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1
Chen, Lihua, Liying Wang, and Yingjie Lan. "Auction models with resource pooling in modern supply chain management." Modern Supply Chain Research and Applications 1, no. 2 (May 13, 2019): 120–34. http://dx.doi.org/10.1108/mscra-01-2019-0001.
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Purpose In this paper, the main focus is on supply and demand auction systems with resource pooling in modern supply chain from a theoretical modeling perspective. The supply and demand auction systems in modern supply chains among manufacturers and suppliers serve as information sharing mechanisms. The purpose of this paper is to match the supply and demand such that a modern supply chain can achieve incentive compatibility and economic efficiency. The authors design such a supply and demand auction system that can integrate resources to efficiently match the supply and demand. Design/methodology/approach The authors propose three theoretic models of modern supply chain auctions with resource pooling according to the Vickrey auction principle. They are supply auction model with demand resource pooling, demand auction model with supply resource pooling, and double auction model with demand and supply resource pooling. For the proposed auction models, the authors present three corresponding algorithms to allocate resources in the auction process by linear programming, and study the incentive compatibility and define the Walrasian equilibriums for the proposed auction models. The authors show that the solutions of the proposed algorithms are Walrasian equilibriums. Findings By introducing the auction mechanism, the authors aim to realize the following three functions. First is price mining: auction is an open mechanism with multiple participants. Everyone has his own utility and purchasing ability. So, the final price reflects the market value of the auction. Second is dynamic modern supply chain construction: through auction, firm can find appropriate partner efficiently. Third is resources integration: in business practices, especially in modern supply chain auctions, auctioneers can integrate resources and ally buyers or sellers to gain more efficiency in auctions. Originality/value In the paper, the authors propose three theoretic models and corresponding algorithms of modern supply chain auctions with resource pooling according using the Vickrey auction principle, which achieves three functions: price mining, dynamic modern supply chain construction and resources integrating. Besides, these proposed models are much closer to practical settings and may have potential applications in modern supply chain management.
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Emiris, Dimitrios M., and Charis A. Marentakis. "A Unified Classification Ecosystem for Auctions." International Journal of Operations Research and Information Systems 1, no. 3 (July 2010): 53–74. http://dx.doi.org/10.4018/joris.2010070104.
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Auctions have known considerable and continuous growth during the last decades due to their interesting properties in price formation when the value of goods traded is not known or varies. The systematic research in the area of auctions has advanced considerably since William Vickrey’s seminal paper on 1961. Although earlier research has been based mainly on Microeconomics and Games Theory, recent advances extended relevant research in Operational Research and Information Technology. Today, auctions and their applications form a challenging topic not only for economists but for operational researchers, marketers, logisticians and management engineers as well. This paper provides an overview of recent literature in auction theory, focusing on contemporary auction techniques and proposes an Auctions Classification Ecosystem (ACE) that encompasses previous works and new developments in the area. The proposed unified classification approach encompasses auction features and mechanism design parameters in a single scheme. This scheme facilitates the understanding of auction characteristics and supports auction practitioners in designing the appropriate format depending on the application requirements.
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Torres-Valderrama, Henry Camilo, and Luis Eduardo Gallego-Vega. "Modeling Dynamic Procurement Auctions of Standardized Supply Contracts in Electricity Markets including Bidders Adaptation." DYNA 82, no. 192 (August 25, 2015): 168–76. http://dx.doi.org/10.15446/dyna.v82n192.48612.
