• Journal of Information Technology Services
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• v.15 no.1
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• pp.197-210
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• 2016

With the advent of text analytics, VOC (Voice of Customer) data become an important resource which provides the managers and marketing practitioners with consumer's veiled opinion and requirements. In other words, making relevant use of VOC data potentially improves the customer responsiveness and satisfaction, each of which eventually improves business performance. However, unstructured data set such as customers' complaints in VOC data have seldom used in marketing practices such as predicting service time as an index of service quality. Because the VOC data which contains unstructured data is too complicated form. Also that needs convert unstructured data from structure data which difficult process. Hence, this study aims to propose a prediction model to improve the estimation accuracy of the level of customer satisfaction by combining unstructured from textmining with structured data features in VOC. Also the relationship between the unstructured, structured data and service processing time through the regression analysis. Text mining techniques, sentiment analysis, keyword extraction, classification algorithms, decision tree and multiple regression are considered and compared. For the experiment, we used actual VOC data in a company.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.258-266
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• 2023

Aiming at the problems of poor customer satisfaction and poor accuracy of customer classification, this paper proposes a customer classification model based on speech recognition. First, this paper analyzes the temporal data characteristics of customer demand data, identifies the influencing factors of customer demand behavior, and determines the process of feature extraction of customer voice signals. Then, the emotional association rules of customer demands are designed, and the classification model of customer demands is constructed through cluster analysis. Next, the Euclidean distance method is used to preprocess customer behavior data. The fuzzy clustering characteristics of customer demands are obtained by the fuzzy clustering method. Finally, on the basis of naive Bayesian algorithm, a customer demand classification model based on speech recognition is completed. Experimental results show that the proposed method improves the accuracy of the customer demand classification to more than 80%, and improves customer satisfaction to more than 90%. It solves the problems of poor customer satisfaction and low customer classification accuracy of the existing classification methods, which have practical application value.

• International Journal of Quality Innovation
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• v.10 no.2
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• pp.109-126
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• 2009

The purpose of this study was to examine overall customer satisfaction associated with medical service quality in Taiwan by integrated Kano's model and customer satisfaction index model. Another purpose was to confirmed nonlinear and asymmetric relationship of Customer Satisfaction and Quality Performance by the research outcome. By analyzing 1,100 patients or their family members, this study used the structural equation model (SEM) with AMOS software for data analysis. The results show that must-be attributes, one-dimensional attributes and attractive attributes had a direct effect on overall customer satisfaction, Surprisingly, overall customer satisfaction had positively influenced customer loyalty customer satisfaction had negatively influenced customer complaints. The study also found that customer complaints have direct effect on customer loyalty. Importantly, the study found out the must-be attributes, the attractive attributes and one-dimensional attributes increased, the level of overall customer satisfaction also increased. The customer satisfaction positively influences customer loyalty in medical service quality in Taiwan. The findings might reveal new insights for researchers dealing with quality of medical service and for hospital managers who devote resources exclusively to achieving highest possible levels of patient satisfaction.

• International Journal of Quality Innovation
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• v.4 no.2
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• pp.101-122
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• 2003

With the development of the American Customer satisfaction index (ACSI), research on customer satisfaction measurement or evaluation methods have become significant in the last decade. Most of international customer satisfaction barometers or indices are evolved based on the cause and effect relationship model of ACSI. Of critical importance to validity of customer satisfaction indices is how to construct a measurement attribute or indicator model and provide an effective implementation method effectively. Quality Function Deployment (QFD) is a very useful tool for translating the customer voice into product design through quality engineering. In fact, this is a methodology for measuring and analyzing evaluation indicators by their relationship matrix. In this paper, we will make an effort to integrate the framework of QFD into the measurement problem of customer satisfaction, and also develop a new multi-phase QFD model for evaluation of Customer Satisfaction Index (CSI). From the houses of quality in this model, the evaluation indicators impacting on customer's global satisfaction are identified by means of their relationship matrix. Then the evaluation indicator hierarchy and its measurement method for the customer satisfaction index are presented graphically. Furthermore, survey data from the Chinese automobile maintenance sector and a relevant case study are utilized to show the implementation method of the QFD model used to measure and analyze of customer satisfaction.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.1
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• pp.90-110
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• 1999

Understanding consumer complaining behaviors plays a key role in post-purchase satisfaction customer retention and long-term customer relationships. This research was conducted to empirically investigate 1) the taxonomy of complaining behavior 2) causes and types of clothing complaining behavior according to sex. The subjects compoed of 250 male and 358 female consuemrs. Data were colleted through questionnaires employing the critical incident methodology. The findings indicated that clothing complaining behavior was fitted well into Singh(1998)'s three-factor model(i. e. voice/private / third-party complaining behaviors) these factors explained 53% of the total variances 75.1% of male and 65.2% of female group complained of poor instruental performance. The types of complaining behaviors were no action negative word-of-mouth to friends and associates n order. Most dissatisfied consumers didn't assert positive consumer's right. Marketer should increase the accessibility of their complaint receiving mechanisms to passive customers.

