E-loyalty networks in online auctions

Creating a loyal customer base is one of the most important, and at the same time, most difficult tasks a company faces. Creating loyalty online (e-loyalty) is especially difficult since customers can ``switch'' to a competitor with the click of a mouse. In this paper we investigate e-loyalty in online auctions. Using a unique data set of over 30,000 auctions from one of the main consumer-to-consumer online auction houses, we propose a novel measure of e-loyalty via the associated network of transactions between bidders and sellers. Using a bipartite network of bidder and seller nodes, two nodes are linked when a bidder purchases from a seller and the number of repeat-purchases determines the strength of that link. We employ ideas from functional principal component analysis to derive, from this network, the loyalty distribution which measures the perceived loyalty of every individual seller, and associated loyalty scores which summarize this distribution in a parsimonious way. We then investigate the effect of loyalty on the outcome of an auction. In doing so, we are confronted with several statistical challenges in that standard statistical models lead to a misrepresentation of the data and a violation of the model assumptions. The reason is that loyalty networks result in an extreme clustering of the data, with few high-volume sellers accounting for most of the individual transactions. We investigate several remedies to the clustering problem and conclude that loyalty networks consist of very distinct segments that can best be understood individually.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS310 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Using fuzzy set approach in multi-attribute automated auctions

This paper designs a novel fuzzy attributes and competition based bidding strategy (FAC-Bid), in which the final best bid is calculated on the basis of the assessment of multiple attributes of the goods and the competition for the goods in the market. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process. The bidding strategy also uses and determines competition in the market (based on the two factors i.e. no. of the bidders participating and the total time elapsed for an auction) using Mamdani's Direct Method. Then the final price of the best bid will be determined based on the assessed attributes and the competition in the market using fuzzy reasoning technique

Equilibrium in Scoring Auctions

This paper studies multi-attribute auctions in which a buyer seeks to procure a complex good and evaluate offers using a quasi-linear scoring rule. Suppliers have private information about their costs, which is summarized by a multi-dimensional type. The scoring rule reduces the multidimensional bids submitted by each supplier to a single dimension, the score, which is used for deciding on the allocation and the resulting contractual obligation. We exploit this idea and obtain two kinds of results. First, we characterize the set of equilibria in quasi-linear scoring auctions with multi-dimensional types. In particular, we show that there exists a mapping between the class of equilibria in these scoring auctions and those in standard single object IPV auctions. Second, we prove a new expected utility equivalence theorem for quasi-linear scoring auctions.Auctions, Procurement

Complementarities and Collusion in an FCC Spectrum Auction

We empirically study bidding in the C Block of the US mobile phone spectrum auctions. Spectrum auctions are conducted using a simultaneous ascending auction design that allows bidders to assemble packages of licenses with geographic complementarities. While this auction design allows the market to find complementarities, the auction might also result in an inefficient equilibrium. In addition, these auctions have equilibria where implicit collusion is sustained through threats of bidding wars. We estimate a structural model in order to test for the presence of complementarities and implicit collusion. The estimation strategy is valid under a wide variety of alternative assumptions about equilibrium in these auctions and is robust to potentially important forms of unobserved heterogeneity. We make suggestions about the design of future spectrum auctions.Technology and Industry

Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces

Negotiating contracts with multiple interdependent issues may yield non- monotonic, highly uncorrelated preference spaces for the participating agents. These scenarios are specially challenging because the complexity of the agents’ utility functions makes traditional negotiation mechanisms not applicable. There is a number of recent research lines addressing complex negotiations in uncorrelated utility spaces. However, most of them focus on overcoming the problems imposed by the complexity of the scenario, without analyzing the potential consequences of the strategic behavior of the negotiating agents in the models they propose. Analyzing the dynamics of the negotiation process when agents with different strategies interact is necessary to apply these models to real, competitive environments. Specially problematic are high price of anarchy situations, which imply that individual rationality drives the agents towards strategies which yield low individual and social welfares. In scenarios involving highly uncorrelated utility spaces, “low social welfare” usually means that the negotiations fail, and therefore high price of anarchy situations should be avoided in the negotiation mechanisms. In our previous work, we proposed an auction-based negotiation model designed for negotiations about complex contracts when highly uncorrelated, constraint-based utility spaces are involved. This paper performs a strategy analysis of this model, revealing that the approach raises stability concerns, leading to situations with a high (or even infinite) price of anarchy. In addition, a set of techniques to solve this problem are proposed, and an experimental evaluation is performed to validate the adequacy of the proposed approaches to improve the strategic stability of the negotiation process. Finally, incentive-compatibility of the model is studied.Spain. Ministerio de Educación y Ciencia (grant TIN2008-06739-C04-04

