• Information Systems Review
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• v.8 no.3
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• pp.225-243
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• 2006

Recently mother company-driven informatization projects have been widely launched for the suppliers. Setting up a proprietary evaluation system for the level of informatization of the suppliers, a mother company provides both financial and consulting supports for the suppliers in order to enhance the utilization level of the ERP(Enterprise Resource Planning) system. With the utilization level enhanced, the whole collaboration network will create a competitive advantage to win over global competition. This paper investigates critical success factors for ERP operational performances through a Samsung Electronics case study. The result of the case study may provide valuable feedback to the strategic decision making and fundamental insights for these collaboration efforts.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.6
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• pp.113-125
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• 2013

Outsourcing is used as one of the effective methods while many companies have to start to innovate everything because of increased fierce global competition, low-growth economy, and varied customers' requirements. Under these conditions, a lot of firms are introducing outsourcing for cost savings, risk reduction, management efficiency, strengthen core competence. The purpose of this study is to analyze the effect of between outsourcing success by outsourcing strategy and factors for selecting outsourcing partners and BSC success in the Korea manufacturing. This study was intended to make it possible to get a practical approach on evaluation and compensation of the outsourcing manufacturing enterprises by identifying outsourcing success factors and BSC performance factors. When an outsourcing partner of enterprise is selected, detailed assessment will be possible in terms of partner's competence, financial factors, institutional factors, and operational factors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.85-100
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• 2023

The stochastic volatility (SV) model is one of the main methods of modeling time-varying volatility. In particular, SV model is actively used in estimation and prediction of financial market volatility and option pricing. This paper attempts to model the time-varying volatility of the bitcoin market price using SV model. Hidden Markov model (HMM) is combined with the SV model to capture characteristics of regime switching of the market. The HMM is useful for recognizing patterns of time series to divide the regime of market volatility. This study estimated the volatility of bitcoin by using data from Upbit, a cryptocurrency trading site, and analyzed it by dividing the volatility regime of the market to improve the performance of the SV model. The MCMC technique is used to estimate the parameters of the SV model, and the performance of the model is verified through evaluation criteria such as MAPE and MSE.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.119-133
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• 2024

As a result of significant investments by the government in promoting public technology commercialization and fostering a venture startup ecosystem, there have been quantitative achievements, such as the registration of over 1,600 Innopolis Start-ups since 2006, generating a total revenue of 1.1 trillion won as of 2021. However, these achievements have been overshadowed by critical qualitative challenges, including a continuous decline in average revenue per Innopolis Start-up. This led to a focus on whether managers' technological and market orientations affect business performance. This study aims to provide insights into improving the qualitative growth of Innopolis Start-ups by analyzing the effects of technological and market orientations on business performance, as well as the moderating effects of adjusting marketing and research and development (R&D) costs on this relationship. Through prior research and empirical analysis, this study derives three main findings. First, technological excellence and innovation significantly influence the business performance of Innopolis Start-ups, while technological intensity does not. Second, customer orientation and competitive orientation significantly impact business performance, whereas entry barriers as a single factor do not. Third, adjusting marketing and R&D costs, as controlled variables obtained through general situations, has no direct impact on other variables. However, it interacts with entry barriers, influencing financial business performance, with R&D costs exhibiting a negative buffering effect and marketing costs showing a positive enhancing effect. This study confirms that both technological and market orientations directly influence the business performance of Innopolis Start-ups, thus being crucial factors affecting their growth. Moreover, it establishes that investments in marketing and R&D play significant roles in alleviating initial entry barriers and enhancing financial performance. Consequently, it underscores the importance of reinforcing technological and market orientations tailored to the characteristics of Innopolis Start-ups. Additionally, it proposes five theoretical contributions: strengthening institutional support systems for technology commercialization and innovation, improving qualitative evaluation criteria during the selection process of Innopolis Start-ups, conducting comprehensive analyses of technological and market aspects during startup selection, enhancing support for marketing education and consulting for smooth market entry, and supporting expenditure strategies and milestone setting tailored to the industrial characteristics of individual Innopolis Start-ups.

