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研究生： 許栢宗
Shiu, Bo-Zong
論文名稱： 生成式AI在木質文創產品產業之影響探討: 以產業生態系為視角
Exploring the Impact of Generative AI on Wooden-based Cultural and Creative Product Industry: An Industry Ecosystem Perspective
指導教授： 楊佳翰
Yang, Chia-Han
學位類別： 博士
Doctor
系所名稱： 規劃與設計學院 - 創意產業設計研究所
Institute of Creative Industries Design
論文出版年： 2025
畢業學年度： 113
語文別： 英文
論文頁數： 357
中文關鍵詞： 生成式人工智慧 、木質文化創意產業 、產業生態系 、人機協同設計 、設計流程
外文關鍵詞： Generative Artificial Intelligence, Wooden Cultural and Creative Industry, Industrial Ecosystem, Human-AI Collaborative Design, Design Process
相關次數： 點閱：22  下載：2 
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    • 本研究旨在深入探討生成式人工智慧（Generative AI, GAI）對臺灣木質文化創意產品產業（Wooden Cultural and Creative Industry, WCCI）生態系的系統性影響。臺灣WCCI以其獨特工藝價值與深厚文化底蘊為核心，然此特質亦形成效率與市場反應速度的發展瓶頸，呈現「工藝悖論」。GAI的崛起，以其自動化內容生成能力，為此困境帶來顛覆性契機。然學界對GAI之研究多集中於數位產業，對WCCI這類具高度「物質性」與「工藝性」的領域影響探討甚少。本研究旨在彌補此缺口，系統性地剖析GAI對臺灣WCCI生態系的衝擊。研究目的包含：(一) 檢視AI導入前之產業生態系現況；(二) 探討GAI在設計與生產流程中的應用模式、效益與挑戰；(三) 分析GAI如何重塑產業生態系結構、價值共創機制與人才需求，並提出永續發展策略。
    本研究採「探索式循序混合研究法」（Exploratory Sequential Mixed Methods Design）。質性階段以臺灣木質文創品牌「東瑭DongTang」為深度個案，輔以十位產業專家（含設計師、製造商、學者）之半結構式訪談、焦點團體與參與觀察，以深入探討現象；量化階段則透過116份有效問卷進行普遍性驗證，並以比較實驗客觀量測AI導入之效益。此多重資料來源的三角驗證，確保了研究發現的信度與效度。
    研究發現，GAI對產業帶來雙重影響。在效益方面，顯著提升效率與創意，比較實驗證實AI輔助可將設計階段工時縮短43%，總體專案時程減少26%；個案公司亦在導入後半年內拓展逾20個新銷售通路。然而，挑戰亦不容忽視，高達87.1%的受訪者指出AI生成內容的「準確性與品質不穩定」為首要挑戰，尤其在生成可製造的複雜結構（如榫卯）上仍有技術瓶頸；其次為「法律與倫理風險」（31.9%），特別是著作權歸屬不明的問題；此外，設計同質化與市場競爭加劇（86.2%）亦是普遍憂慮。
    本研究結論指出，GAI不僅是工具，更是重塑產業生態系的催化劑。其影響體現在：(一) 專業角色的再定義，促使傳統設計師轉型為「增強型設計師」（Augmented Designer），並賦予消費者能力成為「共同創作者」（Co-creating Consumer）；(二) 價值網絡的重組，傳統線性價值鏈轉向多方互動的網絡，AI平台成為新權力核心；(三) 新興商業模式的催生，特別是「大規模客製化」（Mass Customization）成為可能。本研究不僅填補了特定工藝產業受AI衝擊的學術空白，亦為產業、教育與政策制定者提供了應對變革的實務藍圖。

    This research conducts an in-depth investigation into the systemic impact of Generative Artificial Intelligence (GAI) on the ecosystem of Taiwan's Wooden Cultural and Creative Industry (WCCI). The Taiwanese WCCI is characterized by its unique craft value and profound cultural heritage; however, these same qualities have created developmental bottlenecks in efficiency and market responsiveness, presenting a "craftsmanship paradox." The ascent of GAI, with its capacity for automated content generation, offers a disruptive opportunity to address this predicament. Nevertheless, academic inquiry into GAI has predominantly focused on digital industries, with scant exploration of its effects on sectors with high degrees of "materiality" and "craftsmanship" like the WCCI. This study aims to bridge this research gap by systematically analyzing the impact of GAI on the Taiwanese WCCI ecosystem. The research objectives are: (1) to examine the state of the industry's ecosystem prior to AI adoption; (2) to investigate the application models, benefits, and challenges of GAI in design and production processes; and (3) to analyze how GAI reshapes the industry's ecosystem structure, value co-creation mechanisms, and talent requirements, culminating in the proposal of sustainable development strategies.
    This study employs an Exploratory Sequential Mixed Methods Design. The qualitative phase features an in-depth case study of the Taiwanese wooden cultural and creative brand "東堂DongTang", supplemented by semi-structured interviews with ten industry experts (including designers, manufacturers, and academics), focus groups, and participant observation to thoroughly explore the phenomenon. The quantitative phase then utilizes 116 valid questionnaire responses for generalizable verification, coupled with a comparative experiment to objectively measure the benefits of AI implementation. This triangulation of multiple data sources ensures the reliability and validity of the research findings.
