• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.3
• /
• pp.121-129
• /
• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• The Journal of the Korea Contents Association
• /
• v.20 no.4
• /
• pp.159-168
• /
• 2020

This study aims to utilize DEA, analyze the efficiency of Korean coffee franchises, look into the factors that affect efficiency, and improve the efficiency of Korean coffee franchises. The main results of this study are as follows. First, according to CCR model standards, there are a total of 9 efficient coffee franchises and according to BCC model standards, there are a total of 12 efficient coffee franchises. A total of three of the inefficient DMUs were found to have a value of 1 for BCC, while the other 25 were found to be inefficient for both technology and scale. Second, of 28 franchises, 11 were analyzed to be decreasing return to scale and through future increased investments of optimum levels, business performance can be improved and efficiency can be enhanced. Analysis showed that 9 franchises appeared as CRS and it is most ideal to maintain the yield of future output elements at current levels and the work efficiency of 8 franchises in increasing returns to scale states expands as production scales increase according to specialization and role division and yield can relatively improve a lot. Third, the analysis of factors affecting the efficiency of franchises through the Tobit regression analysis showed that the number of franchises and operating periods had a positive (+) effect on efficiency. Based on this study, the efficiency of coffee franchises should be analyzed to establish strategies to maximize efficiency. Based on this study, the efficiency of coffee franchises should be analyzed to establish strategies to maximize efficiency.

• Journal of Navigation and Port Research
• /
• v.45 no.3
• /
• pp.173-180
• /
• 2021

Although accounting is one of the core fields of corporate management, few studies have reported accounting phenomena involving shipping companies. In addition, although financial reporting is very important to shipping companies that use several financial tools such as ship finance and financial lease, it is difficult to identify studies investigating shipping companies' financial reporting, especially their earnings management. The purpose of this study is to analyze accrual earnings management behavior of shipping companies. Companies with high debt ratios and net losses are known to have incentives for earnings management. Due to the nature of the industry, shipping companies have a high debt ratio and often report net losses. Accordingly, shipping companies are expected to engage in substantial earnings management. Based on the analysis of KOSP I companies listed on the Korea Exchange from 2001 to 2020, it was found that shipping companies are engaged in higher levels of earnings management than non-shipping companies. Discretionary accrual was used as a proxy variable for earnings management. Discretionary accrual was measured using the modified Jones model of Dechow et al. (1995) and the performance matched model of Kothari et al.(2005). In this study, significant results were derived by comparatively analyzing the earnings management practices, which is one of the major accounting behaviors of shipping and non-shipping companies. Stakeholders such as external auditors, investors, financial institutions, analysts, and government authorities need to be aware of the earnings management behavior of listed shipping companies during their external audit, financial analysis, and supervision. Finally, listed shipping companies must conduct stricter accounting based on accounting principles.

• International Area Studies Review
• /
• v.22 no.2
• /
• pp.61-91
• /
• 2018

Credit Guarantee scheme is one of the most effective tools for the small business policy. The performance analysis on domestic institution level is relevant in terms of various factors of assisting tools factor. This study measured comparative global efficiency by DEA model and Super-efficiency model among 70 credit guarantee institutions in Japan, Taiwan, and Korea who are operating the schemes. At the result of the analysis, Korean credit guarantee institutions are comparatively efficient than Japanese institutions, and the DMU shows moderate in operation efficiency. The Super-efficiency ranked by Hiroshima, Taiwan SMEG, Pusan, Chiba, Shizuoka, Ulsan, and KOTEC. Most of the Credit Guarantee Institutions showed increasing returns to scale, and it indicates increasing input strategy. The statistical difference of efficiency level in Japan and Korea shows very meaning numbers. This research suggest that (1)Periodical Analysis are needed on Japanese Schemes, (2)The analysis on the impact of credit guarantee scale to the national economy and SME policy, (3) Analysis on the conclusive factors of the efficiency, (4)The policy direction has to be made by inefficient factor analysis, (5) The measurement tools of efficiency of the schemes in various aspects.

• Management & Information Systems Review
• /
• v.37 no.4
• /
• pp.63-74
• /
• 2018

Recently, in the asset management industry, the smart beta strategy, which has an intermediate nature between passive and active strategies, is attracting attention. In this smart beta strategy, value, momentum, low volatility, and quality index are widely used. In this study, we analyzed the quality index which is not clear and complicated to calculate. According to the MSCI methodology, the quality index was calculated using three variables: return on equity, debt to equity, and earnings variability. In addition, we use the index using only return on equity variable, the index using only two variables of return on equity and debt to equity, and the KOSPI index as comparison targets for the quality index. In order to evaluate the performance of the indices used in the analysis, the arithmetic mean return, the coefficient of variation, and the geometric mean return were used. In addition, Fama and French (1993) model, which is widely used in related studies, was used as a pricing model to test whether abnormal returns in each index are occurring. The results of the empirical analysis are as follows. First, in all period analysis, quality index was the best in terms of holding period returns. Second, the quality index performed best in the currency crisis and the global financial crisis. Third, abnormal returns were not found in all indices before the global financial crisis. Fourth, in the period after the global financial crisis, the quality index has the highest abnormal return.

