• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.18-34
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• 2020

This study aims to investigate Dongdaemun fashion industry once thrived in Seoul, now in a rapid decline. For this purpose, three research themes are put forward. That is, to fix the boundary of Dongdaemun fashion industry, to analyze the characteristics of its value chain, production network and industrial agglomeration, and to search for the cause of its decline and to suggest political solutions against it. The following is the findings of this study. Firstly, Dongdaemun fashion industry has spreaded out over the last six decades and now its boundary can be marked within a radius of 10 kilometers of Dongdaemun Market in northeastern Seoul. Secondly, Dongdaemun fashion industry has a buyer-driven chain and star production network, and therefore can be assumed that it is spatially segmented industrial agglomeration. Lastly, its rapid decline is directly from the shrink of market demand on Dondaemun fashion, and inherently in the topological structure of its star production network. Thus the feasible political solutions can be found in that direction. Consequently, these results have academic implications for clearing up some previous studies' misunderstandings and getting over one of the long-criticized research biases that pervades in industrial agglomeration theory, primarily focusing on the successful regions.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.488-512
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• 2019

This study examines the 'Asia Decoupling' hypothesis, focusing on changes in trade patterns between regions and countries, based on the latest value added trade statistics. As an analytical tool, indicators that can directly measure the degree of distribution of actual value added were used. Main findings are: Firstly, creating potential at regional level which used to be the growth engine of East Asia until the mid-2000s declined sharply after the global financial crisis. Secondly, in the development pattern of the value added distribution network, no positive change has been detected in the give-out or gain capacity of emerging countries that can generate future growth in East Asia through GVC development. Lastly, China's value added contributing capacity, as different from the hub countries in other regions such as US and Germany, has declined significantly since the mid 2000s, while its capability to benefit greatly increased, and the gain potential of advanced group countries in competition with China is decreasing. We suggest the establishment of intra-regional economic cooperation mechanism including all countries in East Asia for expanding the value creating capacity in the region.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.184-189
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• 2007

Concerns about food safety continue to rise and under this situation, governments of some countries have reinforced their regulations more strictly for food safety. In order to prevent food safety incidents or, at least to minimize the impact, the preparedness is very important. As a consequence of this, traceability system has become an essential tool for food safety. Recently, it requires more prevention-based food safety control system. One of the most generally used systems for food safety control is Hazard Analysis and Critical Control Point (HACCP). Both traceability and HACCP systems can be integrated through Electronic Product Code (EPC) Sensor Network technologies which have four value propositions. In this paper, we will introduce the concept of product and process traceability system (P2TS) through the integration of three systems to improve food safety management. The final aim is to find out the added values of the P2TS.

• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.109-127
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• 2010

The Network Centric Warfare(NCW) is based on the linkage of forces by network to employ them as they are centralized, even though they are scattered. Also it can be used to overcome spatiotemporal obstacles. Under the concept of NCW, cognitive and social areas are getting more weight than information technology and physical ones. In this study we tried to investigate the affecting factors to execute NCW effectively by user's point of view to place the focus on cognitive and social aspects. We obtained some affirmative results that affect to conduct NCW in Korea. The advanced western NCW can be applicable in theoretically in Korea, however to employ NCW more effectively we need Korean style NCW which portrays the Korean realities and circumstances.

• Journal of Wind Energy
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• v.13 no.4
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• pp.58-69
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• 2022

This study reviews previous studies on the scale of offshore wind power industry ecosystems to provide basic data for a revitalization strategy for the offshore wind power industry and proposes an analysis of transaction networks based on the special classification of the renewable energy industry. First, we examine the localization rate, technology level, and price level of the offshore wind industry. Second, this research compares the methodology and estimation results of previous studies estimating the scale of the wind power industry. Third, we examine the details related to the enactment of a special classification of the renewable energy industry statistics and review the Korea Energy Agency's renewable energy industry statistics (focusing on 2019 and 2020). Finally, this study suggests the necessity of analyzing an inter-company transaction network based on special classifications of the renewable energy industry to grasp the status of each region and value chain of the offshore wind industry.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Advances in nano research
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• v.12 no.4
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.1923-1931
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• 2014

A value creation is understood as important business strategy these days in both academics and industry. But this phenomenon is not fully understood based on systematized framework. In this paper, we summarized value research trend based on exploratory research and inductive reasoning by exploring both international and domestic journals. And we built a research framework that can analyze value creation between supplier and customer. Value research prior to 2004 is primarily divided into values of goods or services and relationship values. After 2004, service-dominant (SD) logic has been outlined. There are other research trends to see the relationship value in terms of relationship benefits and relationship in the network or supply chain. 4 critical resource types (financial resource, knowledge resource, efficiency resource, and intellectual resource) and 5 competence types (relational capability, collaboration capability, innovation capability, managing capability) are constructed as principal factors for value creation from inductive reasoning based upon a resource-based view (RBV) and a competence-based view (CBV). The research framework was built based on 4 resources and 4 competences.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.186-198
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• 2021

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.3
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• pp.174-191
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• 2024

This study analyzed the spatiotemporal evolution of Korean multinational corporations' (MNCs') foreign direct investment (FDI) networks from 1978 to 2023, focusing on Samsung Electronics and LG Electronics. Using data on the consolidated overseas subsidiaries of these two companies, a two-mode network was constructed to examine the status of host countries through the betweenness centrality index and to identify types of countries with similar value chain arrangements by investigating their linkage structures. The main findings are as follows. First, during the early phase of Korean electronics MNCs' overseas expansion in the 1980s, they primarily established sales bases in developed consumer markets. However, over time, they gradually expanded into other business areas, including manufacturing, producer services, and R&D, increasing complexity in their FDI networks as cross-border mergers and acquisitions (M&As) became more frequent. Second, the United States has remained central to these MNCs' FDI networks since the 1980s, but more recently, China has emerged as a significant hub, challenging the U.S. in global value chains. Third, emerging Asian economies, including India, Vietnam, and Indonesia, have strengthened their positions due to the diversification of MNCs' investment objectives from manufacturing bases to a broader range of business areas. Finally, since the 2010s, the convergence of the electronics industry with the automotive electronics sector and new industries has led to a diversification of the value chain arrangements of Korean electronics MNCs.