Building an Integrative Service Management System for Service Failures Identification and Service Recovery

博士 === 中華大學 === 科技管理博士學位學程 === 99 === As service sector plays a decisive role in economic development, it is widely recognized that the success of the service sector is an essential factor in measuring an economy’s progress. Especially in today’s competitive environment, delivering superior serv...

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Bibliographic Details
Main Authors: Chan, Ya-Hui, 詹雅慧
Other Authors: Lin, Shu-Ping
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/54244614723052878810
Description
Summary:博士 === 中華大學 === 科技管理博士學位學程 === 99 === As service sector plays a decisive role in economic development, it is widely recognized that the success of the service sector is an essential factor in measuring an economy’s progress. Especially in today’s competitive environment, delivering superior service to decrease customer complaints and further increase customer satisfaction and value is critical to a firm’s sustainability. As it is difficult for firms to avoid all service failures, the service recovery implementation has then become an important issue. In view of quality functional deployment (QFD) is useful for ensuring that the customer voice is systematically deployed throughout all the stages of product planning and designing, the aim of this study is to apply QFD to develop a SFR model to connect service failures and recovery solutions systematically. To complete the SFR analysis, two advanced methodologies, such as valuable-gap-analysis and KIR function, are proposed with the involvement of Kano’s two-dimensional theory for service failures identification and improvement opportunity matrix construction. Then the Decision-Making Trial and Evaluation Laboratory method is applied to understand the interdependence among recovery solutions as well as the relationship between service failures and recovery solutions, in order to better prioritize recovery solutions operations. The SFR model proposed in this study is illustrated and validated using data collected from mobile telecom industry in Taiwan. Overall, results show that QFD is useful for identifying the core/optimal solutions for service recovery. More implications are discussed in this study.