• Journal of Information Technology Services
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• v.17 no.2
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.476-480
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• 2010

This study deals with stockout costs in the supply chain optimization model under the framework of batch-storage network. Stockout is very popular in chemical industries. Estimating stockout cost involves an understanding of customer reactions to a seller being out of stock at the time the customer wants to buy an item. This involves massively non-trivial work such as direct customer interviews and extensive mail survey. In this study, we will introduce a new interpretation of stockout costs combined with batchstorage network optimization model and thus suggest an easy way of estimating stockout costs. Optimization model suggest that optimal process and storage sizes considering stockout cost are smaller than those that do not consider stockout cost. An illustrative example support the analytical results.

• 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

• Asia pacific journal of information systems
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• v.28 no.1
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• pp.36-60
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• 2018

As an increasing number of people gained access to social network services (SNS), organizations started to use SNS as a channel for marketing and promotional purposes. The online advertising market has significant growth potential. Brand engagement is a key motive for online advertising, but how SNS users engage with brands, particularly in terms of the promotion of organizations, is poorly understood. This study uses customer value theory to examine brand engagement of users in terms of promoting companies in the context of Korean SNS marketing. This study identifies the antecedents of brand engagement based on customer value theory. Our findings show the significance of three factors of SNS marketing, namely, price discount, relationship support, and convenience, on brand engagement. We further show the consequences of brand engagement, namely, purchase decisions and word-of-mouth activities. These findings help advance customer value theory and offer practical insights into the use of information systems and marketing in the context of SNS.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.577-593
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• 2000

A distributed video-on-demand (VoD) system is one where collection of video data is located at dispersed sites across a computer network. In a single site environment, a local video server retrieves video data from its local storage device. However, in the setting of a distributed VoD system, when a customer requests a movie from the local server, the server may need to interact with other servers located across the network. In this paper, we present three types of presentation plans that a local server must construct in order to satisfy the customer request. Informally speaking, a presentation plan is a temporally synchronized detailed sequence of steps that the local server must perform for presenting the requested movie to the customer. This involves obtaining commitments from other video servers, obtaining commitments from the network service provider, as well as making commitments of local resources, within the limitations of available bandwidth, available buffer, and customer data consumption rates. Furthermore, for evaluating the goodness of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing wait time for a customer, and minimizing access bandwidth is used. We develop algorithms to compute optimal presentation plans for all three types, and carry out extensive experiments to compare their performance. We have also mathematically proved certain results for the presentation plans that had previously been verified experimentally in the literature.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.530-538
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• 2003

Recently the needs for keeping existing customers is increasing in the field of marketing. So, the customers needs to be classified by groups and the differentiated responses to the specified customer groups are demanded. In this paper, we implemented a system that classifies the customer groups using the neural network, and classified the purchasing patterns among customer groups. Empirically examining the association rules between two groups, we could find out that similar rules exist between them. So, it is important that customers should be classified into the excellent customer group and the general group for the decision making of marketing. This paper shows that the efficiency of the differentiated marketing can be maximized by raising the correctness of the expectation in the classification of customer groups.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• Asia Marketing Journal
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• v.10 no.4
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• pp.99-121
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• 2009

Social networks can be a powerful force in marketing because they provide new ways to market to young generation. Though many studies on evaluation of customer lifetime value have been conducted, it is not clear how to assess the value of members within social networks. The purpose of this study is to evaluate members based on customer intangible value as well as customer lifetime value. Customer network value in terms of the power and influence within a network is analyzed through network structure analysis. Using Cyworld log file data, this study have shown that high percentage of members are very influential in terms of spreading or withholding information even though their CLV is low. It is expected that the findings of this research contribute to understand the interactive behaviors of members within networks and to provide valuable implications on new product launching and customer management strategies to marketers.

• Information Systems Review
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• v.14 no.2
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• pp.93-102
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• 2012

Network brings new values to the business in rapid changes of business paradigm. While business reveals new business model, the business has kept making efforts to replace traditional business model to network environment in order to solve the problems of spaces and times. In this research, we emphasize necessity through case study that the traditional concept of customer should be related with the concept of business network. The finding of this research mainly focused on business, tries to use traits of network without changes of business model, is easy to trap in structural inertia. However, the targeted companies in the case study preferentially considered customer as subscriber. Consequently, they successfully changed their existing business model as well as their business relationships with other companies. Based on methods of "Value Curve" and "Customer Experience Cycle," we analyzed the changed business model and proposed a conceptual idea regarding concept shifting from traditional customer to network subscriber. We hope that the research implicates to propose a new method for business model to develop more advanced business opportunities through using the concept of network subscriber.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.15-30
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• 2009

As knowledge is now being distributed and shared through the Internet not only in the form of text but also in that of video, UCC (User Created Content) knowledge video sharing services have emerged on the Internet such as Instructables.com. This paper deals with a UCC knowledge video service in real world and reports the case of analyzing its customer model. The knowledge video sharing service can be considered as both a kind of discontinuous innovation, which requires knowledge provider's technical ability of creating and editing UCC video, and a value network, which matches UCC providers and consumers therefore brings network effect, we first adopt the Chasm theory as the base of the customer model and refine the customer model referencing the Technographics, which is also an Internet-refinement of the Chasm model. Finally, non-customer analysis of Blue Ocean strategy is applied for exploring potential customers of the service.