本研究主要探究產品的重大負面事件對公司品牌權益的影響。當產品的重大負面事件發生時，一連串的負面報導與負面口碑也同時因應而起。 因此本研究認為當發生產品的負面報導後，不但會傷害其公司的品牌形象，並且會損壞公司的品牌權益。本研究的實證樣本取自台灣經濟新報上市上櫃公司財報資料庫，以及交通部車輛安全資訊網的車輛瑕疵召回次數，樣本期間取自2003年至2009年。實證結果顯現產品的重大負面事件會影響其公司的品牌權益，但其產品的發生次數必須到達某一數量才能進而影響其公司的品牌權益。現今的科技如此發達，媒體的力量無遠弗屆，此種產品負面事件的爆發不容忽視。因此，本研究建議公司應致力於降低產品重大負面事件的發生，進而提升其公司的品牌權益。

This study investigates the negative impact of critical failure events on firms’ brand equity. Product failures events often result in negative publicity and word-of-mouth, thus damage firms’ brand images. The study posits that these critical failure events will negatively influence a firm’s brand equity. Three listed motor companies in Taiwan Stock Exchange (TSE) together with the Ministry of Transportation and Communication (MOTC) database from 2003 to 2009. The empirical evidences show the critical product failure events negatively impact a firm’s future brand equity. However, the recall counts should be greater than a certain threshold level in order to trigger such an effect on consumers’ perceptions. With today’s internet technology in media industry and online forums, the damage caused by product failure events should not be ignored. Overall, this study demonstrates to managers that investments in reducing product failure events could indeed make financial reaction in terms of promoting firms’ future brand equity.

Abstract i
Acknowledge iii
Table of Contents iv
List of Figures vi
List of Tables vi
Chapter 1 1
Introduction 1
1.1 Research Background and Motivation 1
1.2 Research Aim 3
1.3 Research Process 4
1.4 Research Organization 5
Chapter 2 6
Literature Review 6
2.1 Framework Introduction 6
2.2 Publicity and Word-of-Mouth as Credible Source of Information 6
2.3 The Negativity Effect of WOM and Publicity 7
2.4 The Framing Effect and Prospect Theory on Negative Information 10
2.5 Contextual Priming Effect on Negative Information 13
2.6 The Effect of Source Credibility on Negative Information 14
2.7 The Harmful Impact of Critical Product Failure Events on a Firm’s Brand Equity 17
2.8 Empirical Cases of Critical Product Failure Events 20
2.9 Hypothesis development 22
Chapter 3 24
Methodology 24
3.1 Model specification 24
3.1.1 Input to Time-Series Models 25
3.2 Data Description 27
3.3 Definition of Variable 29
3.3.1 Tobin’s Q 29
3.3.2 Product Failure Events 31
Chapter 4 33
Empirical analysis 33
4. 1 The Effect of Autocorrelation on Tobin’s q - Yulon 34
4.1.1 The Effect of Recall Counts on Yulon’s Tobin’s q 38
4. 2 The Effect of Autocorrelation on Tobin’s q - Hotai 39
4.2.1 The Effect of Recall Counts on Hotai’s Tobin’s q 43
4. 3 The Effect of Autocorrelation on Tobin’s q – China-motor 44
4.3.1 The Effect of Recall Counts on China-motor’s Tobin’s q 48
Chapter 5 49
Conclusion 49
5.1 Research Conclusion 49
5.2 Managerial Implication 50
5.3 Limitation 51
5.4 Future Research 52
References 53
Appendix-Data for Tobin’s q 60

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