• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.263-270
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• 2021

In this study, a reliability-based design optimization of a 130-m class fixed-type offshore platform, to be installed in the North Sea, was carried out, while considering environmental, material, and manufacturing uncertainties to enhance its structural safety and economic aspects. For the reliability analysis, and reliability-based design optimization of the structural integrity, unity check values (defined as the ratio between working and allowable stress, for axial, bending, and shear stresses), of the members of the offshore platform were considered as constraints. Weight of the supporting jacket structure was minimized to reduce the manufacturing cost of the offshore platform. Statistical characteristics of uncertainties were defined based on observed and measured data references. Reliability analysis and reliability-based design optimization of a jacket-type offshore structure were computationally burdensome due to the large number of members; therefore, we suggested a method for variable screening, based on the importance of their output responses, to reduce the dimension of the problem. Furthermore, a deterministic design optimization was carried out prior to the reliability-based design optimization, to improve overall computational efficiency. Finally, the optimal design obtained was compared with the conventional rule-based offshore platform design in terms of safety and cost.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.4
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• pp.491-505
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• 2018

As an alternative to deep geological disposal technology, which is considered as a reference concept, the domestic applicability of deep borehole disposal technology for high level radioactive waste, including spent fuel, has been preliminarily evaluated. Usually, the environment of deep borehole disposal, at a depth of 3 to 5 km, has more stable geological and geo-hydrological conditions. For this purpose, the characteristics of rock distribution in the domestic area were analyzed and drilling and investigation technologies for deep boreholes with large diameter were evaluated. Based on the results of these analyses, design criteria and requirements for the deep borehole disposal system were reviewed, and preliminary reference concept for a deep borehole disposal system, including disposal container and sealing system meeting the criteria and requirements, was developed. Subsequently, various performance assessments, including thermal stability analysis of the system and simulation of the disposal process, were performed in a 3D graphic disposal environment. With these analysis results, the preliminary evaluation of the domestic applicability of the deep borehole disposal system was performed from various points of view. In summary, due to disposal depth and simplicity, the deep borehole disposal system should bring many safety and economic benefits. However, to reduce uncertainty and to obtain the assent of the regulatory authority, an in-situ demonstration of this technology should be carried out. The current results can be used as input to establish a national high-level radioactive waste management policy. In addition, they may be provided as basic information necessary for stakeholders interested in deep borehole disposal technology.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.450-457
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• 2018

Purpose: The evaluation of seismic performance of critical structures has been emerging a key issue in Korea, since a magnitude 5.8 earthquake, the worst in Koran history, struck Gyeongju, southern area in Korea on september 12th, 2016. In particular, the catastrophic failure of nonstructural components such as sprinkler piping systems can cause significant economic loss or loss of life during and after an earthquake. The nonstructural components can be more fragile than structural components in seismic behavior. Method: This study presents the seismic performance evaluation of fire protection piping system, using coupled building-piping system installed with Triple Friction Pendulum Bearings (TPBs). Kobe (Japan), Kocaeli (Turkey), and GyeongJu (Korea) were selected to consider the uncertainty of ground motions in this study. Result: In the simulation results, it was observed that the reduction of maximum displacements of the piping system with the TPBs' system was significant: Kobe, Kocaeli, and Gyeongju cases were 49%, 14.4% and 21.5%, respectively. Conclusion: Therefore, using seismically isolated system in a building-piping system can be more effective to reduce the seismic risk than a normally installed building-piping systems without TPBs in strong earthquakes.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.21-35
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• 2021

The purpose of this paper is to examine how demand for labor affects the job seeker's decision on the level of investment in education. In the current paradigm of economic growth in which innovations and technological developments generally weaken the strength demand for labor and increases the uncertainty related to employment, this paper provides a theoretical framework that can be used as a basic framework in understanding the decision of investment in education in varying conditions of demand for labor. The following are the findings of this paper. First, the level of investment in education can generally be regarded to be higher as the demand for labor exacerbates but for the job seekers with a certain characteristic. Second, the Arrow-Pratt absolute risk-aversion measure is the characteristic of the job seeker that determines in what direction the job seeker changes in the level of investment in education, For an arbitrary level of demand for labor there exists a certain threshold which determines the minimum degree of risk-aversion required for the job seeker's Arrow-Pratt should go over to increase the level of education as demand for labor weakens. Third, the job seekers lower the level of education even though the demand condition in labor markets weakens if the compensation function does not depend on the level of education. This is surprising because it turns out that one of the reasons why job seekers invest in education is that they want to be recognized in their compensation for their level of education even when more education still raises the probability of employment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.128-130
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• 2021

