• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.141-148
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• 2003

Customer retention is a common concern for many industries and a critical issue for the survival in today's greatly compressed marketplace. Current customer retention models only focus on detection of potential defectors based on the likelihood of defection by using demographic and customer profile information. In this paper, we propose a dynamic procedure for defection detection and prevention using past and current customer behavior by utilizing SOM and Markov chain. The basic idea originates from the observation that a customer has a tendency to change his behavior (i.e. trim-out his usage volumes) before his eventual withdrawal. This gradual pulling out process offers the company the opportunity to detect the defection signals. With this approach, we have two significant benefits compared with existing defection detection studies. First, our procedure can predict when the potential defectors could withdraw and this feature helps to give marketing managers ample lead-time for preparing defection prevention plans. The second benefit is that our approach can provide a procedure for not only defection detection but also defection prevention, which could suggest the desirable behavior state for the next period so as to lower the likelihood of defection. We applied our dynamic procedure for defection detection and prevention to the online gaming industry. Our suggested procedure could predict potential defectors without deterioration of prediction accuracy compared to that of the MLP neural network and DT.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.115-136
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• 2014

The game industry has grown steadily and the online game has become one of the most attractive game segments for its remarkable growth. Customer management in the online game industry, however, has received little attention from the academic field. The purpose of this study is to analyze the drivers of customer defection in the online game setting and suggest not only theoretical but also managerial insights into increasing customer retention rates. Prior to empirical analysis, the authors hypothesized that 3 variables of interests (Learning, Playing, Achievement) would explain the customer defection according to preceeding researches. To demonstrate these hypotheses, the authors obtained data from one of the biggest game publishers in Korea, and the empirical analysis model was developed considering context of research settings. The results of analyses provide the following insights. First, the key behavioral variables of Learning, Playing, and Achievement play substantial roles in explaining the customer defection. Next, the effects of these variables vary between customer types: novice and experienced customers. The defection decisions by novice customers are predicted by all key behavioral variables and Playing serves as the most influential indicator of the defection decisions. However, experienced customers are influenced by Playing and Achievement, while Learning has no impact on the defection decisions. Finally, the authors investigated hypothetical customer retention strategies, using the empirical results. The market outcomes indicate that the customer retention strategies work well with novice customers and it is hard-to-impossible to prevent experienced customers from defection using their behavioral data. These findings together deliver several meaningful insights to management as follow. First, the management should support customers to get involved in Learning activities at the very first stage. Second, customer's Achievement and appropriate compensation for it would work as defection barriers. Last, to optimize the outcomes of firm's marketing investments, it is better to focus on retention of novice users not experienced ones.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.445-453
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• 2002

Past and current customer behavior is the best predicator of future customer behavior. This paper introduces a procedure on personalized defection detection and prevention for an online game site. The basic idea for our defection detection and prevention is adopted from the observation that potential defectors have a tendency to take a couple of months or weeks to gradually change their behavior (i.e. trim-out their usage volume) before their eventual withdrawal. For this purpose, we suggest a SOM (Self-Organizing Map) based procedure to determine the possible states of customer behavior from past behavior data. Based on this representation of the state of behavior, potential defectors are detected by comparing their monitored trajectories of behavior states with frequent and confident trajectories of past defectors. The key feature of this study includes a defection prevention procedure which recommends the desirable behavior state for the ext period so as to lower the likelihood of defection. The defection prevention procedure can be used to design a marketing campaign on an individual basis because it provides desirable behavior patterns for the next period. The experiments demonstrate that our approach is effective for defection prevention and efficient for defection detection because it predicts potential defectors without deterioration of prediction accuracy compared to that of the MLP (Multi-Layer Perceptron) neural network.

• Korean Management Science Review
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• v.21 no.3
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• pp.85-99
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• 2004

The retention of customer is an increasingly pressing issue in today's competitive environment. The proposes of this paper is a personalized defection detection and the procedure of prevention based on economic analysis of customer defection possibility, and behaviour state transition cost. This procedure is based on the observation that potential defectors have a tendency to take a couple of months or weeks to gradually change their behaviour before their eventual withdrawal. In this procedure, the SOM(Self-Organizing Map) is used to determine the possible states of customer behaviour from past behaviour data, and to prevent the defection of potential defectors, the proposed procedure recommends the desirable behaviour state for the next period based on the analysis of transition cost. and likelihood of defection. The case study has been conducted for a Korean on-line game provider to evaluate of this procedure.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.213-229
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• 2009

The purpose of this paper is to identify the relationship among five factors of web design, e-satisfaction, e-loyalty, and customer defection and provide the implications of marketing strategies in online shopping. The research findings are as follows: first, ease of use of web design affects positively e-satisfaction more than the other factors except financial security. Second, e-satisfaction affects positively e-loyalty. Third, e-satisfaction does not affect customer defection. Fourth, informativeness, styling, ease of use, and trust of web design affect indirectly e-loyalty by mediating e-satisfaction. Therefore, because there is a good circular relationship among web design, e-satisfaction, and e-loyalty, it is very important to enhance web design for customers. When customers satisfy highly with the factors of web design, e-loyalty is higher and customer defection is lower. Further, in a curriculum of web design it is needed to reflect the findings of this paper.

