The Power of Fair Pricing Mechanisms

We explore the revenue capabilities of truthful, monotone (“fair”) allocation and pricing functions for resource-constrained auction mechanisms within a general framework that encompasses unlimited supply auctions, knapsack auctions, and auctions with general non-decreasing convex production cost functions. We study and compare the revenue obtainable in each fair pricing scheme to the profit obtained by the ideal omniscient multi-price auction. We show that for capacitated knapsack auctions, no constant pricing scheme can achieve any approximation to the optimal profit, but proportional pricing is as powerful as general monotone pricing. In addition, for auction settings with arbitrary bounded non-decreasing convex production cost functions, we present a proportional pricing mechanism which achieves a poly-logarithmic approximation. Unlike existing approaches, all of our mechanisms have fair (monotone) prices, and all of our competitive analysis is with respect to the optimal profit extraction.     

Auctions in a Two-Sided Network: The Market for Meal Voucher Services

In two-sided networks, two parties interact on a platform, caring about the numbers of subjects on the other side. A typical problem, in this context, is setting prices for network services so as to get “both side on boards”. The standard approach in the literature considers the networks ability to convince both sides to join the network, whereas this paper consider an alternative setting, in which one side determines the price balance. This case is exemplified by the market for meal voucher services in Italy, in which one agency organizes the procurement of services for the public sector, through a competitive auction. A formal model of optimal auction is illustrated and used to assess the current procurement scheme. The model reveals that the current system is inefficient and could be improved through increased flexibility and adaptation to local economic conditions.     

A non-parametric estimator for setting reservation prices in procurement auctions

Electronic auction markets collect large amounts of auction field data. This enables a structural estimation of the bid distributions and the possibility to derive optimal reservation prices. In this paper we propose a new approach to setting reservation prices. In contrast to traditional auction theory we use the buyer’s risk statement for getting a winning bid as a key criterion to set an optimal reservation price. The reservation price for a given probability can then be derived from the distribution function of the observed drop-out bids. In order to get an accurate model of this function, we propose a nonparametric technique based on kernel distribution function estimators and the use of order statistics. We improve our estimator by additional information, which can be observed about bidders and qualitative differences of goods in past auctions rounds (e.g. different delivery times). This makes the technique applicable to RFQs and multi-attribute auctions, with qualitatively differentiated offers.     

Analyzing the impact of intermediaries in electronic markets: an empirical investigation of online consumer-to-consumer (C2C) auctions

It has been widely believed that the Internet and electronic markets will eliminate traditional intermediaries. However, a close examination of the market mechanism indicates that the impact of intermediaries is indispensable. Specifically, we consider intermediaries’ impacts in price discovery and trust building. Intermediaries provide a buffer for temporary misalignment between supply and demand by buying low and selling high, and also help build trust by engaging in transactions with risk-averse buyers and sellers who otherwise will not participate in the market. Using a dataset from eBay’s online auctions, we examine empirically these two impacts of human intermediaries. We find that the presence of brokers has a significant impact on market liquidity, resulting in more successful trades and higher auction prices. In addition, we find that brokers are more likely to engage in transactions with less established sellers. Their presence reduces reputation penalty faced by these players and further facilitates the successful sale of items in auctions.     

Optimal Design of Internet-Based Auctions

Online auctions are a profitable, exciting, and dynamic part of electronic commerce, and behave in ways, which do not match classical auction theory. This paper models an online auction in terms of a Markov chain on a state space defined by the current price of the item and the number of bidders who have been previously bumped. It provides a mathematical model, some approximations, which were necessary to convert it into a tractable problem and solutions to a small and a medium-sized theoretical auction. The model results were validated through a comparison with real-world online auction data, showing promise as a predictor of final auction prices. The results of the auction model are also useful in solving an optimization problem that incorporates inventory management considerations in determining optimal auction size.     

