Essays on multidimensional word-of-mouth effects on product performance

다국어 초록 (Multilingual Abstract)

Since the development of Internet technology, marketers actively examine word-of-mouth (WOM) effects. Based on previous research findings (i.e. the positive effect of WOM volume and valence & the negative effect of WOM variance), this thesis focuses on online word-of-mouth (WOM) effects on product performance. First, essay 1 suggests possible interactions between WOM characteristics (volume, valence, and variance) and proposes an integrative framework to measure the effects of WOM on product performance. A panel vector autoregressive with exogeneous variables model is constructed and applied to consumer reviews and book sales data obtained from amazon.com through web crawling. Product performance elasticities with respect to WOM volume are significantly larger than WOM volume elasticities with respect to product performance, especially in the long run. Increased WOM volume have a positive effect on product performance, however WOM valence and variance has no effect on product performance. WOM valence and variance are found to negatively interact with each other. Marketers should pay extra attention to WOM volume, which shows significantly increased short- and long-run effects on product performance. WOM volume may indirectly benefit a firm by interacting with WOM valence and variance, and marketers should attend to the two characteristics, as they negatively affect WOM volume. Essay 1 contributes to the literature by incorporating dynamic interactions between three WOM characteristics and product performance. Unlike previous findings, the effects of WOM valence and variance on product performance are not sizable when considering the interactions between WOM variables. This study also suggests that WOM volume plays a crucial role in future WOM aspects, such as valence and variance.
In addition, essay 2 investigates the effect of WOM volatility, a new WOM variable that measures the over-time fluctuation in the WOM volume, on product performance. High WOM volatility can be regarded similar as the advertising pulsing strategy. An unexpected large WOM volume may be effective for awareness formation that has a positive impact on product performance. However, unlike advertising, WOM may contain various types of information including negative messages. Therefore, high WOM volatility can create information overload. In other words, consumers must spend more time and efforts to interpret a large amount of information due to high WOM volatility, which may lower preference. Moreover, more fluctuating WOM volume can make the contents of WOM less credible because consumers may suspect the firm’s manipulation of the WOM to better expose a product. As a result, these two conflicting forces of WOM volatility (i.e., positive effects on awareness and negative effects on preference and credibility) leave the direct relationship between the WOM volatility and product performance as an empirical question. Also, essay 2 investigate the moderating effects of WOM volatility on the relationship between existing WOM variables (i.e., volume, valence, and variance) and product performance. To verifying WOM volatility effects, cross-sectional regression analysis was conducted, using online WOM data in Korea movie industry. The results show that WOM volatility negatively affects the product performance only when consumers rely more on WOM information. Highly volatile WOMs weaken the positive effects of WOM volume and valence and the negative effects of WOM variance. This research suggested WOM volatility as a new characteristic of WOM. This study examined WOM volatility interacts with existing WOM variables. Managerial and academic implications are discussed.

목차 (Table of Contents)

• Contents
• Research Overview...…………………………………………………………..……...1
• Essay 1…………….…………………………………………………….…..5
• 1. Introduction……………………………………………………………….6
• 2. Research Background…………………………………………………11
• 2.1. Effects of WOM on Product Performance…………………..……..11
• 2.2. Interactions Between WOM Variables…………………………….13
• 2.3. Product Performance Effects on WOM Variables…………………19
• 3. Modeling Approach…………………………………………………....22
• 4. Data…………………………………...………………...……………..30
• 5. Results…………………………………………………….…………..34
• 5.1. Unit Root Test……………………………………………………..35
• 5.2. Model Estimation…………………………………………..……..36
• 5.3. Granger Causality Test……………………………………………36
• 5.4. The Integrative Relationship Between WOM Variables and Product Performance…………………………………………….……………..38
• 5.5. Dynamic Contribution of WOM Variables and Product Performance……………………………………………...……..……..48
• 6. Discussion …………………………………………………………….50
• 7. Conclusion…………………………………………………………….53
• Essay 2…………………………….……………………………………….57
• 1. Introduction………………………………………………….....……..58
• 2. Literature Review………………………………………..…..………..62
• 2.1. Volume of Word-of-mouth………………………………………....62
• 2.2. Valence of Word-of-mouth…………………………………………63
• 2.3. Variance of Word-of-mouth………………………………………..65
• 2.4. Volatility of Word-of-mouth…………………………………...…..66
• 3. Hypothesis Development……………………………...……………....68
• 4. Methodology………………………………………………...………..75
• 4.1. Data collection……………………………………………………75
• 4.2. Measurement……………………………………………………...78
• 4.2.1. Product Performance……………………………………..…..78
• 4.2.2. WOM variables……………………………………………….78
• 4.2.3. WOM volatility…………...………………………………..….78
• 4.2.4. Movie characteristics……….……………………………..…..80
• 5. Model Specification……………………………………………….…..83
• 6. Results…………………………………………………………...………85
• 7. Economic Simulation……………………………………………………91
• 8. Conclusion……………………………………………………..………..93
• References…………………..……………………………………………..99