The Effects of Shilling on Final Bid Prices in Online Auctions

An increasing number of reports of online auction fraud are of growing concern to auction operators and participants. In this research, we discuss reserve price shilling, where a bidder shills in order to avoid paying auction house fees, rather than to drive up the price of the final bid. We examine the effect that premium bids, since they are linked with reserve price shill bids, have upon the final selling price. We use 10,260 eBay auctions during April 2001, and identify 1,389 auctions involving 493 sellers and 1,314 involved in concurrent auctions that involving the exact same item. We find that premium bidding occurs 23 % of the time, in 263 of the 1,389 auctions. Using a theoretical perspective involving valuation signals, we show that other bidders may view high bids as signals that an item is worth more. Thus, they may be willing to pay more for the item than items that do not receive premium bids. The implications are disturbing in that sellers may be more motivated to enter a shill bid in order to drive up the final price in an online auction. We also examine and report on alternative hypotheses involving winner’s curse and the possibility of reserve price shill bids. Our results are developed in the context of a weighted leas

Online Auctions

The economic literature on online auctions is rapidly growing because of the enormous amount of freely available field data. Moreover, numerous innovations in auction-design features on platforms such as eBay have created excellent research opportunities. In this article, we survey the theoretical, empirical, and experimental research on bidder strategies (including the timing of bids and winner's-curse effects) and seller strategies (including reserve-price policies and the use of buy-now options) in online auctions, as well as some of the literature dealing with online-auction design (including stopping rules and multi-object pricing rules).

An Experimental Assessment of Confederate Reserve Price Bids in Online Auction

internet auctions, bid shilling, reserve price, internet fraud, market design

Cyber-Shilling in Automobile Auctions: Evidence from a Field Experiment

We run a large field experiment with an online company specializing in selling used automobiles via ascending auctions. We manipulate experimentally the "price grid," or the possible amounts that bidders can bid above the current standing price. Using two diverse auction sites, one in New York and one in Texas, we find that buyer and seller behavior differs strikingly across the two sites. Specifically, in Texas we find peculiar patterns of bidding among a small but prominent group of buyers suggesting that they are "cyber-shills" working on behalf of sellers. These patterns do not appear in the New York auctions

An Experimental Assessment of Confederate Reserve Price Bids in Online Auction

Confederate bids (i.e. bids placed by sellers´ confederates) are sometimes assumed to enhance sellers´ revenues, if not detected by bidders. As compared to public reserve prices, confederate bids may be used to increase bidding activity (perhaps causing "auction fever") or to evade placement costs without increasing the risk of unacceptably low prices. We present two field experiments with parallel auctions of identical units of a popular DVD and a memorial coin using three different reserve price and confederate bid settings. We find statistically indistinguishable prices and price dispersion in all three auction types. Sellers´ payoffs, however, are significantly lower with public reserve prices, due to placement costs

Assessing online e-marketing and disposal in Neyveli Lignite Corporation Limited (India)

Marketing function per se is undergoing a shift in managing transaction in a transparent emarketing way (Kauffman et al, 2004) especially in Indian Public Sector Undertakings (PSU) – see Reynolds et al (2007). The effectiveness of e-marketing and disposal system of scrap and purchases in PSUs, namely NLC Ltd and ICF, have been studied. Factors such as e-auction offers, time of auction, experience, security deposit (EMD), basic rate per unit, allotment of bid, acceptance of bid; payment and delivery of successful bids on select items in two PSUs over a period of three to five years have been dealt with. The study adds strength to the concept of e-marketing as well as to the theory of marketing

Competition Between Auctions

Even though auctions are capturing an increasing share of commerce, they are typically treated in the theoretical economics literature as isolated. That is, an auction is typically treated as a single seller facing multiple buyers or as a single buyer facing multiple sellers. In this paper, we review the state of the art of competition between auctions. We consider three different types of competition: competition between auctions, competition between formats, and competition between auctioneers vying for auction traffic. We highlight the newest experimental, statistical and analytical methods in the analysis of competition between auctions.auctions, bidding, competition, auction formats, auction houses

Smoothing sparse and unevenly sampled curves using semiparametric mixed models: An application to online auctions

Functional data analysis can be challenging when the functional objects are sampled only very sparsely and unevenly. Most approaches rely on smoothing to recover the underlying functional object from the data which can be difficult if the data is irregularly distributed. In this paper we present a new approach that can overcome this challenge. The approach is based on the ideas of mixed models. Specifically, we propose a semiparametric mixed model with boosting to recover the functional object. While the model can handle sparse and unevenly distributed data, it also results in conceptually more meaningful functional objects. In particular, we motivate our method within the framework of eBay's online auctions. Online auctions produce monotonic increasing price curves that are often correlated across two auctions. The semiparametric mixed model accounts for this correlation in a parsimonious way. It also estimates the underlying increasing trend from the data without imposing model-constraints. Our application shows that the resulting functional objects are conceptually more appealing. Moreover, when used to forecast the outcome of an online auction, our approach also results in more accurate price predictions compared to standard approaches. We illustrate our model on a set of 183 closed auctions for Palm M515 personal digital assistants