• Journal of Distribution Science
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• v.12 no.10
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• pp.75-84
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• 2014

Purpose - This article aims to examine whether the stock issuance of firms in the retail industry follows Myers' (1984) pecking order theory, which is based on information asymmetry. According to the pecking order model, firms have a sequence of financing decisions, of which the first choice is to use retained earnings, the second one is to get into safe debt, the next involves risky debt, and the last involves finance with outside equity. Since the 2000s, the polarization of the LEs (Large enterprises) and SMEs (Small and Medium Enterprises) arose in the retail industry. The LEs exhibited an improvement in growth and profitability, whereas SMEs had a tendency to degenerate. This study contributes to corroborating the features of financing decisions in the retail industry distinguished from the other industries. Research design, data, and methodology - This study considers the stocks listed on the KOSPI and KOSDAQ markets from 1991 to 2013, and is more concentrated on the stocks in the retail industry. The data were collected from the financial information company, WISEfn. The empirical analysis is conducted by employing two measures of net equity issues (and), which were introduced in Fama and French (2005), and can be calculated from firms' accounting information. All variables are generated as the aggregate value of the numerator divided by aggregate assets, which, in effect, treats the entire sample as a single firm. Substantially, the financing decisions of the firms were analyzed by examining how often and under what circumstances firms issue and repurchase equity. Then, this study compares the features of the retail industry with those of the other industries. Results - The proportion of sample firms that show annual net stock issues reaching the level of the year's average was 54.33% for the 1990s, and fell to 39.93% per year for the 2000s. In detail, the fraction of the small firms actually increases from 45.08% to 51.04%, whereas that of large firms shows a dramatic decline from 58.94% to 24.76%. Considering the fact that the large firms' rapid increase in growth after the 2000s may lead to an increase in equity issues, this result is rather surprising. Meanwhile, net stock repurchases of assets are considerably disproportionate between the large (-50.11%) and the small firms (-15.66%) for the 2000s. Conclusions - Stock issuance of retail firms is not in line with the traditional seasoned equity offering based on information asymmetry. The net stock issuance of the small firms in the retail industry can be interpreted as part of an effort to reorganize business and solicit new investment to resolve degenerating business performance. For large firms, on the other hand, the net repurchase can be regarded as part of an effort to rearrange business for efficiency and amplifying synergy across business sections through spin-off. These results can help the government establish a support policy on retail industry according to size.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.117-126
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• 2009

Total number of recorded earthquakes in Korea is more than 2,000 of which 48 were catastrophic. The impacts from infrastructure damage due to an earthquake to production facilities and lifelines may spread across boundaries of several regions via import-export relationships and can bring serious economic impact to other regions. The economic impacts from unscheduled events stem not only from the damage and direct losses, but also from the indirect losses during the recovery and reconstruction periods. To recover and reconstruct the facilities and lifelines damaged by unexpected events through investment or government financial aid, both the direct and the indirect economic impacts from an event need to be measured in regional and interregional contexts. Direct economic impact is the direct change of production and demand due to the disruption of production facilities and lifelines from an unexpected event, and indirect economic impact is the change in other sectors due to inter-industry relationships. The purpose of the paper is to analyze various economic impacts of an earthquake, especially impacts on transportation networks in Korea. We collected spatial and economic data from Korea, and analyzed and estimated final demand loss and commodity flows from the unscheduled event.

• Clean Technology
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• v.28 no.2
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• pp.193-200
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• 2022

The term environmental, social and governance (ESG) was first used in the 2003 United Nations Environmental Programme Finance Initiative (UNEP FI). Among the three areas of ESG, environment refers to the impact of companies on the environment. Environmental factors address climate change policies and attempts to reduce emissions, waste and natural resource consumption. Social factors refer to the direction in which a company can improve the social impact of stakeholder includes employees, customers, communities, and governments involved in direct or indirect interaction with the organization itself and the company. Governance factors refer to stakeholders who make major decisions, the composition of the board of directors, their diversity and independence, and the internal policies that set limits and expectations for decision-making. Research related to ESG management is part of corporate social responsibility, sustainability, corporate or financial performance, and social responsibility investment. Through case studies and data-based empirical studies, it was confirmed that ESG management companies had positive results for most of the ESG related fields. Through literature analysis of domestic and international ESG history, introduction background, and management performance, this paper presents theoretical, practical implications by confirming that ESG's introduction and operation strategies are strong competitive strategies that directly affect corporate growth by creating attractive factors.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Science and Technology Studies
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• v.15 no.1
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• pp.181-214
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• 2015