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<p>Descendant Clock Auctions have been increasingly used in power markets. Traditional approaches are focused on discovering the bidders’ best response but neglecting the bidders’ adaptation. This paper presents an algorithm based on decision theory to estimate the bidders’ behavior along the auction. The proposed model uses portfolio concepts and historical data of spot market to estimate a long term contract supply curve. This model was applied to evaluate the Colombia’s Organized Market (MOR). Demand curve parameters and round size were varied to evaluate their impact over auction outputs. Results show that demand curve has a quite small impact over bidders’ decisions and round size management is useful to avoid non-competitive bidders’ behavior. In addition, it is shown that auction’s starting prices strongly influence auction’s clearing prices. These results are extremely helpful to design market structures in power markets.</p>
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Li, Xiaohui, and Hongbin Dong. "A Transaction Trade-Off Utility Function Approach for Predicting the End-Price of Online Auctions in IoT." Wireless Communications and Mobile Computing 2021 (February 2, 2021): 1–10. http://dx.doi.org/10.1155/2021/6656421.
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To stimulate large-scale users to participate in the big data construction of IoT (internet of things), auction mechanisms based on game theory are used to select participants and calculate the corresponding reward in the process of crowdsensing data collection from IoT. In online auctions, bidders bid many times and increase their bid price. All the bidders want to maximize their utility in auctions. An effective incentive mechanism can maximize social welfare in online auctions. It is complicated for auction platforms to calculate social welfare and the utility of each bidder’s bidding items in online auctions. In this paper, a transaction trade-off utility incentive mechanism is introduced. Based on the transaction trade-off utility incentive mechanism, it can make the forecasting process consistent with bidding behaviors. Furthermore, an end-price dynamic forecasting agent is proposed for predicting end prices of online auctions. The agent develops a novel trade-off methodology for classifying online auctions by using the transaction trade-off utility function to measure the distance of auction items in KNN. Then, it predicts the end prices of online auctions by regression. The experimental results demonstrate that an online auction process considering the transaction utility is more consistent with the behaviors of bidders, and the proposed prediction algorithm can obtain higher prediction accuracy.
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Chung, Yu-Fang, Tzer-Long Chen, Tzer-Shyong Chen, Dai-Lun Chiang, and Yu-Ting Chen. "An Agent-Based Auction Protocol on Mobile Devices." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/314180.
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This paper proposes an English auction protocol to preserve a secure, fair, and effective online auction environment, where the operations are integrated with mobile agent technology for bidders participating in online auctions. The protocol consists of four participants, namely, registration manager, agent house, auction house, and bidder.
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PENG, Yanyan, and Xinwang LIU. "BIDDING DECISION IN LAND AUCTION USING PROSPECT THEORY." International Journal of Strategic Property Management 19, no. 2 (June 19, 2015): 186–205. http://dx.doi.org/10.3846/1648715x.2015.1047914.
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Land auction is widely practiced in company and government decisions, especially in China. Bidders are always faced with two or more auctions in the period of a decision cycle. The outcome of the auction is under high risk. The bidder's risk attitude and preference will have a great influence on his/her bidding price. Prospect theory is currently the main descriptive theory of decision under risk. In this paper, we will consider the preferences of the decision-makers in land bidding decisions with the multi-attribute additive utility and reference point method in cumulative prospect theory. Three land auction models are proposed based on the appearance time of the land auctions. The simultaneous model uses cumulative prospect theory without considering the relationships between the auctions. The time sequential model involves the exchange auction decisions at different time with the third-generation prospect theory. The event sequential model further considers the reference point prediction in sequential land auction decisions. The three models can help the decision-makers make better bidding price decision when they are faced with several land auctions in the period of a decision cycle. A case study illustrates the processes and results of our approaches.
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Chao, Wang, Zhang Dalong, and Ran Xiaomin. "Regional Load Balancing Circuitous Bandwidth Allocation Method Based on Dynamic Auction Mechanism." MATEC Web of Conferences 176 (2018): 01020. http://dx.doi.org/10.1051/matecconf/201817601020.
