wenqi zhou | Duquesne University (original) (raw)
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Massachusetts Institute of Technology (MIT)
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With the broad reach of the Internet, online users frequently resort to various word-of-mouth (WO... more With the broad reach of the Internet, online users frequently resort to various word-of-mouth (WOM) sources, such as online user reviews and professional reviews, during online decision making. Although prior studies generally agree on the importance of online WOM, we have little knowledge of the interplay between online user reviews and professional reviews. This paper empirically investigates a mediation model in which online user reviews mediate the impact of professional reviews on online user decisions. Using software download data, we show that a higher professional rating not only directly promotes software download but also results in more active user-generated WOM interactions, which indirectly lead to more downloads. The indirect impact of professional reviews can be as large as 20% of the corresponding total impact. These findings deepen our understanding of online WOM effect, and provide managerial suggestions about WOM marketing and the prediction of online user choices.
SSRN Electronic Journal, 2000
ABSTRACT Consumers consistently resort to online Word-of-Mouth (WOM) as an effective remedy for t... more ABSTRACT Consumers consistently resort to online Word-of-Mouth (WOM) as an effective remedy for the lack of physical trials in online shopping. Nevertheless, they are confronting relatively different levels of search costs for WOM information depending on the distribution of WOM across websites. This study investigates the sales impacts of dispersion of WOM volume and variation of WOM valence by using sales and WOM data of software programs from Amazon and download.com. Our results suggest that, conditional on the total number of WOM conversations from retailing websites and third-party websites, less evenly distributed WOM leads to more sales. And it is even more beneficial for a product’s sales if having this less dispersed WOM distribution skewed towards retailing websites. In addition, more consistent consumer evaluations across websites encourage online purchasing decisions. By comparing the volume dispersion and variance variation, we find that receiving one hundred reviews of 5-star average rating on Amazon leads to sales almost six time more than receiving fifty reviews of 5-star average rating on Amazon and another fifty reviews of 5-star average rating on download.com.
Our study examines the impact of both a demand side factor (online user reviews) and a supply sid... more Our study examines the impact of both a demand side factor (online user reviews) and a supply side factor
(product variety) on the long tail and superstar phenomena in the context of online software downloading.
The descriptive analysis suggests a significant superstar download pattern and also the
emergence of the long tail. Using the quantile regression technique, we find the significant interaction
effect between online user reviews and product variety on software download. We find that the impacts
of both positive and negative user reviews are weakened as product variety goes up. In addition, the
increase in product variety reduces the impact of user reviews on popular products more than it does
on niche products. After taking the interaction effect into account, we find that the overall impact of
the increased product variety helps niche products to get more downloads. These results highlight the
importance of considering the intricate interplay between demand side and supply side factors in the
long tail and online word-of-mouth research.
Firms use social media marketing to promote products and collect consumer feedback for the produc... more Firms use social media marketing to promote products and collect consumer feedback for the product development process. Their practice of investing in retailer-hosted Word-of-Mouth (internal WOM) is supported by a positive feedback mechanism between internal WOM and retail sales. Internal WOM is a sales influencer: consumers can get informed about a product by a large volume of internal WOM. It is also a sales outcome: greater past sales lead to more WOM. Beyond internal WOM, consumers are shown to search widely for product information on third-party websites. Consequently, many firms also start to invest in content on third-party websites. However, little is known regarding the interplay between internal WOM and the contents of third-party websites, which have both been invested in by firms in recent years. In the context of the online software market, this study examines how WOM hosted by third-party websites (external WOM) and third-party free sampling influence the feedback mechanism between internal WOM and retail sales. Using data from Download.com and Amazon.com, we analyze the impact via a simultaneous equation model in a Bayesian hierarchical framework. We find that external WOM and third-party free sampling moderate the sales-outcome role of internal WOM in different ways. Receiving external user reviews amplifies the impact of past sales on volume of internal WOM; whereas third-party free sampling weakens the impact of past sales on internal WOM. Moreover, this impact of external WOM and third-party free sampling on the sales-outcome role of internal WOM is much more significant than their impact on the sales-influencer role of internal WOM.