This study analyzed the characteristics of the politics of technoscience and governance in South Korea, taking advantage of the policy changes on the stem cell research after Hwang's affair. In spite of generally accepted conventional wisdom that stem cell research had been suffering 'crisis' after the Hwang's affair, South Korea succeeded in developing the first and the largest stem cell product in the world. However, considering the fact that the stem cell research capabilities and technological competitiveness of Korea have been assessed as relatively low compared to the development performance, there is a need to extrapolate how such result could be achieved. To answer these questions, we analyzed changes in the R&D expenditure before and after the scandal and verified the 'crisis of stem cell research' following the reduction of financial support from government. From the analysis of literature on the policy reports and news, we described the process of discourse changes in policy and analyzed the characteristics of the politics of technoscience and governance of stem cell research. This study emphasized that the government R&D and regulation policy play the key roles in the development of stem cell research rather than in the technological competitiveness in South Korea. Furthermore, this study argued that democratic governance still does not work under the policy conditions that technocratic decision-making of stem cell research fails to learn from the Hwang's affairs.

• Korea Trade Review
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• v.41 no.3
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• pp.135-156
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• 2016

This study, with reference to data on economic conditions in Shandong Province, China, looked into trade and investment activities in Korea and major cities of Shandong - Qingdao, Yantai, Weihai and Jinan - and investigated claim cases between the two countries by type. In addition, we investigated the matter empirically by conducting a survey administered to 300 Korean companies investing in Shandong Province and, based on the data, tested hypotheses for inferential analysis. The findings are as follows: i) while hypotheses in which the size of a firm, represented by import and export volume, has a positive relation with the frequency of trade claim filings (H1) and with the financial value of the trade claims (H2) were quoted, company size proved to have a significantly negative relation with the time required to obtain a claim decision, which rejects the third hypothesis (H3) in which the relation was thought to be positive: ii) while products, as represented by the type of business, showed a clearly significant difference with the frequency of trade claim filings (H4) and with methods of preventing and responding to claims (H6), they did not show a significant link to the type of trade claim (H5). This study is a theoretical and empirical overview of Korean companies based in Shandong Province of China, and can be used to address the practical needs of the Korean companies looking to start business in Shandong Province.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.602-609
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• 2021

Under accrual basic accounting, financial statements may be less reliable compared to cash basis accounting. The purpose of this study is to conduct an empirical analysis to determine the possibility of profit adjustment through the increase and decrease of deferred tax accounts. For our empirical analysis, a dummy variable of '1' was used as a dependent variable when the deferred tax net assets increased from the previous year and '0' when the deferred tax net assets decreased. Meanwhile, the variables of interest were discretionary accruals and ROA variation compared to the previous year. Logistic regression analysis was performed to establish the relevance between variables. Results found larger discretionary accruals related to lower net deferred tax assets compared to the previous year. In addition, there was a correlation between ROA and net deferred tax assets only if the ROA increased and net profit was greater than '0'. Study results will enable deferred tax information to be used in investment decision-making, and supervisory institutions can establish policies to prevent profit adjustments and enhance reporting standards.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.61-118
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• 2008