• The Korean Journal of Franchise Management
• /
• v.10 no.3
• /
• pp.25-35
• /
• 2019

Purpose - The major objective of this study was to investigate the effect of franchisor's (economic and philanthropic) CSR in inspiring franchisee's loyalty for the franchisor. Another aim of this investigation also was to clarify the mediating role of economic and social satisfaction in the relationship between franchisor's CSR and franchisee's loyalty. Research design, data, and methodology - This study explores the structural relationship between franchisor's CSR and franchisee's loyalty and in these relationships, the mediating role of relationship satisfaction. Data were gathered from employees(above manager) in food-service franchisee companies in Seoul, Korea. The questionnaires were distributed to managers of the franchise stores. A total of 251 questionnaires were collected. Data management and analysis were performed using SPSS 21.O and SmartPLS 3.0. Evaluation of measurement model and structural model was carried out using confirmatory factor analysis and correlation analysis. Result - The results of this study show as follows. First, economic CSR had positive effects on economic satisfaction and social satisfaction. Second, philanthropic CSR had positive effects on social satisfaction. Third, economic satisfaction and social satisfaction had positive effects on franchisee's loyalty to the franchisor. Conclusions - The important implications of this study have as follows. First, this study has found that economic CSR can create a high economic satisfaction and social satisfaction of franchisee. Second, this findings suggest that the philanthropic CSR can improve the social satisfaction of franchisee. Third, this results demonstrate, for the first time, that the economic satisfaction and social satisfaction of franchisees can play a crucial role to improve their loyalty for the franchisor and pursue mutual development by maintaining the stable business relationship with a franchisor. In this investigation there are at least three limitations. First, Because the research sample is limited to the foodservice franchisee in Seoul, it is not possible to be representativeness of the national franchisee. Second, CSR activities are mostly focused on large franchise companies. Therefore, there is a limit to the research approach. Finally, this study examined the effect of economic CSR and philanthropic CSR on the loyalty of franchisors, but in the future study, it is necessary to analyze the relationship between CSR and loyalty of franchise companies by collecting specific quantitative data such as re-contract rate and management performance of franchisees.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.268-277
• /
• 2020

This study emphasizes that the survival strategy of universities should be a co-evolution strategy based on ecological thinking. Therefore, the purpose of the research is to present a theoretical framework for dividing the university innovation ecosystem into four stages and building a co-evolution strategy for each step, as universities play a prominent role in regional innovation ecosystems. Thus, our research method focused on literature research, and the theoretical framework for the university innovation ecosystem used Moore's Enterprise Ecosystem Model (1996). The university's ecological innovation strategy is divided into four stages of development, and a step-by-step co-evolution strategy is presented. Findings are summarized as follows. The pioneering stage involves the creation of values of the university-led innovation ecosystem. The expansion stage focuses on the establishment of critical mass. The authority stage covers maintaining authority and bargaining power. The renewal stage features continuous performance improvement. In particular, this theoretical model of the university-regional innovation ecosystem is meaningful in that it provides a theoretical basis for enhancing the effectiveness of government financial support projects, and for individual universities, it provides a framework for strategies suitable for their ecosystem building process.

• Journal of Intelligence and Information Systems
• /
• v.28 no.3
• /
• pp.161-183
• /
• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.3
• /
• pp.83-94
• /
• 2022

The number of public rental housing has increased according to the government's 「Housing Welfare Roadmap (2017)」, and facility maintenance costs for the demand of improvement of performance and residential standards due to the aging of long-term public housing are significantly increasing. Consequently, the financial burden of public housing rental business for maintaining stocked housing is aggravated. However, there is a lack of objective data to analyze the size of the maintenance costs that are executed by the type of repair work, and the elapsed years of the aged long-term public rental housing. This study analyzes the execution status of 33 long-term public rental housing complexes located in Seoul for 14 to 28 years of elapsed years based on the data of maintenance costs. In addition, this study proposes a model to predict the maintenance costs by elapsed years by dividing 'Long-term Repair Plan Work and Government-Funded Project [Y₁]', 'Planned Repair Work and General & Unplanned Repair Work [Y₂]', and 'Total maintenance costs [Y₃]'. It is intended to be used as basic data for the establishment of the maintenance plan at the stage of setting up the budget and the establishment of the sustainable operation plan for public rental housing

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