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研究生: 樂涵雅
Lemercier, Andréa Gabrielle
論文名稱: The Impact of Online Consumer Review (OCR) on Perceived Credibility: the Moderating Effect of Codeswitching.
The Impact of Online Consumer Review (OCR) on Perceived Credibility: the Moderating Effect of Codeswitching.
指導教授: 陳正忠
Cheng, Jeng-Chung
學位類別: 碩士
Master
系所名稱: 管理學院 - 國際經營管理研究所
Institute of International Management
論文出版年: 2017
畢業學年度: 105
語文別: 英文
論文頁數: 83
外文關鍵詞: Online consumer review (OCR), Dual-process theory, Luna & Peracchio 2005, Review volume, Review valence, Reviewer credibility, perceived credibility, Intention to reserve, Real Behaviour.
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  • The present study investigates the impact of social and technological cues in user-generated contents and reviewer’s profile in a travel recommendation system context, and its impact on perceived credibility and intention to reserve a product (i.e., hotel room and tourism services). First, Through the Dual-Process Theory (DPT) we investigate two processes normative and informative influence, from which we derive respectively two variables: review valence (i.e., positive vs negative reviews) and reviewer credibility (i.e., personal information and ranking), and review consistency and review rating (i.e., helpful vote system); and whether those processes influence perceived credibility and booking intention. Then, with the Communication Accommodation Theory (CAT), we demonstrate whether code-switching and its sociolinguistics aspects can moderate the relationship between the previous variables (i.e., review consistency, review rating, review valence and reviewer credibility) and perceived credibility and influence booking intention. We focus on travel reviews from TripAdvisor and this study’s respondents are bilingual with English proficiency as either first or second language. This present paper is inspired by previous researches on eWOM and we developed an experimental design to test our model to confirm the impact of eWOM on perceived credibility and moderating effect of language switching.

    ABSTRACT I ACKNOWLEDGEMENTS TABLE OF CONTENTS I LIST OF TABLES V LIST OF FIGURES VII CHAPTER ONE INTRODUCTION 1 1.1 Research Background and Motivation. 1 1.1.1 The Importance of Electronic Word-of-Mouth (eWOM) for Travel. 1 1.1.2 Keen Interest for the Sharing Economy. 2 1.1.3 BlaBlacar: The European Car Sharing Platform. 3 1.2 Research Objectives. 4 1.3 Research Contributions. 5 1.4 Research Procedures and Scope of Study. 5 1.5 Research Structure. 6 CHAPTER TWO LITERATURE REVIEW 7 2.1 Theoretical Background. 7 2.1.1 Dual-Process Theory (DPT). 7 2.1.2 Luna & Peracchio 2005. 8 2.2 Online Consumer Review (OCR). 10 2.2.1 Review Volume. 10 2.2.2 Review Valence. 12 2.2.3 Reviewer Credibility. 14 2.3 Bilingual-Switching: Number of Code-Switching. 18 2.4 Perceived Credibility. 21 2.5 Booking Intention. 22 2.6 Real Behaviour. 23 2.7 Control Variable. 23 CHAPTER THREE RESEARCH DESIGN AND METHODOLOGY 24 3.1 Conceptual Model. 24 3.2 Definition of Variables. 24 3.3 Summary of Hypotheses. 25 3.4 Research Design. 26 3.5 Experimental Procedure. 26 3.6 Measurement of Independent Variables. 27 3.6.1 Review Volume. 27 3.6.2 Review Valence. 28 3.6.3 Reviewer Credibility. 28 3.7 Measurement of Dependent Variables. 29 3.7.1 Perceived Credibility. 29 3.7.2 Booking Intention. 29 3.8 Measurement of Moderator: Code-switching. 30 3.9 Measurement of Control Variables. 31 3.9.1 Demographic Information. 31 3.9.2 Linguistic Information. 31 3.9.3 Recommendation System Familiarity. 32 3.10 Sampling Plan. 32 3.11 Data Analysis Procedure. 32 3.11.1 Descriptive Statistical Analysis. 32 3.11.2 Factor Analysis. 32 3.11.3 Reliability and Validity Test. 33 3.11.4 Confirmatory Factor Analysis (CFA) and Correlation Matrix. 33 3.11.6 Structural Equation Modelling (SEM). 33 CHAPTER FOUR RESEARCH RESULTS 34 4.1 Characteristic of Respondents. 34 4.2 Descriptive Statistics. 36 4.3 Confirmatory Factor Analysis and Reliability Test. 38 4.4 Manipulation Check Results. 40 4.4.1 Manipulation Check for Review Volume. 40 4.4.2 Manipulation Check for Review Valence. 40 4.4.3 Manipulation Check for Reviewer Credibility. 41 4.5 Confirmatory Factor Analysis (CFA). 42 4.5 Structural Equation Modelling (SEM). 43 4.6 Real Behaviour. 49 CHAPTER FIVE CONCLUSIONS AND SUGGESTIONS 51 5.1 Theoretical and Practical Implications. 51 5.2 Limitations and Suggestions for Future Research. 53 5.3 Research Discussion and Conclusions. 54 REFERENCES 55 APPENDICES 60 Appendix 1A: Examples of High and Low Review Volume. 60 Appendix 1B: Examples of High and Low Review Valence. 62 Appendix 1C: Examples of High and Low Reviewer Credibility. 63 Appendix 2: Screenshots of Our Survey. 64 Appendix 3A: CFA Overall. 77 Appendix 3B: SEM Model. 78 Appendix 3C: SEM Interaction Codeswitching and Review Volume. 79 Appendix 3D: SEM Interaction Codeswitching and Review Valence. 80 Appendix 3E: SEM Interaction Codeswitching and Reviewer Credibility. 81 Appendix 3F: Reviewer Credibility First Order Factor Model. 81 Appendix 3G: Review Valence First Order Factor Model. 82 Appendix 3H: Review Volume First Order Factor Model. 82 Appendix 3I: Perceived Credibility First Order Factor Model. 83

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