• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.3
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• pp.55-61
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• 2006

The purpose of this study is to propose guidelines for Introducing the JIT(Just-In-Time) purchasing to enhance the competitiveness of Korean manufacturing companies. This study employed an extensive survey on the use of the JIT purchasing systems among different Korean manufacturing companies to understand the current status of the JIT purchasing in use and to identify the benefits from implementing JIT purchasing. The survey has covered 163 manufacturing companies of different sizes from various sectors of Korean industries including electronics, automobiles, machineries, and textiles. The research results support that the JIT purchasing would contribute to increase the purchasing performances of Korean manufacturing companies.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.39-52
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• 2013

Purpose: The purpose of this study was to investigate if purchasing companies' efforts of supplier development activities to supplier companies have positive impacts on the purchasing companies' performance as the first step. In the second step, we tried to confirm if the concept of Supply Chain Corporate Social Responsibility activities and Coexistence activities take the roles of moderate variable on relationship between supplier development and three performances respectively. Methods: The collected data through survey were analysed using multiple regression for the first step of the study and moderate regression for the second one of it. Results: The results of this study are as follows; supplier development efforts effect on all three performances positively. Moreover, Supply Chain CSR has significant moderate effect on relationship between supplier management and corporate performances, while Coexistence does between supplier management and logistics performances. In the case of relationship between supplier management and production performances, both Supply Chain CSR and Coexistence show significant moderate effect. Conclusion: Manufacturing companies in Korea need to make effort of supplier development in selective way when they want to practice Supply Chain CSR and Coexistence concurrently considering strategies and objectives.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.168-182
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• 2016

The domestic market for performances and concerts is rapidly growing. However, despite of the various efforts to attract audience, the market still struggles in securing consumers for classical music performances. In this context, the following thesis first explores the factors that determine the choice of performances through open-ended questions to categorize the types of consumers based on the results. Then, effects of different factors of choices for each type of consumer are studied to find out how these factors affect the consumers' purchasing decisions. As a result, 35 factors out of the 40 factors were ultimately confirmed as the factors that determine the consumers' choice for purchasing classical music performances. Then, the 35 factors were classified into seven categories. Moreover, an empirical analysis showed that personal factors, factors regarding contents of the performance, information factors, environmental factors and marketing factors had significant effects on the consumers' purchasing decisions. The degree of influence of the factors for each type of audience varied. This study conclusively seeks to contribute to developing a more thorough marketing strategies for performance arts institutions and performance venues.

• Journal of the Korea Fashion and Costume Design Association
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• v.9 no.3
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• pp.115-132
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• 2007

The purpose of this research is that to study of musical performer's purchasing behavior, satisfaction and design preference, and to give the information for better performance costume market based on that result. The target for the survey is limited only for above 4th grade female students and have experienced more than three times of performances. Total 364 questionnaires are used for this research. The SPSS was used for the analysis. The results were, first, in the survey of place of purchasing, specialty shop for musical performance shop was the most. The most group for the budget that they spent was under 100,000 Won. Rational price for costume would be 150,000-300,000 Won. Most people purchase costume before 2 weeks and compare 3-4 stores mostly. There were not many complaints about being comfort for costume itself. The preference for costume was different depends on not only scale of performance but also whether solo, duet or trio or more. Also harmony with other person costume was most consideration factor when they perform duet or more. For the choice of shop factor following were considered the most important; various selections, kindness of sales persons and possibility for trying various costumes. However, locations of shop or delivery service were not important relatively. For the choice of costume factor, design color, comfort and functionality were considered the most important but price, quality and decoration were not. For 'the satisfaction after purchase costume' factor, people's opinions, best appearance on the stage and meeting image with themselves were considered the most important. Second, on the subject for 'design preference of costume based on type of performance', people chose different color of dress depends on what types of performance. In case of solo, they prefer vivid primary color; in case of trio or more, they prefer black; in case of duet, they prefer pastel tone. As for preference of sleeve design, all of them prefer non-sleeve type.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.226-247
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• 2024

Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.69-81
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• 2005

As the competition in business becomes severe, companies are focusing their capacity on customer relationship management (CRM) for survival. One of the important issues in CRM is to build a purchase prediction model, which classifies customers into either purchasing or non-purchasing groups. Until now, various techniques for building purchase prediction models have been proposed. However, they have been criticized because their performances are generally low, or it requires much effort to build and maintain them. Thus, in this study, we propose the support vector machine (SVM) a tool for building a purchase prediction model. The SVM is known as the technique that not only produces accurate prediction results but also enables training with the small sample size. To validate the usefulness of SVM, we apply it and some of other comparative techniques to a real-world purchase prediction case. Experimental results show that SVM outperforms all the comparative models including logistic regression and artificial neural networks.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.109-118
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• 2020

In this study, the selection attributes of contemporary dance audience were constructed based on prior study and the selection attributes of contemporary dance performance were identified through EFA(Exploratory Factor Analysis). Therefore, Six attributes were derived: physical evidence, tickets, people, information, product, and reputation. Based on these attributes, the selected attributes were identified through 'ETPB(Extended Theory of Planned Behavior)' to see if they affect ticket purchase behavior. In result, Among the selection attributes of contemporary dance performances, three attributes of reputation, people and product influenced the audience's attitude, while only product and human attributes influenced the purchase intention of tickets. Among the variables of ETPB to enhance the ability to purchase intention of tickets, audience attitude, perceive behavior control, and prior knowledge have had a positive effect on purchase intention of tickets, except for subjective norm. Therefore, it is meaningful that this study presented and verified empirically the attributes of select centered on visitors, which can improve the intention of purchasing tickets for contemporary dance performances.

• Korean Management Science Review
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• v.29 no.3
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• pp.45-65
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• 2012

Test and evaluation of weapon system is an important task to evaluate the performance of overseas weapon system purchasing project. Especially, quantitative evaluation of performances is hardly completed in defense projects where multiple criteria are conflicted each other. In order to solve this problem, we apply Axiomatic Design (AD) and Inner Dependence AHP method. First, finite functional requirements (FRs) are categorized in hierarchy structure by selecting proper design parameters (DPs) to implement their corresponding FRs. If there are no ways to select DPs when design is coupled between FRs and DPs, then inner dependence is allowed to overcome the strict rule of independence in AHP. Second, the weights of DPs are calculated by applying both Inner Dependence AHP method for coupled design and normal AHP method for uncoupled or decoupled design. Finally, information axiom of AD is applied to the proposed weapon systems by calculating information contents for all parameters. Weapon system with minimum sum of information contents is considered as the best solution. The proposed method in this study should be used in multiple criteria decision making problems involving various conflicting criteria.

• Journal of Distribution Science
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• v.15 no.5
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• pp.17-28
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• 2017

Purpose - Considering the environmental issues in corporate management is now a necessity, not an option. In addition, consumers' interest in health and environment has increased rapidly. This study aims to investigate how the management style that pursues environmental protection affects the various outcomes at each management process such as planning, producing and supervising process. Research design, data, and methodology - We surveyed 319 manufacturing companies from April 1 to April 30, 2016. Green purchasing, environmental technology management and management support are selected as independent variables and firm performances as dependent variables. Three analyses including factor, regression and moderating were conducted. Results - Regression analysis was performed to set up hypotheses. Consequently, the total six hypotheses were adopted and then innovative management style showed moderating effect. Conclusions - Companies should consider environmental factors to improve the financial performance in the long term. Especially the cooperative style enhances financial performance by implementing eco-friendly design in cooperation with customers. Also, eco-friendly activities with suppliers could have direct environmental protection effects. Therefore, a manufacturer needs to cooperate with both suppliers and customers to maximize the protection effect. The production of eco-friendly products and implementing eco-friendly design with customers positively affect product quality.