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Abstract:
Popularity information is usually thought to reinforce existing sales trends by encouraging customers to flock to mainstream products. We propose an opposite hypothesis: popularity information may benefit niche products disproportionately, because the same level of popularity implies higher quality for a niche product than for a mainstream product. We examine this hypothesis empirically using field experiment data from a web site that lists wedding service vendors. Consistent with our hypothesis, we find that popular niche vendors receive more visits than popular mainstream vendors, across several definitions of niche.

Popularity Information, Observational Learning, Niche Marketing, Long Tail, Internet Marketing, Field Experiment

Abstract:
It is puzzling that firms often knowingly continue to invest in product development projects even after receiving damning customer feedback. We argue that bad products are hard to kill because firms face an inherent conflict when designing managers’ incentives. Rewarding success encourages managers to forge ahead even when demand is low. To prevent managers from ignoring signs of low demand, the firm must also reward decisions to kill bad products. However, rewarding failure effectively undermines the rewards for success. The inability to resolve this tension forces the firm to choose between paying an even larger bonus for success or accepting continued investment in low-demand products. We explore the boundaries of this argument by evaluating different motivations for rewarding success, and comparing how the timing of demand information affects the outcome.

product development, managerial incentives, moral hazard, adverse selection, information acquisition

Abstract:
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 $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 $21,500. Sellers respond to the new policy by reducing the listing price to shorten their property’s days on market.

Abstract:
Mere observation of others' choices can be informative about product quality. This paper develops an individual-level dynamic model of observational learning, and applies it to a novel data set from the U.S. kidney market where transplant candidates on a waiting list sequentially decide whether to accept a kidney offer. We find strong evidence of observational learning: patients draw negative quality inferences from earlier refusals in the queue, thus becoming more inclined towards refusal themselves. This self-reinforcing chain of inferences leads to poor kidney utilization despite the continual shortage in kidney supply. Counterfactual policy simulations show that patients would have made more efficient use of kidneys had the concerns behind earlier refusals been shared. This study yields a set of marketing implications. In particular, we show that observational learning and information sharing shape consumer choices in markedly different ways. Optimal marketing strategies should take into account on how consumers learn from others.

observational learning, learning models, informational cascades, herding, quality inference, Bayes' rule, dynamic programming, kidney allocation

Abstract:
It has been a popular business practice to use consumers' past product choices as a segmentation variable to offer custom product designs to different segments. This paper suggests one reason why such product customization strategy can hurt the profits of competing firms. We look at a two-period duopolist market. In the early period, each firm offers one product and learns its clientele. In the late period, firms may offer either uniform design to the entire market or custom designs to their own customers and their rivals' customers respectively. We find that in equilibrium both firms would want to offer custom designs although simultaneous customization intensifies competition. To escape the perils of customization, forward-looking firms therefore prefer to have a market leader in the early period occupy the entire market to essentially circumvent segmentation. However, both firms would compete to be the market leader. Furthermore, forward-looking consumers prefer segmentation in order to get a custom design at a lower price in future. Consequently, when firms are patient enough and consumers myopic enough, a market leader emerges in the early period, and firms successfully avoid customization in the late period. Otherwise, firms split the early period market evenly, where firm patience and consumer myopia intensifies competition, contrary to common belief.

Customization, Product Design, Segmentation, Behavior-Based Price Discrimination, Competition, Customer Relationship Management

Abstract:
The format of pricing contracts varies substantially across business contexts, a major variable being whether a contract imposes a fixed fee payment. This paper examines how the use of the fixed fee in pricing contracts affects market outcomes of a manufacturer-retailer channel. Standard economic theories predict that channel efficiency increases with the introduction of the fixed fee and is invariant to its framing. We conduct a laboratory experiment to test these predictions. Surprisingly, the introduction of the fixed fee fails to increase channel efficiency. Moreover, the framing of the fixed fee does make a difference: an opaque frame as quantity discounts achieves higher channel efficiency than a salient frame as a two-part tariff, although these two contractual formats are theoretically equivalent.

To account for these anomalies, we generalize the standard economic model by allowing the retailer's utilities to be reference dependent so that the up-front fixed fee payment is perceived as a loss and the subsequent retail profits as a gain. We embed this reference-dependent utility function in a quantal response equilibrium framework where the retailer is allowed to make decision mistakes due to computational complexity. The key prediction of this behavioral model is that channel efficiency decreases with loss aversion for sufficiently Nash-rational retailers. Consistent with this prediction, the estimated loss-aversion coefficient is 1.37 in the two-part tariff condition, significantly higher than 1.27 in the quantity discount condition. At the same time, loss aversion dominates contract complexity in explaining the data. Lastly, we conduct a follow-up experiment to confirm the central role of loss aversion as a behavioral driver. In one condition, the retailer becomes less loss averse when we temporally compress the fixed fee payment and the realization of retail profits, which supports the loss aversion theory. In the other condition, the retailer's contract acceptance rate does not decline when we reward the manufacturer a higher cash payment for each experimental point earned, which rules out the competing hypothesis that the retailer rejects contract offers due to fairness concerns.

fixed fee, two-part tariffs, quantity discounts, distribution channels, loss aversion, behavioral economics, experimental economics