• Journal of Korean Society for Quality Management
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• v.33 no.2
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• pp.74-86
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• 2005

The project objectives, called critical-to-quality (CTQs) in six sigma, should be defined to faithfully reflect the customer requirements. The identification of such a set of CTQs, which is currently done using brainstorming in practice, is a challenging task. Notwithstanding the rapid growth of the six sigma literature, development of a systematic procedure for identifying CTQs has scarcely been addressed. This paper proposes a systematic method for generating CTQ candidates based on the given voice of the customer in the DFSS/C (Design for Six Sigma / Commercial) context. By providing a step-by-step procedure, the proposed method ensures that all the important CTQ candidates are identified and subjective judgments are minimally required. Hence, the shortcomings associated with the existing practice based on brainstorming can be effectively overcome. The unique characteristics of the proposed method are also demonstrated via a case study.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.574-578
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• 2005

The project objectives, called critical-to-quality (CTQs) in six sigma, should be defined to faithfully reflect the customer requirements. The identification of such a set of CTQs, which is currently done using brainstorming in practice, is a challenging task. Notwithstanding the rapid growth of the six sigma literature, development of a systematic procedure for identifying CTQs has scarcely been addressed. This paper proposes a systematic method for generating CTQ candidates based on the given voice of the customer in the DFSS/C (Design for Six Sigma / Commercial) context. By providing a step-by-step procedure, the proposed method ensures that all the important CTQ candidates are identified and subjective judgments are minimally required. Hence, the shortcomings associated with the existing practice based on brainstorming can be effectively overcome. The unique characteristics of the proposed method are also demonstrated via a case study.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.171-187
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• 2006

Modern management considers customer satisfaction as a baseline standard of performance and a possible standard of excellence for any business organization including the college. Quality function deployment(QFD) is a structured approach to seek out voice of customers, understanding their needs, and ensure that their needs are met. The strategy value proposed by Chien et al. combines importance, satisfaction, performance, and ability to enhance decision making effectiveness. But in their model, the correlation among the strategic alternatives isn't considered the decision chain and is therefore eliminated. This paper proposes how to calculate the new weight of columns to consider various strength levels of correlations matrix, representing the correlation among the strategic alternatives, using normalization procedure. The aim of this paper is to present and original customer satisfaction survey conducted in the college. Thus, this paper presents an original customer satisfaction survey in the college and provides to demonstrate the practical usage of the design model to compare this model with Chien's model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4164-4169
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• 2015

In this paper planed Real-time Shopping System using Multipurpose Visual Language System(MVLS) with voice recognition remote controller. This system has a merit that using existing on-line & off-line shopping system with addition MVLS data. This can realization little modification existing shopping system. Also, customer's a point of view that has a merit to using easy device for shopping. That is no more using difficult device like that keyboard or mouse, and approach to easy device that voice recognition remote controller or smart phone. Especially, aspect of the old and the infirm and disabled persons that information minority group, can easy buy the product using this system. And, the sellers can more easily collection customer's data and using that future sales strategy.

• Asia-Pacific Journal of Business
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• v.3 no.2
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• pp.16-22
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• 2012

Korean mobile telecommunications market is shifting from 2G to 3G service. Considering the revenue of voice-based communication has reached its maximum, 3G services can provide telecommunication companies with the opportunity to increase their revenues. As the competition in the market is becoming fierce, mobile carriers are trying to increase their profits by preventing their customers from switching to rivals. In this regard, managing customer can be a key success factor of the mobile telecommunications business by retaining existing customer. In this research, we tried to develop and test a model that aids further understanding of the determinants of continuance intention to use the current 3G service. We conducted empirical study through the analysis of 3G service users' data in Korea. The results indicated that continuance intention to use the current 3G is dependent on the customer's satisfaction with the service quality, handset, and brand image. We hope that analysis results will have significant implications in terms of both practical and theoretical aspects.