Applying the Factor-Structure of Customer Satisfaction to Evaluate the Service Quality - Case Studies of the Convenience Store on Campus and the Library at Asia University

[[abstract]]By the Importance-Performance Analysis (IPA), the major strengths can be found and maintained, the major weaknesses can be specifically improved and then the quality of service will be enhanced. But IPA method can not reflect consumer?s cognition and experience fully, Kano model was introduced to analyze the factor structure of customer satisfaction and find out about the quality characteristic of each products or service. In this study, four methods (such as Kano questionnaire, importance grid analysis, penalty-reward-contrast analysis, and correspondence analysis) were used to analyze the factor structure of customer satisfaction. This study also suggests that the variance-based and entropy-based importance grid analysis to analyze the factor structure of customer satisfaction when the questionnaire does not have the overall satisfaction information, respectively. For understanding the stability of the factor structure, the trends of the quality elements evolving over time were observed. There are two case studies in this study. The first one is to analyze the factor structure of customer satisfaction in library service by Kano questionnaire, importance grid analysis, penalty reward contrast analysis, and correspondence analysis. Some studies reveal that the quality elements will evolve over time. For observing this phenomenon, the second case study is to observe the trends of the quality elements evolving over time in a convenience store. Because importance grid analysis is easy to construct and implement, four importance grid analysis methods were used to observe the trends of the quality elements evolving over time. The results of the first case study using traditional Kano questionnaire are that by summarizing 27 items quality elements, we find that no one can be sorted as ?attractive quality element?, ?reverse?, and ?question? quality elements. There are eighteen quality elements are classified as ?indifferent quality element?. Seven quality elements are classified as ?one-dimensional quality element?. Finally, there are two quality elements are classified as ?must-be quality element?; The study also shows that the consistency between the result of the variance-based importance grid analysis and that of the entropy-based importance grid analysis is 92.59%; the consistency between the result of the regression analysis-based importance grid analysis and that of the partial correlation coefficient-based importance grid analysis is 66.67%; the consistency between the result of the correlation coefficient-based importance grid analysis and that of the partial correlation coefficient-based importance grid analysis is 55.56%. The results of the second study show that the trend of the variance-based importance grid analysis is very similar to that of the entropy-based importance grid analysis; they also show that the trend of the correlation-based importance grid analysis is very similar to that of that of the partial correlation coefficient-based importance grid analysis. So we propose that the variance-based importance grid analysis is better choice to analyze factor structure of customer satisfaction for its easy-computing when the questionnaire without using the overall satisfaction; The correlation coefficient-based importance grid analysis is better choice to analyze factor structure of customer satisfaction for its easy-computing when the questionnaire with using the overall satisfaction