Explore the vast range of titles available.

In today’s online markets, the reputation mechanism undergoes its most successful propagation in human history. Online reputation systems substitute informal sanctioning mechanisms at work in close-knit groups and enable complete strangers to trade with each other across large geographic distances. The organizational features of online markets support actors in solving three problems that hamper mutually beneficial market exchange: the value, competition, and cooperation problems. However, due to the plethora of trading opportunities available online, actors face a problem of excess, i.e., the difficulty of choosing a trading partner. Imitation of other actors’ choices of trading partners (i.e., herding) can solve the problem of excess but at the same time lead to the neglect of information about these trading partners’ trustworthiness. Using a large set of online-auction data (N ≈ 88 k), we investigate whether herding as a strategy for solving the problem of excess undermines the reputation mechanism in solving the cooperation problem. Our analysis shows that although buyers follow others in their decisions of which offers to consider, they do not follow others at any price and refer to sellers’ reputations to establish seller trustworthiness. Our results corroborate that reputation systems are viable organizational features that promote mutually beneficial exchanges in anonymous online markets.

This study examines the nature and role of Psychological Contract Violation (PCV) in online marketplaces, a critical factor that has been largely overlooked by previous research. Applied to buyer-seller relationships, PCV is defined as a buyer’s perception of having being treated wrongly regarding the terms of an exchange agreement with an individual seller. PCV with individual sellers is proposed as a formative first-order construct driven by the occurrence of fraud, product misrepresentation, contract default, delivery delay, and failure to follow product guarantees and payment policies. PCV with an individual seller is proposed to prompt a generalized perception of PCV with the entire community of sellers in a marketplace. PCV with the community of sellers is hypothesized to negatively affect buyer transaction behavior in a marketplace by directly impacting transaction intentions, price premiums, trust, perceived risk, and the perceived effectiveness of institutional structures. PCV is also hypothesized to act as a moderator, transforming the buyers’ initial trust-based mindset to one more centered on perceived risk. Finally, PCV is hypothesized to attenuate the positive impact of trust on transaction intentions, while reinforcing the negative impact of perceived risk on transaction intentions. It is also proposed to attenuate the impact of the perceived effectiveness of institutional structures on trust, while strengthening its negative effect on perceived risk. As a means of preventing PCV, the buyers’ positive experience and the sellers’ favorable past performance are hypothesized to make PCV with the community of sellers less likely. A combination of primary and secondary longitudinal data from 404 buyers in eBay’s and Amazon’s online auctions support the proposed hypotheses, validating PCV as a central element of buyer-seller relationships in online marketplaces. Interestingly, ex post facto results show that buyers with higher perceptions of PCV with the community of sellers are less likely to experience PCV with an individual seller in the future. Implications for buyer-seller relationships in online marketplaces and the PCV literature are discussed. Also discussed is how the increasing number of buyers who experience PCV in online marketplaces extends the literature that has been largely developed based on buyers who had not experienced PCV.

To study the role of targeted couponing in auctions, we develop a stylized model in which bidders have heterogeneous valuations and participation costs wherein their entry probabilities are endogenous. Couponing impacts the seller’s profit in two ways: (i) impact on bidders’ entry probability including negative externalities for the bidder who does not receive a coupon and (ii) value extraction. We find that targeting a coupon to the low-valuation bidder can be optimal for the firm even if it leads to a reduction in the joint entry probability of the two bidders because of the benefit from value extraction. A novel result is that in the context of auctions it can be optimal for the seller to issue targeted coupons to the high-valuation bidder. We also find that an increase in the bidders’ valuation or reduction in the participation cost can lead to lower profit for the seller. This result is driven by the nonmonotonicity of the joint entry probability of the two bidders and the seller profits being nonmonotone functions of bidders’ valuations and participation costs.

We analyze a revenue management problem in which a seller facing a Poisson arrival stream of consumers operates an online multiunit auction. Consumers can get the product from an alternative list price channel. We consider two variants of this problem: In the first variant, the list price is an external channel run by another firm. In the second one, the seller manages both the auction and the list price channels. Each consumer, trying to maximize his own surplus, must decide either to buy at the posted price and get the item at no risk, or to join the auction and wait until its end, when the winners are revealed and the auction price is disclosed. Our approach consists of two parts. First, we study structural properties of the problem, and show that the equilibrium strategy for both versions of this game is of the threshold type, meaning that a consumer will join the auction only if his arrival time is above a function of his own valuation. This consumer’s strategy can be computed using an iterative algorithm in a function space, provably convergent under some conditions. Unfortunately, this procedure is computationally intensive. Second, and to overcome this limitation, we formulate an asymptotic version of the problem, in which the demand rate and the initial number of units grow proportionally large. We obtain a simple closed-form expression for the equilibrium strategy in this regime, which is then used as an approximate solution to the original problem. Numerical computations show that this heuristic is very accurate. The asymptotic solution culminates in simple and precise recipes of how bidders should behave, as well as how the seller should structure the auction, and price the product in the dual-channel case.

The day of the last live auction at Sotheby’s in the spring of 2020 was on 19 March 2020 as multiple coronavirus lockdowns forced auction rooms to close worldwide. In the following months, hundreds of live auctions were cancelled or postponed, and combined revenue at Christie’s, Sotheby’s, and Phillips for the second Quarter 2020 plummeted 79% year on year from USD 4.4 bn in Q2 2019 to USD 0.9 bn in Q2 2020. This article focuses on public auctions at Christie’s, Sotheby’s, and Phillips and uses primary research to demonstrate how leading auction houses responded to the unprecedented challenges posed by the COVID-19 crisis. Leveraging Pi-eX’s public auction results database and its 12-month-rolling methodology, our analysis shows (1) the surge of online only auctions while the number of live auctions plummeted; (2) the limitations of online only auctions and the rise of new opportunities; and (3) a comparison of the COVID-19 crisis with previous art market crisis in the past 15 years.

