Amid soaring LNG spot prices, concerns have emerged regarding potential strategic behaviors by direct LNG importers, which may increase  their profits at the expense of Korea Gas Corporation and users of the  average rate system. These concerns stem from observed patterns of  reduced direct imports during periods of high spot prices and increased  direct imports when spot prices fall. However, direct LNG importers argue that such behavior is infeasible under the current system, as selective purchases based on spot price fluctuations are not allowed. To address this controversy, this study examines the mechanisms underlying  fluctuations in spot prices and direct import volumes. The findings reveal  that direct LNG importers have an incentive to enhance profits by reselling  long-term contracted volumes to overseas markets and intentionally  increasing the proportion of spot market purchases during periods of  high spot prices. This behavior explains the observed trends in spot  price and direct import volumes. Furthermore, the study theoretically  investigates how these actions disadvantage Korea Gas Corporation and  users of the average rate system. These findings clarify the optimal choice  of direct LNG importers and offer policy implications for regulating  future direct LNG import practices
 

This study investigates the impact of public research and development (R&D) investment in energy technology on carbon intensity across 30 OECD countries from 1995 to 2020. The results of the empirical exercise, employing the IEA Energy Technology RD&D Budgets database, show that per capita CO2 significantly decreases in the share of energy R&D investment relative to GDP. However, it takes two- to three years to see the effects of these investments. Our findings emphasize the role of carbon pricing mechanisms, such as emissions trading systems and carbon taxation. Robustness tests on the dynamic panel model confirm the impact of energy R&D on emissions reduction.
 

The long-term decline in industrial accidents in South Korea has recently reversed due to expanded recognition criteria and increased approval rates. In response, policy discussions continue over increasing  the employment of dedicated safety and health managers to enhance  workplace safety. This study empirically examines their impact using  data from the Industrial Safety and Health Survey.

 The results show that in manufacturing and services, appointing at least one safety manager reduces serious accidents, with additional hires  offering diminishing returns. Health managers help prevent minor accidents  but show no added effect with further appointments. In construction,  higher occupational safety and health (OSH) expenditures are more  effective in reducing accidents than increasing manager numbers. 

 These results suggest that simply increasing the number of dedicated managers is insufficient. Instead, effective policies should target industry- specific risks and adopt a fault-based, differentiated regulatory framework that adjusts oversight based on accident history and demonstrated safety efforts.

In this study, we examined the impact of the Fourth Industrial Revolution’s new technologies on the economic performance of enterprises using a propensity score-matching approach, grounded in a potential outcome framework, to mitigate endogeneity issues in estimating the effects using regression. Propensity score estimation performance was bolstered by employing a machine-learning algorithm, the random forest. Data from the Survey of Business Activities in Korea, collected through comprehensive enumeration, were used to enhance the results’ generalizability. Findings revealed that enterprises adopting new technologies experienced an approximately 40% surge in annual sales compared to those that abstained. Effect magnitude varied based on enterprise size. For small-and mediumsized enterprises, the increase was approximately 43%; for large enterprises, 77%. Thus, large enterprises appear to have an advantage over smaller ones in utilizing new technologies. This study is significant for its application of the latest research methodology in estimating economic effects of Fourth Industrial Revolution techn ologies on enterprises and identifying policy implications.

 The TIC(Testing, Inspection, Certification) industry has long developed into an oligopolistic service market where a small number of companies provide services under state management and supervision. In this  process, the industry is facing an industry-wide crisis due to the lack of  response to ICT convergence and market opening. In this context, this  study examines key factors influencing the competitiveness of the testing  and certification industry, focusing on confidentiality and expertise. Using  conjoint analysis, we assess the part-worth values of key attributes, including  original document tamper prevention, digital test reports, the number of  confidentiality violations, competency of testing personnel, investment  rate in testing and certification infrastructure, report quality, and service fees. The results indicate that confidentiality is more critical than expertise,  with confidentiality violations and tamper prevention having the greatest  impact on client preferences. Market share simulations demonstrate that  improvements in confidentiality and expertise significantly contribute to  market expansion, while fee reductions serve as an effective strategy for  strengthening competitiveness. This study provides practical insights for  testing and certification institutions, highlighting the need to enhance  confidentiality, expertise, and pricing strategies to improve service reliability  and professionalism
 

Using a range of macroeconomic and financial variables as predictors, we examined the out-of-sample predictability of iron ore prices through machine learning (ML) models. Our result shows that traditional factor models or/and ML models such as random forests and extra-trees, outperform the linear regression. For longer forecasting horizons, the Elastic Net model demonstrates superior accuracy. This suggests that choosing informative predictors is crucial for improving the forecastability of iron ore prices.

 This study analyzes the determinants of innovation among sellers in the digital platform-based e-commerce market and examines the impact of the market structure formed by platforms on companies’ strategic choices. Specifically, it compares the effects of market environment factors perceived by companies (e.g., degree of competittion and technological uncertainty) and market strategies (e.g., platform selection, multi-homing, and export status) on various innovation indicators (product innovation, service innovation, business process innovation, innovation activities, innovation collaboration, and digital transformation) across different industries.

