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The objective of this research is to propose a new theoretical framework. The quantification of the interaction between RP and BIN gives managers the ability to jointly take advantage of both RP and BIN.Įmpirical results about the effect of open reserve price on ending prices in auctions are mixed, with some researchers finding a positive effect on ending price and others reporting a negative or no effect. Thus, retailers can increase WTP through changing these reference cues and exploit a richer choice set over which to shape a malleable WTP.
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Open RP and BIN's effect on ending price is due to a reference point effect rather than a price truncation effect. The study design allows the authors to rule out alternative explanations.
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Furthermore, results show that RP is more effective than a comparable BIN magnitude and that these two pricing cues are substitutes. Results of two field studies, augmented with a laboratory study, show that both BINs and RPs result in lower bidder entry, but have an overall positive effect on ending price. Our focus is on two such cues: BINs and RPs. Using auctions, we uncover consumers’ willingness to pay (WTP) through bids. We examine the effect of RP and BIN presence and magnitude on the number of bidders and ending price. Price floors and ceilings in our auction settings are referred to as reserve prices (RP) and Buy It Now (BIN) prices, respectively. Such consumer pricing autonomy often requires the seller to set limits in the form of price floors and price ceilings. In recent years, a trend in retail pricing has been to give consumers greater autonomy in setting their own prices, be it through auctions or other forms of participative pricing. These findings are good news for NYOP sellers and show that NYOP can be a sustainable pricing mechanism even in the long run. However, buyers are risk averse in that they prefer to settle a deal rather than break it off. Their bids are based mainly on their knowledge of the seller's costs, not on their own willingness to pay. Buyers, realizing that they can close deals at lower prices, place lower bids over time. We find that sellers quickly learn to set lower reservation prices, which ultimately increases the total surplus. We assess its applicability in a laboratory experiment simulating a common NYOP design.
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In this paper, we present a game-theoretical model that incorporates interactions between buyers and sellers as well as learning effects. In the long run, this may lead to deals at low prices, leaving sellers little surplus and thus no incentive to sell via NYOP. However, these aspects are vital: If participants behaved as game theory suggests (i.e., anticipating their counterpart's actions), buyers would place their bids very close to their assumption about the seller costs. Until now, research has focused mainly on optimizing either the buyer's or the seller's strategy, without considering learning effects or interactions between the two sides in the process. Name your own price (NYOP) is an interactive pricing mechanism in electronic commerce that lets both buyers and sellers influence the selling price of a product. Our results highlight the importance of the design of user interfaces for interactive pricing, demonstrating that even seemingly innocuous aspects of interfaces can have a dramatic impact on bidding behavior and retailer profit. We propose and find support for two distinct pathways driving this phenomenon – the candidate bid amounts (1) influence bidders’ valuations of the offered product and (2) shape bidders’ beliefs about what bid amounts will be successful. Critically, we show that the former effect can more than offset the latter to cause an increase in retailer profit. In particular, the level of candidate bid amounts has a positive effect on actual bid amounts, whereas it has a negative impact on the likelihood that a consumer will actually submit a bid. Evidence from four experiments involving economically consequential bids demonstrates that the candidate bid amounts specified by the retailer have a strong influence on bidding behavior, and consequently also on retailer profit. Our focus is on one key aspect of the bid-elicitation interface – how retailers require bidders to articulate their bids. This article examines how the interface used for bid elicitation affects bidding behavior and, ultimately, retailer profit. Advances in information technology have led to a substantial increase in the use of interactive pricing mechanisms, where buyers (i.e., consumers) and sellers (i.e., retailers) enter a formal computer-mediated price-negotiation process during which consumers submit bids for a specific product.