• Journal of Distribution Science
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• v.13 no.2
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• pp.85-94
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• 2015

Purpose - This study attempts to examine the impacts of consumers' perceived service convenience of retailers on various service performance metrics such as service quality and customer satisfaction. It also tries to investigate differences in the importance of service convenience dimensions on service performance between a department store and a general super market. Research design, data, and methodology - The four hypotheses in this study were proposed and tested. Two hypotheses were on the causal relationships between service convenience dimensions and service performances (service quality and customer satisfaction). The other two hypotheses were on comparisons for the effects of convenience dimensions on service quality and customer satisfaction between department stores and general super markets. To test the hypotheses, three department store chains (Hyundai, Lotte, and Shinsegae department Store) and three general super markets (E-mart, Homeplus, and Lotte mart) were involved. Overall, 510 usable responses were used. The data were analyzed using regression analysis. Results - The results largely support the hypothesized relationships of the proposed model. The results show that access convenience, transaction convenience, benefit convenience, and post-benefit convenience have positive influences on service quality, whereas decision convenience, access convenience, transaction convenience, benefit convenience, and post-benefit convenience have positive effects on customer satisfaction. Furthermore, the results show that there are differences between department stores and general super markets in the effects of benefit convenience and post-benefit convenience on service quality as well as the effects of transaction convenience and post-benefit convenience on customer satisfaction. Conclusions - The concept of service convenience is important in retail environments but little is known about this topic in retail literature. Specially, while service convenience dimensions have different impacts on service performance in distinct retail environments, there has been little investigation or comparison between retail types as regards service convenience. This study is the first to test the differences between distinct retail types (department stores and general super markets) on the service convenience-service performance links. Managerially, the findings of this study suggest that the service convenience management of retailers is an important part of successful service performance management. Because it is most important that both department stores and general super markets enhance benefit convenience to improve service performance, managers of both store types need to invest their resources to reduce consumers' perceived time and effort expenditures to experience the retailer's core benefits. Therefore, the results of this study suggest that retail stores should spend human and financial resources to enhance customer perceptions of service convenience, while also considering what constitutes the service outcome in the consumer's mind. Furthermore, the findings suggest that managers need to use different service convenience management tactics in department stores and general super markets. Specifically, managers in general super markets should pay more attention to benefit convenience and transaction convenience to achieve better service performance whereas managers in department stores should concentrate on post-benefit convenience to create customers' positive evaluation.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2993-3002
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• 2018

This case study introduces the process of developing the technology rating evaluation model for investment. The technology evaluation rating model for investment is a project that the Financial Services Commission and the Ministry of Commerce, Industry and Energy collaborated to expand the scope of technology finance from loan to investment. The technology evaluation model for investment was developed with the aim of predicting high growth companies. The model consists of a statistical model and an expert model. Here, statistical models were modeled by using logistic regression analysis. Expert models gathered opinions of experts and identified the weight of each evaluation item and set the model. The rating system of the model is composed of 10 grades. The distribution of the model was consistent with KTRS grade distribution. Interestingly, the emphasis is on technology and marketability. In the technology valuation grade model for the goddess, there is a considerable difference from the emphasis on managerial competence or business performance.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.49-58
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• 2010

