KJCKorea
Journal Central

The structural transformation of the power industry—decarbonization, decentralization, and electrification—demands a paradigm shift in electricity network regulation from a traditional cost-recovery model to a Performance-Based Regulation (PBR) framework focused on value creation. This study analyzes the UK's RIIO (Revenue = Incentives + Innovation + Outputs) model from the perspective of regulatory design to derive policy implications for reforming Korea's power grid regulation. To this end, this study systematically examines the RIIO model through four analytical frameworks: (1) long-term investment incentives, (2) a total expenditure (TOTEX) approach, (3) output-reward linkages (ODI), and (4) innovation stimuli. The analysis reveals that RIIO has achieved significant outcomes in institutionalizing energy transition by shifting the regulatory focus from inputs to outputs, thereby mitigating CAPEX bias and fostering innovation. However, limitations identified during its operation—such as excess profits and information asymmetry—demonstrate that the success of PBR depends not merely on adoption but on the precision of parameter calibration and the analytical capacity of the regulator. In conclusion, this study suggests that Korea's electricity network regulation must evolve beyond simple cost compensation into a dynamic framework. This transition requires aligning incentive structures with policy objectives and continuously refining the system based on operational feedback.

This study empirically examines how national digital capacity and government capacity influence the development of the artificial intelligence (AI) environment under varying levels of Digital Product Market Regulation (Digital PMR). While previous studies have primarily focused on the direct effects of regulatory intensity, this study adopts a regulatory governance perspective to investigate how AI environments are shaped through the interaction between Digital PMR and national capacities. Using panel data from OECD countries covering the period 2020–2024, a mixed-effects model was employed for empirical analysis. Data Representativeness and AI Infrastructure were used as dependent variables. Digital Capacity and Government Capacity were included as independent variables, while Digital PMR served as the moderating variable. The results indicate that higher levels of Digital PMR are negatively associated with both Data Representativeness and AI Infrastructure. However, the interaction between Digital PMR and Government Capacity significantly affects both dimensions of the AI environment. In addition, the interaction between Digital Capacity and Digital PMR has a significant effect on AI Infrastructure but does not significantly influence Data Representativeness. These findings suggest that the effects of national policy implementation capacity and digital administrative capacity on AI environment development vary depending on the level of digital market regulation. Furthermore, this study highlights the need to understand regulation in emerging technology sectors not merely as a constraint but as a governance mechanism that interacts with national capacities to shape AI development outcomes.

This study investigates how configurations of the regulatory environment and entrepreneurial ecosystem are associated with high levels of Total Early-Stage Entrepreneurial Activity (TEA). Using 2024 Global Entrepreneurship Monitor (GEM) data from 51 countries, this study employs fuzzy-set Qualitative Comparative Analysis (fsQCA). The results demonstrate that no single condition constitutes a necessary condition for high TEA. Instead, high entrepreneurial activity emerges through multiple configurations of ecosystem conditions. The regulatory environment does not operate as an independent sufficient condition but is associated with high TEA when combined with favorable financial and policy support and entrepreneurial education. Furthermore, the configurations linked to high TEA differ between high-income and non-high-income countries, suggesting that entrepreneurial activity is shaped by distinct national contexts. These findings show the importance of understanding entrepreneurship through the interaction of ecosystem conditions rather than through regulatory reform alone, highlighting the importance of policy mix approaches tailored to national contexts.