Author List: Hinz, Oliver; Hann, Il-Horn; Spann, Martin;
MIS Quarterly, 2011, Volume 35, Issue 1, Page 81-A10.
The enhanced abilities of online retailers to learn about their customers’ shopping behaviors have increased fears of dynamic pricing, a practice in which a seller sets prices based on the estimated buyer’s willingness-to-pay. However, among online retailers, a deviation from a one-price-for-all policy is the exception. When price discrimination is observed, it is often in the context of customer outrage about unfair pricing. One setting where pricing varies is the name-your-own-price (NYOP) mechanism. In contrast to a typical retail setting, in NYOP markets, it is the buyer who places an initial offer. This offer is accepted if it is above some threshold price set by the seller. If the initial offer is rejected, the buyer can update her offer in subsequent rounds. By design, the final purchase price is opaque to the public; the price paid depends on the individual buyer’s willingness-to-pay and offer strategy. Further, most forms of NYOP employ a fixed threshold price policy. In this paper, we compare a fixed threshold price setting with an adaptive threshold price setting. A seller who considers an adaptive threshold price has to weigh potentially greater profits against customer objections about the perceived fairness of such a policy. We first derive the optimal strategy for the seller. We analyze the effectiveness of an adaptive threshold price vis-à-vis a fixed threshold price on seller profit and customer satisfaction. Further, we evaluate the moderating effect of revealing the threshold price policy (adaptive versus fixed) to buyers. We test our model in a series of laboratory experiments and in a large field experiment at a prominent NYOP seller involving real purchases. Our results show that revealing the usage of an adaptive mechanism yields higher profits and more transactions than not revealing this information. In the field experiment, we find that applying a revealed adaptive threshold price can increase profits by over 20 percent without lowering customer satisfaction.
Keywords: Name-your-own-price; bargaining games; dynamic pricing; electronic commerce; customer satisfaction
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List of Topics

#62 0.266 price buyers sellers pricing market prices seller offer goods profits buyer two-sided preferences purchase intermediary traditional marketplace decisions intermediaries selling
#260 0.163 policy movie demand features region effort second threshold release paid number regions analyze period respect availability released lower effect results
#51 0.142 results study research experiment experiments influence implications conducted laboratory field different indicate impact effectiveness future participants evidence test controlled involving
#118 0.084 online consumers consumer product purchase shopping e-commerce products commerce website electronic results study behavior experience b2c impact internet purchases websites
#195 0.082 pricing services levels level on-demand different demand capacity discrimination mechanism schemes conditions traffic paper resource expected based constraints solution latency
#288 0.055 customer customers crm relationship study loyalty marketing management profitability service offer retention it-enabled web-based interactions operations sales strategy channels set
#18 0.051 adaptive theory structuration appropriation structures technology use theoretical ast capture believe consensus technologies offices context based initial advanced exploring findings