• Korean Management Science Review
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• v.26 no.1
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• pp.183-196
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• 2009

Customer retention has been a pressing issue for companies to get and maintain the loyal customers in the competing environment. Lots of researchers make effort to seek the characteristics of the churning customers and the loyal customers using the data mining techniques such as decision tree. However, such existing researches don't consider relationships among customers. Social network analysis has been used to search relationships among social entities such as genetics network, traffic network, organization network and so on. In this study, a customer network is proposed to investigate the differences of network characteristics of churning customers and loyal customers. The customer networks are constructed by analyzing the real purchase data collected from a Korean cosmetic provider. We investigated whether the churning customers and the loyal customers have different degree centralities and densities of the customer networks. In addition, we compared products purchased by the churning customers and those by the loyal customers. Our data analysis results indicate that degree centrality and density of the churning customer network are higher than those of the loyal customer network, and the various products are purchased by churning customers rather than by the loyal customers. We expect that the suggested social network analysis is used to as a complementary analysis methodology with existing statistical analysis and data mining analysis.

• Journal of Distribution Science
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• v.14 no.10
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• pp.73-79
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• 2016

Purpose - Customer satisfaction has been considered important as a way to retain current customers. Specifically, the retention of current customers through customer satisfaction has been considered important in an industry where competition between companies is fierce. Major Korean airlines have confronted fierce competition with the growth of low cost carriers (LCCs). In order to survive, these airlines need to retain their customers. This research aims to investigate the relationships between customer satisfaction and the customer intention to remain loyal. Moreover, this study examines how the influence of customer satisfaction on customer loyalty is moderated by gender. Research design, data, and methodology - A regression model is developed in which customer satisfaction, gender, and an interaction of satisfaction and gender are predictors and the customer's intention to remain loyal is a dependent variable. To analyze this research model, data were collected from 402 university students taking a marketing class in universities in Seoul, Chung-Cheong province, and Kangwon province. After eliminating data from students who had never flown and data with missing values, a final sample of 201 was analyzed. The hypotheses were tested using SPSS 21.0. Internal reliability was supported by the results of Cronbach's α. Multiple regression was performed. Results - Empirical results showed that customer satisfaction toward the airline's service had a positive influence on the customer intention to remain loyal to the airlines. Moreover, this influence was moderated by gender. More specifically, a male customer's intention to remain loyal was more determined by his satisfaction toward airline service than a female customer's. Conclusions - This research contributes to the aviation service marketing literature by showing how customer satisfaction influences customer intention to remain loyal and how this influence is moderated by gender. More specifically, male customer loyalty is more determined by airline service satisfaction than female customers. These results have manager implications for major Korean airlines in terms of customer satisfaction and gender as ways to enhance customer retention.

• Culinary science and hospitality research
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• v.24 no.1
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• pp.50-62
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• 2018

The purpose of this study was to overview the meaning of customer loyalty to segment customers based on their loyalty and to analyze the difference of loyal customers' perception of relational benefits in the restaurant industries. A self-administered questionnaire was distributed to 500 adults with dining experience at restaurants. Participants were given a brief description of loyalty and were made to choose a specific restaurant they felt loyal to and one with no loyalty. Attitudinal and behavioral loyalty were used in cluster analysis resulting 4 cluster groups. Each group was named true, spurious, latent, and low loyalty. After the groups were separated, ANOVA was used to see if the score of perceived relational benefit showed difference. All four relational benefit including social, psychological, economic, and customization benefit showed significant difference(p<.001). True loyal customers perceived relational benefit as the highest while low loyal customers showed the lowest. For latent and spurious loyal customers, it was found that latent loyal customers showed higher perception than spurious customers.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.391-399
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• 2020

Every port is competing for attracting loyal customers from other ports to achieve more profits stably. This paper proposes a data-mining scheme to facilitate this process. For resolving the problem, the OD (Origination-Destination) data are gathered from the AIS (Automatic Identification System) data. The OD data are clustered according to the arrival dates and ports. The FP-growth algorithm is applied to mine the frequent patterns of ships arriving at ports. Maintaining a loyal customer list for port updates and accuracy is critical in establishing its usefulness. These lists are critical as they can be used to provide suggestions for new products and services to loyal customers. Finally, based on the frequent patterns of the ships and the mode of arrival times, a formula proposed in this paper to derive shipping companies' loyalty to ports was applied. The case of Kaohsiung port was shown as an example of our algorithm, and the OD data of ships in 2017-2018 were processed. Using the results of our algorithm, other rival ports, such as Shanghai or Busan, may attract customers no longer loyal to Kaohsiung ports in the last two years and attract them as new loyal customers.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.45-60
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• 2005

The purpose of this study is to classify customer by e-mailing responsiveness on time-series analysis and testify the effectiveness of grouping by ROI analysis. Response recency, response frequency and Activity(RFA) of e-mailing systems were adapted for Customer segmentations. ROI analysis were consisted of open, click-through, duration time, personalization, conversion rate and email loyalty index of email systems. Major findings are as follows: RFA analysis is used for customer segmentations that is fundamental process of e-CRM applications. Customer segmentations were loyal customer, odds customer, dormant customer, secession customer and observation customer by RFA grouping. Loyal customer group has high point in all ROI index compared to other groups. These results indicated that customer responsiveness of e-mailing systems were appropriate methods to grouping the customer with demographic variables. Therefore, effective e-mailing marketing strategy of e-Biz have suitable active DB and Behavior targeting is best approach to enforcing the target e-mailing marketing.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.39-62
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• 2002

