• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.389-390
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• 2002

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.97-117
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• 2021

Predicting term deposit subscriptions is one of representative financial marketing in banks, and banks can build a prediction model using various customer information. In order to improve the classification accuracy for term deposit subscriptions, many studies have been conducted based on machine learning techniques. However, even if these models can achieve satisfactory performance, utilizing them is not an easy task in the industry when their decision-making process is not adequately explained. To address this issue, this paper proposes an explainable scheme for term deposit subscription forecasting. For this, we first construct several classification models using decision tree-based ensemble learning methods, which yield excellent performance in tabular data, such as random forest, gradient boosting machine (GBM), extreme gradient boosting (XGB), and light gradient boosting machine (LightGBM). We then analyze their classification performance in depth through 10-fold cross-validation. After that, we provide the rationale for interpreting the influence of customer information and the decision-making process by applying Shapley additive explanation (SHAP), an explainable artificial intelligence technique, to the best classification model. To verify the practicality and validity of our scheme, experiments were conducted with the bank marketing dataset provided by Kaggle; we applied the SHAP to the GBM and LightGBM models, respectively, according to different dataset configurations and then performed their analysis and visualization for explainable term deposit subscriptions.

• Management & Information Systems Review
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• v.36 no.5
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• pp.27-44
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• 2017

The purpose of this study was to empirically verify the effect of social entrepreneurship on market orientation. total of 500 questionnaires were distributed to workers in social enterprise and preliminary social enterprise. 202 questionnaires were used for final validation of research model, The hypotheses set in this study were validated through SPSS18.0 and LISREL8.3 based on the research model. The results showed that all hypotheses were accepted, except for 5 hypotheses(Hypothesis 1-1, Hypothesis 1-2, Hypothesis 1-3, Hypothesis 1-6, Hypothesis 1-9). First, we examined the effect that empathy might have on market orientation in connection with social entrepreneurship. The results suggested that empathy did not have a statistically significant effect on customer-orientation, inter-department cooperation and coordination, and competitor orientation. Second, we examined the effect that innovativeness might have on market orientation in connection with social entrepreneurship. The results showed that innovativeness had a positive(+) effect on customer-orientation and inter-department cooperation and coordination but did not have a statistically significant effect on competitor-orientation. Third, we examined the effect that risk-taking might have on market orientation in connection with social entrepreneurship. The results implied that risk-taking had a positive(+) effect on customer-orientation and inter-department cooperation and coordination but did not have a statistically significant effect on competitor-orientation. Finally, the relationship among market orientation variables was like this: The inter-department cooperation and coordination had a positive(+) effect on both customer-orientation and competitor-orientation. The results of this study are expected to provide a useful basis for overall understanding about the effect of social entrepreneurship on market orientation and present important theoretical and practical implications.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• Culinary science and hospitality research
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• v.15 no.4
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• pp.187-199
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• 2009

The objective of the research is to investigate the causal relationships among functional value, emotional value, social value, perceived sacrifice, satisfaction, loyalty and behavioral intention. All in all, 296 respondents completed a questionnaire themselves in the presence of an interviewer who could be consulted about the response scales and other technical matters. Behavioral intention models were estimated by structural equation modelling using 7 latent constructs. The results demonstrated that the confirmatory factor analysis model provided a good model fit. The unconstrained model yielded a significantly better fit to the data than the constraint model. The effects of functional value and social value on satisfaction and behavioral intention were statistically significant. The effects of perceived sacrifice, satisfaction and loyalty on behavioral intention were statistically significant. As expected, satisfaction had a significant effect on loyalty. Functional value had an indirect effect on behavioral intention through satisfaction and loyalty. Moreover, social value had an indirect effect on behavioral intention through satisfaction and loyalty. Replicating and extending this study in other regions and other samples would test the generalizability of the present findings and provide a basis for an external validation of the framework developed in this paper.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.1
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• pp.1-15
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• 2014

Refinery plant producing petroleum products from crude oil has significantly contributed to the creation of the national interests as a leading engineering industries. However, domestic Engineering Procurement Construction (EPC) companies are facing heavy competition for orders. Domestic EPC companies as EPC contractors are faced with some problems such as undertaking responsibility for FEED packages produced by other FEED companies. But domestic EPC contractors are unfamiliar to development and validation of FEED packages. It causes poor profitability and lower competitiveness of domestic companies. It is necessary for domestic companies to have capability to perform FEED activities in order to overcome these limitations instead of focusing on EPC phase after FEED phase. The systematic procedure is needed to perform the FEED activities, however, there are present difficulties on it due to the lack of experience in FEED packages development which require various engineering knowledge of chemical process, mechanics, electrics, instrumentation, civil engineering. This study has applied systems engineering method which is multi-disciplinary approach to derive and verify the solution to meet the customer's needs when the complex system is developed to task execution process development of FEED activities for refinery plant. The problems that may occur in the future were identified in advance by taking into account the various stakeholders and system context through the application of systems engineering. It helps to develop the task execution process systematically. The developed task execution process of FEED activities is planned to make effectiveness verified by engineering professionals experienced in FEED and continually enhance this process by field application.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.189-196
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• 2020

