A Statistical Measure of a Population's Propensity to Engage in Post-Purchase Online Word-of-Mouth

The emergence of online communities has enabled firms to monitor consumer-generated online word-of-mouth (WOM) in real-time by mining publicly available information from the Internet. A prerequisite for harnessing this new ability is the development of appropriate WOM metrics and the identification of relationships between such metrics and consumer behavior. Along these lines this paper introduces a metric of a purchasing population's propensity to rate a product online. Using data from a popular movie website we find that our metric exhibits several relationships that have been previously found to exist between aspects of a product and consumers' propensity to engage in offline WOM about it. Our study, thus, provides positive evidence for the validity of our metric as a proxy of a population's propensity to engage in post-purchase online WOM. Our results also suggest that the antecedents of offline and online WOM exhibit important similarities.Comment: Published at http://dx.doi.org/10.1214/088342306000000169 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Media, Aggregators, and the Link Economy: Strategic Hyperlink Formation in Content Networks

A defining property of the World Wide Web is a content site's ability to place virtually costless hyperlinks to third-party content as a substitute or complement to its own content. Costless hyperlinking has enabled new types of players, usually referred to as content aggregators, to successfully enter content ecosystems, attracting traffic and revenue by hosting links to the content of others. This, in turn, has sparked a heated controversy between content creators and aggregators regarding the legitimacy and costs/benefits of uninhibited free linking. To our knowledge, this work is the first to model the complex interplay between content and links in settings where a set of sites compete for traffic. We develop a series of analytical models that distill how hyperlinking affects the (a) incentives of content nodes to produce quality content versus link to third-party content, (b) profits of the various stakeholders, (c) average quality of content that becomes available to consumers, and (d) impact of content aggregators. Our results provide a nuanced view of the so-called link economy, highlighting both the beneficial consequences and the drawbacks of free hyperlinks for content creators and consumers.This paper was accepted by Lorin Hitt, information systems

The Lord Of The Ratings: Is A Movie\u27s Fate is Influenced by Reviews?

Third-party reviews play an important role in many contexts in which tangible attributes are insufficient to enable consumers to evaluate products or services. In this paper, we examine the impact of professional and amateur reviews on the box office performance of movies. Using a simple diffusion model, we establish an econometrics framework to control for the interaction between the unobservable quality of movies and a word-of-mouth diffusion process and thereby estimate the residual impact of online amateur reviews on demand. The results indicate the significant influence of the valence measure (star ratings) of online reviews, but their volume measure (propensity to write reviews) is not significant once we control for quality. Furthermore, the analysis suggests that the variance measure (disagreement) of reviews does not play a significant role in the early weeks after a movie opening. The estimated influence of the valence measure implies that a one-point increase in the valence can be associated with a 4–10% increase in box office revenues

Exploring the Value of Online Reviews to Organizations: Implications for Revenue Forecasting and Planning

One of the most intriguing social phenomena brought forth by advances in information and communication technologies is the vast amplification of the power of word-of-mouth. With the help of the Internet, wireless networking, and mobile telephony, today’s citizens and consumers are forming a bewildering array of technology-mediated communities where they exchange opinions and experiences on companies, products, services, and even world events

Harnessing Crowds: Mapping the Genome of Collective Intelligence

Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia, Threadless, and many others. To take advantage of the possibilities these new systems represent, it is necessary to go beyond just seeing them as a fuzzy collection of “cool” ideas. What is needed is a deeper understanding of how these systems work. This article offers a new framework to help provide that understanding. It identifies the underlying building blocks—to use a biological metaphor, the “genes”—at the heart of collective intelligence systems. These genes are defined by the answers to two pairs of key questions: – Who is performing the task? Why are they doing it? – What is being accomplished? How is it being done? The paper goes on to list the genes of collective intelligence—the possible answers to these key questions—and shows how combinations of genes comprise a “genome” that characterizes each collective intelligence system. In addition, the paper describes the conditions under which each gene is useful and the possibilities for combining and re-combining these genes to harness crowds effectively. Using this framework, managers can systematically consider many possible combinations of genes as they seek to develop new collective intelligence systems. ∗ University of Maryland

