| Summary: | 博士 === 雲林科技大學 === 管理研究所博士班 === 96 === Quality Function Deployment QFD (QFD) has been successfully applied in a number of fields. However, relatively little studies have been done in integrating grey theory and Kano''s model and QFD to evaluate multiple quality characteristics. Moreover, to achieve high customer satisfaction, companies have to reduce complaints and provide something more to obtain high customer satisfaction. Therefore, it is worthwhile to plan customer needs in advance by integrating exponential smoothing in QFD. There are two parts in this dissertation.
First, grey relational analysis is one of the best decision analytic methods. Incorporating grey relational analysis into QFD allows the importance of customer needs to be prioritized with reference to quality characteristics. This study concerns an Retail Support International (RSI) automatic distribution center as a case to demonstrate the benefits of applying grey relational analysis in QFD. On the other hand, we proposed integrated approach involving Kano''s model and QFD of evaluating service quality for the mobile phones of various brands. This study attempts to evaluate service quality using an integrated approach to improve innovative product development for mobile phones. A case example is presented to evaluate the service quality of mobile phone for various brands in Taiwan. Several important and unimportant quality characteristics and customer needs were identified and analyzed for innovative product development.
The second part of this dissertation discusses in detail of meeting customer needs is not enough to capture and retain market share. Hence, by integrating Kano''s model into QFD to execute the most technical characteristics of eliminating customer dissatisfaction and quality characteristics of increasing customer satisfaction to exceed customer satisfaction under the resource limitation. And, a proposed method of applying exponential smoothing
in QFD to analyze dynamic and future customer needs based on historical, present and
predicted data sets is presented. With the use of the proposed method, the importance of each customer needs is monitored and analyzed and the importance of each quality characteristics is evaluated in order to fulfill dynamic and future customer needs. Doing so would allow companies to plan customer needs in advance, fulfill their needs, and, most importantly, significantly improve customer satisfaction and enhance their competitiveness in the market.
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