臺灣博碩士論文加值系統

由於消費者對所購買的產品或服務的滿意度預測了消費者未來的品牌偏好和購買行為，因此了解購買後消費者負面情緒對滿意度之影響因素，對行銷者來說至關重要。本研究之目的是以台灣化妝品行業為例，探討消費者後悔傾向（CTR），購買後認知失調（PCD）與消費者滿意度之間的關係。此外，本研究以客戶品牌識別（CBI）作為可能的調節變數，探討CBI在購買後階段對CTR，PCD和消費者滿意度之間關係的作用。本研究主要針對過去12個月曾購買化妝品或保養品的台灣消費者為研究對象，並利用線上平台發放問卷，共收集了796份有效問卷。本研究使用結構方程模型（SEM）和多群組比較（Multi-group SEM）來驗證所提出的假設，分析結果如下：
（一）CTR對消費者滿意度和PCD均有正向影響。
（二）PCD對消費者滿意度產生了負向影響，並中介CTR和滿意度之間的關係。
（三）CBI強化CTR和PCD之間的關係，但削弱了PCD和滿意度之間的關係。

Since consumer’s satisfaction with the products/services purchased predicts consumers’ future brand preference and purchase behavior, understanding the factors influencing the effects of consumers’ negative emotions after purchase on their satisfaction with the purchase is a critical issue. The objective of this study was to investigate the relationship among consumer tendency to regret (CTR), post-purchase cognitive dissonance (PCD) and consumer satisfaction in the context of the cosmetics industry in Taiwan. Furthermore, this study used customer-brand identification (CBI) as a possible moderator, exploring the role of CBI at the post-purchase stage on the relationships among CTR, PCD and consumer satisfaction. The research conducted an online survey on Taiwanese consumers who had purchased cosmetics/skincare products in the past 12 months. A total of 796 valid questionnaires were collected. This study used structural equation modelling (SEM) and multi-group SEM to verify the hypotheses proposed. Results indicated that (1) CTR had positive effects on both consumer satisfaction and PCD. (2) PCD negatively influenced consumer satisfaction and mediated the CTR-consumer satisfaction relationship. (3) CBI strengthened the CTR-PCD relationship but attenuated the PCD-consumer satisfaction relationship.

CONTENTS
Abstract I
摘要 III
CONTENTS IV
TABLES V
FIGURES V
Introduction 1
Literature Review and Hypotheses Development 9
Consumer Tendency to Regret (CTR) 9
Post-purchase Cognitive Dissonance (PCD) 10
Customer-brand Identification (CBI) 16
Research Method 24
Procedure 24
Variables and Questionnaire Design 25
Results 28
Descriptive Statistics 28
Exploratory Factor Analysis (EFA) 30
Reliability Analysis 37
Confirmatory Factor Analysis (CFA) 37
Structural Equation Modelling (SEM) 44
Moderation Analysis – Multi-group SEM 50
The Results of the Hypothesis Test 54
Discussion and Limitation 55
Discussion 55
Research Contributions and Limitations 60
Suggestions for Future Research 62
References 63
Appendix 67

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