Wenjing Duan

Social Media and Firm Equity Value

Companies have increasingly advocated social media technologies to transform businesses and improve organizational performance. This study scrutinizes the predictive relationships between social media and firm equity value, the relative effects of social media metrics compared with conventional online behavioral metrics, and the dynamics of these relationships. The results derived from vector autoregressive models suggest that social media-based metrics Web blogs and consumer ratings are significant leading indicators of firm equity value. Interestingly, conventional online behavioral metrics Google searches and Web traffic are found to have a significant yet substantially weaker predictive relationship with firm equity value than social media metrics. We also find that social media has a faster predictive value, i.e., shorter “wear-in” time, than conventional online media. These findings are robust to a consistent set of volume-based measures total blog posts, rating volume, total page views, and search intensity. Collectively, this study proffers new insights for senior executives with respect to firm equity valuations and the transformative power of social media.

An Analysis of One-Star Online Reviews and Responses in the Washington, D.C., Lodging Market

The hotel industry continues to develop strategies for addressing consumer-generated online reviews, and particularly responding to poor reviews, which can have a damaging effect on a hotel’s reputation. To gain a greater understanding of the dynamics of poor reviews, this study analyzed 1,946 one-star reviews from ten popular online review websites, as well as 225 management responses from eighty-six Washington, D.C., hotels. A comprehensive complaint framework found that the most common complaints related to front desk staff, bathroom issues, room cleanliness, and guestroom noise issues. Complaints were also analyzed by hotel characteristics, including chain-scale segments, and reviewer characteristics, including purpose of travel and geographic location. Examining the reviews, highly rated hotels often respond to online complaints with appreciation, apologies, and explanations for what had gone wrong. Compensation adjustments are rarely mentioned by any hotel. The increasingly prominent role of social media necessitates that hotels use online reviews for market research and service recovery opportunities, regardless of whether they respond publicly.

To Continue Sharing or Not to Continue Sharing? – An Empirical Analysis of User Decision in Peer-to-Peer Sharing Networks

Peer-to-peer sharing networks have seen explosive growth recently. In these networks, sharing files is completely voluntary, and there is no financial reward for users to contribute. Yet many users continue to share despite the massive free-riding by others. Using a large-scale dataset of individual activities in a peer-to-peer music-sharing network, we seek to understand users’ continued-sharing behavior as a private contribution to a public good. We find that the more benefit users “get from” the network, in the form of downloads, browses, and searches, the more likely they are to continue sharing. Also, the more value users “give to” the network, in the form of downloads by other users and recognition by the network, the more likely they are to continue sharing. Moreover, our findings suggest that, overall, “getting-from” is a stronger force for the continued-sharing decision than “giving-to.”

Online user reviews, product variety, and the long tail: An empirical investigation on online software downloads

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.

Exploring the Impact of Social Media on Hotel Service Performance A Sentimental Analysis Approach

Online user-generated content in various social media websites, such as consumer experiences, user feedback, and product reviews, has increasingly become the primary information source for both consumers and businesses. In this study, we aim to look beyond the quantitative summary and unidimensional interpretation of online user reviews to provide a more comprehensive view of online user-generated content. Moreover, we would like to extend the current literature to the more customer-driven service industries, particularly the hotel industry. We obtain a unique and extensive dataset of online user reviews for hotels across various review sites and over long time periods. We use the sentiment analysis technique to decompose user reviews into different dimensions to measure hotel service quality and performance based on the SERVPERF model. Those dimensions are then incorporated into econometrics models to examine their effect in shaping users’ overall evaluation and content-generating behavior. The results suggest that different dimensions of user reviews have significantly different effects in forming user evaluation and driving content generation. This paper demonstrates the importance of using textual data to measure consumers’ relative preferences for service quality and evaluate service performance.

A social network matrix for implicit and explicit social network plates

A majority of social network research deals with explicitly formed social networks. Although only rarely acknowledged for its existence, we believe that implicit social networks play a significant role in the overall dynamics of social networks. We propose a framework to evaluate the dynamics and characteristics of a set of explicit and associated implicit social networks. Specifically, we propose a social network matrix to measure the implicit relationships among the entities in various social networks. We also derive several indicators to characterize the dynamics in online social networks. We proceed by incorporating implicit social networks in a traditional network flow context to evaluate key network performance indicators such as the lowest communication cost, maximum information flow, and the budgetary constraints. We consider (online) implicit social networks.We propose a social network matrix to measure the implicit relationships among the entities in various social networks.We derive several indicators to characterize the dynamics in online social networks.

Do Professional Reviews Affect Online User Choices through User Reviews?: An Empirical Study

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.

Analyzing the impact of intermediaries in electronic markets: an empirical investigation of online consumer-to-consumer (C2C) auctions

It has been widely believed that the Internet and electronic markets will eliminate traditional intermediaries. However, a close examination of the market mechanism indicates that the impact of intermediaries is indispensable. Specifically, we consider intermediaries’ impacts in price discovery and trust building. Intermediaries provide a buffer for temporary misalignment between supply and demand by buying low and selling high, and also help build trust by engaging in transactions with risk-averse buyers and sellers who otherwise will not participate in the market. Using a dataset from eBay’s online auctions, we examine empirically these two impacts of human intermediaries. We find that the presence of brokers has a significant impact on market liquidity, resulting in more successful trades and higher auction prices. In addition, we find that brokers are more likely to engage in transactions with less established sellers. Their presence reduces reputation penalty faced by these players and further facilitates the successful sale of items in auctions.

Implicit Many-to-One Communication in Online Communities

The recent explosive growth of popular social communities such as Flickr.com, YouTube.com and Digg.com has generated much renewed interest on the Internet as a new medium. This new movement is often considered attributable to the Web 2.0 technologies (e.g., Ajax, XML, RSS, and Wiki) and social computing concepts (e.g. blog, tagging, and voting) that make mass user interactions both easy and multi-faceted. They retain the existing ingredients of online community-based communications, such as individual relationship and message-based conversations. At the same time, non-message-based and often collective interactions, e.g., voting and ranking, enrich user communication.

Online Peer-to-Peer Communities: An Empirical Investigation of a Music Sharing Community as a Dynamic Two-Sided Network

Online peer-to-peer communities and online social networks have become increasingly popular. In particular, the recent boost of online peer-to-peer communities leads to exponential growth in sharing of user-contributed content which have brought profound changes to business and economic practices. Understanding the formation and sustainability of such peer-to-peer communities has important implications for businesses. We develop a dynamic two-sided network model that relates growth of communities to interactions between contribution and consumption of resources in online sharing activities. Using online music sharing data collected from a popular IRC music sharing service over five years, we empirically apply the model to identify dynamics in the music sharing community. We find that the music sharing community demonstrates distinctive characteristics of a two-sided network. Contribution in the community leads to more consumption and consumption leads to more contribution, creating positive network effects in the community. Moreover, we find significant negative externalities among consumption activities and among contribution activities. The combination of the positive and negative externalities drives the underlying dynamics and growth of online sharing communities. Using the dynamic model, we quantify equilibrium growth rate of the community. We find that the equilibrium growth rate changes over time, possibly as a result of legal actions taken by the music industry. Our study provides a first glimpse into the mechanism through which peer-to-peer communities sustain and thrive in a constantly changing environment.