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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 堯里昂 | zh_TW |
| dc.contributor.advisor | Leon van Jaarsveldt | en |
| dc.contributor.author | 梶谷良德 | zh_TW |
| dc.contributor.author | Yoshinori Kajitani | en |
| dc.date.accessioned | 2025-07-23T16:36:47Z | - |
| dc.date.available | 2025-07-24 | - |
| dc.date.copyright | 2025-07-23 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-07-17 | - |
| dc.identifier.citation | Ministry of Internal Affairs and Communications. (2021). White Paper on Information and Communications in Japan 2021. https://www.soumu.go.jp/johotsusintokei/whitepaper/ja/r03/html/nd112220.html
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DX report—Overcoming the "2025 cliff" of IT systems and the full-fledged deployment of DX. Digital Transformation Study Group, METI. https://www.meti.go.jp/shingikai/mono_info_service/digital_transformation/pdf/20180907_03.pdf Information-technology Promotion Agency, Japan. (2023, December). DX Promotion Index and its Guidance. https://www.ipa.go.jp/digital/dx-suishin/ug65p90000001j8i-att/dx-suishin-guidance.pdf Kasahara, K. (2023, March 23). Generative AI has an impact comparable to the advent of the iPhone and will bridge the digital divide, says NVIDIA CEO Jensen Huang. PC Watch. https://pc.watch.impress.co.jp/docs/news/1487685.html McKinsey & Company. (2023, June). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/the%20economic%20potential%20of%20generative%20ai%20the%20next%20productivity%20frontier/the-economic-potential-of-generative-ai-the-next-productivity-frontier.pdf McKinsey & Company. (2023, June). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/the%20economic%20potential%20of%20generative%20ai%20the%20next%20productivity%20frontier/the-economic-potential-of-generative-ai-the-next-productivity-frontier.pdf McKinsey & Company. (2023, June). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/the%20economic%20potential%20of%20generative%20ai%20the%20next%20productivity%20frontier/the-economic-potential-of-generative-ai-the-next-productivity-frontier.pdf United Nations Development Programme. (2019). UNDP Digital Strategy 2019. https://digitalstrategy.undp.org/documents/UNDP-digital-strategy-2019.pdf Tavos, F. (2023). Survive and thrive in the digital age: A growth study of digital transformation in Japan's small and medium-sized enterprises (SMEs), KTH Royal Institute of Technology]. DiVA Portal. https://www.diva-portal.org/smash/get/diva2:1856748/FULLTEXT01.pdf IPA, Japan. (2024, June 27). DX Trends 2024. https://www.ipa.go.jp/digital/chousa/dx-trend/eid2eo0000002cs5-att/dx-trend-2024.pdf Khare, A., Ishikura, H., & Baber, W. W. (Eds.). (2019). Transforming Japanese Business: Rising to the Digital Challenge (Future of Business and Finance). Springer Singapore. https://doi.org/10.1007/978-981-15-0327-6 Okada, K. (2023, November). Promotion of DX by SMEs is the key to revival of the Japanese economy. Meiji.net. https://english-meiji.net/articles/4461/ Moriguchi, Y. (2023, January 16). How to support SMEs in promoting DX: Enhancing equality of opportunity, efficiency, and effectiveness (Research Focus No. 2022‑053). Japan Research Institute. https://www.jri.co.jp/page.jsp?id=104310 Kobayashi, K. (2021). A consideration on the issues of Japan's ICT policy as seen in "DX Report 2". Gendai Shakai Kenkyu (Contemporary Social Research), 19, 55–64. Hofstede Insights. (n.d.). Uncertainty avoidance (UAI) — Hofstede’s 6 dimension model of national culture. Retrieved June 13, 2025, from https://hofstede.jp/6dimentionsmodel_uai/ Matsunaga, M. (2024). Employee uncertainty over digital transformation: Mechanisms and solutions. Springer. https://doi.org/10.1007/978-981-99-8409-1 