    The findings indicate that GAI exerts a dual influence on the industry. In terms of benefits, it significantly enhances efficiency and creativity. The comparative experiment confirmed that AI assistance can reduce work hours in the design phase by 43% and shorten the overall project timeline by 26%. Furthermore, the case study company expanded to over 20 new sales channels within six months of implementation. However, the challenges are equally significant. A substantial 87.1% of respondents identified the "instability of accuracy and quality" of AI-generated content as the primary challenge, particularly the technical bottlenecks in generating manufacturable complex structures, such as mortise and tenon joints. This was followed by "legal and ethical risks" (31.9%), especially concerning the ambiguity of copyright ownership. Additionally, design homogenization and intensified market competition (86.2%) are widespread concerns.
    This research concludes that GAI is not merely a tool but a catalyst for reshaping the industry's ecosystem. Its impact is manifested in: (1) the redefinition of professional roles, compelling traditional designers to transform into "Augmented Designers" and empowering consumers to become "Co-creating Consumers"; (2) the restructuring of the value network, shifting the traditional linear value chain towards a multi-agent interactive network where AI platforms become the new locus of power; and (3) the emergence of new business models, particularly making "Mass Customization" a viable possibility. This study not only fills the academic void concerning the impact of AI on a specific craft-based industry but also provides a practical blueprint for industry, education, and policymakers to navigate this transformative change.

    摘要 I Abstract III LIST OF FIGURES VIII LIST OF TABLES X CHAPTER 1. INTRODUCTION 1 1.1 Research motivation and background 1 1.2 Research Motivation 5 1.2.1 Academy motivation 5 1.2.2 Industry Motivation 9 1.2.3 Individual Motivation 14 1.3 Research Objectives 19 1.4 Research Questions 22 1.5 Research Target 23 1.6 Research Scope and Delimitation 26 1.7 Research Flow 27 1.8 Key Terminology and Concepts 28 CHAPTER 2. LITERATURE REVIEW 30 2.1 Introduction 30 2.2 The Wooden Cultural and Creative Industry: Characteristics, Challenges, and Innovation Needs 31 2.2.1 The Connotation of the Cultural and Creative Industry and Its Developmental Context in Taiwan 31 2.2.2 The Uniqueness and Application of Wooden Materials in Cultural and Creative Products 32 2.2.3 The Impact of the Maker Spirit and Customization Trends on the Wooden Cultural and Creative Industry 38 2.2.4 Key Challenges and Transformational Opportunities for the Wooden Cultural and Creative Industry (Before the Emergence of Generative AI) 41 2.3 Generative Artificial Intelligence: Technological Evolution and Its Empowerment in the Field of Creative Design 43 2.3.1 The Developmental Trajectory from Artificial Intelligence to Generative AI 43 2.3.2 The Diverse Applications and Potential of Generative AI in the Creative Industries 47 2.3.3 Application of Generative AI in the New Product Development Process 53 2.3.4 Benefits, Ethical Challenges, and Limitations of Generative AI in Creative Design 62 2.4 Industrial Ecosystem Theory: An Integrative Analytical Perspective 67 2.4.1 The Origins and Core Concepts of Ecosystem Theory 67 2.4.2 The Value of the Industrial Ecosystem Perspective in Researching Technological Innovation and Industrial Transformation 73 2.4.3 Preliminary Construction of the Ecosystem of Taiwan’s Wood-Based Cultural and Creative Industries (Pre AI) 75 2.4.4 Typical Interaction Patterns and Value Flow Mechanisms (Prior to AI Adoption) 76 2.4.5 Preliminary Observations and Key Challenges from the Ecosystem Perspective 77 2.5 Literature Summary and Research Gap 79 2.5.1 Synthesis: The Potential Impact of Generative AI on the Transformation of the Wood-Based Cultural and Creative Industry Ecosystem 79 2.5.2 Summary 81 CHAPTER 3. RESEARCH DESIGN 83 3.1 Research Framework 83 3.2 Introduction to the Case Study Background 90 3.2.1 Case Company Selection 90 3.2.2 Selection Criteria 90 3.2.3 Case Background 91 3.2.4 Basic Product Development Process of the Case Study 102 3.3 Research Methods 107 3.3.1 Case Study Method 107 3.3.2 Focus Group Interview 108 3.3.3 Participant Observation 108 3.3.4 Comparative Experiment 109 3.3.5 Expert Interview 109 3.3.6 Survey Research 110 3.4 Data Collection and Data Analysis 110 3.4.1 Reliability and Validity 112 3.4.2 Reliability and Validity