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Aiming at the problem of link congestion caused by the shortage of network bandwidth resources at the user end, this paper first proposes a regional load balancing idea. Then, for the problem of bandwidth resource allocation in regional load balancing, a bandwidth allocation model is established and a dynamic auction algorithm is proposed. The algorithm calculates the link quality and stability by constructing a link model, and introduces the auction bandwidth to the auctioneer's incentive degree to obtain the auction bidding function. The simulation results show that the algorithm can effectively improve the user's network status, reduce the service response delay, increase the throughput, and at the same time can effectively prevent the auction user's false bidding behavior, so that the auction quote quickly converges to the maximum quote, reduces the number of auctions, and reduces Communication overhead.
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Han, Jidong, Chun Qiu, and Peter Popkowski Leszczyc. "The effects of competitive reserve prices in online auctions." European Journal of Marketing 52, no. 7/8 (July 9, 2018): 1439–56. http://dx.doi.org/10.1108/ejm-10-2017-0684.
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PurposeThis paper aims to investigate how competition among online auction sellers influences the setting of both open and secret reserve prices, thereby affecting auction outcome.Design/methodology/approachUsing a data set collected from eBay consisting of 787 identical product auctions, three empirical models have been proposed. Model 1 simultaneously estimates the effects of auction competition on a seller’s own open and secret reserve price strategies; Model 2 estimates the effects of auction competition on bidder participation; and Model 3 estimates the direct and indirect effects of auction competition on selling price.FindingsCompetition among sellers is central to shaping sellers’ reserve price strategies. When there are more concurrent auctions for identical items, sellers tend to specify a low open reserve and are less likely to set a secret reserve. Sellers are strongly influenced by competitors’ reserve price strategies, and tend to follow competition. Finally, auction competition and competitive reserve price strategies influence both bidder entry and selling prices.Practical implicationsThis study has important implications for both sellers and bidders. It highlights the importance for sellers to adapt their reserve price strategies in light of their competitors’ reserve price strategies and offers implications for bidders regarding auction selection. An auction with low starting bid does not necessarily lead to a lower selling price as it attracts more bidders.Originality/valueThis paper focuses on competition among auction sellers, whereas previous literature has focused on competition among bidders. This paper is the first to study the impact of competing reserve prices in auctions.
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Lucking-Reiley, David. "Vickrey Auctions in Practice: From Nineteenth-Century Philately to Twenty-First-Century E-Commerce." Journal of Economic Perspectives 14, no. 3 (August 1, 2000): 183–92. http://dx.doi.org/10.1257/jep.14.3.183.
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William Vickrey (1961) proposed an auction mechanism in which bidders submit sealed bids, and the highest bidder wins the good in return for payment of the second-highest bid amount. For decades, economists have credited Vickrey with inventing this auction format, and have believed that the Vickrey auction is rarely used in practice. This paper presents evidence that Vickrey auctions have long been the predominant auction format for mail sales of collectible postage stamps. Stamp auctioneers developed this auction format on their own, as early as 1893, even before Vickrey was born.
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Zeng, Ming Fei, and Shun Zheng Yu. "The Reputation System Based on Auctions." Applied Mechanics and Materials 644-650 (September 2014): 5505–10. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.5505.
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This paper proposes some monetary policies for the reputation system based on auctions in p2p networks. In the model, releasers controlled the money supply of the auction market. The money supply can just satisfy the needs of peers. Let auction market keep fair and incent peers to share. And those policies can be implemented without centralized authority or infrastructure.
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Xiang, Jie, Juliang Zhang, T. C. E. Cheng, Jose Maria Sallan, and Guowei Hua. "Efficient Multi-Attribute Auctions Considering Supply Disruption." Asia-Pacific Journal of Operational Research 36, no. 03 (June 2019): 1950013. http://dx.doi.org/10.1142/s0217595919500131.
