Published Papers

We leverage a temporary block of the Chinese microblogging platform Sina Weibo due to political events to estimate the causal effect of online word-of-mouth content on product demand in the context of TV show viewership. Based on this source of exogenous variation, we estimate an elasticity of TV show ratings (market share in terms of viewership) with respect to the number of relevant comments (comments were disabled during the block) of 0.016. We find that more postshow microblogging activity increases demand, whereas comments posted prior to the show airing do not affect viewership. These patterns are inconsistent with informative or persuasive effects and suggest complementarity between TV consumption and anticipated postshow microblogging activity.

Interpersonal communications have long been recognized as an influential source of information for consumers. Internet-based media have facilitated information exchange among firms and consumers, as well as observability and measurement of such exchanges. However, much of the research addressing online communication focuses on ratings collected from online forums. In this paper, we look beyond ratings to a more comprehensive view of online communications. We consider the sales effect of the volume of positive, negative, and neutral online communications captured by Web crawler technology and classified by automated sentiment analysis. Our modeling approach captures two key features of our data, dynamics and endogeneity. In terms of dynamics, we model daily measures of online communications about a firm and its products as contributing to a latent demand-generating stock variable. To account for the endogeneity, we extend the latent instrumental variable technique to account for dynamic endogenous regressors. Our results demonstrate a significant effect of positive, negative, and neutral online communications on daily sales performance. Failure to account for endogeneity results in a severe attenuation of the estimated effects. From a managerial perspective, we demonstrate the importance of accounting for communication valence as well as the impact of shocks to positive, negative, and neutral online communications.

We study how opinion leadership and social contagion within social networks affect the adoption of a new product. In contrast to earlier studies, we find evidence of contagion operating over network ties, even after controlling for marketing effort and arbitrary systemwide changes. More importantly, we also find that the amount of contagion is moderated by both the recipients' perception of their opinion leadership and the sources' volume of product usage. The other key finding is that sociometric and self-reported measures of leadership are weakly correlated and associated with different kinds of adoption-related behaviors, which suggests that they probably capture different constructs. We discuss the implications of these novel findings for diffusion theory and research and for marketing practice.

We examine whether the likelihood of entrepreneurial activity is related to the prior career experiences of an individual's coworkers, using a unique matched employer-employee panel data set. We argue that coworkers can increase the likelihood that an individual will perceive entrepreneurial opportunities as well as increase his or her motivation to pursue those opportunities. We find that an individual is more likely to become an entrepreneur if his or her coworkers have been entrepreneurs before. Peer influences also appear to be substitutes for other sources of entrepreneurial influence: we find that peer influences are strongest for those who have less exposure to entrepreneurship in other aspects

Using box-office data for all movies released between 1982 and 2000, I quantify how much the consumption decisions of individuals depend on information they receive from their peers, when quality is ex ante uncertain. In the presence of social learning, we should see different box-office sales dynamics depending on whether opening weekend demand is higher or lower than expected. I use a unique feature of the movie industry to identify ex ante demand expectations: the number of screens dedicated to a movie in its opening weekend reflects the sales expectations held by profit-maximizing theatre owners. Several pieces of evidence are consistent with social learning. First, sales of movies with positive surprise and negative surprise in opening weekend demand diverge over time. If a movie has better than expected appeal and therefore experiences larger than expected sales in Week 1, consumers in Week 2 update upward their expectations of quality, further increasing Week 2 sales. Second, this divergence is small for movies for which consumers have strong priors and large for movies for which consumers have weak priors. Third, the effect of a surprise is stronger for audiences with large social networks. Finally, consumers do not respond to surprises in first-week sales that are orthogonal to movie quality, like weather shocks. Overall, social learning appears to be an important determinant of sales in the movie industry, accounting for 32% of sales for the typical movie with positive surprise. This implies the existence of a large "social multiplier" such that the elasticity of aggregate demand to movie quality is larger than the elasticity of individual demand.

