- 學位論文
應用顧客滿意度要素結構來評估服務品質─以校園周邊便利商店和亞洲大學圖書館為例
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
摘要
IPA分析是最常被使用來找出優劣勢的方法，但IPA分析並不能充分反映出消費者心裡的認知及感受，故本研究採用顧客滿意度之要素結構分析，來了解各項產品或服務的品質特性，並提供其他要素結構分析的方法。大部分Kano問卷因為題目過於繁瑣，導致受訪者填答時間太冗長，影響作答。因此本研究針對要素結構各種方法(如Kano問卷、重要度方格分析、懲罰報酬對比分析及對應分析等)進行個案分析，以供日後在問卷資料中如未包括有傳統Kano模式資訊時，其他的替代分析方法。一般要素結構分析皆須總滿意度的問題，當問卷無總滿意度問題時，本研究提供分別以變異數及亂度為基礎之重要度方格分析來做要素結構分析，並觀察要素結構隨時間之變化。 本研究使用二個不同類型的案例，來進行各種要素結構分析及穩定性分析。第一個案例為探討學校核心之圖書館服務品質，但有些研究顯示要素結構會隨時間而變化，為了觀察此現象，再加入大專院校週邊便利商店為第二個案例。 第一個案例主要使用傳統Kano問卷分析，研究結果顯示亞洲大學圖書館的服務品質， 27項品質要素中被歸類為無差異評價者佔大多數，共有18項。其次有7項是一維品質要素，有2項當然品質要素者，沒有選項是魅力評價者。 此案例亦使用重要度方格分析、懲罰報酬對比分析及對應分析等來進行產品或服務品質屬性分類。在重要度方格分析中，結果顯示在無總滿意度的問卷中，以變異數及亂度為基礎之方格分析所得結果一致性達92.59%；在有總滿意度的問卷中，以迴歸分析為基礎的重要度方格分析與以相關係數為基礎的重要度方格分析所得結果的一致性百分比為66.67%；以相關係數及淨相關為基礎之重要度方格分析所得結果一致性也有55.56%。 因為重要度方格分析較容易建構，所以第二個案例使用重要度方格分析來作動態要素結構分析。本研究發現以變異數及亂度為基礎之重要度方格所得之趨勢非常類似，同樣的以相關係數及淨相關為基礎之重要度方格所得之趨勢也非常類似。因此我們建議在無總滿意度的問卷可用較容易計算的變異數為基礎之重要度方格分析來作要素結構分析；在有總滿意度的問卷可用容易計算的相關係數為基礎之重要度方格來做要素結構分析。
並列摘要
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.