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Although supply disruption is ubiquitous because of natural or man-made disasters, many firms still use the price-only reverse auction (only the cost is considered) to make purchase decisions. We first study the suppliers’ equilibrium bidding strategies and the buyer’s expected revenue under the first- and second-price price-only reverse auctions when the suppliers are unreliable and have private information on their costs and disruption probabilities. We show that the two auctions are equivalent and not efficient. Then we propose two easily implementable reverse auctions, namely the first-price and second-price format announced penalty reverse auction (APRA), and show that the “revenue equivalence principle” holds, i.e., the two auctions generate the same ex ante expected profit to the buyer. We further show that the two reverse auctions are efficient and “truth telling” is the suppliers’ dominant strategy in the second-price format APRA. We conduct numerical studies to assess the impacts of some parameters on the bidding strategies, the buyer’s profit and social profit.
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Engel, Y., and M. P. Wellman. "Multiattribute Auctions Based on Generalized Additive Independence." Journal of Artificial Intelligence Research 37 (March 30, 2010): 479–525. http://dx.doi.org/10.1613/jair.3002.
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We develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences. We propose an iterative auction mechanism that maintains prices on potentially overlapping GAI clusters of attributes, thus decreases elicitation and computational burden, and creates an open competition among suppliers over a multidimensional domain. Most significantly, the auction is guaranteed to achieve surplus which approximates optimal welfare up to a small additive factor, under reasonable equilibrium strategies of traders. The main departure of GAI auctions from previous literature is to accommodate non-additive trader preferences, hence allowing traders to condition their evaluation of specific attributes on the value of other attributes. At the same time, the GAI structure supports a compact representation of prices, enabling a tractable auction process. We perform a simulation study, demonstrating and quantifying the significant efficiency advantage of more expressive preference modeling. We draw random GAI-structured utility functions with various internal structures, generate additive functions that approximate the GAI utility, and compare the performance of the auctions using the two representations. We find that allowing traders to express existing dependencies among attributes improves the economic efficiency of multiattribute auctions.
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Takahashi, Satoshi, Tokuro Matsuo, and Roger Y. Lee. "An Approach to Co-Dependent Value Based Internet Advertisement Auction." International Journal of Software Innovation 1, no. 2 (April 2013): 1–15. http://dx.doi.org/10.4018/ijsi.2013040101.
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A structure of the Internet advertisement is that the service providers decide order of placement of many advertisements and advertising fees by auctions when advertisers offer their promotions. It is known that Generalized Second Price Auction (GSP) mechanism is the most efficient auction mechanism of the advertisement auction. Searching engine companies employ GSP mechanism basically. There are a lot of researches on GSP in order to analyze and clarify its feature and advantages. However, these researches assume that traded advertisements are mutually independent. That is means that each advertisement does not influence other advertisements. Also these researches do not consider a value of advertisement, which means some criterions of a name value of a company, effectiveness and an importance, that is dependently each other. This paper proposes a new advertisement auction mechanism based on GSP with considering the value of advertisement. The authors analyze the auctioneer's profit in comparison between normal GSP, normal VCG (Vickrey-Clarke-Groves Mechanism) and their proposed mechanism.
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BHARGAVA, BHARAT, MAMATA JENAMANI, and YUHUI ZHONG. "COUNTERACTING SHILL BIDDING IN ONLINE ENGLISH AUCTION." International Journal of Cooperative Information Systems 14, no. 02n03 (June 2005): 245–63. http://dx.doi.org/10.1142/s0218843005001158.
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The popularity of online auctions and the associated frauds have led to many auction sites preferring English auction over other auction mechanisms. The ease of adopting multiple fake identities over the Internet nourishes shill bidding by fraudulent sellers in English auction. In this paper, we derive an equilibrium bidding strategy to counteract shill bidding in an online English auction. An algorithm based on this strategy is developed. We conduct experiments to evaluate the strategy in a simulated eBay like auction environment. Five popular bidding strategies are compared with the proposed one. In the simulation, bidders compete to buy a product in the presence of a shill. Each bidder is randomly assigned a bidding strategy. She draws her valuation from a uniform distribution. The experiments show hat the average expected utility of agents with proposed strategy is the highest when the auction continues for a longer duration.