This study aims to implement a Regression Analysis system for predicting the appropriate production of flatfish. Due to Korea's signing of FTAs with countries around the world and accelerating market opening, Korean flatfish farming businesses are experiencing many difficulties due to the specificity and uncertainty of the environment. In addition, there is a need for a solution to problems such as sluggish consumption and price drop due to the recent surge in imported seafood such as salmon and yellowtail and changes in people's dietary habits. in this study, Using the python module, xlwings, it was used to obtain for the production amount of flatfish and to predict the amount of flatfish to be produced later. was used to predict the amount of flatfish to be produced in the future. Therefore, based on the analysis results of this prediction of flatfish production, the flatfish aquaculture industry will be able to come up with a plan to achieve an appropriate production volume and control supply and demand, which will reduce unnecessary economic loss and promote new value creation based on data. In addition, through the data approach attempted in this study, various analysis techniques such as artificial neural networks and multiple regression analysis can be used in future research in various fields, which will become the foundation of basic data that can effectively analyze and utilize big data in various industries.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Knowledge Management Research
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• v.24 no.3
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• pp.217-237
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• 2023

Recently, in the face of successive and unexpected global economic risks, ESG(Environmental, Social, and Governance) management has risen as an essential survival strategy for businesses. Particularly, the supply chain disruptions due to the COVID-19 pandemic have added to the uncertainty of risks, heightening the importance of ESG management in the distribution industry. In this context, the role of blockchain technology in strengthening and managing the connection between the distribution industry and ESG management has become increasingly significant. While there have been extensive proposals for business models that integrate blockchain technology into distribution, few studies have specifically focused on the feasibility and effectiveness of applying blockchain to ESG management in this field. Therefore, this study analyzed the relationship between blockchain and ESG management in the distribution industry by employing association analysis, a text mining technique, on Korean academic research. Through this, the study confirmed the possibility of implementing blockchain in the distribution industry's ESG management and presented keywords to guide future research directions. The findings obtained from this study are expected to be utilized as foundational research for future studies in constructing blockchain-based business models for ESG management in the distribution industry.

• International Commerce and Information Review
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• v.14 no.3
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• pp.3-30
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• 2012

In the development process, small and medium-sized enterprises in China have shown their unique features and regularities which are closely related to China's national condition and economic characteristics. But in 2008, because of the global financial crisis which started in the USA, the rate of Chinese export and the rate of economic growth has evidently slowed. Due to shortage of funds, foreign orders fell, increase the value of RMB, lack of talented factors, Chinese SMEs are facing bankruptcy. In this context, the purpose of this study is to examine the effects of domestic and international market environment, the government assistance for entering overseas market, entrepreneur characteristics, etc. on the global performance. Based on these, a research model and some hypotheses were set up and tested by the multiple regression analysis with total 317 effective survey data. The results of this paper are as follows. First, a positive effect relation on the financial performance was shown for the companies with high domestic and international market environment in the aspect of market environment. According to such analysis result, it was found that the market environment in which SMEs belong to is a very important factor. Second, in the aspect of government export assistance related to overseas, market development showed a positive effect relation on the both financial and non-financial performance. However, the direct financial assistance showed a positive effect relation only on the non-financial performance. Overall, it was found that the government assistance program on entering overseas market is having significant effects on SMEs, but direct financial assistance have not achieved the desired results. Third, the innovative-ness and progressiveness of entrepreneur showed a positive effect relation on the global market performance. However, the risk-taking of entrepreneur only showed a negative effect relation on the non-financial performance. Overall, it was found that the entrepreneurship of SMEs is an important and influential factor. This is a result implying that the propensity of taking too much risk is not desirable based on the uncertainty of the global environment market. To sum up, this study confirmed that the market environment, the government assistance and entrepreneur characteristics, which are the major prerequisites of global performance, have effects on global performance.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.19-36
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• 2020

The bidding phase for logistics outsourcing services is critical for both shippers and logistics companies. According to the logistics bidding phase, the shipper should provide logistics operation information to logistics companies to resolve uncertainty. In addition, the logistics company can win the contract volume that was placed in the bid by expressing their experience and know-how, and proposing to share the risks and benefits of the shipper's logistics operation. Therefore, it is necessary to examine the factors that can be identified during the bidding phase for logistics outsourcing and how these factors affect the satisfaction of logistics outsourcing services. Based on the factors identified in the preceding studies on logistics outsourcing partnership factors and those on logistics outsourcing determinants, a survey was conducted on experts engaged in logistics companies, performing logistics for domestic shippers and analyzed using Smart-PLS. This study presents the following implications. First, in the logistics bidding phase, the shipper should provide its logistics operation information to logistics firms to resolve uncertainties. Details An in-depth explanation of the operation details will be presented via the bidding presentation, and on-site tours of manufacturing plants and logistics centers should also be carried out if necessary. Second, in the bidding phase, logistics companies should appeal through proposals to their competitiveness, such as experience and knowledge of the logistics of the shipper, and also consider alliances with other logistics companies to supplement their insufficient logistics services. Third, logistics companies should make proposals to share profits and risks through logistics outsourcing during the bidding phase, propose accepting risks from environmental uncertainties of the shipper within its capacity to an acceptable extent, and share the benefits of carrying out the shipper's logistics.