• Asia pacific journal of information systems
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• v.16 no.3
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• pp.49-65
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• 2006

This study proposes a model for customer segmentation using the psychological characteristics of Internet banking customers. The model was developed through two phased clustering method, called SONN-HC by integrating self-organizing neural networks (SONN) and hierarchical clustering (HC) method. We applied the SONN-HC method to internet banking customer segmentation and performed an empirical analysis with 845 cases. The results of our empirical analysis show the psychological characteristics of Internet banking customers have significant differences among four clusters of the customers created by SONN-HC. From these results, we found that the psychological characteristics of Internet banking customers had an important role of planning a strategy for customer segmentation in a financial institution.

• Asia pacific journal of information systems
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• v.11 no.4
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• pp.27-41
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• 2001

CRM is at the core of any customer-focused business strategy and includes the people, processes, and technology questions associated with marketing, sales, and service. In today's hyper-competitive world, organizations looking to implement successful CRM strategies need to focus on a common view of the customer using integrated information systems and contact center implementations that allow the customer to communicate via any desired communication channel. A CRM solution contains a number of sophisticated tools that enable to extract detailed information about customers. This information can be used to gain a better understanding of customers. From this we can determine trends, and so refine business toward customers' needs and target new products to particular customer groups. This paper presents an approach for forming the product-customer groups using neural networks for customer relationship management. The Carpenter-Grossberg's neural network, which has been used for manufacturing cell formation in group technology, is modified and applied for product-customer group formation. As a result of numerical experiments, it is also useful for more complex problems in which customers have different preferences for each product.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.426-429
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• 2001

The customer cabling telecommunication facilities assume an important role in the telecommunication networks. The present technologies for domestic customer cabling facilities are established with the multimedia environment reflected, but are insufficient for accommodation of multimedia services of the ultra high-speed information and communication networks. In the present paper, the status of international and domestic standardization are reviewed and the operational environment of customer premise telecommunication facilities are investigated and analyzed in order to enhance customer cabling facilities in Korea. The problems with the operational environment are analyzed, and how to improve customer cabling telecommunication facilities is suggested based on the above.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.131-140
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• 2014

Customer networks go through constant changes. They may expand or shrink once they are formed. In dynamic environments, it is a critical corporate challenge to identify and manage influential customer groups in a cost effective way. In this context, we apply inverse optimization theory to suggest an efficient method to manage customer networks. In this paper, we assume that there exists a subset of nodes that might have a large effect on the network and that the network can be modified via some strategic actions. Rather than making efforts to find influential nodes whenever the network changes, we focus on a subset of selective nodes and perturb as little as possible the interaction between nodes in order to make the selected nodes influential in the given network. We define the following problem based on the inverse optimization. Given a graph and a prescribed node subset, the objective is to modify the structure of the given graph so that the fixed subset of nodes becomes a minimum dominating set in the modified graph and the cost for modification is minimum under a fixed norm. We call this problem the inverse dominating set problem and investigate its computational complexity.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.361-364
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• 2003

The customer premise facilities assume an important role in the telecommunication networks. The present technical standards for domestic customer cabling facilities are established with the multimedia environment reflected, but are insufficient for accommodation of multimedia services of the ultra high-speed information and communication networks In the present paper, the status of international standardization as well as technical standards in the U.S.A., Japan, other countries are reviewed and the domestic technical standard and emblem is investigated and analyzed in order to enhance customer cabling facilities in Korea. The problems with emblem are analyzed, and how to improve customer cabling telecommunication facilities is suggested based on the above.

• 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

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.573-575
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• 2004

This study presents a new customer segmentation method based on features that can predict the customer's buying behavior. In this method, we consider all variables that can affect the customer's buying behavior including demographics, psychographics, technographics, transaction pattern-related variables, etc. We define several features which are the combination of variables with the interaction effect by using C5.0, use SOM (Self-Organizing Map) neural networks in odor to extract the feature's patterns and classify, and then make features' rules using C5.0 far the prediction of customer buying behavior

• Korean Journal of Human Ecology
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• v.21 no.2
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• pp.269-284
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• 2012

The main purpose of this study was to investigate factors affecting performance of casual wear franchise stores including franchiser support and social network between owners/managers. The study included the franchise stores of 55 casual wear brands located in Seoul, Incheon and Gyeonggi-do. In each store, one manager, owner or staff member with management responsibility was asked to fill out a questionnaire. A total of 184 questionnaires were collected with 165 used in the final analysis. The results showed that franchiser support consisted of educational support, marketing support and customer support. Path analysis indicated that only the educational support had a significant influence on the franchiser-franchise relationship, and in turn, the franchiser-franchise relationship positively influenced customer performance. Marketing support did not have a significant influence on the franchiser-franchise relationship, but did demonstrate a direct influence on customer performance. Social networks positively influenced customer performance, and there was significant a correlation between regions and social networks on customer performance. Sales performance was significantly influenced by customer performance.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.823-832
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• 1997

As enterprises use ATM networks for their private networks and as these private networks use public ATM networks for wide area communication, the need for the customers to be able to manage both private and public networks. Currently, some standardization work is being done towards providing this capability to customers. In this paper, we propose a new customer network management (CNM) system architecture for the management of both ATM a private network and a public network in a uniform way. The particular features of the proposed architecture lies in the efficient support of the complex hierarchial TMN manager-agent relationships at M3 and M4 interfaces, and the support of SNMP and CMIP integration which is necessary for the implementation of a CNM system. The TMN hierarchical many-to-many manager-agent relationships are realized by the utilization of CORBA-Based SMK (Shared Management Knowledge) implementation. We have also implemented the prototype of a ATM CNM system, and measures the performance for the demonstration of the suitability of the proposed architecture.