial Management & Data Systems.
Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
Hede, A. (2010). The dynamics of mindfulness in managing emotions and stress. Journal of Management Development, 29(1), 94-110.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New Challenges to International Marketing. Emerald Group Publishing Limited.
Iacovou, C. L., Benbasat, I., & Dexter, A. S. (1995). Electronic data interchange and small organizations: Adoption and impact of technology. MIS Quarterly, 465-485.
Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI: Strategy and leadership when algorithms and networks run the world. Harvard Business Press.
IBM. (2022). IBM Global AI Adoption Index 2022.
Ifinedo, P. (2005). Measuring Africa′s e-readiness in the global networked economy: A nine-country data analysis. International Journal of Education and Development using ICT, 1(1), 53-71.
Ifinedo, P. (2011). An empirical analysis of factors influencing Internet/e-business technologies adoption by SMEs in Canada. International Journal of Information Technology & Decision Making, 10(04), 731-766.
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes—an interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63, 5-20.
Kumar, K. N., Chandra, S., Bharati, S., & Manava, S. (2016). Factors Influencing Adoption of Augmented Reality Technology for E-Commerce. PACIS,
Langer, E. J. (1989). Mindfulness. Addison-Wesley/Addison Wesley Longman.
Langer, E. J. (2009). Counterclockwise: Mindful Health and the Power of Possibility. Ballantine Books.
Leroy, H., Anseel, F., Dimitrova, N. G., & Sels, L. (2013). Mindfulness, authentic functioning, and work engagement: A growth modeling approach. Journal of Vocational Behavior, 82(3), 238-247.
Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management & Data Systems.
Matt, C., Hess, T., & Benlian, A. (2015). Digital transformation strategies. Business & Information Systems Engineering, 57, 339-343.
Molla, A., Cooper, V. A., & Pittayachawan, S. (2009). IT and eco-sustainability: Developing and validating a green IT readiness model. ICIS 2009 proceedings, 141.
Molla, A., & Licker, P. S. (2005). eCommerce adoption in developing countries: a model and instrument. Information & Management, 42(6), 877-899.
Najdawi, A. (2020). Assessing AI readiness across organizations: The case of UAE. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 1-5.
Ndubisi, N. O. (2012). Mindfulness, reliability, pre-emptive conflict handling, customer orientation and outcomes in Malaysia′s healthcare sector. Journal of Business Research, 65(4), 537-546.
Nosova, S., Norkina, A., Medvedeva, O., Abramov, A., Makar, S., Lozik, N., & Fadeicheva, G. (2021). Artificial intelligence technology as an economic accelerator of business process. Biologically Inspired Cognitive Architectures Meeting, (pp. 355-366).
Ocasio, W. (2011). Attention to attention. Organization Science, 22(5), 1286-1296.
Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. Electronic Journal of Information Systems Evaluation, 14(1), pp110‑121-pp110‑121.
Pickert, K. (2014). The mindful revolution. TIME Magazine, 3(2014), 2163560-2163561.
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539-569.
Porter, M. E. (2008). The five competitive forces that shape strategy. Harvard Business Review, 86(1), 78.
Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
Premkumar, G., & Ramamurthy, K. (1995). The role of interorganizational and organizational factors on the decision mode for adoption of interorganizational systems. Decision Sciences, 26(3), 303-336.
Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467-484.
Purdy, M., & Daugherty, P. (2016). Why Artificial Intelligence is the Future of Growth. Accenture Institute for High Performance.
Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192-210.
Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2017). Reshaping business with artificial intelligence: Closing the gap between ambition and action. MIT Sloan Management Review, 59(1).
Ray, J. L., Baker, L. T., & Plowman, D. A. (2011). Organizational mindfulness in business schools. Academy of management Learning & Education, 10(2), 188-203.
Rerup, C. (2005). Learning from past experience: Footnotes on mindfulness and habitual entrepreneurship. Scandinavian Journal of Management, 21(4), 451-472.
Richey, R. G., Daugherty, P. J., & Roath, A. S. (2007). Firm technological readiness and complementarity: capabilities impacting logistics service competency and performance. Journal of Business Logistics, 28(1), 195-228.
Rogers, E. M. (1983). Diffusion of Innovations 3rd edition. Free Press.