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Ball, Michael O., Alexander S. Estes, Mark Hansen, and Yulin Liu. "Quantity-Contingent Auctions and Allocation of Airport Slots." Transportation Science 54, no. 4 (July 2020): 858–81. http://dx.doi.org/10.1287/trsc.2020.0995.
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In this paper, we define and investigate quantity-contingent auctions. Such auctions can be used when there exist multiple units of a single product and the value of a set of units depends on the total quantity sold. For example, a road network or airport will become congested as the number of users increase so that a permit for use becomes more valuable as the total number allocated decreases. A quantity-contingent auction determines both the number of items sold and an allocation of items to bidders. Because such auctions could be used by bidders to gain excessive market power, we impose constraints limiting market power. We focus on auctions that allocate airport arrival and departure slots. We propose a continuous model and an integer programming model for the associated winner determination problem. Using these models, we perform computational experiments that lend insights into the properties of the quantity-contingent auction.
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DONG, FEI, SOL M. SHATZ, and HAIPING XU. "REASONING UNDER UNCERTAINTY FOR SHILL DETECTION IN ONLINE AUCTIONS USING DEMPSTER–SHAFER THEORY." International Journal of Software Engineering and Knowledge Engineering 20, no. 07 (November 2010): 943–73. http://dx.doi.org/10.1142/s0218194010005018.
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This paper describes the design of a decision support system for shill detection in online auctions. To assist decision making, each bidder is associated with a type of certification, namely shill, shill suspect, or trusted bidder, at the end of each auction's bidding cycle. The certification level is determined on the basis of a bidder's bidding behaviors including shilling behaviors and normal bidding behaviors, and thus fraudulent bidders can be identified. In this paper, we focus on representing knowledge about bidders from different aspects in online auctions, and reasoning on bidders' trustworthiness under uncertainties using Dempster–Shafer theory of evidence. To demonstrate the feasibility of our approach, we provide a case study using real auction data from eBay. The analysis results show that our approach can be used to detect shills effectively and efficiently. By applying Dempster–Shafer theory to combine multiple sources of evidence for shill detection, the proposed approach can significantly reduce the number of false positive results in comparison to approaches using a single source of evidence.
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Mabu, Shingo, Donggeng Yu, Chuan Yue, and Kotaro Hirasawa. "No Time Limit and Time Limit Model of Multiple Round Dutch Auction Based on Genetic Network Programming." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 1 (January 20, 2011): 3–12. http://dx.doi.org/10.20965/jaciii.2011.p0003.
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Nowadays, Dutch auction is used widely at online auction sites. To make online Dutch auction more efficient and more intelligent, it is useful to develop an agent using evolutionary computation which will be adaptive to different auction environments. In this paper, a Genetic Network Programming (GNP) based strategy for auction agents has been proposed to do auctions in multiple round Dutch Auction environments under two types of auction models, no time limit model and time limit model. GNP is a graph-based evolutionary method extended from Genetic Algorithms (GA) and Genetic Programming (GP), which can create optimal solutions by evolution. Although the application of GNP to English auction has been done already, here, a new GNP structure is used for Dutch auction. The simulation results show that the GNP based strategy can also make the agents work well in Dutch auction and the advanced GNP structure makes the agents perform better than that in English auction.
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Armantier, Olivier, Charles A. Holt, and Charles R. Plott. "A Procurement Auction for Toxic Assets with Asymmetric Information." American Economic Journal: Microeconomics 5, no. 4 (November 1, 2013): 142–62. http://dx.doi.org/10.1257/mic.5.4.142.
