• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.233-244
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• 2022

One of the most noteworthy topics in recent corporate management is ESG(Environmental, Social, Governance). Although there are many companies that have declared ESG management, KT has declared full-fledged ESG management in 2021 and is sharing its sustainable management strategy with stakeholders. In addition, KT is strengthening ESG management by issuing ESG bonds for the first time in the domestic ICT industry. At a time when the information technology industry became more important due to COVID-19, this study attempted to examine KT's ESG management goals and strategies by dividing them into environmental, social, and governance areas. KT was aiming to achieve environmental integrity through 'environmental management', 'green competence', 'energy resources', and 'eco-friendly projects' in the environmental field. In addition, in the social field, genuine creating social value was pursued through 'social contribution', 'co-growth', and 'human rights management'. Finally, in the governance area, it was aiming for a transparent corporate management system to pursue economic reliability through 'ethics and compliance' and 'risk management'. In particular, KT was promoting its own ESG management by promoting strategies to solve environmental and social problems using AI and BigData technologies based on the characteristics of a digital platform company. This study aims to derive implications for ESG strategy establishment and ESG management development direction through KT's ESG management case in relation to ESG management, which has emerged as a hot topic.

• Journal of Technology Innovation
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• v.31 no.2
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• pp.1-27
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• 2023

This study first reviews the evolving literature on industrial innovation policy and thereby identifies three main goals of such policy. The first goal is traditional industrial policy aiming growth of existing and future industries, the second goal is sustainable development and quality of life, and third goal encompasses the issues related to supply chain and economic security. Then, the paper evaluates industrial innovation policy goals of the five economies (United States, China, Germany, Japan, and Taiwan) in terms of the relative weights given to each goal by each economy, and derives implications for Korea. The United States emphasizes economic security and supply chain stability amid its rivalry with China. In contrast, China focuses more on traditional industrial policies but has recently begun to consider supply chain and economic security. Germany and Japan tend to give similar weights to each of the three goals. Taiwan follows this trend with a new and additional emphasis on economic security given the rising threats from China. For Korea, economic security may not be the top priority, unlike the two super-powers. Instead, it seems more appropriate for Korea to follow Germany or Japan to prioritize supply chain stability and technology sovereignty, and, at the same time, fostering future growth industries must be still an important goal. Further, the concept of economic security for Korea should include promotion of defense industry and food security.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.27-40
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• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.765-778
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• 2008

Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.505-508
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• 2022

Artificial intelligence itself has the value of advancing technology, and it is used in various industrial fields to enhance the added value of products and services produced in various industries. Therefore, regulations and policies related to artificial intelligence should be considered from a broader perspective. However, researchers have different understandings, and there is no agreement on how to regulate artificial intelligence. Therefore, we will examine the direction of government regulation on artificial intelligence technology in an exploratory manner. First, accountability, transparency, stability, and fairness are derived as the goals of artificial intelligence regulation, and the system itself, development process, and utilization process are set as the scope of regulation, and users and developers are subject to regulation. The academic significance of this study can be seen as analyzing the current level of artificial intelligence technology and laying the foundation for consistent discussions on artificial intelligence regulations in the future. Considering the life cycle from AI development to application, what is important is the balance of promotion policies to promote the artificial intelligence industry and regulatory policies to respond to the resulting risks. The goal of law related to artificial intelligence is to establish a system in which artificial intelligence can be accommodated in a positive direction to all participants, including developers, companies, and users.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.327-328
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• 2022

The recent spread of the corona pandemic and a temporary surge in demand for consumer goods have resulted in an increase in port cargo volume, and the resulting port congestion is coupled with a shortage of labor in the port, exacerbating the global supply chain chaos. Supply chain disruptions will increase logistics costs and ultimately increase global inflationary pressures. In this situation, the role of the port, which is the nodal point between land and sea, is gradually becoming more important. And fully automated ports that are operated unmanned are evaluated as being able to respond stably and flexibly by reducing operational risks in situations such as COVID-19. Therefore, this study compared the operational performance of fully automated and non-fully automated terminals within the same port before and after the corona outbreak, and analyzed the fully automated terminal was stable in actual operation. As a result of the analysis, the fully automated terminal showed stable operating efficiency in all aspects of operational performance compared to the non-fully automated terminal even under severe port congestion due to COVID-19.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.179-194
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• 2023

ASEAN is emerging as the next-generation market following BRICs. Korea is also an important economic cooperation partner as a second trading partner and third target for overseas investment. ASEAN is attracting attention as an attractive business place for many companies as a future investment area in the future. Therefore, the Korean government is strongly promoting a "New Southern Policy(NSP)" to develop cooperative relations with ASEAN. As ASEAN has recently emerged as a central area for shipping and logistics development, development cooperation and support for the shipping and logistics sector in the ASEAN region of neighboring countries are also active in entering the new southern region and the government is supporting it. In order to enter these countries, it is necessary to accurately understand the investment attraction system, strategy, and market for entering the business in other countries. Among the various methods of entering the overseas market, it is essential to understand the business selection and establishment method suitable for localization strategies such as foreign direct investment and establishment of foreign corporations. In order to understand the Overseas Investment Act and the Corporate Establishment Act of shipping and logistics-related companies who want to enter marine ASEAN countries, we will study the overseas investment method and the establishment method according to the type of company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.109-121
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• 2023

This paper examines whether angel investors affect startup's financial performance (profitability and growth ratios) in the Korean startup market over 10 years period from 2009 to 2018. In particular, we consider not only the behavior of angel investor such as the investment amount or the type of investments (stocks, bonds) but also the type of angle investor (individual or corporation). Our empirical results are as follows. First, we find that the startup's profitability ratios are higher after the investment of angel investors. However, the growth ratios show different results in assets and sales. Second, we identify that the investment amount of angel investors negatively affects on the startup's growth ratios. Lastly, we find that equity investment such as common stock or preferred stock and the individual angel investors such as personal investment association or professional angels show higher financial performance than bond investment or corporate angel investors. Overall, our findings imply that angel investors positively affect startup's financial performance. In particular, we infer that the superior financial performance is largely attributed to monitor startups by participating as shareholders or to select more carefully by the individual angel investors who may be exposed to more investment risk. In conclusion, our findings support that angel investors play a positive role in the Korean venture investment market.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.