A growing number of vendors are using a sequence of online auctions to sell large inventories of identical items. Although bidding strategies and bidder behavior in single auctions have been extensively studied, limited research exists on bidding in sequential auctions. We seek to explain how bidders in such an environment learn from the information, and form and update their willingness to pay (WTP). Using a large data set from an online auction retailer, we analyze the evolution of the bidders' WTP as well as the effect of auction design on bidders' WTP in sequential auctions. We see our study in the context of a longitudinal field experiment, in which we were able to track actions of repeat bidders over an extended period of time. Our results show that bidders' WTP in sequential auctions can be explained from their demand characteristics, their participation experience in previous auctions, outcomes in previous auctions, and auction design parameters. We also observe, characterize, and measure what we call a modified demand reduction effect exhibited across different auctions, over time, by multiunit demand bidders. Our findings are important to enable better auction mechanism design, and more sophisticated bidding tools that explore the rich information environment of sequential auctions.

This paper is a mechanism design study for a monopolist selling multiple identical items to potential buyers arriving over time. Participants in our model are time sensitive, with the same discount factor; potential buyers have unit demand and arrive sequentially according to a renewal process; and valuations are drawn independently from the same regular distribution. Invoking the revelation principle, we restrict our attention to direct dynamic mechanisms taking a sequence of valuations and arrival epochs as input. We define two properties (discreteness and stability), and prove under further distributional assumptions that we may at no cost of generality consider only mechanisms satisfying them. This effectively reduces the mechanism input to a sequence of valuations and leads to formulate the problem as a dynamic program (DP). As this DP is equivalent to a well-known infinite-horizon asset-selling problem, we finally characterize the optimal mechanism as a sequence of posted prices increasing with each sale. Remarkably, this result rationalizes somewhat the frequent restriction to dynamic pricing policies and impatient buyers assumption. Our numerical study indicates that, under various valuation distributions, the benefit of dynamic pricing over a fixed posted price may be small. Besides, posted prices are preferable to online auctions for a large number of items or high interest rate, but in other cases auctions are close to optimal and significantly more robust.

Online markets pose a difficulty for evaluating products, particularly experience goods, such as used cars, that cannot be easily described online. This exacerbates product uncertainty, the buyer's difficulty in evaluating product characteristics, and predicting how a product will perform in the future. However, the IS literature has focused on seller uncertainty and ignored product uncertainty. To address this void, this study conceptualizes product uncertainty and examines its effects and antecedents in online markets for used cars (eBay Motors). Extending the information asymmetry literature from the seller to the product, we first theorize the nature and dimensions (description and performance) of product uncertainty. Second, we propose product uncertainty to be distinct from, yet shaped by, seller uncertainty. Third, we conjecture product uncertainty to negatively affect price premiums in online markets beyond seller uncertainty. Fourth, based on the information signaling literature, we describe how information signals (diagnostic product descriptions and third-party product assurances) reduce product uncertainty. The structural model is validated by a unique dataset comprised of secondary transaction data from used cars on eBay Motors matched with primary data from 331 buyers who bid on these used cars. The results distinguish between product and seller uncertainty, show that product uncertainty has a stronger effect on price premiums than seller uncertainty, and identify the most influential information signals that reduce product uncertainty. The study's implications for the emerging role of product uncertainty in online markets are discussed.

Anthropomorphism is the attribution of human characteristics to a non-human object. Past research shows that anthropomorphism changes how we perceive objects (e.g., believing them to be more attractive). Does this mean we would be willing to pay more for them? We examined whether displaying a product in an anthropomorphized form influenced how much a consumer was willing to pay. We examined two design aspects, visual (i.e., a face) and auditory (e.g., a voice), in the context of an online auction, and proposed three theoretical routes by which an anthropomorphic product display might affect willingness to pay (emotional, product attachment, and product quality). Results show that adding visual anthropomorphizing features to the way a product was displayed increased the amount bid by 7 percent, but adding auditory anthropomorphizing features had no effect. The visual anthropomorphizing features increased product attachment but had no effect on emotions or perceptions of product quality. Therefore, we conclude that anthropomorphizing the way a product is displayed increases willingness to pay primarily through the theoretical route of creating attachment to the product. There is an additional, as yet undiscovered, theoretical route through which anthropomorphism influences willingness to pay. The results also suggest that the conventional wisdom that the combination of visual and auditory design features is best for triggering anthropomorphism is not always true.

Due to the high maintenance cost of traditional online auction system, poor load balance ability and down problems occurring in the peak value of system access, this paper aims to propose a solution to transit from traditional online auction system to cloud computing to get higher work efficiency, lower expenditure and less energy cost. The GAE platform is used to deploy application of the overall framework of online auction system in cloud computing, including development environment as well as online auction system components, and software architecture. The online auction negotiation algorithms in cloud computing are also proposed. Based on these key technologies, the business processes of the online auction system in cloud computing is designed, including users' login system, starting an auction, bidding processes, online auction data storage, and logout system. The online auction system constructed on GAE platform with cloud computing resources and storage ability can reduce the pressure of terminal equipment, which is more robust than traditional online auction system facing users' changeable needs in the process of online auction.