The authors quantify the impact of social interactions and peer effects in the context of physicians' prescription choices. Using detailed individual-level prescription data, along with self-reported social network information, the authors document that physician prescription behavior is significantly influenced by the behavior of research-active specialists, or "opinion leaders," in the physician's reference group. The authors leverage a natural experiment in the category: New guidelines released about the therapeutic nature of the focal drug generated conditions in which physicians were more likely to be influenced by the behavior of specialist physicians in their network. The authors (1) find important, statistically significant peer effects that are robust across model specifications; (2) document asymmetries in response to marketing activity across nominators and opinion leaders; (3) measure the incremental value to firms of directing targeted sales force activity to these opinion leaders; and (4) present estimates of the social multiplier of detailing in this category.

Word of mouth affects consumer behavior, but how does the language used in word of mouth shape that impact? Might certain types of consumers be more likely to use certain types of language, affecting whose words have more influence? Five studies, including textual analysis of more than 1,000 online reviews, demonstrate that compared to more implicit endorsements (e.g., "I liked it," "I enjoyed it"), explicit endorsements (e.g., "I recommend it") are more persuasive and increase purchase intent. This occurs because explicit endorsers are perceived to like the product more and have more expertise. Looking at the endorsement language consumers actually use, however, shows that while consumer knowledge does affect endorsement style, its effect actually works in the opposite direction. Because novices are less aware that others have heterogeneous product preferences, they are more likely to use explicit endorsements. Consequently, the endorsement styles novices and experts tend to use may lead to greater persuasion by novices. These findings highlight the important role that language, and endorsement styles in particular, plays in shaping the effects of word of mouth.

This article uses actual word-of-mouth (WOM) information to examine the dynamic patterns of WOM and how it helps explain box office revenue. The WOM data were collected from the Yahoo Movies Web site. The results show that WOM activities are the most active during a movie's prerelease and opening week and that movie audiences tend to hold relatively high expectations before release but become more critical in the opening week. More important, WOM information offers significant explanatory power for both aggregate and weekly box office revenue, especially in the early weeks after a movie opens. However, most of this explanatory power comes from the volume of WOM and not from its valence, as measured by the percentages of positive and negative messages.

Many consumers base their purchase decisions on online consumer reviews. An overlooked feature of these texts is their narrativity: the extent to which they tell a story. The authors construct a new theory of narrativity to link the narrative content and discourse of consumer reviews to consumer behavior. They also develop from scratch a computerized technique that reliably determines the degree of narrativity of 190,461 verbatim, online consumer reviews and validate the automated text analysis with two controlled experiments. More transporting (i.e., engaging) and persuasive reviews have better-developed characters and events as well as more emotionally changing genres and dramatic event orders. This interdisciplinary, multimethod research should help future researchers (1) predict how narrativity affects consumers' narrative transportation and persuasion, (2) measure the narrativity of large digital corpora of textual data, and (3) understand how this important linguistic feature varies along a continuum.

Does the number of people with whom someone communicates influence what he or she discusses and shares? Six studies demonstrate that compared with narrowcasting (i.e., communicating with just one person), broadcasting (i.e., communicating with multiple people) leads consumers to avoid sharing content that makes them look bad. Narrowcasting, however, encourages people to share content that is useful to the message recipient. These effects are driven by communicators' focus of attention. People naturally tend to focus on the self, but communicating with just one person heightens other-focus, which leads communicators to share less self-presenting content and more useful content. These findings shed light on the drivers of word of mouth and provide insight into when the communication sender (vs. receiver) plays a relatively larger role in what people share.

Internet review forums increasingly supplement expert opinion and social networks in informing consumers about product quality. However, limited empirical evidence links digital word-of-mouth to purchasing decisions. We implement a regression discontinuity design to estimate the effect of positive Yelp.com ratings on restaurant reservation availability. An extra half-star rating causes restaurants to sell out 19 percentage points (49%) more frequently, with larger impacts when alternate information is more scarce. These returns suggest that restaurateurs face incentives to leave fake reviews but a rich set of robustness checks confirm that restaurants do not manipulate ratings in a confounding, discontinuous manner.

The authors examine the effect of consumer reviews on relative sales of books at Amazon.com and Barnesandnoble.com. The authors find that (1) reviews are overwhelmingly positive at both sites, but there are more reviews and longer reviews at Amazon.com; (2) an improvement in a book's reviews leads to an increase in relative sales at that site; (3) for most samples in the study, the impact of one-star reviews is greater than the impact of five-star reviews; and (4) evidence from review-length data suggests that customers read review text rather than relying only on summary statistics.