International Political Economy: Investment & Finance, 2026
This essay explores the transformation of the nation-state into an Operating System (OS) within t... more This essay explores the transformation of the nation-state into an Operating System (OS) within the context of digital globalization. It argues that the digitalization of institutions, technologies, and even human consciousness and desires may lead to unprecedented confusion and risks. By employing strong metaphors such as "digital massacre" and "invisible empire", the essay warns of the dangers of unchecked digital expansion. It emphasizes that preemptive measures and institutional safeguards are essential to prevent such a society from materializing. The analysis highlights the emergence of virtual citizenship, the codification of digital rights, the mechanisms of soft colonization through code, monopolization via network effects, and the invisible war over data sovereignty. Ultimately, the essay positions the OS-based nation as both a guarantor of trust and a potential site of extreme power concentration, calling for urgent scholarly and policy debate.
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Papers by Sungduck Lee
This dialogue between Lee and Copilot highlights how the On-Site Adaptive Innovation theory connects past strategies with present challenges. It emphasizes industrialization as the backbone, convergence as reinforcement, and national R&D systems as the framework for emergent innovation.
To overcome market stagnation, the study revisits evolutionary strategies such as developing "killer applications" for early market entry and the "Robot Inside" modular platform strategy, which aimed to standardize core technologies like vision, mobility, and control. The paper also highlights the role of contest-based R&D, such as robot soccer, in fostering real-time decision-making and multi-robot collaboration.
Finally, the research explores the convergence of abstract intelligence (LLMs) and physical manipulation into Embodied AI. It addresses critical engineering requirements for humanoids—including on-device LLM implementation, low-power neuromorphic computing, and autonomic nervous system design—to transition robots from machines performing predefined tasks into autonomous intelligent agents capable of coexisting with humans.
Within this trajectory, Onsite Adaptive Innovation (OAI) presents a new paradigm in which humans and artificial intelligence jointly transform tacit knowledge into explicit knowledge and solve problems in real time. This essay weaves together modular architecture theory, embedded software, the essence of convergence, OAI innovation theory, and the metaphor of the nation as OS, to reflect simultaneously on innovation and structural risks in the digital age.
This study synthesizes a theoretical framework established through the author's series of prior works (2025). It first builds the theoretical foundation of OAI by tracing the genealogy of firm theories and identifying their evolution toward OAI (The Genealogy of Firm Theories and the Development Toward On-site Adaptive Innovation), while clarifying the concepts of field adaptivity and hybrid complex-modular characteristics (Clarification of On-site Adaptivity and Hybrid Complex-Modular Characteristics).
Furthermore, this paper empirically applies this theoretical framework to cutting-edge industries. It analyzes the core dynamics of the semiconductor industry in the AI era, focusing on co-evolution and regime-disruptive substitution (In the Age of AI, Core Dynamics of the Semiconductor Industry...), and demonstrates the mechanism of intelligent assetization through the application of the OAI framework to the robotics industry (On-site Adaptive Innovation Framework Applied to the Robotics Industry). In particular, it derives policy implications by presenting a strategic model for securing leadership in the intelligent industrial robotics sector (Strategic Model for Securing Korea’s Leadership in Intelligent Industrial Robotics).
In conclusion, this paper proclaims OAI as a new paradigm for complex systems (On-site Adaptive Innovation: A New Paradigm for Complex Systems) and redefines the rationale for the firm's existence—from "cost minimization" to "adaptive orchestration under field conditions." This provides essential theoretical and practical guidelines for securing dominance in the contemporary industrial landscape.
Drawing insights from the semiconductor industry—particularly the collapse of NVIDIA’s CUDA-centered regime due to chiplet architecture, packaging, and vertical integration—the study highlights the transition of leadership from design-centric actors to those with manufacturing and integration capabilities. Applying this dynamic to robotics, the paper identifies AI middleware as the central nervous system that integrates fragmented modular innovations and transforms upper-level systems.
The analysis outlines three dominant business models in the Physical AI era: the Platform Specialization Model, the Vertical Integration Model, and the Specialized Cooperation Model, which together evolve into a Multipolar System. To secure leadership, the study proposes strategies including open middleware standardization, contest-based R&D and modular libraries, an open-closed IP governance model, and dual standardization strategies for platforms.
The findings suggest that future competitiveness in robotics will depend not on superior standalone technologies but on integration capabilities and adaptivity at the system level. Institutionalizing these strategies through open consortium governance and IP management is identified as the next critical step for embedding on-site adaptive innovation into industrial regimes.
The semiconductor industry exemplifies this paradigm. NVIDIA’s CUDA-centered regime has achieved co-evolutionary stability, yet regime-disrupting substitution is emerging through the centrality of packaging, the strategic transformation of memory firms, and the expansion of vertical integration by Big Tech. These dynamics convey the core message of shifting innovation actors (from designers to integrators), transforming innovation goals (from peak performance to field optimization), and expanding innovation methods (from internal knowledge changes to real-time integration of heterogeneous modules).
Furthermore, the paper distinguishes itself from Henderson and Clark’s innovation typology. While the latter focuses on changes in product knowledge and component linkages, On-site Adaptive Innovation highlights field responsiveness and systemic integration. Future refinement requires precise conceptual definitions, empirical validation across diverse industries, and exploration of policy and strategic implications, thereby advancing the theory into a generalized paradigm with both academic and practical contributions.
Drawing on insights from complex product systems (CoPS) and modular innovation studies, this framework identifies three core elements: (1) the shift from maximum performance to optimal adaptability, (2) the rise of integration capabilities as a source of strategic advantage, and (3) the disruptive reallocation of industrial leadership. Case studies in semiconductor chiplet architectures, modular humanoid robotics, and AI ecosystems illustrate how integration-driven adaptability reshapes competitive dynamics.
The paper further explores strategic implications for national R&D systems, including modular architecture design, standardized technology libraries, and intellectual property differentiation. By bridging theory, industry practice, and policy design, On-site Adaptive Innovation contributes to innovation studies by offering a comprehensive lens to understand and guide technological leadership in the era of complex, interconnected systems.