請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99126完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 簡睿哲 | zh_TW |
| dc.contributor.advisor | Ruey-Jer Jean | en |
| dc.contributor.author | 李英群 | zh_TW |
| dc.contributor.author | YING CHUN LEE | en |
| dc.date.accessioned | 2025-08-21T16:29:19Z | - |
| dc.date.available | 2025-08-22 | - |
| dc.date.copyright | 2025-08-21 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-08-01 | - |
| dc.identifier.citation | Accenture. (2021). How to unleash competitiveness on the cloud continuum. https://www.accenture.com/content/dam/accenture/final/a-com-migration/custom/pdf/Accenture-Unleashing-Competitiveness-On-The-Cloud-Continuum-Slideshare.pdf
Accenture. (2023a). Leading with edge computing. https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Leading-With-Edge-Computing.pdf Al-Dulaimy, A., Jansen, M., Johansson, B., Trivedi, A., Iosup, A., Ashjaei, M., Galletta, A., Kimovski, D., Prodan, R., Tserpes, K., Kousiouris, G., Giannakos, C., Brandic, I., Ali, N., Bondi, A. B., & Papadopoulos, A. V. (2024). The computing continuum: From IoT to the cloud. Internet of Things, 27, 101272. https://doi.org/10.1016/j.iot.2024.101272 Åström, J., Reim, W., & Parida, V. (2022). Value creation and value capture for AI business model innovation: A three-phase process framework. Review of Managerial Science, 16(5), 2111–2133. https://doi.org/10.1007/s11846-022-00521-z Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 Bocken, N. M. P., de Pauw, I., Bakker, C., & van der Grinten, B. (2016). Product design and business model strategies for a circular economy. Journal of Industrial and Production Engineering, 33(5), 308–320. https://doi.org/10.1080/21681015.2016.1172124 Carter, L., Liu, D., & Cantrell, C. (2020). Exploring the intersection of the digital divide and artificial intelligence: A hermeneutic literature review. AIS Transactions on Human-Computer Interaction, 12(4), 253–275. https://doi.org/10.17705/1thci.00138 Costa, C. J., Aparicio, M., Aparicio, S., & Aparicio, J. T. (2024). The democratization of artificial intelligence: Theoretical framework. Applied Sciences, 14(18), 8236. https://doi.org/10.3390/app14188236 Dell Technologies. (2025). Dell APEX. Retrieved July 2025, from https://www.dell.com/en-us/shop/dell-apex-subscription-as-a-service-solutions/sc/apex Deloitte. (2023a). 2023 mid-market technology trends report. https://www.deloitte.com/us/en/services/deloitte-private/articles/technology-trends-middle-market-companies-survey.html Deloitte. (2023b). Digital risk framework: Managing risks in digital ecosystems. Deloitte UK. https://www.deloitte.com/uk/en/services/consulting-risk/services/digital-risk.html Evcenko, D., Kett, H., & Falkner, J. (2023). Equipment as a service – Necessary changes for service-based business models. Human Systems Engineering and Design: Future Trends and Applications, 112, 491–500. https://doi.org/10.54941/ahfe1004162 Forti, V., Baldé, C. P., Kuehr, R., & Bel, G. (2020). The global e-waste monitor 2020: Quantities, flows and the circular economy potential. United Nations University (UNU)/United Nations Institute for Training and Research (UNITAR) – SCYCLE Programme, International Telecommunication Union (ITU), & International Solid Waste Association (ISWA). https://www.itu.int/en/ITU-D/Environment/Documents/Toolbox/GEM_2020_def.pdf Geissdoerfer, M., Savaget, P., Bocken, N. M. P., & Hultink, E. J. (2017). The circular economy – A new sustainability paradigm? Journal of Cleaner Production, 143, 757–768. https://doi.org/10.1016/j.jclepro.2016.12.048 Godofprompt.ai. (2024). DeepSeek’s hidden features professional developers love. https://www.godofprompt.ai/blog/deepseeks-hidden-features-professional-developers-love Grand View Research. (2024). Artificial intelligence as a service market size report, 2030. https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-as-a-service-market-report Grefen, P., Wilbik, A., Kuitems, F., & Blanken, M. (2021). Outcome-based business design in IoT-enabled