• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.195-201
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• 2018

This study is attempted to demonstrate the structure of the influencing factors on the performance of services of knowledge based service firms. In the model presented, the structure is that service performance in knowledge-based services are affected by the strategic utilization of knowledge resources and service orientation factors of the service organization. And the service performance are also affected in which the systemization of service processes and customer satisfaction play a mediating role. As an analysis result of examining 148 practitioners engaged in the knowledge service industry, it is necessary to increase the satisfaction of external customers in order to improve service performance in a knowledge-based service organizations. This can be achieved by increasing the satisfaction of internal customers. In addition, for this structure to be successful, the service production process to be provided to the customer must be enhanced. The service production process has been found to be an important factor influencing the internal customer satisfaction and service delivery process, especially in the use of knowledge resource, and customer oriented service among service orientation factors.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1574-1586
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• 2016

The aims of this research is to build Customer Delight index contents model for measuring the influential factors - Customer Delight and identify the relationship among Customer Delight, Customer Satisfaction and Customer Loyalty. Customer Delight hypothesis model was proposed by Catering Service Industry of Starbucks and validate the final questionnaire; 7 point Likert scale was used in the questionnaire, Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) are used to analyze the reliability. And path analysis was used to evaluating the final hypothesis model. The results of this research was that the customer Self-involvement can lead to high awakening level and it also bring positive emotion to the customer. Awakening Level and positive emotion were the key factors for the Customer Delight. Instead of customer expectation, Customer Delight is based on customer awakening level and positive emotion which is different from Customer Satisfaction model. It is clearly to see the discrepancies between Customer Delight and Customer Satisfaction.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.153-162
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• 2006

Customer satisfaction is an ever-growing concern of management throughout the world. To find the way to increase customer satisfaction, we must understand customer requirements. Kano distinguishes between three types of product requirements (must-be, one-dimensional, attractive requirement) which influence customer satisfaction in different ways when met. In this paper, potential customer satisfaction improvement (PCSI) index was developed using Kano model and CS coefficient. Timko has developed customer satisfaction (CS) coefficient based on Kano model. The PCSI index represents how much a service feature can increase the degree of customer satisfaction when the service feature is fully fulfilled. In order to explain the meaning of PCSI index, a case syudy of a Family Restaurant is done. It is also discussed how to use the index strategically.

• The Journal of Society for e-Business Studies
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• v.5 no.2
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• pp.49-60
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• 2000

A major topic in the field of network and telecommunications is doing business on the Word Wide Web(WWW), which is called Electronic Commerce(EC). Another major topic is blending Artificial Intelligent techniques with the WWW. To provide customer with the information of goods in suit with a customer liking, we propose multi agent system which is consist of customer agent and search agent etc. Also we use case-based reasoning for customer liking searching the information of goods and training through the reuse. This reuse make efficient management of information and a process of operation. In the relation between customer and goods, if there are some goods which is not search from case-base reasoning, we calculate satisfaction function for customer purchase goods. And to provide customer with the information of goods in the first of satisfaction function, This EC system can always provide the information of goods which is satisfied to customer.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.8-13
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• 2006

In this paper, we try to find success factor to satisfy Female Customer of a Family Restaurant We survey Female Customers Requirement and make a Questionnaire based on Female Customer by interview and internet Homepage. We find Potential customer satisfying factor by using Kano Analysis and Timko's CS coefficient and Potential Customer Satisfactionv improvement Index(PCSI) which is suggested by Leem represents how much a service feature can increase the degree of customer satisfaction when the service feature is fully fulfilled. We also discuss how to use this result, we hope our result to apply customer satisfying many fields not only Family Restaurant.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.176-183
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• 2021

The purpose of this study is was to analyze customer experience attribute of professional baseball. To achieve objectives of this study, a method was used the in-depth interview and experts' consultation which understanding the attributes and structure of customer experience attribute of professional baseball. As a result, the professional baseball customer experience attributes are 'viewing plan & purchase', 'stadium movement', 'entrance stadium', 'move to seat', 'game viewing', 'amenities/services', 'events/cheering', 'move after match'. The review of the experience section and attributes derived through in-depth interviews with professional baseball fans was verified through an expert' consultation to secure content validity. Through this process, 8 experience section and 41 attributes were analyzed. The customer experience journey was analyzed for a more in-depth analysis of the viewing experience of professional baseball fans. The customer experience journey was presented based on the needs of fans and discomfort in each experience section activity.

• Asia Marketing Journal
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• v.22 no.3
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• pp.87-105
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• 2020

With the development of Information Technology, customers require promptly higher quality products and services. Companies try to make newly digital marketing strategies, but there are no empirical researches on them. This article empirically presents a new perspective that companies can shape the customer decision journey ahead by coordinating customer experience. In this article, based on Elaborated Likelihood Model (ELM) theory, customer experience consists of the emotional or cognitive experience. We surveyed about 200 subjects (N = 217) in their 20s and 30s based on the International Music Industry Association's Music Listening 2019 report, then analyzed four different models (before personalization-cognitive experience, before personalization-emotional experience, after personalization- cognitive experience, after personalization-emotional experience) by JASP and R Studio. We conducted Structural Equation Model (SEM) and paired t-test. Personalization factors are about recommendation systems in Spotify. The results of survey represent that companies can shape the Customer Decision Journey (CDJ) ahead especially through enhance cognitive experience. It empirically proves Elaborated Likelihood Model (ELM). The conclusion can be drawn that 'pulling' customer experience can be a new marketing strategies in the digital era.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.121-133
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• 2003

Due to the rapid growth of Internet, means of communication with customers in a traditional customer support environment such as telephone calls are being replaced by mainly e-mail in a Web-based customer support system. Although such a Web-based support is efficient and promises potential benefits for firms, including reduced transaction costs, reduced time, and high quality of support, there are some difficulties associated with responding to many types of customer's inbound e-mails appropriately. As many types of e-mail are received, considerable attention is being paid to methods for increasing the efficiency of managing and responding e-mails. This research proposes an intelligent system for managing customer's inbound e-mails in organizations by applying case based reasoning technique for responding to various customers' inbound e-mails more effectively. In this approach, a case is represented as a frame-typed data structure corresponding to an inbound e-mail, keywords, and its reply e-mail. In the retrieval procedure, keywords and affinity set is developed to index a case, and then the case is represented as a vector, a case vector. Also, cosines value is calculated to measure the similarity between a new inbound e-mail and the cases in the case base. In the adaptation procedure, we provide several adaptation strategies to adapt and modify the retrieved case. The strategies guide to make an outbound e-mail using product databases, databases for customer support, etc. Additionally, the Web-based system architecture is proposed to implement our methodology. The proposed methodology and system will be helpful for developing more efficient Web-based customer support.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.187-190
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• 2003

Since the early 1980s, the concept of relationship management in marketing area has gained its importance. Acquiring and retaining the most profitable customers are serious concerns of a company to perform more targeted marketing campaigns. For effective CRM (Customer Relationship Management), it is important to gather information on customer value. Many researches have been performed to calculate customer value based on CLV (Customer Lifetime Value). It, however, has some limitations. It is difficult to consider the churn of customers, because the previous prediction models have focused mainly on expected future cash flow derived from customers'past profit contribution. In this paper we suggest a CLV model considering past profit contribution, potential benefit, and churn probability of a customer. We also cover a framework for analyzing customer value and segmenting customers based on their value. Customer value is classified into three categories: current value, potential value and customer loyalty. Customers are segmented according to the three categories of customer value. A case study on calculating customer value of a wireless communication company will be illustrated.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.135-148
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• 2003

In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.