• Korean Management Science Review
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• v.26 no.3
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• pp.169-184
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• 2009

Recently, mobile telecommunication businesses contend with each other to expand their customer base by using aggressive marketing strategies. In order to determine if there strategies are effective, customer's switching behavior needs to be studied. This study identifies and analyzes direct, indirect factors that may customer switching behavior : attractiveness of alternatives, network externality, and switching cost. Results reveals that attractiveness of alternatives, network externalities have a direct impact on customer switching behavior. These two factors also have moderating effects on customer switching behavior but the switching cost does not In short, network externalities and alternatives strategically determine the success of 3.5G service. In this regard, mobile business should improve their own attractiveness of alternatives by developing specialized service in 3.5G service.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.176-180
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• 2023

Aim of this study to examine the mediating role of network service between perceived quality, retailer service and customer satisfaction during COVID-19. Primary data gathered through adopted questionnaire from previous studies and 200 university students were asked to fill online questionnaire during COVID-19 situation in country. Structural Equation Modelling technique applied in order to test the proposed hypothesis generated from existing literature review. Findings revealed full mediation effect of network service for both perceived quality and retailer service on customer satisfaction during COVID-19. New insights of this study are key role of network services is identified and university students' satisfaction is measured for online classes in developing country, Pakistan. In future serial mediation is suggested for validity of existing results in developed and developing countries.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.55-60
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• 2022

Churn prediction is a critical long-term problem for many business like music, games, magazines etc. The churn probability can be used to study many aspects of a business including proactive customer marketing, sales prediction, and churn-sensitive pricing models. It is quite challenging to design machine learning model to predict the customer churn accurately due to the large volume of the time-series data and the temporal issues of the data. In this paper, a parallel artificial neural network is proposed to create a highly-accurate customer churn model on a large customer dataset. The proposed model has achieved significant improvement in the accuracy of churn prediction. The scalability and effectiveness of the proposed algorithm is also studied.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.13-24
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• 2015

Customer complaints handling helps organizations to retain existing customers and attract new customers, as well. As Voice of the Customer (VOC) is one of the main sources of customer complaints, many organizations utilize VOC to enhance customer satisfaction. Effective management of VOC has been proved as one of the best ways to maintain organization's brand image and reputation. In spite of its importance, little has been reported on the utilization of VOC to detect faults in a telecommunication industry. In this paper, association rule mining based on VOC is used to identify root fault causes of a telecommunications network. To do that, VOC of a Communication Service Provider has been collected first. Then, association rule mining has also been conducted with various support and confidence levels. As a result, root fault causes of the telecommunications network can be identified. It is expected that this study can be used as a basis for decisions about customer satisfaction management such as preventive maintenances or reduction of the customer maintenance cost.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.111-125
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• 2011

Smartphone is becoming as a core device of mobile environment. The purpose of this study is to investigate the factors affecting customer's buying decision on smartphone. Based on prior studies and cases, this study identifies network effect, switching cost, function, design, brand, after service, price as affecting factors of customer's buying decision on smartphone. It also aims to investigate the relationship between network effect/switching cost and re-purchasing. Result shows that network effect brand, after service are significantly related to customer's buying decision on smartphone by device types, but switching cost, function, design, price are not. Network effect also was found to be significantly related to the re-purchasing. The result of this study may provide a guideline of supply strategy with smartphone suppliers.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.1-24
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• 2013

The research about customer value has developed over the past years in the marketing field. On the other hand, the stream of the idea has not fully been structured yet. It is the purpose of this research to present the process of development together with the intellectual structure in the field of customer value researches using "Author Co-citation Analysis" (ACA). For the purpose of the research, authors chosen were ranked in order of frequency according to their citations which were used for network analysis. Further, it was of advantage in finding the development process for this research from 1996 to 2011. The trend were set into three time-line groups/trends (1996~2000, 2001~2005, and 2006~2011) that were respectively analyzed. In conclusion, the research represents the intellectual structure of customer value in each period. The research having been tried, influenced a variable field in other marketing researches. While still, many researches limit their focus on a "one-way customer value, used by companies in the past and some in the present, many researches now have a wider perspective about the value and relationship of their customer and their company, together with the society at large.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.109-120
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• 2021

Despite the growing online exposure of retailes, offline retail channels still outperform online channels in the total retail volume of some countries. There is much interest in the physical layout plans of retail stores to expand sales. Product placement that have a large impact on customer purchasing behavior at offline retailers influences customer movement and sales volume. But in many cases, each retailer relies on unsystematic and autonomous product placement. When multiple products are sold with one purchase, the customer's movement for shopping may be evaluated in terms of customer efficiency and additional impulse purchase. In this paper, the social network is applied to sales data of a retail store and the result is used for evaluation of product placement and customer path. The frequent sales product composition was identified using k-core from sales data in the form of shopping baskets. The location was checked for the identified compositions of products, the spatial variance was measured and the customer's path was identified. With these results, the store arrangement of products was evaluated with appropriate improvement directions. The analysis method of this paper can be an alternative analysis approach for better layout of retail stores.

• Journal of Korean Society for Quality Management
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• v.33 no.2
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• pp.32-39
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• 2005

The Customer Satisfaction which effects directly the performance of almost all companies. Therefore, it is very important for a company to reflect totally market environment which can be changed fast and diversely by customer requirements. In spite of many studies on the marketing decision, it has been rarely applied for the quantitative method and result of Customer Satisfaction Index Assessment in the marketing decision process. This study used ANP(Analytic Network Process) approach permitting the interdependent relationship between hierarchy and decision factors in the decision process. Moreover, we propose the method which represents efficiently the Customer Satisfaction Index so that the Suggested Model in this study becomes Customer-Oriented.

• Journal of Distribution Science
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• v.20 no.5
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• pp.97-104
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• 2022

Purpose: This study intends to analyze the effect of competitor pressure and customer pressure on social media technology use and the value of the business network and their implications for marketing performance. Research design, and methodology: A constructed questionnaire was conducted with 90 respondents of MSME's Business Actors in South Sulawesi Partial Least Square (PLS) analysis was applied to analyze and verify all the data. Results: Competitor pressure has a significant effect on social media technology, Competitor pressure has a positive and significant impact on business network accentuation. Customer pressure has a positive and significant impact on social media technology. Customer pressure has a positive and significant impact on business network accentuation. Social media technology utilization has a significant impact on Business Network Accentuation. Social media technology utilization has a significant effect on Marketing Performance. Business Network has a significant effect on Marketing Performance. Conclusions: It is an important thing for MSMEs to increase the use of social media technology to meet the demands of consumers and pressure from competitors. The use of social media technology must be implemented effectively and efficiently so that it can be utilized as an effective tool for distributing the value that own by a company to improve the company's marketing performance.