digital supply chain transformation. In 2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) (pp. 28–34). IEEE. https://doi.org/10.1109/IoTaIS53735.2021.9628770 Hewlett Packard Enterprise. (2024). HPE GreenLake. Retrieved July 2025, from https://www.hpe.com/us/en/greenlake.html IDC. (2024). IDC FutureScape: Worldwide small and medium-sized business 2025 predictions (Report No. US52638024). https://www.idc.com/getdoc.jsp?containerId=US52638024 IDC. (2025a). Worldwide spending on edge computing to reach $261 billion in 2025. https://my.idc.com/getdoc.jsp?containerId=prUS53261225 IDC. (2025b). Worldwide spending on edge computing to approach $378 billion by 2028. https://www.idc.com/getdoc.jsp?containerId=prUS52587424 IDC. (2025c). Global AI and generative AI spending projections. https://info.idc.com/futurescape-generative-ai-2025-predictions.html IDC. (2025d). Semiconductor market outlook: AI supercycle. https://my.idc.com/getdoc.jsp?containerId=US53129625 IDC. (2025e). CIO Playbook 2025: It’s time for AI-nomics (Ebook, commissioned by Lenovo). IDC. https://pages.lenovo.com/rs/183-WCT-620/images/CIO%20Playbook%202025%20-%20Its%20Time%20for%20AI-nomics_February%202025_AP242508IB.pdf Iyelolu, T. V., Agu, E. E., Idemudia, C., & Ijomah, T. I. (2024). Driving SME innovation with AI solutions: Overcoming adoption barriers and future growth opportunities. International Journal of Science and Technology Research Archive, 7(1), 36–54. https://doi.org/10.53771/ijstra.2024.7.1.0055 Kergroach, S., & Héritier, J. (2025). Emerging divides in the transition to artificial intelligence. OECD Regional Development Papers, No. 147. OECD Publishing. https://doi.org/10.1787/7376c776-en Kirchherr, J., Reike, D., & Hekkert, M. (2017). Conceptualizing the circular economy: An analysis of 114 definitions. Resources, Conservation and Recycling, 127, 221–232. https://doi.org/10.1016/j.resconrec.2017.09.005 Lafley, A. G., & Martin, R. L. (2013). Playing to Win: How strategy really works. Harvard Business Review Press. Lenovo. (2024). Lenovo TruScale. Retrieved July 2025, from https://www.lenovo.com/us/en/solutions/truscale/ McKinsey & Company. (2025, March). The state of AI: How organizations are rewiring to capture value. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai Menon, K., Mittal, S., Kärkkäinen, H., & Kuismanen, O. (2022). Systematic steps towards concept design of pay–per-X business models: An exploratory research. In O. Canciglieri Junior, F. Noël, L. Rivest, & A. Bouras (Eds.), Product lifecycle management. Green and blue technologies to support smart and sustainable organizations. PLM 2021 (IFIP Advances in Information and Communication Technology, Vol. 640, pp. 350–360). Springer. https://doi.org/10.1007/978-3-030-94399-8_28 Mohammed, A. L., Kutar, M., & Albakri, M. (2024). Conceptualising the artificial intelligence divide: A systematic literature review and research agenda. In Proceedings of the UK Academy for Information Systems Conference 2024 (Paper 14). https://aisel.aisnet.org/ukais2024/14 Muminova, E., Akhunova, S., Ashurov, M., & Turgunov, M. (2024). AI in small and medium enterprises: Assessing the barriers, benefits, and socioeconomic impacts. In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS) (pp. 1–6). IEEE. https://doi.org/10.1109/ICKECS61492.2024.10616816 Ng, I. C. L., Ding, D. X., & Yip, N. (2013). Outcome-based contracts as new business model: The role of partnership and value-driven relational assets. Industrial Marketing Management, 42(5), 730–743. https://doi.org/10.1016/j.indmarman.2013.05.009 OECD. (2021). The digital transformation of SMEs. OECD Studies on SMEs and Entrepreneurship. OECD Publishing. https://doi.org/10.1787/bdb9256a-en Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. John Wiley & Sons. Pickton, D. W., & Wright, S. (1998). What’s SWOT in strategic analysis? Strategic Change, 7(2), 101–109. https://doi.org/10.1002/(SICI)1099-1697(199803/04)7:2<101::AID-JSC332>3.0.CO;2-6 Porter, M. E. (1979). How competitive forces shape strategy. Harvard