In retail industry, it has been a major focus of marketing to identify and manage loyal customers effectively. Being established as a mature distribution channel, Internet retailing has launched various one-to-one marketing efforts and enjoyed much more fruitful outcome because it is founded on digitally enabled infrastructure. As more complicated and crowded transactions are expected, Internet retailing is in need of electronically available customer management services. This research presents architectural design of Web services for loyal customer management in Internet retailing. The fundamental models of the services are based on traditional RFM analysis. The Web services provide various agents that automate complicated loyal customer management tasks. beadily available Web services are expected to easily integrate into existing applications of any electronic retailers.

• Journal of Korea Technology Innovation Society
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• v.7 no.3
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• pp.681-709
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• 2004

The purpose of this study is to classify customers by e-mail responsiveness on time-series analysis and testify the effectiveness of grouping by ROI analysis. Response recency, response frequency and Activity(RFA) of e-mailing systems are adapted for Customer segmentations. ROI analysis are consisted of open, click-through, duration time, personalization, conversion rate and email loyalty index of email systems. Major findings are as follows: RFA analysis is used for customer segmentations that is fundamental process of e-CRM applications. Customers can be grouped into loyal customers, odds customers, dormant customers, secession customers, and observation customers by RFA grouping. Loyal customer group has high point in all ROI index compared to other groups. These results indicated that customer responsiveness of e-mail systems were appropriate methods to group the customer with demographic variables. Therefore, effective e-mail marketing strategy of e-Biz should have suitable active DB and Behavior targeting is best approach to enforce the target e-mail marketing.

• Journal of Global Scholars of Marketing Science
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• v.14
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• pp.125-144
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• 2004

The purpose of this study is to classify customer bye-mailing responsiveness on time-series analysis and RFM module and testify the effectiveness of grouping by ROI analysis. RFM (Recency, Frequency, Monetary Value) analysis are used for customer classification that is fundamental process of e-CRM application. ROI analysis were consisted of open, click-through, duration time, conversion rate, personalization and e-mail loyalty index. Major findings are as follows; Customer segmentation were loyal customer, odds customer, dormant customer, secession customer and observation customer by Activity email module. And Loyal, dormant and secession customer are segregated by RFM module. Loyal customer group have higher point of all ROI index than other groups. These results indicated that customer responsiveness of e-mailing and RFM analysis were appropriate methods to grouping the customer. Mid-small Internet Biz adapted marketing strategy by optimization of consumer information.

• Knowledge Management Research
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• v.9 no.2
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• pp.129-146
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• 2008

Customers' evaluation of Website with satisfaction is critical in electroniccommerce. Previous research has studied in a distinct approach; especially IT oriented constructs-perceived usefulness, easy of use and marketing oriented constructs-product, shopping experience, service quality. Despite those important previous studies regarding the usage and the purchase of goods and services, how consumers are satisfied and why consumers leave Web sites without purchasing have not been extensively researched. This study explored those determinants of consumer satisfaction with Web site using expectation-disconfirmation theory (EDT). The present paper extends the range of EDT from antecedents of expectation to consequence of satisfaction. The result suggests that experience and familiarity has an impact on expectation as well as perceived performance and satisfaction. Second, higher expectation makes a negative impact on disconfirmation of expectation. Third, positive disconfirmation of expectation makes a positive impact on satisfaction. Forth. satisfaction produces loyalty and repurchasing intention. Finally, loyal customer has stronger intention to repurchase than satisfied customer.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.4
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• pp.408-420
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• 2011

This study identifies the fashion luxury customer segments grouped by expenditures and the number of purchasing brands to verify the effects of perceived luxury consumption values on the intention to maintain a brand relationship for each group. A survey questionnaire was developed and implemented to collect data to measure fashion luxury expenditures, number of purchasing brands, luxury customer values, intention to maintain brand relationships, and demographic variables. A total of 326 responses were analyzed by factor analysis, multiple regression, one-way ANOVA, and $X^2$ analysis with SPSS18.0. Respondents were grouped by luxury expenditures; in addition, the number of purchasing brands were grouped into four segments of Switching/Heavy (31.6%), Switching/Light (19.9%), Loyal/Heavy (31.3%), and Loyal/Light (7.2%) Customer Group, that was different in terms of age and marital status. When the luxury customer value for the most patronized luxury brand was factor analyzed, five distinctive sub dimensions were identified, such as Social Value, Aesthetic/Expressive Value, Experiential Value, Quality Value, and Economic Value. For the Loyal/Heavy Group, the Experiential Value had a significant effect on the customer intention to maintain a brand relationship. For the Loyal/Light group, the Aesthetic /Expressive and Economic Value had a significant effect, and for the Switching/Heavy and Switching/Light Group, Quality and Economic Value had a significant effect on the customer intention to maintain a brand relationship. In conclusion, each luxury customer value in the behavioral segments works differently in influencing the intention to maintain a brand relationship. In addition, the implications for retail strategy were discussed based on the findings.