Corporate social responsibility has become a very important issue for researchers (Greenfield, 2004; Maignan & Ralston, 2002; McWilliams et al., 2006; Pearce & Doh 2005), and many consider it necessary for businesses to define their role in society and apply social and ethical standards to their businesses (Lichtenstein et al., 2004). As a result, a significant number of retailers have adopted CSR as a strategic tool to promote their businesses. To this end, this study sought to discover U.S. consumers' attitudes and behavior in ethical purchasing and consumption based on their subjective perception and evaluation of a retailer. The objectives of this study include: 1) determine the participants awareness of retailers corporate social responsibility; 2) assess how participants evaluate retailers corporate social responsibility; 3) examine whether participants evaluation process of retailers CSR influence their attitude toward the retailer; and 4) assess if participants attitude toward the retailers CSR influence their purchase behavior. This study does not focus on actual retailers' CSR performance because a consumer's decision making process is based on an individual assessment not an actual fact. This study examines US college students' awareness and evaluations of retailers' corporate social responsibility (CSR). Fifty six college students at a major Southeastern university participated in the study. The age of the participants ranged from 18 to 26 years old. Content analysis was conducted with open coding and focused coding. Over 100 single-spaced pages of written responses were collected and analyzed. Two steps of coding (i.e., open coding and focused coding) were conducted (Esterberg, 2002). Coding results and analytic memos were used to understand participants' awareness of CSR and their ethical purchasing behavior supported through the selection and inclusion of direct quotes that were extracted from the written responses. Names used here are pseudonyms to protect confidentiality of participants. Participants were asked to write about retailers, their aware-ness of CSR issues, and to evaluate a retailer's CSR performance. A majority (n = 28) of respondents indicated their awareness of CSR but have not felt the need to act on this issue. Few (n=8) indicated that they are aware of this issue but not greatly concerned. Findings suggest that when college students evaluate retailers' CSR performance, they use three dimensions of CSR: employee support, community support, and environmental support. Employee treatment and support were found as an important criterion in evaluation of retailers' CSR. Respondents indicated that their good experience with a retailer as an employee made them have a positive perception and attitude toward the retailer. Regarding employee support four themes emerged: employee rewards and incentives based on performance, working environment, employee education and training program, and employee and family discounts. Well organized rewards and incentives were mentioned as an important attribute. The factors related to the working environment included: how well retailers follow the rules related to working hours, lunch time and breaks was also one of the most mentioned attributes. Regarding community support, three themes emerged: contributing a percentage of sales to the local community, financial contribution to charity organizations, and events for community support. Regarding environments, two themes emerged: recycling and selling organic or green products. It was mentioned in the responses that retailers are trying to do what they can to be environmentally friendly. One respondent mentioned that the company is creating stores that have an environmentally friendly design. Information about what the company does to help the environment can easily be found on the company’s website as well. Respondents have also noticed that the stores are starting to offer products that are organic and environmentally friendly. A retailer was also mentioned by a respondent in this category in reference to how the company uses eco-friendly cups and how they are helping to rebuild homes in New Orleans. The respondents noticed that a retailer offers reusable bags for their consumers to purchase. One respondent stated that a retailer uses its products to help the environment, through offering organic cotton. After thorough analysis of responses, we found that a participant's evaluation of a retailers' CSR influenced their attitudes towards retailers. However, there was a significant gap between attitudes and purchasing behavior. Although the participants had positive attitudes toward retailers CSR, the lack of funds and time influenced their purchase behavior. Overall, half (n=28) of the respondents mentioned that CSR performance affects their purchasing decisions making when shopping. Findings from this study provide support for retailers to consider their corporate social responsibility when developing their image with the consumer. This study implied that consumers evaluate retailers based on employee, community and environmental support. The evaluation, attitude and purchase behavior of consumers seem to be intertwined. That is, evaluation is based on the knowledge the consumer has of the retailers CSR. That knowledge may influence their attitude toward the retailer and thus influence their purchase behavior. Participants also indicated that having CSR makes them think highly of the retailer, but it does not influence their purchase behavior. Price and convenience seem to surpass the importance of CSR among the participants. Implications, recommendations for future research, and limitations of the study are also discussed.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• The Journal of Korean Medicine
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• v.28 no.3 s.71
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• pp.1-12
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• 2007

Objectives : The purpose of this study was to explore the perceptions of health promotion programmes using traditional Korean medicine among public health centre staff in charge of running such programmes. To do so, we examined and analysed the current situation of implementing the programmes in the public health centre. Methods : A survey was designed to collect information on perception of the health promotion programmes using traditional Korean medicine by public health centre staff in charge of running such programmes. The survey, using a structured questionnaire designed for this study, was conducted on 161 public health centre staff attending an annual meeting to presenting the results of activity evaluation related to public health programmes using traditional Korean medicine in public health centres. The participants were asked about the most successful programme, the benefits of the programmes, the positive aspects of the programmes, the most desirable outcomes of the programmes and so on. The data were analysed using SPSS system 12.0 for Windows. Results : Of the 161 questionnaires, 121 were analysed. The main findings of this research were as follows. Of the health promotion programmes using traditional Korean medicine implemented in public health centres, qigong and stroke preventive health promotion programmes were perceived as the most successful. The major benefits of the programmes were having merit for health promotion and expecting a positive performance outcome. The major positive aspects of the programmes for health promotion were cultivating community citizen's support and showing consistency between the philosophy of the programmes and the direction of existing health promotion programmes. The most desirable outcomes of the programmes were spreading community understanding of the programme and establishing an effective and unique health promotion model for implementing the programme. Two major causes of implementation difficulties were lack of material resources such as manpower, facility, and equipment, and methods of performance evaluation. One of the most urgent needs for activating the implementation of programmes was continuing financial and technical support from the central government. Conclusions : To promote the role of traditional Korean medicine in the public health sector in order to integrate traditional medicine into the public health system, government should develop some measures for solving the identified causes of implementation difficulties and coping with the most urgent needs for activating the implementation of programmes.