Business Review, 57(2), 137–145. Schwaeke, J., Peters, A., Kanbach, D. K., Kraus, S., & Jones, P. (2024). The new normal: The status quo of AI adoption in SMEs. Journal of Small Business Management, 63(3), 1297–1331. https://doi.org/10.1080/00472778.2024.2379999 Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. arXiv preprint. https://arxiv.org/abs/1906.02243 Taheri, J., Dustdar, S., Zomaya, A., & Deng, S. (2023). Edge intelligence: From theory to practice. Springer. https://doi.org/10.1007/978-3-031-22155-2 Tse, B., Hartwich, F., & Slater, J. (2024, August). AI readiness: What industries in developing countries can do. UNIDO Industrial Analytics Platform. https://iap.unido.org/articles/ai-readiness Van Eck, M., & Leenhouts, E. (2014). The one page business strategy: Streamline your business plan in four simple steps. Pearson Education. Wang, X., Han, Y., Leung, V. C. M., Niyato, D., Yan, X., & Chen, X. (2020). Edge AI: Convergence of edge computing and artificial intelligence. Springer. https://doi.org/10.1007/978-981-15-6186-3 Weihrich, H. (1982). The TOWS matrix—A tool for situational analysis. Long Range Planning, 15(2), 54–66. https://doi.org/10.1016/0024-6301(82)90120-0 Yusuf, S. O., Durodola, R. L., Ocran, G., Abubakar, J. E., Echere, A. Z., & Paul-Adeleye, A. H. (2024). Challenges and opportunities in AI and digital transformation for SMEs: A cross-continental perspective. World Journal of Advanced Research and Reviews, 23(3), 668–678. https://doi.org/10.30574/wjarr.2024.23.3.2511 Zavodna, L. S., Überwimmer, M., & Frankus, E. (2024). Barriers to the implementation of artificial intelligence in small and medium-sized enterprises: Pilot study. Journal of Economics & Management, 46, 331–352. https://doi.org/10.22367/jem.2024.46.13 Zhou, Z., Chen, X., Li, E., Zeng, L., Luo, K., & Zhang, J. (2019). Edge intelligence: Paving the last mile of artificial intelligence with edge computing. Proceedings of the IEEE, 107(8), 1738–1762. https://doi.org/10.1109/JPROC.2019.2918951 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99126 | - |
| dc.description.abstract | 隨著數位轉型加速，製造、零售、物流及能源領域的中小企業面臨採用邊緣人工智慧(Edge AI)的重大障礙，包括高成本、技術複雜性及專業知識不足。這些挑戰加深了AI落差，限制了中小企業在快速數位化經濟中的競爭力。本論文提出「Edgino」，一個以諮詢為導向的邊緣人工智慧服務提供者，透過三大關鍵策略克服上述障礙：採用成果導向的定價機制，依據可量化的商業成效計算費用，有效降低財務風險；運用翻新硬體與循環經濟原則推動永續經營，兼顧成本控制與環境保護；並提供靈活的硬體選擇與諮詢整合，結合預先驗證的垂直產業專屬AI套件，簡化部署流程並加速價值實現。透過涵蓋市場趨勢、商業模式、策略定位及財務可行性的綜合分析，本研究證明Edgino的可擴展、永續發展方法如何有效解決中小企業在技術與財務上的限制，同時融入環境、社會及治理（ESG）價值。Edgino協助中小企業釋放邊緣AI的變革潛力，促進符合永續發展的包容性數位轉型。最終，Edgino為未充分覆蓋的中小企業市場，提供彌合AI落差的實踐方案，結合成果導向的獲利模式、深度諮詢專業及循環經濟理念，創造持久的商業與社會價值。 | zh_TW |
| dc.description.abstract | As digital transformation accelerates, Small and Medium-sized Businesses (SMBs) in manufacturing, retail, logistics, and energy face significant barriers to adopting Edge AI, including high costs, technical complexity, and limited expertise. These challenges deepen the AI divide, limiting SMBs’ competitiveness in a rapidly digitizing economy. This thesis introduces Edgino, a consultative Edge AI service provider designed to overcome these obstacles through three core pillars: outcome-based pricing that links payment to measurable business results, reducing financial risk; sustainability-driven operations leveraging refurbished hardware and circular economy principles to lower costs and environmental impact; and vendor-agnostic, consultative integration with pre-validated, industry-specific AI bundles that simplify deployment and accelerate time-to-value. Through a comprehensive analysis covering market trends, business models, strategic positioning, and financial feasibility, this research demonstrates how Edgino’s scalable, sustainable approach addresses SMBs’ technological and financial constraints while embedding environmental, social, and governance (ESG) values. By enabling SMBs to unlock AI’s transformative potential at the edge, Edgino fosters inclusive digital transformation aligned with sustainability. Ultimately, Edgino offers a blueprint for bridging the AI divide in underserved SMB markets by combining outcome-driven monetization, deep consultative expertise, and circular economy principles to create lasting business and societal value. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-08-21T16:29:19Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-08-21T16:29:19Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgement i