Institutional dependencies in dynamic buyout price models for online auctions

There is disagreement in the auction literature on the question of whether dynamic Buy-It-Now (BIN) prices can increase the efficiency of online auctions, compared to static BIN price auctions. In a previous paper (Vragov et al. 2010), we reported experimental evidence that suggested, contrary to the current theoretical auction literature, that dynamic BIN pricing is indeed economically more efficient. The current paper presents a replication study of this research that interestingly fails to reproduce the earlier findings. It is based on the same general experimental design, but modifying the implementation of the specific trading institution by using a linearly declining BIN price (Online Linear Dutch Auction—OLDA) rather than the discrete one-time price change (Online One-time BIN-price Change Auction—OOBCA) that was used in the previous study. OLDA is more dynamic in nature than OOBCA, yet OOBCA outperforms a generalized static online auction design in the laboratory while the OLDA does not. We explain these different results, and thus resolve the ostensible contradiction between the two sets of experiments, by concluding that the specific implementation of the trading institution (i.e., the dynamic BIN pricing mechanism) has a significant effect on the overall market efficiency. In other words, our research finds that the efficiency of dynamic buyout price auctions is institution-dependent. This has important theoretical implications as most formal auction models assume that the auction outcome is institution-free. We also discuss some practical implications of our findings.     

Maximizing sellers’ welfare in online auction by simulating bidders’ proxy bidding agents

This paper presents an agent-based simulation model to estimate the effects of auction parameters on the auction outcomes, and to find an optimal or, at least, a near-optimal infrastructure. In particular, this study intends to study how bidders’ personalities and bidding strategies with other auction parameters affect the closing prices in two auction mechanisms: English and Yankee auction. Experimental results show that the aggregated outcome of multiple English auctions is more favorable to auctioneers and sellers than that of a corresponding single Yankee auction. It is also shown that raising minimum bid increment or bid starting price positively affects the closing prices in both auction types. However, two auction systems respond differently to the changes in parameter values in terms of magnitude and robustness. Further, it is noted that the closing price of an auction is negatively related to the proportion of risk-takers who adopt sniping strategy to submit their bids. As the proportion of risk-takers increases, the closing price significantly decreases in hard-ending auctions (eBay-like system), but only marginally in soft-ending auctions (Amazon-like system). In particular, soft-ending auctions with less snipers and a longer time window of automatic extension return the most favorable closing price to sellers.     

Should we collude? Analyzing the benefits of bidder cooperation in online group-buying auctions

Cooperation among bidders in traditional auctions is typically forbidden. This is because it is viewed as being harmful to the interests of sellers, who hope to obtain fair prices for their sale items. It also may be harmful to other bidders who are not able to take advantage of any cooperation that is occurring. In online group-buying auctions, in contrast to traditional auctions, cooperation results in higher welfare, leading to market expansion that benefits buyers and sellers, as well as the auction intermediary. This has not been well understood in prior research, however. In this article, we show how the online group-buying auction mechanism on the Internet can be effectively enhanced to produce higher welfare for the participants. The key to achieving this, we find, is for the auction intermediary to provide a means for bidders to cooperate, so as to collectively express greater demand. Such cooperation, it turns out, permits the group-buying auction mechanism to dominate the fixed-price mechanism from the seller’s point of view under some circumstances. Through an analytical modeling analysis, we offer insights into how sellers can set their group-buying auction price curves more effectively, so as to take advantage of bidder cooperation to improve auction performance. We further argue that the goal of the auction intermediary should be to offer an information sharing mechanism to facilitate bidding ring formation, as a means to maximize the value of this market mechanism.     

A theoretical and empirical investigation of multi‐item on‐line auctions

In this paper we explore and analyze the structure of Internet auctions from an analytical and an empirical perspective. Such web‐based auctions are rapidly emerging as a mercantile process of choice in the electronic marketplace. We observe current Internet auctions for one‐time products, such as rapidly aging hardware, and analyze them within the framework of the existing auction theory. While traditional auction theory focuses on single‐item auctions, we observe that a majority of on‐line auctions are multi‐item auctions. A significant contribution of this work is the theoretical derivation of the structure of the winning bids in multi‐item progressive on‐line auctions. Additionally, for comparative purposes, we explore the structural characteristics of alternative multi‐item auction mechanisms proposed in the auction theory. We derive hypotheses based on our analytical results and compare two different types of auction mechanisms. We test the traditional auction theory assumption regarding the homogeneity of bidders and present the first ever empirically derived classification and performance‐comparison of on‐line bidders. We test our hypotheses using real‐world empirical data obtained by tracking a premier web‐based auction site. Statistical analysis of the data indicates that firms may gain by choosing alternative auction mechanisms. We also provide directions for further exploration of this emerging but important dimension of electronic commerce. This revised version was published online in July 2006 with corrections to the Cover Date.     