Attention allocation in information-rich environments:the case of news aggregators

News aggregators have emerged as an important component of digital content ecosystems, attracting traffic by hosting curated collections of links to third party content, but also inciting conflict with content producers. Aggregators provide titles and short summaries (snippets) of articles they link to. Content producers claim that their presence deprives them of traffic that would otherwise flow to their sites. In light of this controversy, we conduct a series of field experiments whose objective is to provide insight with respect to how readers allocate their attention between a news aggregator and the original articles it links to. Our experiments are based on manipulating elements of the user interface of a Swiss mobile news aggregator. We examine how key design parameters, such as the length of the text snippet that an aggregator displays about articles, the presence of associated images, and the number of related articles on the same story, affect a reader’s propensity to visit the content producer's site and read the full article. Our findings suggest the presence of a substitution relationship between the amount of information that aggregators offer about articles and the probability that readers will opt to read the full articles at the content producer sites. Interestingly, however, when several related article outlines compete for user attention, a longer snippet and the inclusion of an image increase the probability that an article will be chosen over its competitors

On the motivating impact of price and online recommendations at the point of online purchase

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 ElsevierDo online recommendations have the same motivating impact as price at the point of online purchase? The results (n = 268) of an conjoint study show that: (1) when the price is low or high relatively to market price, it has the strongest impact (positive and negative) on the likelihood of an online purchase of an mp3 player, (2) when the price is average to market price, online recommendation and price are equal in their impact at the point of online purchase, and, (3) the relative impact from price increases when online shopping frequencies increases. The implications these results give are that online retailers should be aware that online recommendations are not as influential as a good offer when consumers purchase electronics online. However, other customer recommendations have a stronger impact on novice online shoppers than towards those consumers that shop more frequently online

Universality in movie rating distributions

In this paper histograms of user ratings for movies (1,...,10) are analysed. The evolving stabilised shapes of histograms follow the rule that all are either double- or triple-peaked. Moreover, at most one peak can be on the central bins 2,...,9 and the distribution in these bins looks smooth `Gaussian-like' while changes at the extremes (1 and 10) often look abrupt. It is shown that this is well approximated under the assumption that histograms are confined and discretised probability density functions of L\'evy skew alpha-stable distributions. These distributions are the only stable distributions which could emerge due to a generalized central limit theorem from averaging of various independent random avriables as which one can see the initial opinions of users. Averaging is also an appropriate assumption about the social process which underlies the process of continuous opinion formation. Surprisingly, not the normal distribution achieves the best fit over histograms obseved on the web, but distributions with fat tails which decay as power-laws with exponent -(1+alpha) (alpha=4/3). The scale and skewness parameters of the Levy skew alpha-stable distributions seem to depend on the deviation from an average movie (with mean about 7.6). The histogram of such an average movie has no skewness and is the most narrow one. If a movie deviates from average the distribution gets broader and skew. The skewness pronounces the deviation. This is used to construct a one parameter fit which gives some evidence of universality in processes of continuous opinion dynamics about taste.Comment: 8 pages, 5 figures, accepted for publicatio

Credit Scoring with Social Network Data

Motivated by the growing practice of using social network data in credit scoring, we analyze the impact of using network-based measures on customer score accuracy and on tie formation among customers. We develop a series of models to compare the accuracy of customer scores obtained with and without network data. We also investigate how the accuracy of social network-based scores changes when consumers can strategically construct their social networks to attain higher scores. We find that those who are motivated to improve their scores may form fewer ties and focus more on similar partners. The impact of such endogenous tie formation on the accuracy of consumer score is ambiguous. Scores can become more accurate as a result of modifications in social networks, but this accuracy improvement may come with greater network fragmentation. The threat of social exclusion in such endogenously formed networks provides incentives to low-type members to exert effort that improves everyone\u27s creditworthiness. We discuss implications for managers and public policy