Dash, B., Sharma, P., & Swayamsiddha, S. (2023). Organizational digital transformations and the importance of assessing theoretical frameworks such as TAM, TTF, and UTAUT: A review. International Journal of Advanced Computer Science and Applications, 14(2), 1–6. https://doi.org/10.14569/IJACSA.2023.0140201 Ismail, M. N., Jameel, S. H., Saeed, A. M., Al-Zeyadi, B. K. A., Salman, S. M., Dakov, S. S. Y., & Ali, H. (2024, November). Investigating three digital transformation theories: TAM, TTF, and UTAUT. Proceedings of the 36th Conference of Open Innovations Association FRUCT. https://www.fruct.org/publications/volume-36/fruct36/files/Nut1.pdf Small and Medium Enterprise Agency. (n.d.). Definitions of small and medium enterprises and small businesses [Web page]. Retrieved June 1, 2025, from https://www.chusho.meti.go.jp/soshiki/teigi.html Ministry of Economy, Trade and Industry, Small and Medium Enterprise Agency. (2024, May). 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98054 | - |
| dc.description.abstract | 本研究旨在釐清日本中小企業在推動數位轉型(DX)政策方面的現況與挑戰,並在日本數位競爭力落後與生成式人工智慧(GenAI)快速發展、作為DX潛在突破技術的背景下,提出具體的優化建議。特別是,本研究針對數位競爭力排名領先的新加坡與臺灣,從多面向分析其對中小企業的DX支援政策之內容、成效與制度背景。
研究方法包括文獻回顧、國際統計資料的比較分析、政策文件的檢視,並輔以對日本經濟產業省(METI)官員的半結構式訪談,以納入實務層面的政策執行情況。分析架構則從「政策設計」、「執行體系」及「成果對齊」三個面向切入,並輔以UTAUT作為補充的分析框架。 研究主要發現指出,日本中小企業在DX進展遲緩的原因,並非僅限於技術層面,而是受到企業文化、對不確定性的迴避傾向、以及組織與心理因素等深層影響。相對而言,新加坡與臺灣透過政府主導的戰略性、整合性支援措施,例如明確劃分產業領域的轉型路線圖、以及一站式的支援平台,有效提升了中小企業的數位成熟度。 基於上述分析,本研究提出以下四點政策建議,以促進日本中小企業的DX政策優化:(1)建立日本式的一站式支援體系;(2)強化重視質性面的實地輔導支援;(3)明確制定有策略性且具體的GenAI導入支援措施;(4)提升政策評估的透明度與客觀性。 本研究有助於補足日本在DX政策方面的國際比較研究空白,並提供具實證性與實務參考價值的政策意涵。 | zh_TW |
| dc.description.abstract | This study aims to clarify the current state and challenges of digital transformation (DX) policies for SMEs in Japan and to derive practical insights for their optimization, against the backdrop of Japan’s lagging digital competitiveness and the rapid advancement of generative AI (GenAI) as a potential breakthrough technology for DX. In particular, the study conducts a multifaceted analysis of the content, effectiveness, and institutional background of DX support policies for SMEs in Singapore and Taiwan—two countries that rank high in digital competitiveness.
The research methodology includes a literature review, comparative analysis of international statistics, and examination of policy documents, supplemented by a semi-structured interview with a policy officer from Japan’s Ministry of Economy, Trade and Industry (METI), thereby incorporating practical aspects of policy implementation. The analysis is structured around three perspectives: “policy design,” “implementation structure,” and “alignment of outcomes,” with the UTAUT theory utilized as a supplementary analytical framework. The main findings reveal that the delay in DX among Japanese SMEs is not solely due to technological limitations but is also heavily influenced by corporate culture, uncertainty avoidance tendencies, and organizational and psychological factors. In contrast, in Singapore and Taiwan, strategic and comprehensive government-led support measures—such as clearly defined sector-specific roadmaps and one-stop support platforms—have had a significant positive impact on improving the digital maturity of SMEs. Based on these findings, the study presents several policy recommendations for improving DX policies for SMEs in Japan, including: (1) the establishment of a Japanese-style one-stop support system; (2) the enhancement of hands-on support focusing on qualitative aspects; (3) the clarification of strategic and concrete support measures for the adoption of GenAI; and (4) the improvement of transparency and objectivity in policy evaluation. This study contributes to filling the gap in international comparative research on Japan’s DX policies, providing empirical and practically relevant implications for policymaking. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-07-23T16:36:47Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-07-23T16:36:47Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgment ii
