Marketing Mini Symposium

Social Influence Among Customers (Peter Verhoef, RUG)
Many firms capitalize on their customers’ social networks to improve the success rate of their new products. In this paper, the authors analyze the dynamic effects of social influence and direct marketing on the adoption of a new high-technology product. Social influence is likely to play a role because the decision to adopt a high-involvement product requires extensive search of information from various sources. The authors use call detail records to construct ego networks for a large sample of customers of a Dutch mobile telecommunications operator. Using a fractional polynomial hazard approach to model adoption timing and multiple social influence variables, they provide a fine-grained analysis of social influence. They show that the effect of social influence from cumulative adoptions in a customer’s network decreases from the product introduction onward, whereas the influence of recent adoptions remains constant. The effect of direct marketing is also positive and decreasing from the product introduction onward. Hence, this study provides new insights into adoption of high-technology products by analyzing dynamic effects of social influence and direct marketing simultaneously.  

Hyper Media Search and Consumption (Carl Mela, Duke University)
In the past five years, the number of Americans using the Internet as their main source of news has doubled to more than 40%, while those choosing newspapers has dropped to just over 30%. Although this trend signals a shift in the consumption of information in favor of hyper-media, wherein excerpting and linking is commonplace, research regarding how consumers acquire news in online environments has not proceeded apace. We develop a model of forward-looking consumers who gain knowledge and utility through the search and consumption of hyper-media, and explore its implications for welfare and site policy.

The model is estimated using comScore browsing data for five celebrity news and gossip sites, supplemented with link data scraped from site archives. The model is estimated by coupling Imai, Jain, and Ching’s (2009; Econometrica 77(6):1865–1899) method with the Riemann manifold sampling algorithm of Girolami and Calderhead (2011; JRSS-B 73(2):123–214). The pairing of these recent advances enables researchers to estimate dynamic models with many more variables and states than previously considered.

Results indicate consumers are heterogeneous in their preferences for certain types of celebrity sites (e.g., females prefer sites that emphasize gossip over pictorials of female models and entertainers). Results also indicate that links to other sites are informative about the target site’s potential quality; after observing one link to another site, consumers’ uncertainty about the linked site’s quality is about 20% lower.

Counterfactual analyses show that network throttling, in which access to all sites is slowed down uniformly in an effort to reduce congestion, has an unequal effect on site traffic. For example, sites frequented by consumers with higher than average browsing costs lose a greater share of their traffic. A related analysis shows that when carriers take bandwidth from one site and reallocate it to others, some consumers who browse less are actually better off, and some who browse more are worse off. A third counterfactual analysis shows how a change in fair use law, in which excerpts and links become less informative of the linked sites’ quality, causes consumers with more niche tastes to curtail their searches, consequently decreasing traffic at sites with mainstream content and many inbound links.

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