A Study on Emerging Technology Identification Methodology Using Text Mining Techniques : Focusing on Unmanned Aerial Vehicle R＆D
- 주제(키워드) UAV innovation , Emerging technology , Text mining , National innovation systems , Adaptive R＆D governance
- 주제(DDC) 352.745
- 발행기관 아주대학교 일반대학원
- 지도교수 Min Jae Park
- 발행년도 2026
- 학위수여년월 2026. 8
- 학위명 박사
- 학과 및 전공 일반대학원 과학기술정책학과
- 실제URI http://www.dcollection.net/handler/ajou/000000036511
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
Over the past two decades, innovation in Unmanned Aerial Vehicles （UAVs） has undergone rapid transformation driven by advances in artificial intelligence, autonomous systems, and evolving geopolitical and societal demands. Despite the growing strategic importance of UAV technologies, limited attention has been given to how national R＆D systems adapt to external shocks, how structural lag emerges within innovation systems, and how technological recombination shapes emerging technological trajectories under conditions of geopolitical uncertainty. Based on 8,523 government-funded R＆D projects conducted between 2005 and 2025, this dissertation examines the evolution and structural adaptation of UAV-related technologies within South Korea’s national R＆D system. A two-stage analytical framework is developed to capture both the temporal evolution and structural convergence of technologies. In the first stage, dynamic topic modeling and recombination analysis are employed to identify temporal topic shifts, delayed adaptation patterns, and emerging technological recombination. In the second stage, network-based structural analysis is conducted to examine technological connectivity, mediating roles, and strategic positioning within the UAV innovation ecosystem. Through this integrated analytical framework, the dissertation explains how national innovation systems adapt to geopolitical uncertainty through delayed technological recombination and structural convergence. The findings reveal that major geopolitical and societal shocks—including the 2014 North Korean UAV incident, the COVID-19 pandemic, and the Russia–Ukraine war—are associated with significant shifts in national R＆D agendas, although these responses exhibit measurable temporal delays reflecting institutional and structural inertia. Furthermore, emerging UAV technologies were found to evolve primarily through delayed recombination among existing technological domains rather than through immediate disruptive transformation, with AI-based technologies functioning as key mediating technologies facilitating cross-domain recombination among previously separated technological domains within the UAV innovation ecosystem. These results suggest that the critical challenge for national innovation systems lies not merely in technological development itself, but in strengthening the institutional and governance capabilities required to enable rapid cross-domain technological recombination under conditions of geopolitical uncertainty. In this regard, the dissertation provides policy implications for adaptive R＆D governance and strategic technology planning aimed at enhancing national technological adaptation capabilities within emerging technology systems. Keywords: UAV innovation, Emerging technology, Text mining, National innovation systems, Adaptive R＆D governance
more목차
Chapter1. Introduction 1
1.1 Background and Motivation 1
1.2 Research Gap and Problem Statement 3
1.3 Research Purpose 4
1.4 Contributions 5
1.5 Research Scope 5
Chapter2. Theoretical Background 8
2.1 Evolution of UAV Technologies and Drivers of Diffusion 8
2.2 Geopolitical Shocks, Techno-Nationalism, and Adaptive Governance 9
2.3 Technological Recombination and Structural Adaptation under Institutional Constraints 10
2.4 Mission-Oriented Technological Systems and Network-Based Structural Perspectives 12
2.5 The Korean National Innovation System and the Need for Adaptive Governance 14
2.6 Hypotheses Development 16
Chapter3. Methodology 17
3.1 Overall Analytical Framework 17
3.1.1 Stage 1. Technology Evolution and Recombination Framework 18
3.1.2 Stage 2. Structural Convergence and Strategic Positioning Framework 20
3.2 Data Collection and Preprocessing 21
3.3 Stage 1: Technology Evolution and Recombination Analysis 24
3.3.1 LDA-Based Topic Identification 25
3.3.2 Dynamic Topic Modeling 26
3.3.3 Recombination Analysis 28
3.3.4 Event Alignment and Temporal Lag Estimation 30
3.4 Stage 2: Technology Network and Structural Analysis 31
3.4.1 Network Analysis 31
3.4.2 Structural Analysis 33
3.5 Complementary Interpretive Validation 34
3.6 Robustness Checks 36
Chapter4. Results 37
4.1 Temporal Evolution and Structural Adaptation Lag 37
4.1.1 Identification of UAV Technological Domains 37
4.1.2 Temporal Topic Concentration and Transition 39
4.1.3 Dynamic Topic Evolution and Structural Adaptation Lag 41
4.2 Recombination Dynamics and Structural Convergence 43
4.2.1 Semantic Convergence and Intertopic Structure 45
4.2.2 Recombination and Integration Potential 47
4.3 Bridge Technologies and Strategic Positioning within the UAV Innovation System 51
4.3.1 Network Connectivity and Centrality Structure 52
4.3.2 Bridge Technologies and Structural Mediation 56
4.3.3 Strategic Positioning within the UAV Innovation Ecosystem 61
4.4 Integrated Interpretation of Adaptation Mechanisms 66
4.5 Evaluation of Hypotheses and Structural Robustness 69
4.5.1 Structural Adaptation Lag under Geopolitical and Societal Shocks （H1） 69
4.5.2 Recombination-Driven Technological Adaptation （H2） 70
4.5.3 Robustness Test 71
Chapter5. Discussion 74
5.1 Structural Adaptation Lag in Korea's National R＆D System 74
5.2 Recombination-Based Technological Adaptation under Geopolitical Uncertainty 76
5.3 Asymmetric Adaptation across Technological Domains 78
5.4 Adaptive Governance under Geopolitical Uncertainty: Strengthening Recombination Capacity, Flexibility, and Ecosystem Agility 80
5.5 Limitations and Future Research 82
Chapter6. Conclusion 84
6.1 Summary of Findings 84
6.2 Theoretical Contributions 85
6.3 Policy Implications 86
6.4 Final Remarks 88
Reference 89
Appendix 94
