Juanjuan Zhang

Rational Herding in Microloan Markets

Microloan markets allow individual borrowers to raise funding from multiple individual lenders. We use a unique panel data set that tracks the funding dynamics of borrower listings on Prosper.com, the largest microloan market in the United States. We find evidence of rational herding among lenders. Well-funded borrower listings tend to attract more funding after we control for unobserved listing heterogeneity and payoff externalities. Moreover, instead of passively mimicking their peers (irrational herding), lenders engage in active observational learning (rational herding); they infer the creditworthiness of borrowers by observing peer lending decisions and use publicly observable borrower characteristics to moderate their inferences. Counterintuitively, obvious defects (e.g., poor credit grades) amplify a listings herding momentum, as lenders infer superior creditworthiness to justify the herd. Similarly, favorable borrower characteristics (e.g., friend endorsements) weaken the herding effect, as lenders attribute herding to these observable merits. Follow-up analysis shows that rational herding beats irrational herding in predicting loan performance. This paper was accepted by Pradeep Chintagunta, marketing.

Growing Two-Sided Networks by Advertising the User Base: A Field Experiment

Two-sided exchange networks (such as eBay.com) often advertise their number of users, presumably to encourage further participation. However, these networks differ markedly on how they advertise their user base. Some highlight the number of sellers, some emphasize the number of buyers, and others disclose both. We use field experiment data from a business-to-business website to examine the efficacy of these different display formats. Before each potential seller posted a listing, the website randomized whether to display the number of buyers and/or sellers, and if so, how many buyers and/or sellers to claim. We find that when information about both buyers and sellers is displayed, a large number of sellers deters further seller listings. However, this deterrence effect disappears when only the number of sellers is presented. Similarly, a large number of buyers is more likely to attract new listings when it is displayed together with the number of sellers. These results suggest the presence of indirect network externalities, whereby a seller prefers markets with many other sellers because they help attract more buyers.

De)marketing to Manage Consumer Quality Inferences

Savvy consumers attribute a products market performance to its intrinsic quality as well as the sellers marketing push. The authors study how sellers should optimize their marketing decisions in response. They find that a seller can benefit from “demarketing” its product, meaning visibly toning down its marketing efforts. Demarketing lowers expected sales ex ante but improves product quality image ex post, as consumers attribute good sales to superior quality and lackluster sales to insufficient marketing. The authors derive conditions under which demarketing can be a recommendable business strategy. A series of experiments confirm these predictions.

Learning from Experience, Simply

There is substantial academic interest in modeling consumer experiential learning. However, approximately optimal solutions to forward-looking experiential learning problems are complex, limiting their behavioral plausibility and empirical feasibility. We propose that consumers use cognitively simple heuristic strategies. We explore one viable heuristic-index strategies-and demonstrate that they are intuitive, tractable, and plausible. Index strategies are much simpler for consumers to use but provide close-to-optimal utility. They also avoid exponential growth in computational complexity, enabling researchers to study learning models in more complex situations. Well-defined index strategies depend on a structural property called indexability. We prove the indexability of a canonical forward-looking experiential learning model in which consumers learn brand quality while facing random utility shocks. Following an index strategy, consumers develop an index for each brand separately and choose the brand with the highest index. Using synthetic data, we demonstrate that an index strategy achieves nearly optimal utility at substantially lower computational costs. Using IRI data for diapers, we find that an index strategy performs as well as an approximately optimal solution and better than myopic learning. We extend the analysis to incorporate risk aversion, other cognitively simple heuristics, heterogeneous foresight, and an alternative specification of brands.

Days on market and home sales

In April 2006, the real estate listing service in Massachusetts adopted a new policy that prohibits home sellers from resetting their property’s “days on market” to zero through relisting. We study the effect of this new policy on single-family home sales along the Massachusetts-Rhode Island border, using homes in Rhode Island, which did not change its policy, as the control group. We find that the policy change leads to a relative sale price reduction of around

Tweeting as a Marketing Tool – Field Experiment in the TV Industry

11,000 for affected homes in Massachusetts. Homes caught in the middle of the policy change are the hardest hit; the sudden release of the cumulative days on market information lowers the average sale price by

Deadlines in Product Development

21,500. Sellers respond to the new policy by reducing the listing price to shorten their property’s days on market.(This abstract was borrowed from another version of this item.)

Designing Pricing Contracts for Boundedly Rational Customers: Does the Framing of the Fixed Fee Matter?

Many businesses today have adopted tweeting as a new form of product marketing. However, whether and how tweeting affects product demand remains inconclusive. The authors explore this question using a randomized field experiment on Sina Weibo, the top tweeting website in China. The authors collaborate with a major global media company and examine how the viewing of its TV shows is affected by (1) the media companys tweets about its shows, and (2) recruited Weibo influentials’ retweets of the company tweets. The authors find that both company tweets and influential retweets increase show viewing, but in different ways. Company tweets directly boost viewing, whereas influential retweets increase viewing if the show tweet is informative. Meanwhile, influential retweets are more effective than company tweets in bringing new Weibo followers to the company, which indirectly increases viewing. The authors discuss recommendations on how to manage tweeting as a marketing tool.

The Sound of Silence: Observational Learning in the U.S. Kidney Market

Deadlines are common in product development and are often felt to be too harsh—many development efforts are still worth continuing at the time of mandated termination. We examine the value of deadlines from the agency-theoretic perspective. We consider a firm that pays an agent to lead product development activities. The chance of success depends on the viability of the project and the effort of the agent. As the project proceeds without success, doubts grow as to whether the project is viable. To motivate continued effort, the firm must promise the agent a generous reward if success is achieved during the late stage of development. However, rewarding late success undermines effort incentives in the early stage. The firm may find it more profitable to impose a hard, early deadline to eliminate the agent’s dynamic incentive to procrastinate. We derive conditions under which the firm should impose such deadlines. This paper was accepted by Pradeep Chintagunta, marketing .