Contracting with Word-of-Mouth Management

We incorporate word of mouth (WoM) in a classic Maskin-Riley contracting problem, allowing for referral rewards to senders of WoM. Current customers’ incentives to engage in WoM can affect the contracting problem of a firm in the presence of positive externalities of users. We fully characterize the optimal contract scheme and provide comparative statics. In particular, we show that offering a free contract is optimal only if the fraction of premium users in the population is small. The reason is that by offering a free product, the firm can incentivize senders to talk by increasing expected externalities that they receive and this is effective only if there are many free users. This result is consistent with the observation that companies that successfully offer freemium contracts oftentimes have a high percentage of free users

Contracting with Word-of-Mouth Management

We incorporate word of mouth (WoM) in a classic Maskin-Riley contracting problem, allowing for referral rewards to senders of WoM. Current customers’ incentives to engage in WoM can affect the contracting problem of a firm in the presence of positive externalities of users. We fully characterize the optimal contract scheme and provide other comparative statics. In particular, we show that offering a free contract is optimal only if the fraction of premium users in the population is small. The reason is that by offering a free product, the firm can incentivize senders to talk by increasing expected externalities that they receive and this can (partly) substitute for paying referral rewards only if there are few premium customers. This result is consistent with the observation that companies that successfully offer freemium contracts oftentimes have a high percentage of free users

Influence or Advertise: The Role of Social Learning in Influencer Marketing

We compare influencer marketing to targeted advertising from information aggregation and product awareness perspectives. Influencer marketing leverages network effects by allowing consumers to socially learn from each other about their experienced content utility, but consumers may not know whether to attribute promotional post popularity to high content or high product quality. If the quality of a product is uncertain (e.g., it belongs to an unknown brand), then a mega influencer with consistent content quality fosters more information aggregation than a targeted ad and thereby yields higher profits. When we compare influencer marketing to untargeted ad campaigns or if the product has low quality uncertainty (e.g., belongs to an established brand), then many micro influencers with inconsistent content quality create more consumer awareness and yield higher profits. For products with low quality uncertainty, the firm wants to avoid information aggregation as it disperses posterior beliefs of consumers and leads to fewer purchases at the optimal price. Our model can also explain why influencer campaigns either go viral or go bust, and how for niche products, micro-influencers with consistent content quality can be a valuable marketing tool

The Benefit of Collective Reputation

We study a model of collective reputation and use it to analyze the benefit of collective brands. Consumers form beliefs about the quality of an experience good that is produced by one firm that is part of a collective brand. Consumers’ limited ability to distinguish among firms in the collective and to monitor firms’ investment decisions creates incentives to free-ride on other firms’ investment efforts. Nevertheless, we show that collective brands induce stronger incentives to invest in quality than individual brands under two types of circumstances: if the main concern is with quality control and the baseline reputation of the collective is low, or if the main concern is with the acquisition of specialized knowledge and the baseline reputation of the collective is high. We also contrast the socially optimal information structure with the profit maximizing choice of branding if branding is endogenous. Our results can be applied to country-of-origin, agricultural appellation, and other collective brands

When do consumers talk?

The propensity of consumers to engage in word-of-mouth (WOM) can differ after good versus bad experiences, resulting in positive or negative selection of user-generated reviews. We study how the propensity to engage in WOM depends on information available to customers through different marketing channels. We develop a model of WOM in which a target customer makes a purchase decision based on his private brand association, public product-specific information (e.g. from advertising or past reviews) and WOM content, and an early adopter of the new product engages in WOM only if her information is instrumental to the target customer’s purchase decision. We define brand image to be the distribution of the customers’ brand associations, and strength of the brand image to be the precision of this distribution. We show that if the brand image is strong, then in equilibrium only negative WOM can arise. In contrast, with a weak brand image, positive WOM must occur. Moreover, holding product quality fixed, a positive advertising signal realization leads to a more positive WOM selection. We use restaurant review data from Yelp.com to motivate our model assumptions and validate the predictions. For example, a textual analysis of reviews is consistent with prevalence of an instrumental motive for WOM. Further, a review rating for national established chain restaurant locations, where the brand image is strong, is almost 1-star lower (on a 5-star scale) than a review rating for a comparable independent restaurant, controlling for reviewer and restaurant characteristics

When Do Consumers Talk?

The propensity of consumers to engage in word-of-mouth (WOM) differs after good versus bad experiences, which can result in positive or negative selection of user-generated reviews. We show how the dispersion of consumer beliefs about quality (brand strength), informativeness of good and bad experiences, and price can affect selection of WOM in equilibrium. WOM is costly: Early adopters talk only if they can affect the receiver’s purchase. Under homogeneous beliefs, only negative WOM can arise. Under heterogeneous beliefs, the type of WOM depends on the informativeness of the experiences. We use data from Yelp.com to validate our predictions

The Benefit of Collective Reputation

We study a model of reputation with two long-lived firms that sell their products under a collective brand or under two different individual brands. Firms face a moral hazard problem because their quality investments are not observed. Investments can only be sustained due to reputational concerns. In a collective brand, consumers cannot distinguish between the two firms. We show that in the long run, this makes it harder to establish a good reputation because of the incentives to free-ride on the other firm’s investments. But in the short run it mitigates the temptation to milk good reputation. Consequently, a collective brand can provide stronger incentives to invest in quality if firms are sufficiently impatient. We explain the connection between incentives and the type of industry in which the firms operate as captured by the underlying signal structure and consumers’ prior beliefs. We discuss the relation to country-of-origin labelling, agricultural cooperatives, and other collective brands

Aiming for the Goal: Contribution Dynamics of Crowdfunding

We study reward-based crowdfunding, a new class of dynamic contribution games where a private good is produced only if the funding goal is reached by a deadline. Buyers face a problem of coordination rather than free-riding. A long-lived donor may alleviate this coordination risk, signaling his wealth through dynamic contributions. We characterize platform-, donor-, and buyer-optimal equilibrium outcomes, attained by Markov equilibria with simple donation strategies. We test the model’s predictions using high-frequency data collected from the largest crowdfunding platform, Kickstarter. The model fits the data well, especially for predictions concerning comparative statistics, donation dynamics, and properties of successful campaigns

Dynamic Price Competition: Theory and Evidence from Airline Markets

We introduce a model of dynamic pricing in perishable goods markets with competition and provide conditions for equilibrium uniqueness. Pricing dynamics are rich because both own and competitor scarcity affect future profits. We identify new competitive forces that can lead to misallocation due to selling units too quickly: the Bertrand scarcity trap. We empirically estimate our model using daily prices and bookings for competing U.S. airlines. We compare competitive equilibrium outcomes to those where firms use pricing heuristics based on observed internal pricing rules at a large airline. We find that pricing heuristics increase revenues (4-5%) and consumer surplus (3%)