Testing for Quantitative Data 112 3.4.3 Strategies for Enhancing Overall Research Validity 113 CHAPTER 4. RESEARCH RESULTS 114 4.1 Data Sources and Collection Overview 115 4.1.1 Data Collection Methods and Procedures 116 4.1.2 Research Subjects and Sample Distribution 119 4.2 Case Study Analysis: DongTang International Co., Ltd. (DongTang) 126 4.2.1 Company Background and AI Adoption Process 127 4.2.2 AI Applications in Each Process (Focus Group) 129 4.3 Qualitative Data Analysis: In-depth Interview Results 132 4.3.1 Industry Status Before AI Adoption: Structural Challenges and Development Dilemmas 133 4.3.2 Characteristics and Bottlenecks of Traditional Design and Production Processes 136 4.3.3 Application Models and Process Restructuring of Generative AI 137 4.3.4 Perceived Benefits and Empirical Evidence of AI Adoption 142 4.3.5 Challenges, Risks, and Ethical Dilemmas in Applying AI 145 4.3.6 Transformation of Professional Roles and the Core Competencies of Future Talent 148 4.4 Main Data Analysis: Quantitative Data Analysis (Online Questionnaire) 151 4.4.1 Expert Review and Pilot Testing 151 4.4.2 Questionnaire Distribution and Collection Process 151 4.4.3 Reliability and Validity Testing 153 4.4.4Sample Structure and Demographic Characteristics 154 4.4.5 Analysis of Generative AI Awareness 156 4.4.6 Practical Application of Generative AI: Current Status Analysis 158 4.4.7 Perceived Benefits and Impacts of Generative AI 162 4.4.8 Analysis of the Impact of Generative AI Applications 167 4.4.9 Cross-Tabulation Results: Comparative Analysis among Groups with Different Backgrounds 177 4.4.10 Comparison by Organizational Size 183 4.4.11 Regional, Age, and Gender Differences 184 4.5 Comparative Case Experiment on AI-Assisted Design Process 185 4.5.1 Experimental Motivation and Objectives 186 4.5.2 Experimental Case and Research Participants 186 4.5.3 Definition of Workflow 188 4.5.4 Time Measurement Methods 189 4.6 Process Comparison Results 190 4.6.1 Concept Generation Stage: Iterative Effects of Multimodal Prompts 197 4.6.2 Structural Development Stage: Human-AI Collaborative “Dual-Layer Validation” Mechanism 198 4.6.3 Unfolded Drawings and Six-Sided Views: Reducing Structural Design Friction 199 4.6.4 Comparison of Time Allocation: Traditional Design vs. AI-Assisted Design 199 4.7 Observation and Comparison of Design Outcome Quality 201 4.7.1 Efficiency Analysis 202 4.7.2 Quality Observation 203 4.7.3 Redefining the Division of Labor Between Humans and AI 203 4.7.4 Limitations 203 4.8 Summary 204 CHAPTER 5. FINDINGS 205 5.1 Pre‑AI Industry Ecosystem: The Status Quo (Addressing RO1) 205 5.1.1 Historical Evolution and Current Developmental Features of Taiwan’s Wood-Based Cultural and Creative Products Industry (Addressing RQ1.1) 206 5.1.2 Typical Design Processes and Production Models for New Products in the Wood-Based Cultural-Creative Industry Prior to AI Adoption (Addressing RQ1.2) 208 5.1.3 Ecosystem Structure and Value Flow in Taiwan’s Wood-Based Cultural-Creative Industry Prior to AI Adoption (Addressing RQ1.3) 210 5.2 Current Applications and Challenges of Generative AI (Addressing RO2) 213 5.2.1 Patterns and Prevalence of Generative AI Adoption 213 5.2.2 Key Benefits of Generative AI Adoption 216 5.2.3 Principal Challenges in the Adoption of Generative AI 218 5.3 Changes in the Industrial Ecosystem and Strategic Directions (Addressing RO3) 221 5.3.1 Reshaping Relationships and Interaction Mechanisms within the Industrial Ecosystem 221 5.3.2 Emergence of New Business Models 223 5.3.3 Impacts on Industry Structure and Competitive Dynamics 225 5.3.4 Changing Roles of Stakeholders 226 5.3.5 Transformation of Core Competencies for Professionals 229 5.4 Integrated findings 233 CHAPTER 6. DISCUSSION AND CONCLUSION 236 6.1 The Craftsmanship Paradox: Industry Conditions and Structural Tensions Prior to AI Adoption 236 6.2 Catalyst for Transformation: Generative AI Enters the Creative Process 238 6.3 A New Industrial Ecosystem: An AI-Driven Transformation Blueprint 240 6.4 Navigating New Frontiers: The Duality of Opportunities and Challenges 243 6.5 Future Professionals: A New Core Competency Matrix 244 6.6 Research Contributions and Strategic Implications 245 6.7 Research Limitations and Directions for Future Research 247 6.8 Conclusion 249 REFERENCE 250 APPENDIX A. EXPERT INTERVIEW QUESTIONNAIRE 256 APPENDIX B. EXPERT CODE REFERENCE TABLE 258 APPENDIX C. INTERVIEW TRANSCRIPT COMPILATION 259 APPENDIX E. ONLINE QUESTIONNAIRE SURVEY 333

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