執行摘要 ii Executive Summary iii Table of Contents iv List of Figures vi List of Tables vii List of Abbreviations viii 1. Business Description 1 1.1 Background & Industry Problem 1 1.2 Bridging the AI Divide: An Outcome-Based Edge AI Service Model 3 1.3 Research Objectives & Approach 6 2. Literature Review 8 2.1 Introduction 8 2.2 From Edge Computing to Edge AI: Evolution and Convergence 8 2.3 Emergence of the Computing Continuum and Hybrid AI 10 2.4 Shift to Outcome-Based and As-a-Service Models 12 2.5 Growing Pressure of Sustainable Innovation 15 2.6 AI Divide and Democratization of AI 17 2.7 Analytical Frameworks and Tools 20 2.8 Market and Research Gaps 21 3. Market & Industry Analysis 24 3.1 Industry Trends and Technology Adoption 24 3.2 Market Opportunity for Edgino 28 3.3 Competitive Landscape 32 3.4 Strategic Environment Analysis 34 3.5 SWOT Analysis 45 3.6 Integrated Strategic Implications 47 4. Business Model & Value Delivery Strategy 49 4.1 Value Proposition 49 4.2 Revenue Model 52 4.3 Business Model Canvas 53 4.4 Strategic Resources & VRIN Analysis 55 4.5 Competitive Differentiation 60 5. Go-To-Market and Execution Strategy 63 5.1 Target Customer Segmentation & Persona Development 63 5.2 Market Entry Strategy 64 5.3 Partner Ecosystem Strategy 65 5.4 Sales & Marketing Strategy 68 5.5 Service Delivery & Technology Infrastructure 69 5.6 Talent Strategy 69 5.7 Execution Risks and Mitigation 70 5.8 Strategic Execution Recap 72 6. Financial Feasibility & Expected Outcomes 73 6.1 Revenue Projections & Milestones 73 6.2 Cost Structure & Operating Requirements 75 6.3 Funding Plan & Use of Capital 77 6.4 Financial Projections and Profitability Outlook 77 6.5 Validation Metrics & Scaling Path 83 6.6 Investment Case Summary & Financial Implications 84 7. Strategic Execution and Future Outlook 85 7.1 Strategic Analysis and Option Development: TOWS Matrix 85 7.2 From Strategy to Action: OGSM Framework for Execution 87 7.3 Future Outlook and Market Trends 93 7.4 Risk Assessment and Implications 95 7.5 Risk Mitigation Strategies 101 7.6 Concluding Remarks and Strategic Summary 107 Reference 110 Appendix A: Target Customer Personas 117 Appendix B: Service Level Agreements (SLAs) and Quality Assurance Details 120 Appendix C: Technical Specifications of Edgino’s Edge AI Platform 122 | - |
| dc.language.iso | en | - |
| dc.subject | 邊緣人工智慧 | zh_TW |
| dc.subject | 中小企業 | zh_TW |
| dc.subject | 成果導向定價 | zh_TW |
| dc.subject | 循環經濟 | zh_TW |
| dc.subject | 永續發展 | zh_TW |
| dc.subject | 數位轉型 | zh_TW |
| dc.subject | Outcome-Based Pricing | en |
| dc.subject | Edge AI | en |
| dc.subject | Digital Transformation | en |
| dc.subject | Sustainability | en |
| dc.subject | Circular Economy | en |
| dc.subject | SMBs | en |
| dc.title | Edgino 商業計畫：透過成果導向與永續商業模式普及邊緣人工智慧 | zh_TW |
| dc.title | Edgino’s Business Plan: Democratizing Edge AI via an Outcome-Based and Sustainable Business Model | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 堯里昂;許耀文 | zh_TW |
| dc.contributor.oralexamcommittee | Leon van Jaarsveldt;Yao-Wen Hsu | en |
| dc.subject.keyword | 邊緣人工智慧,中小企業,成果導向定價,循環經濟,永續發展,數位轉型, | zh_TW |
| dc.subject.keyword | Edge AI,SMBs,Outcome-Based Pricing,Circular Economy,Sustainability,Digital Transformation, | en |
| dc.relation.page | 123 | - |
| dc.identifier.doi | 10.6342/NTU202502971 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2025-08-05 | - |
| dc.contributor.author-college | 管理學院 | - |
| dc.contributor.author-dept | 企業管理碩士專班 | - |
| dc.date.embargo-lift | N/A | - |
| 顯示於系所單位： | 管理學院企業管理專班(Global MBA) | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-113-2.pdf 未授權公開取用 | 2.14 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。