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研究生:陳宥君
研究生(外文):CHEN,YU-CHUN
論文名稱:以對稱與非對稱資料分析基礎探究品牌形象與品質對顧客滿意度之影響效果
論文名稱(外文):Exploring the Impacts of Brand Image and Quality on Customer Satisfaction from Symmetric and Asymmetric Thinking in Data Analysis
指導教授:鄭正豐鄭正豐引用關係
指導教授(外文):CHENG,CHENG-FENG
口試委員:王冠婷謝存瑞鄭正豐
口試委員(外文):WANG,KUAN-TINGXIE,CUN-RUICHENG,CHENG-FENG
口試日期:2019-04-26
學位類別:碩士
校院名稱:亞洲大學
系所名稱:經營管理學系
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:英文
論文頁數:74
中文關鍵詞:模糊理論品牌形象品質知覺價值知覺風險顧客滿意度
外文關鍵詞:fuzzy-set theorybrand imagequalityperceived valueperceived riskcustomer satisfaction
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本研究旨在探討運用對稱與非對稱概念方法研究知覺價值和知覺風險對於顧客滿意度的影響。因此,本研究的主要研究重點是分別探討品牌形象和品質對於知覺價值和知覺風險的影響。此外,本研究更進一步探討了知覺價值,知覺風險和顧客滿意度之間的關聯性。為了評估此模型的適用性,本研究採用了網路的問卷調查,並將其分發給有購買產品行為或得到服務的消費者組成的樣本。分析工具採用了敘述性統計分析,因素分析,信度分析,結構方程模型(SEM)和模糊集合質性比較分析(fsQCA)。就對稱分析而言,結構方程模型的結果顯示,品牌形象和品質皆可以提高知覺價值,而品質與知覺風險具有關聯性,因此,知覺價值顯著影響顧客滿意度。另一方面,資料分析中的不對稱分析(即模糊集合質性比較分析)的結果表示,本研究中,有五種因果配置(即路徑1到路徑5)足以滿足客戶滿意度。例如,路徑1表明,當品牌形象較高,感知風險較低時,可能會導致較高的客戶滿意度結果。此外,路徑2表示即使顧客感知價值較低,如果他/她同時具有較高的質量評價和較低的感知風險,也可以獲得較高的顧客滿意度。
This study intends to investigate the influences of perceived value and perceived risk on customer satisfaction based on symmetric and asymmetric thinking in data analysis. Accordingly, major proposes of this study are focus on investigating the impacts of brand image and quality on perceived value and perceived risk, respectively. In addition, this study further exploring the relationships among perceived value, perceived risk, and customer satisfaction. To assess the applicability of this conceptual model, this study employs an Internet-based questionnaires survey and distributed it to a sample consisted of consumers who had purchased the products or obtained the services. The statistical techniques adopts contain descriptive statistics, factor analysis, reliability analysis, structural equation modeling (SEM), and fuzzy set qualitative comparative analysis (fsQCA). In terms of symmetric thinking in data analysis, the results of SEM show that both brand image and quality can enhance perceived value, quality is associated with the perceived risk, and perceived value is significantly affects customer satisfaction. On the other hands, the results of asymmetric thinking in data analysis (i.e., fsQCA) show that there are five causal configurations (i.e., path 1 to path 5) found to be sufficient for high customer satisfaction in this study. For instance, path 1 indicates that when the brand image is high and perceived risk is low it can cause high customer satisfaction results. Furthermore, path 2 represents that even customer has low perceived value, if he/she has high evaluations with quality and low perceived risk at the same time, it also can achieve high customer satisfaction.
Table of Contents
謝誌 I
中文摘要 II
Abstract III
Table of contents V
List of tables VII
List of figures VIII
Chapter 1 Introduction 1
Chapter 2 Literature review 5
2.1  Brand image 5
2.2  Quality 6
2.3  Perceived value 8
2.4  Perceived risk 10
2.5  Customer satisfaction 12
2.6  Hypotheses development 14
Chapter 3 Empirical research 19
3.1 Measure development 19
3.2 Sampling design 23
3.3 Data analysis procedures 24
Chapter 4 Results of data analysis 27
4.1  Descriptive statistical analysis 27
Page
4.2  Factor analysis 29
4.3  Reliability analysis 33
4.4  Structural equation modeling (SEM) 38
4.5  Fuzzy set qualitative comparative analysis (fsQCA) 40
Chapter 5  Discussion 43
5.1  Conclusion 43
5.2  Managerial implications 43
5.3  Limitation and future research 45
References 46
Appendix A:Questionnaire 56
Appendix B:研究問卷 60

List of tables
Table 1  the results of descriptive statistical analysis 28
Table 2  KMO and Bartlett’s Test 29
Table 3  Brand image of factor analysis 30
Table 4  Factor analysis for quality 30
Table 5 Factor analysis for perceived value 31
Table 6 Factor analysis for perceived risk 32
Table 7 Factor analysis for consumer satisfaction 32
Table 8 Reliability analysis for brand Image 33
Table 9 Reliability analysis for quality 34
Table 10 Reliability analysis for perceived value 35
Table 11 Reliability analysis for perceived risk 36
Table 12 Reliability analysis for consumer satisfaction 37
Table 13 Result of SEM 39
Table 14 fsQCA output— customer satisfaction 41

List of figures
Figure 1 Results of path analysis 38
Figure 2 Causal paths for high customer satisfaction 42


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