 The analysis employed a comprehensive set of data, integrating the Fair Trade Commission’s registry of telecommunications sales companies with Market DB Pro’s list of platform-using sales companies, along with the Korea Institute of Science and Technology Policy’s corporate innovation survey data. To analyze the differences in the average innovation indicators  across market environments, an independent samples t-test was employed.  In addition, to analyze the impact of distribution strategies on innovation incentives, a Probit model was used for the binary innovation indicators. 

This study aims to clarify the structural conditions and industry-specific heterogeneity surrounding innovation incentives for sellers in the platform  industry and provide an empirical foundation for balanced policy design.

UK spec may vary. Based on In the process of implementing carbon neutrality around the world,eco-friendly energy such as renewable energy is expanding. Because renewable energy, however, is highly variable and has a distributed form of energy, new challenges are created in balancing electricity demand and supply at the local level. Korea’s demand response projects have been mainly implemented in industrial and commercial sectors with high electricity consumption, but since 2018, small-scale demand response projects have been implemented for residential use as well. This study targets demand response projects in the industrial, commercial, and residential power sectors and estimates cost-benefit ratio (BC ratio), net present value (NPV), and internal rate of return (IRR). and break-even point (payback period). However, since the demand response project is a project in which the government intervenes and receives national subsidies, it should be analyzed separately from the government perspective and the user perspective. Additionally, in order to reflect the uncertainty of cost and benefit variable, this study intends to perform a stochastic economic analysis using Monte Carlo simulation methods. The result shows that in the case of the residential demand response project, the economic feasibility was very low from the government perspective due to the large amount of government subsidies, but from the user perspective, the economic feasibility was very high. In the case of commercial and industrial demand response projects, it was found that there was a need to expand their distribution as it is a desirable policy that can achieve a win-win for all stakeholders by securing economic feasibility from both the government and user perspectives.

This study examines the participation of the Chungcheong region in the global value chain (GVC), which has a large intermediate trade scale and an economic scale similar to that of Greece and Portugal. To measure the GVC participation of the Chungcheong region, the regional input-output tables of the Bank of Korea and the multi-regional input-output table (MRIO) of the Asian Development Bank (ADB) were integrated and connected in 2010, 2013, and 2015. First, the Chungcheong region was integrated from Daejeon, Sejong, Chungnam, and Chungbuk regions into a regional input-output table composed of two regions: Chungcheong and other regions outside of Chungcheong. The ADB's MRIO was integrated into an international input-output table consisting of Korea and other countries, and the Korean portion of the international input-output table was integrated using the regional input-output table composed of two regions previously prepared. The GVC participation of the Chungcheong region measured using the MRIO was found to be much higher than that of regions outside of Chungcheong and even higher than that of Greece and Portugal with similar economic scales. 

When examining the forward and backward participation of the GVC, the Chungcheong region showed a steady rate of around 45% for each during the target period. Furthermore, when divided into simple and complex participation, the forward simple participation rate of the Chungcheong region was higher than its complex participation rate, which was similar to that of regions outside of Chungcheong. However, the backward complex participation rate of the Chungcheong region was higher than its simple participation rate, which was different from other regions outside of Chungcheong. When examining by industry, the GVC participation of the manufacturing industry in the Chungcheong region was higher than that of the service industry, especially in the chemical,
electrical and electronic equipment and precision instruments, and transport equipment industries. However, the transport equipment industry showed a different pattern from other industries, with a higher forward complex participation rate than its forward simple participation rate.
 

The export structure of South Korea’s Chungnam Province exhibits considerable vulnerability to external shocks, primarily due to its heavy dependence on specific industries, notably the semiconductor and display sectors dominated by large corporations, as well as its concentrated export markets in China and Vietnam. Amid intensifying global economic uncertainties and heightened export volatility, export diversification has emerged as a critical policy imperative for ensuring regional economic resilience and sustainable growth. This study employs both the Herfindahl-Hirschman Index and Theil Index to quantify export concentration patterns, while utilizing fuzzy-set Qualitative Comparative Analysis (fsQCA) to examine the determinants of export market diversification across 39 manufacturing industries among regional SMEs. The analytical framework incorporates six conditional variables: foreign investment, productivity, export competitiveness, firm distribution, product diversity, and large firm dependency.

Through fuzzy-set calibration and truth table analysis, multiple causal configurations  leading to export market diversification are identified. The findings demonstrate that export market diversification among SMEs manifests through four distinct patterns: global competitiveness, intra-industry diversification, large firm linkages, and hidden champions. This research advances the understanding of export diversification by systematically analyzing the complex configurations of conditional variables, thereby providing an empirical foundation for developing industry-specific policy interventions to enhance regional export resilience.