Snyder-Halpern, R. (2001). Indicators of organizational readiness for clinical information technology/systems innovation: a Delphi study. International Journal of Medical Informatics, 63(3), 179-204.
Soluk, J., Kammerlander, N., & Darwin, S. (2021). Digital entrepreneurship in developing countries: The role of institutional voids. Technological Forecasting and Social Change, 170, 120876.
Stark, L., & Crawford, K. (2015). The conservatism of emoji: Work, affect, and communication. Social Media+ Society, 1(2), 2056305115604853.
Sternberg, R. J. (2000). Images of mindfulness. Journal of Social Issues, 56(1), 11-26.
Sun, H. (2011). Making sound adoption decisions: A longitudinal study of mindfulness in technology adoption and continued use. ICIS 2011 proceedings, HCI(2).
Sun, H. (2012). Understanding user revisions when using information system features: Adaptive system use and triggers. MIS Quarterly, 453-478.
Sutcliffe, K. M., Vogus, T. J., & Dane, E. (2016). Mindfulness in organizations: A cross-level review. Annual Review of Organizational Psychology and Organizational Behavior, 3, 55-81.
Tadavarthi, Y., Makeeva, V., Wagstaff, W., Zhan, H., Podlasek, A., Bhatia, N., Heilbrun, M., Krupinski, E., Safdar, N., & Banerjee, I. (2022). Overview of noninterpretive artificial intelligence models for safety, quality, workflow, and education applications in radiology practice. Radiology: Artificial Intelligence, 4(2), e210114.
Teece, D. J. (2010). Technological innovation and the theory of the firm: the role of enterprise-level knowledge, complementarities, and (dynamic) capabilities. In Handbook of the Economics of Innovation (Vol. 1, pp. 679-730). Elsevier.
Teo, T. S., Lim, G. S., & Fedric, S. A. (2007). The adoption and diffusion of human resources information systems in Singapore. Asia Pacific Journal of Human Resources, 45(1), 44-62.
Thatcher, J. B., Wright, R. T., Sun, H., Zagenczyk, T. J., & Klein, R. (2018). Mindfulness in information technology use: Definitions, distinctions, and a new measure. MIS Quarterly, 42(3), 831-848.
Thiesse, F., Staake, T., Schmitt, P., & Fleisch, E. (2011). The rise of the “next‐generation bar code”: an international RFID adoption study. Supply Chain Management: An International Journal, 16(5), 328-345.
Thong, J. Y. (1999). An integrated model of information systems adoption in small businesses. Journal of Management Information Systems, 15(4), 187-214.
Aldrich, H. E., & Pfeffer, J. (1976). Environments of organizations. Annual Review of Sociology, 2(1), 79-105
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478.
Wade, M., & Hulland, J. (2004). Review: The resource-based view and information systems research: Review, extension, and suggestions for future research. MIS Quarterly, 107-142.
Weick, K. E., & Sutcliffe, K. M. (2001). Managing the unexpected (Vol. 9). San Francisco: Jossey-Bass.
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (1999). Organizing for high reliability: Processes of collective mindfulness. In Research in Organizational Behavior, Vol. 21. (pp. 81-123). Elsevier Science/JAI Press.
Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(1), 1-9.
Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model. Computers in Human Behavior, 45, 254-264.
Zhai, C. (2010). Research on post-adoption behavior of B2B e-marketplace in China. 2010 International Conference on Management and Service Science, Wuhan, China, 2010, pp. 1-5.
Zhang, D. T., Maslej, N., Brynjolfsson, E., Etchemendy, J., Lyons, T., Manyika, J., Ngo, H., Niebles, J. C., Sellitto, M., Sakhaee, E., Shoham, Y., Clark, J., & Perrault, R. (2022). The AI Index 2022 Annual Report. ArXiv, abs/2205.03468.
Zhang, J., & Wu, C. (2014). The influence of dispositional mindfulness on safety behaviors: A dual process perspective. Accident Analysis & Prevention, 70, 24-32.
Zhu, K., Kraemer, K., & Xu, S. (2003). Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors. European Journal of Information Systems, 12, 251-268.
Zhu, K., & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information Systems Research, 16(1), 61-84.
Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business. Management Science, 52(10), 1557-1576.
指導教授 王存國(Tswen-Gwo Wang) 審核日期 2023-7-20
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