• Journal of Global Scholars of Marketing Science
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• v.14
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• pp.101-124
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• 2004

This study is to investigate structure relationship between factors influencing or mediating store loyalty in service encounter. The result of study suggests salesperson's voluntary service has an effect on store loyalty through interpersonal relationship and store satisfaction. On the other hand, nonvoluntary service doesn't statistically influence interpersonal relationship but influences store loyalty through store satisfaction. Interestingly this results shows that store loyalty is consisted of cognitive loyalty, affective loyalty, intentional loyalty, and behavioral loyalty and each loyalty have an affect in sequence each other. Managerial implications on research result is followed as first, as an evaluation method of salesperson, it is useful to evaluate salesperson's behavioral performance. second, to build store loyalty, it must make an effort for marketer to differentiate through store promotion in terms of customer's cognitive perspectives. It is meaningful for these results to apply to current retailing situations practically.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.925-933
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• 2018

In this paper, we propose a new smart ordering application system for granting the customer numbers. The proposed system assigns sequence number of customers who visit at offline store as using speaker and microphone of smart device. This system has more advantage than the existing ordering system. Because the proposed system does not need any customer information like as phone number or SNS ID, it can protect customer privacy information. In this system, we use high frequency which is inaudible to the human ear as communication signal between speaker and microphone. To confirm performance evaluation, we perform a test with ten smart devices like as iPhone 6, 7, 8, Galaxy s8 and the result shown a success rate of 98.7 percent. Therefore, the proposed system can be useful service technology at the various offline store which need to assign a sequence number for customers, because many customers visit at the store.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.25-35
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• 2011

In the Semantic Web, storage models are required to efficiently store and retrieve metadata and ontology represented using OWL that can provide expressive power and reasoning support. In this paper, we propose an OWL storage model that can store and retrieve many restrictions and semantic relations defined on ontology with metadata. In addition, we propose some methods and rules to improve query processing efficiency of the proposed storage model. The proposed storage model can store and process large amounts of ontology and metadata because it consists of tables based on the relational database. And the proposed model can quickly provide more accurate results to users because of performing two different types of ontology reasoning and using the prime number labeling scheme to easily identify hierarchy relationships between classes or properties. The comparative evaluation results show that our storage model provides better performance than the existing storage model.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.937-938
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• 2006

There are lots of intelligent service robots in these days. People are unwilling to do routine works, dangerous works, and difficult works. But a robot can do these works instead of human. We introduce a intelligent service robot for unmanned store management. The robot can detect and recognize a person, deliver some goods, manage a store, and answer the telephone. We have developed the robot and tested the performance.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.935-936
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• 2006

In this paper, we have applied a real-time face processor includes detection, recognition, and learning to a intelligent store management service robot. We use the Haar classifier and adaboost learning algorithm for face detection. For face recognition and learning, a PCA algorithm and a SVDD algorithm is used. We have developed a store management service robot and applied these algorithms to verify the performance.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.11-20
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• 2015

In this paper, we propose a context awareness system to transfer accurate information of the app store based on collective intelligence. By using collective intelligence the system minimizes the errors that could occur when an individual process the problems, recommends APIs for developers and builds the app store for not only customers but also developers. In addition, this system applies the ontology technique to aware the context of consumers, recommends the app suitable for the consumer and provides the information for app developers. By utilizing the deduction technique of the Jena, the context awareness system infers the context of a consumer and constructs the app store system which improves the existing app stores. In the point of service transfer and accuracy, the proposed app store system module show better performance than the existing app store.

• Industrial Engineering and Management Systems
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• v.8 no.2
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• pp.80-92
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• 2009

This paper addresses the inventory rationing issue embedded in the regional supply chain inventory replenishment problem (RSIRP). The concerned supply chain, which was fed by the national supply chain, consisted of a single warehouse distributing a single product to multiple stores (M-stores) with independent and normally distributed customer demand. It was assumed that the supply chain operated under the order-up-to level inventory replenishment system and had only one truck at the regional warehouse. The truck could make one replenishment trip to one store per period (a round trip per period). Based on current inventories and the vehicle constraint, the warehouse must make two decisions in each period: which store in the region to replenish and what was the replenishment quantity? The objective was to position inventories so as to minimize lost sales in the region. The warehouse inventory was replenished in every fixed-interval from a source outside the region, but the store inventory could be replenished daily. The truck destination (store) in each period was selected based on its maximum expected shortage. The replenishment quantity was then determined based on the predetermined order-up-to level system. In case of insufficient warehouse inventories to fulfill all projected store demands, an inventory rationing rule must be applied. In this paper, a new inventory rationing rule named Expected Cost Minimization (ECM) was proposed based on the practical purpose. The numerical results based on real data from a selective industry show that its performance was better and more robust than the current practice and other sharing rules in the existing literature.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2610-2615
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• 2010

This paper proposes an object-oriented software development guidance and an evaluation index for the productivity related to Spring 2.5 and Seam 2.0 framework. Lightweight container architecture, such as the EJB, but not heavy, to provide all of the architecture is possible. Currently in production until the lightweight container architecture, known most commonly used architecture framework is Spring and Seam. However, there is no comparison research about the performance of Spring 2.5 and Seam 2.0 framework with same identical platform. In this study, the Java Pet Store blueprint application development platform environment based on the same ordering system JPetStore Spring 2.5 and Seam 2.0 is in the design and implementation. In addition, comparison and standardization of software development productivity assessment is to provide guidance.

• Journal of Distribution Research
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• v.9 no.1
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• pp.47-65
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• 2004

The purpose of this study is to analyze the investment returns and profitability of major Korean retail companies and to discuss the implications of their published accounting data. We have found that Korean department store companies shows the sound ROIC (return on invested capital) compared with U,5. counterparts. However, major discount store companies have problems in terms of poor ROIC ratios in spite of their rapid growth for the last decade. The results of ROIC performance of 3 major department stores and 3 discount stores are compared and the implications of the study are discussed. Furthermore, the published accounting data of major U.S. department stores and discount stores are analyzed in the context of benchmarking for Korean companies.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.169-177
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• 2020

The purpose of this study is to forecast the sales of convenience store flagship products with nonlinear characteristics and time series characteristics. According to the results, the sales of 'Ice Cup' began to increase from March, reached the highest value in summer, especially July and August, and then decreased, revealing a seasonal pattern. Cigarettes showed a seasonal pattern of higher sales in summer and lower sales in winter and was predicted to decrease in sales in the future. This study provides an academic implication in that it focused on the top-selling products that affected an increase in financial performance in a specific convenience store, a method that has been hardly adopted by the existing studies.