With the broad reach of the Internet, online users frequently resort to various word-of-mouth (WO... more With the broad reach of the Internet, online users frequently resort to various word-of-mouth (WOM) sources, such as online user reviews and professional reviews, during online decision making. Although prior studies generally agree on the importance of online WOM, we have little knowledge of the interplay between online user reviews and professional reviews. This paper empirically investigates a mediation model in which online user reviews mediate the impact of professional reviews on online user decisions. Using software download data, we show that a higher professional rating not only directly promotes software download but also results in more active user-generated WOM interactions, which indirectly lead to more downloads. The indirect impact of professional reviews can be as large as 20% of the corresponding total impact. These findings deepen our understanding of online WOM effect, and provide managerial suggestions about WOM marketing and the prediction of online user choices.
SSRN Electronic Journal, 2000
ABSTRACT Consumers consistently resort to online Word-of-Mouth (WOM) as an effective remedy for t... more ABSTRACT Consumers consistently resort to online Word-of-Mouth (WOM) as an effective remedy for the lack of physical trials in online shopping. Nevertheless, they are confronting relatively different levels of search costs for WOM information depending on the distribution of WOM across websites. This study investigates the sales impacts of dispersion of WOM volume and variation of WOM valence by using sales and WOM data of software programs from Amazon and download.com. Our results suggest that, conditional on the total number of WOM conversations from retailing websites and third-party websites, less evenly distributed WOM leads to more sales. And it is even more beneficial for a product’s sales if having this less dispersed WOM distribution skewed towards retailing websites. In addition, more consistent consumer evaluations across websites encourage online purchasing decisions. By comparing the volume dispersion and variance variation, we find that receiving one hundred reviews of 5-star average rating on Amazon leads to sales almost six time more than receiving fifty reviews of 5-star average rating on Amazon and another fifty reviews of 5-star average rating on download.com.
Our study examines the impact of both a demand side factor (online user reviews) and a supply sid... more Our study examines the impact of both a demand side factor (online user reviews) and a supply side factor
(product variety) on the long tail and superstar phenomena in the context of online software downloading.
The descriptive analysis suggests a significant superstar download pattern and also the
emergence of the long tail. Using the quantile regression technique, we find the significant interaction
effect between online user reviews and product variety on software download. We find that the impacts
of both positive and negative user reviews are weakened as product variety goes up. In addition, the
increase in product variety reduces the impact of user reviews on popular products more than it does
on niche products. After taking the interaction effect into account, we find that the overall impact of
the increased product variety helps niche products to get more downloads. These results highlight the
importance of considering the intricate interplay between demand side and supply side factors in the
long tail and online word-of-mouth research.
Firms use social media marketing to promote products and collect consumer feedback for the produc... more Firms use social media marketing to promote products and collect consumer feedback for the product development process. Their practice of investing in retailer-hosted Word-of-Mouth (internal WOM) is supported by a positive feedback mechanism between internal WOM and retail sales. Internal WOM is a sales influencer: consumers can get informed about a product by a large volume of internal WOM. It is also a sales outcome: greater past sales lead to more WOM. Beyond internal WOM, consumers are shown to search widely for product information on third-party websites. Consequently, many firms also start to invest in content on third-party websites. However, little is known regarding the interplay between internal WOM and the contents of third-party websites, which have both been invested in by firms in recent years. In the context of the online software market, this study examines how WOM hosted by third-party websites (external WOM) and third-party free sampling influence the feedback mechanism between internal WOM and retail sales. Using data from Download.com and Amazon.com, we analyze the impact via a simultaneous equation model in a Bayesian hierarchical framework. We find that external WOM and third-party free sampling moderate the sales-outcome role of internal WOM in different ways. Receiving external user reviews amplifies the impact of past sales on volume of internal WOM; whereas third-party free sampling weakens the impact of past sales on internal WOM. Moreover, this impact of external WOM and third-party free sampling on the sales-outcome role of internal WOM is much more significant than their impact on the sales-influencer role of internal WOM.