Multi-attribute auctions with different types of attributes: Enacting properties in multi-attribute auctions

International audienceMulti-attribute auctions allow agents to sell and purchase goods and services taking into account more attributes besides the price (e.g. service time, tolerances, qualities, etc.). In this paper we analyze attributes involved during the auction process and propose to classify them between verifiable attributes, unverifiable attributes and auctioneer provided attributes. According to this classification we present VMA2, a new Vickrey-based reverse multi-attribute auction mechanism which, taking into account the different types of attributes involved in the auction, allows the auction customization in order to suit the auctioneer needs. On the one hand, the use of auctioneer provided attributes enables the inclusion of different auction concepts such as social welfare, trust or robustness whilst, on the other hand, the use of verifiable attributes guarantee truthful bidding. The paper exemplifies the behaviour of VMA2 describing how an egalitarian allocation can be achieved. The mechanism is then tested in a simulated manufacturing environment and compared with other existing auction allocation methods

Deciding on the Appropriateness of B2B Reverse Auction Technology Adoption: An AHP Approach Combined with Integer Programming

Although Business-to-Business online reverse auctions have emerged as a promising purchasing tool, no research has been found that provides a model to assess the reverse auction decision in a systematic way. This paper fills this gap by presenting an integrated approach, utilizing Analytic Hierarchy Process techniques and an Integer Programming Formulation, to decide whether Reverse Auction Technology (RAT) adoption is cost-effective and appropriate. The model developed is a practical decision support tool that allows for the consideration of both qualitative and quantitative decision factors, and for the adoption of multiple modes of RATs, which are contrasted to traditional purchasing

Empirical analyses of online procurement auctions - business value, bidding behavior, learning and incumbent effect

While there is an ever increasing adoption of e-sourcing, where a buyer auctions off procurement contracts to a small group of pre-qualified suppliers, there is a lack of understanding of the impact of dynamic bidding process on procurement outcomes and bidding behavior. To extend the knowledge of this important issue, in this thesis, we explore empirically the value of online procurement auction on cost reduction, quality management, and winner selection from the buyer's perspective. We also explore how incumbent status affects the procurement outcomes. From suppliers' perspective, we characterize their bidding behavior and examine the effect of incumbent status on bidding. First, we collect detailed auction and contract awarding data for manufacturing goods during 2002-2004 from a large buyer in the high-tech industry. The rich data set enables us to apply statistical model based cluster technique to uncover heterogeneous bidding behavior of industry participants. The distribution of the bidding patterns varies between incumbent and non-incumbent suppliers. We also find that the buyer bias towards the incumbent suppliers by awarding them procurement contracts more often and with a price premium. Next, focusing on recurring auctions, we find that suppliers bid adaptively. The adaptive bidding is affected by the rank of suppliers' final bids. Finally, with field data of procurement auction for legal services, we demonstrate that service prices are on average reduced after dynamic bidding events. Most interestingly, the cost savings are achieved without the sacrifice of quality. Incumbent winners' quality is higher, on average, than the quality of buyer's supplier base before the auctions, while non-incumbent winner's quality is lower. These findings imply that the main value of online procurement auctions for business services comes from incumbents in the form of reduced price and enhanced quality. We find that after adjusting for incumbents' higher quality, incumbent bias disappears. Our results also imply that the buyer might possess important information about the incumbents, through past experiences, that cannot be easily included in the buyer's scoring function due to uncodifiability.Ph.D.Committee Chair: Wu, D.J.; Committee Member: Keskinocak, Pinar; Committee Member: Narasimhan, Sridhar; Committee Member: Toktay, Beril; Committee Member: Zhang, Ha