The purpose of this research is to construct research framework for international franchising based on existing literature and to identify research components in the framework. Franchise can be defined as management styles that allow franchisee use various management assets of franchisor in order to make or sell product or service. It can be divided into product distribution franchise that is designed to sell products and business format franchise that is designed for running it as business whatever its form is. International franchising can be defined as a way of internationalization of franchisor to foreign country by providing its business format or package to franchisee of host country. International franchising is growing fast for last four decades but academic research on this is quite limited. Especially in Korea, research about international franchising is carried out on by case study format with single case or empirical study format with survey based on domestic franchise theory. Therefore, this paper tries to review existing literature on international franchising research, providing research framework, and then stimulating new research on this field. International franchising research components include motives and environmental factors for decision of expanding to international franchising, entrance modes and development plan for international franchising, contracts and management strategy of international franchising, and various performance measures from different perspectives. First, motives of international franchising are fee collection from franchisee. Also it provides easier way to expanding to foreign country. The other motives including increase total sales volume, occupying better strategic position, getting quality resources, and improving efficiency. Environmental factors that facilitating international franchising encompasses economic condition, trend, and legal or political factors in host and/or home countries. In addition, control power and risk management capability of franchisor plays critical role in successful franchising contract. Final decision to enter foreign country via franchising is determined by numerous factors like history, size, growth, competitiveness, management system, bonding capability, industry characteristics of franchisor. After deciding to enter into foreign country, franchisor needs to set entrance modes of international franchising. Within contractual mode, there are master franchising and area developing franchising, licensing, direct franchising, and joint venture. Theories about entrance mode selection contain concepts of efficiency, knowledge-based approach, competence-based approach, agent theory, and governance cost. The next step after entrance decision is operation strategy. Operation strategy starts with selecting a target city and a target country for franchising. In order to finding, screening targets, franchisor needs to collect information about candidates. Critical information includes brand patent, commercial laws, regulations, market conditions, country risk, and industry analysis. After selecting a target city in target country, franchisor needs to select franchisee, in other word, partner. The first important criteria for selecting partners are financial credibility and capability, possession of real estate. And cultural similarity and knowledge about franchisor and/or home country are also recognized as critical criteria. The most important element in operating strategy is legal document between franchisor and franchisee with home and host countries. Terms and conditions in legal documents give objective information about characteristics of franchising agreement for academic research. Legal documents have definitions of terminology, territory and exclusivity, agreement of term, initial fee, continuing fees, clearing currency, and rights about sub-franchising. Also, legal documents could have terms about softer elements like training program and operation manual. And harder elements like law competent court and terms of expiration. Next element in operating strategy is about product and service. Especially for business format franchising, product/service deliverable, benefit communicators, system identifiers (architectural features), and format facilitators are listed for product/service strategic elements. Another important decision on product/service is standardization vs. customization. The rationale behind standardization is cost reduction, efficiency, consistency, image congruence, brand awareness, and competitiveness on price. Also standardization enables large scale R&D and innovative change in management style. Another element in operating strategy is control management. The simple way to control franchise contract is relying on legal terms, contractual control system. There are other control systems, administrative control system and ethical control system. Contractual control system is a coercive source of power, but franchisor usually doesn't want to use legal power since it doesn't help to build up positive relationship. Instead, self-regulation is widely used. Administrative control system uses control mechanism from ordinary work relationship. Its main component is supporting activities to franchisee and communication method. For example, franchisor provides advertising, training, manual, and delivery, then franchisee follows franchisor's direction. Another component is building franchisor's brand power. The last research element is performance factor of international franchising. Performance elements can be divided into franchisor's performance and franchisee's performance. The conceptual performance measures of franchisor are simple but not easy to obtain objectively. They are profit, sale, cost, experience, and brand power. The performance measures of franchisee are mostly about benefits of host country. They contain small business development, promotion of employment, introduction of new business model, and level up technology status. There are indirect benefits, like increase of tax, refinement of corporate citizenship, regional economic clustering, and improvement of international balance. In addition to those, host country gets socio-cultural change other than economic effects. It includes demographic change, social trend, customer value change, social communication, and social globalization. Sometimes it is called as westernization or McDonaldization of society. In addition, the paper reviews on theories that have been frequently applied to international franchising research, such as agent theory, resource-based view, transaction cost theory, organizational learning theory, and international expansion theories. Resource based theory is used in strategic decision based on resources, like decision about entrance and cooperation depending on resources of franchisee and franchisor. Transaction cost theory can be applied in determination of mutual trust or satisfaction of franchising players. Agent theory tries to explain strategic decision for reducing problem caused by utilizing agent, for example research on control system in franchising agreements. Organizational Learning theory is relatively new in franchising research. It assumes organization tries to maximize performance and learning of organization. In addition, Internalization theory advocates strategic decision of direct investment for removing inefficiency of market transaction and is applied in research on terms of contract. And oligopolistic competition theory is used to explain various entry modes for international expansion. Competency theory support strategic decision of utilizing key competitive advantage. Furthermore, research methodologies including qualitative and quantitative methodologies are suggested for more rigorous international franchising research. Quantitative research needs more real data other than survey data which is usually respondent's judgment. In order to verify theory more rigorously, research based on real data is essential. However, real quantitative data is quite hard to get. The qualitative research other than single case study is also highly recommended. Since international franchising has limited number of applications, scientific research based on grounded theory and ethnography study can be used. Scientific case study is differentiated with single case study on its data collection method and analysis method. The key concept is triangulation in measurement, logical coding and comparison. Finally, it provides overall research direction for international franchising after summarizing research trend in Korea. International franchising research in Korea has two different types, one is for studying Korean franchisor going overseas and the other is for Korean franchisee of foreign franchisor. Among research on Korean franchisor, two common patterns are observed. First of all, they usually deal with success story of one franchisor. The other common pattern is that they focus on same industry and country. Therefore, international franchise research needs to extend their focus to broader subjects with scientific research methodology as well as development of new theory.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.