In this paper, we propose a study on the purchasing intent of the new e-commerce consumer, the coronavirus may once again drive the structural change of China's economy, and the new online marketing model will be noticed during the epidemic. Through 438 questionnaires collected on the Internet, frequency analysis, element analysis, reliability analysis and structural equation analysis were performed using SPSS V22.0 and AMOS V22.0 methods. Study the validation of hypotheses in the model to reveal the reasons why consumers in the new e-business are exposed. The results show that e-commerce features of Internet celebrities and individual characteristics of Internet celebrities can only enhance consumers' satisfaction. Quasi social relationships only increase consumer satisfaction without generating the will to purchase directly. Consumer satisfaction is the core foundation that dominates long-term consumption. E-commerce should focus on the ability of online celebrities to sell their expertise and the adaptability of value and product characteristics when conducting online celebrity marketing.

• The Journal of Korean Medicine
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• v.31 no.2
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• pp.124-136
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• 2010

Objective:: This study aimed to examine the customers' utilization of and satisfaction with oriental medical clinics in South Korea. Method: The data for this study were collected from 1,208 patients of 391 oriental medical clinics through a mail questionnaire survey from September to December 2008. The collected data were analyzed by the frequency analysis and $X^2$-test. Results: The results of the study were as follows. First, the most important reason that patients used oriental medical services was to get both oriental and western medical services simultaneously, because they thought such approach would be more effective for treating their diseases. Second, two important reasons that patients visited oriental medical clinics were "the reputation of and trust in the oriental medical clinics" and "the recommendation of their family and friends". Third, many patients of the oriental medical clinics have concerns about the "high prices and the outcome of oriental medical services". Fourth, the most preferred oriental medical service was "acupuncture". Fifth, it was found that 75% of the respondents were satisfied with the services they had received. They told that the outcome of the care and the kindness of the clinics' staff were very important factors that have an impact on their satisfaction. Conclusion: The study results imply that oriental medical clinics have to make an effort to strengthen their reputation and trust in the community through the scientific validation of oriental medicine, differentiated services mixed with traditional value, customer relationship management, reasonable and acceptable price of the services, staff education, and continuous quality improvement.

• Industry Promotion Research
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• v.2 no.2
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• pp.23-29
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• 2017

This study aims to suggest a new method to escape crisis of manufacturing industry. We focused on the field - oriented management innovation promotion performance divided into qualitative performance and quantitative performance. The site-centered management innovation is an organization that helps managers to quickly solve the problems faced by field management personnel by switching from manager-centered management method to on-site management personnel-oriented management. Find out the waste factors of the work and improve the process and set the process standards according to the customer's needs. Before working on the site, an employee should know exactly the process standard of what I will do, and frequently inspect the raw materials to make sure they meet the specifications. After the self-inspection is carried out, the standard is reviewed. If there is no abnormality, the cross-validation is carried out by the method which is carried over to the next step. The results of this study can be used to enhance the competitiveness of manufacturing companies. New management innovation techniques are required to adapt to the rapidly changing international business environment, and this study has implications for this research.

• Journal of Nutrition and Health
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• v.55 no.6
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• pp.601-616
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• 2022

In the era of the fourth industrial revolution technology, the inclusion of personalized nutrition for healthcare (PNH), when establishing a healthcare platform to prevent chronic diseases such as obesity, diabetes, cerebrovascular and cardiovascular disease, pulmonary disease, and inflammatory diseases, enhances the national competitiveness of global healthcare markets. Furthermore, since the government experienced COVID-19 and the population dead cross in 2020, as well as numerous health problems due to an increasing super-aged Korean society, there is an urgent need to secure, develop, and utilize PNH-related technologies. Three conditions are essential for the development of PNH technologies. These include the establishment of causality between obesity genome (genotype) and prevalence (phenotype) in Koreans, validation of clinical intervention research, and securing PNH-utilization technology (i.e., algorithm development, artificial intelligence-based platform, direct-to-customer [DTC]-based PNH, etc.). Therefore, a national control tower is required to establish appropriate PNH infrastructure (basic and clinical research, cultivation of PNH-related experts, etc.). The post-corona era will be aggressive in sharing data knowledge and developing related technologies, and Korea needs to actively participate in the large-scale global healthcare markets. This review provides the importance of scientific evidence based on a huge dataset, which is the primary prerequisite for the DTC obesity gene-based PNH technologies to be competitive in the healthcare market. Furthermore, based on comparing domestic and internationally approved DTC obese genes and the current status of Korean obesity genome-based PNH research, we intend to provide a direction to PNH planners (individuals and industries) for establishing scientific PNH guidelines for the prevention of obesity.