• Journal of Distribution Research
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• v.16 no.1
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• pp.179-222
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• 2011

This research investigates the influence of relational characteristics on 'co-defection', customer defection following salesperson turnover, in the context of salesperson-customer relationship. Based on the social exchange theory, it was hypothesized that perceived relational benefits and switching costs affect directly the customer's intentions to defect. Key constructs in relationship marketing such as customer satisfaction, trust, and loyalty were hypothesized to affect the customer's intention to defect as well as perceived relational benefits and switching costs. The results of structural equation modeling using a survey sample of 503 insurance customers who purchased life insurance policies through salespersons unveiled that the customer satisfaction with salesperson and the customer trust in salesperson strongly influence the salesperson-owned customer loyalty. However, they did not have significant direct effects on co-defection intentions. All paths from salesperson-owned customer loyalty to perceived relational benefits and perceived switching costs were also significant. Salesperson-owned customer loyalty did not have significant direct effects on co-defection intentions, but it had significant indirect effects on co-defection intentions through relational benefits and switching costs. Three sub-dimensions of perceived relational benefits had significant positive effects on co-defection intentions while the perceived switching costs had significant negative effects on co-defection intentions. The significance of our research findings were verified by comparing the hypothesized model and the rival model in the past studies.

• Journal of Global Scholars of Marketing Science
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• v.16 no.2
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• pp.27-54
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• 2006

As maintaining customer long term relationship is critical factor for improving to firm value as well as customer lifetime value, the academicians and practitioners have paid attention to customer defection. It is said that service failures are key factors to customer defection or customer switching(Keaveney 1995 etc.). This study examines that the effect on customer defection of service failures is differential according to the various customer-firms relationship characteristics. We consider relationship duration, usage level, decision making influence, industry knowledge and switching cost as customer-firm relationship characteristics based on marketing literature. Predictions are developed and tested using Internet service provider(ISP) user survey data(n=212). Results show that the customer-firms relationship characteristics/above variables) play a moderating roles in the service failures and customer defection links.

• Journal of the Korea Society of Computer and Information
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• v.6 no.3
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• pp.29-34
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• 2001

Competition is increasing in telecommunication service market. Effective customer retention strategies are based on a clear understanding of customer defection. Data mining offers service providers great opportunities to get closer to customer. In this paper, we propose an efficient data mining algorithm using neural network. Especially Analysis of CRM Using Neural Networks in Telecommunication service Market and a practical application of neural network is described telco, churn management This paper builds model of customer defection management and analyzes customer defection with data mining

• The Korean Journal of Food And Nutrition
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• v.24 no.4
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• pp.670-679
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• 2011

This study investigated the hotel buffet restaurant's service quality, emotional reaction of customer, recommendation intention, and defection intention. The survey was conducted from January 3 to February 7 in 2011, and 400 respondents were used in the data analysis. As a results of this study, the hotel buffet restaurant's service quality was classified by the interaction, outcome, and physical environment quality. The emotional reaction of hotel buffet restaurant's customer was classified by the positive and negative emotion. The all factors of hotel buffet restaurant's service quality had a positive impact on positive emotion, while it had a negative impact on negative emotion. The positive emotion reaction of hotel buffet restaurant's customer had a positive impact on the recommendation intention, while the negative emotion had a negative impact on the recommendation intention. And the negative emotion had a positive impact on the defection intention in hotel buffet restaurants. In addition, there were partially differences in the service quality and emotional reaction by general characteristics. There were significant differences in the recommendation intention by marriage status and monthly income. Therefore, the hotel buffet restaurants have to design a strategy of service for increasing customer's positive emotion and recommendation intention.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.413-425
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• 2016

This study investigated what effects the relational benefits perceived by the customers of solely operated beauty salons have on customer satisfaction, recommendation intention, and defection intention through the convergence of cosmetology and business management. For this, a total of 322 customers of solely operated beauty salons were chosen as final valid samples. For data analysis, frequency analysis, reliability analysis, confirmatory factor analysis, and correlation analysis were performed using SPSS 15.0 and AMOS 18. For a hypothesis test, lastly, path analysis was conducted using structural equation modeling. The study results found the following: First, among the relational benefits perceived by the customers of solely operated beauty salons, confidence benefits and social benefits had a positive effect on customer satisfaction. Second, the relational benefits perceived by the customers of solely operated beauty salons had a positive effect on recommendation intention. Third, confidence benefits and social benefits had a negative effect on defection intention. Fourth, customer satisfaction had a positive effect on recommendation intention. Fifth, customer satisfaction had a negative effect on defection intention. Sixth, in relationship between the relational benefits perceived by the customers of solely operated beauty salons and recommendation/defection intention, customer satisfaction revealed partial mediating effects.