Abstract iii Table of Contents vii List of Tables and Figures ix List of Abbreviations x 1. Introduction 1 1.1 Background and Context 1 1.2 Problem Statement 3 1.3 Research Aims and Objectives 8 1.4 Structure of the Thesis 9 2. Background 11 2.1 Definition and Conceptual Overview of DX 11 2.2 The Rise of GenAI and Its Interrelationship with DX 18 2.3 Clarification of Concepts Related to DX 20 2.4 Definition of DX in This Study 21 3. Literature Review 23 3.1 Existing Research on DX and SME Policy 23 3.2 Cultural Barriers to DX in Japanese SMEs 26 3.3 Theoretical Framework 29 4. Methodology 33 4.1 Research Design and Approach 33 4.2 Selection and Validity of Countries for Comparison 33 4.3 Research Procedures and Analytical Process 34 4.4 Expected Academic and Policy Contributions 37 5. Comparative Analysis of SME DX Context and Policies 39 5.1 Digital Competitiveness Benchmarking 39 5.2 DX Landscape and Policy Frameworks by Country 43 5.3 Cross-National Comparative Analysis and Key Insights 75 5.4 Key Insights 82 6. Policy Recommendations 87 6.1 Development of a Japan-Style One-Stop DX Support Platform 87 6.2 Designing Effective Financial Support 90 6.3 Deepening Accompaniment Support Focused on Qualitative Aspects 91 6.4 Strategic and Concrete Support for GenAI 93 6.5 Improving Transparency and Objectivity in Policy Evaluation 94 6.6 Enhancing Private Sector-Led and Industry-Collaborative Support Systems 95 7. Conclusion and Limitations 99 7.1 Conclusion 99 7.2 Limitations and Future Research Directions 102 Appendix: Interview Question for Japanese Policymakers 105 References 109 | - |
| dc.language.iso | en | - |
| dc.subject | 數位競爭力 | zh_TW |
| dc.subject | 中小企業 | zh_TW |
| dc.subject | 生成式人工智慧 | zh_TW |
| dc.subject | 政策比較分析 | zh_TW |
| dc.subject | UTAUT | zh_TW |
| dc.subject | 日本 | zh_TW |
| dc.subject | 新加坡 | zh_TW |
| dc.subject | 臺灣 | zh_TW |
| dc.subject | 數位轉型 | zh_TW |
| dc.subject | Taiwan | en |
| dc.subject | Digital Transformation (DX) | en |
| dc.subject | Digital Competitiveness | en |
| dc.subject | Small and Medium-sized Enterprises (SMEs) | en |
| dc.subject | Generative AI (GenAI) | en |
| dc.subject | Comparative Policy Analysis | en |
| dc.subject | UTAUT (Unified Theory of Acceptance and Use of Technology) | en |
| dc.subject | Japan | en |
| dc.subject | Singapore | en |
| dc.title | 生成式AI時代的日本中小企業數位轉型政策:新加坡與台灣的案例比較與實證分析 | zh_TW |
| dc.title | Digital Transformation Policies for Japanese SMEs in the Generative AI Era: A Comparative and Empirical Study of Singapore and Taiwan | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 鄭名道;張佳欽 | zh_TW |
| dc.contributor.oralexamcommittee | MingDaw Cheng;Charles Zhang | en |
| dc.subject.keyword | 數位轉型,數位競爭力,中小企業,生成式人工智慧,政策比較分析,UTAUT,日本,新加坡,臺灣, | zh_TW |
| dc.subject.keyword | Digital Transformation (DX),Digital Competitiveness,Small and Medium-sized Enterprises (SMEs),Generative AI (GenAI),Comparative Policy Analysis,UTAUT (Unified Theory of Acceptance and Use of Technology),Japan,Singapore,Taiwan, | en |
| dc.relation.page | 119 | - |
| dc.identifier.doi | 10.6342/NTU202501743 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2025-07-20 | - |
| dc.contributor.author-college | 管理學院 | - |
| dc.contributor.author-dept | 企業管理碩士專班 | - |
| dc.date.embargo-lift | 2030-07-11 | - |
| 顯示於系所單位: | 管理學院企業管理專班(Global MBA) | |
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