Real time prediction of closing price and duration of B2B reverse auctions

Nowadays, online auctions have become the most successful business model in the electronic marketplace. To the best of the authors’ knowledge, no other work has been devoted to the prediction of closing price and duration of Business-to-Business (B2B) English reverse online auctions in which goods or service providers compete with each other to win contracts by lowering offering prices with each bid, which is conducted on a virtual platform hosted on the Internet. This research designs and proposes a new methodology to predict closing prices and duration within the first few bids of the corresponding auctions based on real time bidding information rather than static auction information. In this article, we employ real time information and prediction rules to forecast the behavior of live auctions. This is in contrast to the static prediction approach that takes into consideration only information available at the beginning of an auction such as products, item features, or the seller’s reputation. This simulation is based on discretized auction data derived from a B2B online auction marketplace over a two-year period. Three measurements including accuracy, coverage, and benefit are used to evaluate the methodology. Results show that after observing the first 4 bids, this methodology can predict closing prices and duration with 84.6 and 71.9% accuracy, respectively.     

Optimal reserve prices in weighted GSP auctions

Most search engines use the weighted Generalized Second Price (wGSP) auction to sell keyword-based text ads, generating billions of dollars of advertising revenue every year. Designing and implementing near-optimal reserve prices for these wGSP auctions are naturally important problems for both academia and industry.In this paper, we show how to calculate and implement the near-optimal reserve price of the wGSP mechanism in realistic settings. Unlike reserve prices in standard single-item auctions, optimal reserve prices in wGSP auctions are discriminatory, different even for advertisers bidding on the same keyword. The optimal reserve price results can be extended to support CPA/CPC/CPM¹ hybrid auctions.Our simulations indicate that setting a proper reserve price will transfer some bidder utility (payoff) to auctioneer utility, resulting in higher revenue for the search engine. We describe a practical methodology to implement optimal reserve prices in production systems.     

Winner's curse and parallel sales channels—Online auctions linked within e-tail websites

A sample of 416 online auctions was examined to determine the extent of overpayment (winner's curse) where online auctions and e-tail websites were linked together to form a parallel sales channel. The results indicated that 8.7% of the highest winning online auction bidders exceeded e-tail posted reference prices of identical retail merchandise found at the same website. Significantly, such bids exceeded the reference prices by a mean percentage dollar amount of 14.1% thus suggesting the existence of a winner's curse. The results also indicated that (1) there was a significant negative association between reference price and mean percentage dollar amount overbid; (2) there was a significant negative association between auction lot size and mean percentage dollar amount overbid; and (3) there was no significant association between overtime auctions and mean percentage dollar amount overbid. While manipulation of reference price and auction lot size might minimize winner's curse, erratic or irrational behavior (by online auction and/or e-tail websites) may lead to disinformation.     

On organization of markets of homogeneous goods

Different supply function auctions in a market of homogeneous good are considered. The problems of the unique existence and computation of a Nash equilibrium are studied for these models. Estimates of the Nash equilibrium deviation from the competitive equilibrium are obtained for each case. For a first-price auction different indexes of the “market power” are investigated as applied to the electricity market. It is shown that the ordinary criteria of competitive behavior are too gentle for this market. Stronger conditions are formulated that provide sufficiently small deviation of the market price from the competitive equilibrium price. The problem of optimal organization of an auction is discussed from the viewpoint of welfare maximization. The obtained results are applied to the analysis of the electricity market in Russia.     

Improving the Performance of Online Auctions Through Server-side Activity-based Caching

Online auction sites have very specific workloads and user behavior characteristics. Previous studies on workload characterization conducted by the authors showed that (1) bidding activity on auctions increases considerably after 90% of an auction’s life time has elapsed, (2) a very large percentage of auctions have a relatively low number of bids and bidders and a very small percentage of auctions have a high number of bids and bidders, (3) prices rise very fast after an auction has lasted more than 90% of its life time. Thus, if bidders are not able to successfully bid at the very last moments of an auction because of site overload, the final price may not be as high as it could be and sellers, and consequently the auction site, may lose revenue. In this paper, we propose server-side caching strategies in which cache placement and replacement policies are based on auction-related parameters such as number of bids placed or percent remaining time till closing time. A main-memory auction cache at the application server can be used to reduce accesses to the back-end database server. Trace-based simulations were used to evaluate these caching strategies in terms of cache hit ratio and cache efficiency. The performance characteristics of the best policies were then evaluated through experiments conducted on a benchmark online auction system.     

