We study a dynamic contribution game where investors seek private benefits that are offered in exchange for contributions and a single, publicly-minded donor values project success. We show that donor contributions serve as costly signals that encourage socially-productive contributions by investors who face a coordination problem. Investors and the donor prefer different equilibria but all benefit in expectation from the donor’s ability to dynamically signal his valuation. We explore various contexts in which our model can be applied and delve empirically into the case of Kickstarter. We calibrate our model and quantify the coordination benefits of dynamic signaling in counterfactuals.
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%).
Fundraising campaigns draw support from a wide pool of contributors. Some contributors are interested in private rewards offered in exchange for contributions (buyers), whereas others are publicly-minded and value success (donors). Buyers face a coordination problem because of the positive externalities of campaign success. A leadership donor who strategically times contributions can promote coordination by dynamically signaling his valuation. The ability to signal increases the probability of success and benefits all participants relative to the donor valuation being known. We validate our modeling assumptions and theoretical predictions using Kickstarter data.
The propensity of consumers to talk after a good versus bad experience with a product can differ based on information available from other marketing channels, for example the brand image or advertising. This can result in selection of positive/negative word-of-mouth for reasons outside of product quality. We develop a unifying framework of WOM, brand image, product advertising, and pricing with a focus on the instrumentality motive of word-of-mouth: early adopters talk to inform new buyers’ purchasing decisions. The different marketing channels shape the information sharing behavior of the early adopter as well as the target consumer’s purchase decision. 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. We also show that holding product quality fixed, a positive advertising signal realization leads to a more positive WOM selection. The model can be applied to both one-one informal WOM as well as online reviews. The assumptions and main predictions of our model are consistent with those that we identified from a primary survey and observational Yelp data.
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.
We introduce a model of oligopoly dynamic pricing where ﬁrms with limited capacity face a sales deadline. We establish conditions under which the equilibrium is unique and converges to a system of diﬀerential equations. Using unique and comprehensive pricing and bookings data for competing U.S. airlines, we estimate our model and ﬁnd that dynamic pricing results in higher output but lower welfare than under uniform pricing. Our theoretical and empirical ﬁndings run counter to standard results in single-ﬁrm settings due to the strategic role of competitor scarcity. Pricing heuristics commonly used by airlines increase welfare relative to estimated equilibrium predictions.
We analyze the long-term workforce composition when the quality of mentoring available to majority and minority juniors depends on their representation in the workforce. A workforce with at least 50 percent majority workers invariably converges to one where the majority is overrepresented relative to the population. To maximize welfare, persistent interventions, such as group-specific fellowships, are often needed, and the optimal workforce may include minority workers of lower innate talent than the marginal majority worker. We discuss the role of mentorship determinants, talent dispersion, the scope of short-term interventions, various policy instruments and contrast our results to the classic fairness narrative.
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.
The propensity of consumers to engage in word-of-mouth (WOM) can diﬀer after good versus bad experiences. This can result in positive or negative selection of user-generated reviews. We show how the strength of brand image - determined by the dispersion of consumer beliefs about quality - and the informativeness of good and bad experiences impact the selection of WOM in equilibrium. Our premise is that WOM is costly: Early adopters talk only if their information is instrumental for the receiver’s purchase decision. If the brand image is strong, i.e., consumers have close to homogeneous beliefs about quality, then only negative WOM can arise. With a weak brand image, positive WOM can occur if positive experiences are suﬀiciently informative. We show that our theoretical predictions are consistent with restaurant review data from Yelp.com. A review rating for a national established chain restaurant is almost 1-star lower (on a 5-star scale) than a review rating for a comparable independent restaurant, controlling for various reviewer and restaurant characteristics. Further, negative chain restaurant reviews have more instances of expectation words, indicating agreement over beliefs about the quality, whereas positive reviews of independent restaurants feature disproportionately many novelty words.
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.
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.
We study reward-based crowdfunding campaigns, a new class of dynamic contribution games where consumption is exclusive. Two types of backers participate: buyers want to consume the product while donors just want the campaign to succeed. The key tension is one of coordination between buyers, instead of free-riding. Donors can alleviate this coordination risk. We analyze a dynamic model of crowdfunding and demonstrate that its predictions are consistent with high-frequency data collected from Kickstarter. We compare the Kickstarter mechanism to alternative platform designs and evaluate the value of dynamically arriving information. We extend the model to incorporate social learning about quality.
In many labor markets, e.g., for lawyers, consultants, MBA students, and professional sport players, workers get oﬀered and sign long-term contracts even though waiting could reveal signiﬁcant information about their capabilities. This phenomenon is called unraveling. We examine the link between wage bargaining and unraveling. Two ﬁrms, an incumbent and an entrant, compete to hire a worker of unknown talent. Informational frictions prevent the incumbent from always observing the entrant’s arrival, inducing unraveling in all equilibria. We analyze the extent of unraveling, surplus shares, the average talent of employed workers, and the distribution of wages within and across ﬁrms.
We analyze the long-term workforce composition when the quality of mentoring available to majority and minority juniors depends on their representation in the workforce. A workforce with ≥ 50% majority workers invariably converges to one where the majority is overrepresented relative to the population. To maximize welfare, persistent interventions, such as group-speciﬁc fellowships, are often needed, and the optimal workforce may include minority workers of lower innate talent than the marginal majority worker. We discuss the role of mentorship determinants, talent dispersion, the scope of short-term interventions, various policy instruments and contrast our results to the classic fairness narrative.
We study the evolution of labor force composition when mentoring is more eﬀective within members of the same socio-demographic type. Typically, multiple steady states exist. Some completely exclude juniors of one type. Even a mixed steady state tends to over-represent the type that is dominant in the population. In contrast, the eﬀicient labor force balances talent recruitment against mentoring frictions. It may even underrepresent the dominant type and typically calls for persistent government intervention. This contrasts with the public discourse around temporary aﬀirmative action. We consider speciﬁc policy instruments and show that hiring quotas can induce equilibrium employment insecurity.