• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.4
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• pp.131-137
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• 2004

The impacts of electric service interruption to customers depend on customer and interruption characteristics. Customer characteristics include demographic aspects (residential type, and number of household members) and power supply types whereas interruption characteristics include frequency, duration, time, and day of interruption. Accordingly evaluation of these customer interruption costs is very complicated and subjective. For residential customers, customer survey method seems most appropriate because interruption impact to residential customers is intangible. In other. words, the value of housework or lost leisure due to interruption is individual. Accordingly, this paper selected the customer survey method to assess the interruption costs for residential customers.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.205-212
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• 2020

The article aims to identify the main factors affecting customers' decision to use mobile banking service in Vietnam, a case study in Thanh Hoa province. Based on theoretical frameworks of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study has been conducted with 370 questionnaires to consumers who have not yet used and are currently using mobile banking in Thanh Hoa province. The research results indicates that several factors have been evaluated to be more important than others, of which, the social influence is the strongest, the second is the compatibility and some others factors such as perceived ease of use, perceived trust, etc., all affecting the intention to use mobile banking in Thanh Hoa. Based on these important results, the article propose a number of recommendations: (i) Exploiting the advantages of social influence on the increase of intention to use; (ii) Increasing compatibility and minimizing costs for customers when they use Mobile Banking; (iii) Developing a strategy to increase the users' perceived ease of using banking services; (iv) Issuing a policy on increasing the security of Mobile Banking system to meet customers' needs; and (v) Developing an individual customer management system to improve service quality.

• The Journal of Information Systems
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• v.24 no.3
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• pp.47-74
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• 2015

Purpose By participating in the business ecosystems, customers make both positive and negative impacts in the ecosystem. In particular, users of platform businesses participate in the business ecosystem as partial employees who voluntarily create and manage content. According to the organizational behavior literature, employees' psychological ownership toward the organization has an influence on the organizational competitiveness. Thus, with an assumption that customers gain psychological ownership toward the business that they participate in, it is important to analyze the process and the factors that influence their psychological ownership. This study proposes a research model that describes the process: customers undertake customer socialization, which then lead them to participate in the business-level and the business ecosystem-level activities. Through the participation, customers gain psychological ownership toward the business. Design/methodology/approach Based on a structural equation model, this study analyzes the data regarding the factors in the research model. Data was collected by surveying college students who represent themselves as Facebook and DaumKakao users. By analyzing the collected data, the relationships are validated between customer socialization and customer participations (i.e., both business-level and business ecosystem-level participation), and between the participations and customers' psychological ownership. Findings Based on the validation, this study confirms the importance of managing customers' psychological ownership and offers customers' participation by their socialization as a solution for increasing customers' psychological ownership. Also, this study proposes the business ecosystem research model as the general research framework for future research and expands the scope of strategic management from the individual level strategy to the business ecosystem wide perspective.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.135-154
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• 2003

Credit scoring system (CSS) starts from an analysis of delinquency trend of each individual or industry. This paper conducts a research on credit card delinquency of bank customers as a preliminary step for building effective credit scoring system to prevent excess loan or bad credit status. To serve this purpose, we use association rules as a rule generating data mining technique. Specifically, we generate sets of rules of customers who are in bad credit status because of delinquency by association rule mining. We expect that the sets of rules generated by association rule mining could act as an estimator of good or bad credit status classifier and basic component of early warning system.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.7
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• pp.1220-1231
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• 2010

This study examined customer misbehaviors in retail settings by identifying behavioral patterns and exploring behavioral backgrounds and consequences from the employee's perspectives. Qualitative data were collected from an individual interview method, and 222 interviews were analyzed. Customer misbehavior was categorized into unethical returns, problem behaviors in service encounters, unreasonable demands, shoplifting/fraud, ill-mannered behaviors, and selfish behaviors. Behavioral backgrounds included dissatisfaction, unreasonable expectations, actively benefiting of service failures, taking advantage of service standards, illegitimate complaints, monetary gains, transferring responsibility, and demanding special treatment. Employees experienced stress facing misbehaving customers with no other choice except to accept misbehaviors and learned misbehaviors as customers themselves. The study further discusses the implications.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.7
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• pp.1126-1137
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• 2010

Customer misbehavior is a behavior that disrupts generally accepted behavioral norms in consumption situations. This study examined customer misbehavior in retail settings by identifying behavioral patterns and exploring behavioral backgrounds and consequences from a customer viewpoint. Qualitative data were collected from individual in-depth interviews, and 149 interviews were analyzed. Customer misbehavior was categorized into unethical returns, problem behaviors in service encounters, shoplifting/fraud, ill-mannered behaviors, and selfish behaviors. Motivations included monetary gain, adventurism, perceived acceptability of misbehavior, planned unfair complaints, and retaliation. Customers showed a negative image to unkind employees and stores yielding to misbehaviors that were learned and socialized among customers. The study further discusses implications.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.149-154
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• 2003

Credit scoring system (CSS) starts from an analysis of delinquency trend of each individual or industry. This paper conducts a research on credit card delinquency of bank customers as a preliminary step for building effective credit scoring system to prevent excess loan or bad credit status. To serve this purpose, we use association rules that ore generating method. Specifically, we generate sets of rules of customers who are in bad credit status because of delinquency by using association rules. We expect that the sets of rules generated by association rules could act as an estimator of good or bad credit status classifier.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.43-48
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• 2019

An IoT-based server system for store management was developed in this study. Its client-server structure having a product categorization function allows the system to read the NFC tags attached to individual products and provides information about them to customers automatically. The system also provides an effective promotional effect as it not only offers necessary information about the items the customers are seeking but also displays the advertisements related to them. This server system was designed specifically designed for the use in a smart shopping Mall or a department store so that the store owners can manage their sales operation more effectively while their customers enjoy shopping more conveniently. It is expected that the technology used for this IoT-utilized server system can be one of the efficient and effective platform technologies in the current and future store management systems.

• IE interfaces
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• v.17 no.3
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• pp.314-329
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• 2004

The rapid growth of investments in mobile service to reach a large and growing body of customers, coupled with low communication costs, has made user acceptance an increasingly critical management issue. The study draws upon the task-technology fit (TTF) model as its theoretical basis and its empirical findings to pragmatically explain the key factors that affect the performance and user acceptance of mobile service in medical field. A total of 110 usable responses were obtained. The findings indicate that the task, technology, and individual user characteristics positively affect task-technology fit and mobile service usage. The task-technology fit and mobile service usage are the dominant factors that affect mobile service performance. The result points out the importance of the fit between technologies and users' tasks in achieving individual performance impact from mobile service in medical arena.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.3-15
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• 1996

An approximation algorithm is presented for cyclic queueing networks with finite buffers. The algorithm decomposes the queueing network into individual queues with revised arrival and service process and revised queue capacity. Then, each queue is analyzed in isolation. The service process reflects the additional delay a unit might undergo due to blocking and the arrival process is described by a 2-phases Coxian ($C_2$) distribution. The individual queues are modelled as $C_2/C_2$/1/B queues. The parameters of the individual queues are computed approximately using an iterative scheme. The population constraint of the closed network is taken into account by ensuring that the sum of the average queue lengths of the individual queues is equal to the number of customers of the network. Extensive numerical experiments show that this method provides a fairly good estimation of the throughput.