P2P网络中的代理拍卖协议

提出一个点对点（P2P）网络中的二价代理拍卖协议。投标者在投放出价链之后即可自由进出协议,由P2P节点代理完成拍卖;在整个拍卖过程中,低的出价链会在未被完全解密的状态下先被淘汰,最后只留下最高出价链。与已有的其他协议相比,它兼具密闭拍卖和分布式拍卖的优点,不仅能做到异步出价,而且能保护所有出价者的出价隐私。     

Consumer adoption of group-buying auctions: an experimental study

Internet-based group-buying auctions enable consumers to obtain volume discounts, but they face risk and trust issues that are not present in other e-retailing formats, which affects their adoption by consumers. Bidders experience uncertainty about the final auction price, and the risk of whether the auction will be completed. We evaluate textual comments and the number of bids made in an auction as drivers of a consumer’s perceived financial and psychological risks toward the group-buying auction mechanism and trust in the auction initiator. We use an Internet-based experimental test bed for online group-buying auctions and will report on one experiment that we conducted. Our results indicate that textual comments made by the participants about sellers in past auctions and existing bids affected a consumer’s perceived trust in the auction initiator and the financial risk of the mechanism. Positive textual comments and more bids appear to enhance perceived trust in the auction initiator and reduce financial risk, and other consumers are more willing to make bids as a result. Consumers continued to express concerns about the uncertainty of the final group-buying auction price though.     

Evolutionary mechanism design: a review

The advent of large-scale distributed systems poses unique engineering challenges. In open systems such as the internet it is not possible to prescribe the behaviour of all of the components of the system in advance. Rather, we attempt to design infrastructure, such as network protocols, in such a way that the overall system is robust despite the fact that numerous arbitrary, non-certified, third-party components can connect to our system. Economists have long understood this issue, since it is analogous to the design of the rules governing auctions and other marketplaces, in which we attempt to achieve socially-desirable outcomes despite the impossibility of prescribing the exact behaviour of the market participants, who may attempt to subvert the market for their own personal gain. This field is known as “mechanism design”: the science of designing rules of a game to achieve a specific outcome, even though each participant may be self-interested. Although it originated in economics, mechanism design has become an important foundation of multi-agent systems (MAS) research. In a traditional mechanism design problem, analytical methods are used to prove that agents’ game-theoretically optimal strategies lead to socially desirable outcomes. In many scenarios, traditional mechanism design and auction theory yield clear-cut results; however, there are many situations in which the underlying assumptions of the theory are violated due to the messiness of the real-world. In this paper we review alternative approaches to mechanism design which treat it as an engineering problem and bring to bear engineering design principles, viz.: iterative step-wise refinement of solutions, and satisficing instead of optimization in the face of intractable complexity. We categorize these approaches under the banner of evolutionary mechanism design.     

An options-based solution to the sequential auction problem

The sequential auction problem is commonplace in open, electronic marketplaces such as eBay. This is the problem where a buyer has no dominant strategy in bidding across multiple auctions when the buyer would have a simple, truth-revealing strategy if there was but a single auction event. Our model allows for multiple, distinct goods and market dynamics with buyers and sellers that arrive over time. Sellers each bring a single unit of a good to the market while buyers can have values on bundles of goods. We model each individual auction as a second-price (Vickrey) auction and propose an options-based, proxied solution to provide price and winner-determination coordination across auctions. While still allowing for temporally uncoordinated market participation, this options-based approach solves the sequential auction problem and provides truthful bidding as a weakly dominant strategy for buyers. An empirical study suggests that this coordination can enable a significant efficiency and revenue improvement over the current eBay market design, and highlights the effect on performance of complex buyer valuations (buyers with substitutes and complements valuations) and varying the market liquidity.     

Revisiting feedback systems: Trust building in digital markets

Data from ebay.com online auctions were used to examine the impact of buyer feedback and other trust-evoking variables on the final auction prices realized by sellers. Direct counts of positive and negative feedback were found to influence ending auction price significantly. However, when difference measures between positive and negative feedback were used as buyer feedback measures, no significant price effects were found. Since much more positive, than negative, feedback is obtained by sellers, the marginal impact of negative feedback is much greater than that of positive feedback. Therefore, subtracting negative feedback counts from positive feedback counts may not be appropriate. Support was also found for other factors, such as product warranties, impacting final auction prices.