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The proposed 2008 TARP auction was intended to remove “toxic” assets from portfolios of financially stressed banks. The Treasury selected a design whereby bids to sell different securities would be normalized by “reference prices” that reflect relative value estimates. We conduct a series of experiments indicating that a simple Reference Price Auction can be an effective mechanism for avoiding serious effects of adverse selection and strategic bid manipulation, even with inaccurate reference prices. Beyond the TARP auction, our results are relevant to various multi-object auctions with value heterogeneity. (JEL D44, D82, G21)
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Kawasaki, Takehiro, Nathanael Barrot, Seiji Takanashi, Taiki Todo, and Makoto Yokoo. "Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 2062–69. http://dx.doi.org/10.1609/aaai.v34i02.5579.
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Auctions via social network, pioneered by Li et al. (2017), have been attracting considerable attention in the literature of mechanism design for auctions. However, no known mechanism has satisfied strategy-proofness, non-deficit, non-wastefulness, and individual rationality for the multi-unit unit-demand auction, except for some naïve ones. In this paper, we first propose a mechanism that satisfies all the above properties. We then make a comprehensive comparison with two naïve mechanisms, showing that the proposed mechanism dominates them in social surplus, seller's revenue, and incentive of buyers for truth-telling. We also analyze the characteristics of the social surplus and the revenue achieved by the proposed mechanism, including the constant approximability of the worst-case efficiency loss and the complexity of optimizing revenue from the seller's perspective.
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Zaidi, Bizzat Hussain, Ihsan Ullah, Musharraf Alam, Bamidele Adebisi, Atif Azad, Ali Raza Ansari, and Raheel Nawaz. "Incentive Based Load Shedding Management in a Microgrid Using Combinatorial Auction with IoT Infrastructure." Sensors 21, no. 6 (March 10, 2021): 1935. http://dx.doi.org/10.3390/s21061935.
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This paper presents a novel incentive-based load shedding management scheme within a microgrid environment equipped with the required IoT infrastructure. The proposed mechanism works on the principles of reverse combinatorial auction. We consider a region of multiple consumers who are willing to curtail their load in the peak hours in order to gain some incentives later. Using the properties of combinatorial auctions, the participants can bid in packages or combinations in order to maximize their and overall social welfare of the system. The winner determination problem of the proposed combinatorial auction, determined using particle swarm optimization algorithm and hybrid genetic algorithm, is also presented in this paper. The performance evaluation and stability test of the proposed scheme are simulated using MATLAB and presented in this paper. The results indicate that combinatorial auctions are an excellent choice for load shedding management where a maximum of 50 users participate.
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Ghosh, Susobhan, Sujit Gujar, Praveen Paruchuri, Easwar Subramanian, and Sanjay Bhat. "Bidding in Smart Grid PDAs: Theory, Analysis and Strategy." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 1974–81. http://dx.doi.org/10.1609/aaai.v34i02.5568.
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Periodic Double Auctions (PDAs) are commonly used in the real world for trading, e.g. in stock markets to determine stock opening prices, and energy markets to trade energy in order to balance net demand in smart grids, involving trillions of dollars in the process. A bidder, participating in such PDAs, has to plan for bids in the current auction as well as for the future auctions, which highlights the necessity of good bidding strategies. In this paper, we perform an equilibrium analysis of single unit single-shot double auctions with a certain clearing price and payment rule, which we refer to as ACPR, and find it intractable to analyze as number of participating agents increase. We further derive the best response for a bidder with complete information in a single-shot double auction with ACPR. Leveraging the theory developed for single-shot double auction and taking the PowerTAC wholesale market PDA as our testbed, we proceed by modeling the PDA of PowerTAC as an MDP. We propose a novel bidding strategy, namely MDPLCPBS. We empirically show that MDPLCPBS follows the equilibrium strategy for double auctions that we previously analyze. In addition, we benchmark our strategy against the baseline and the state-of-the-art bidding strategies for the PowerTAC wholesale market PDAs, and show that MDPLCPBS outperforms most of them consistently.
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Brünner, Tobias. "Price formation in call auctions with insider information." Studies in Economics and Finance 36, no. 3 (July 26, 2019): 408–26. http://dx.doi.org/10.1108/sef-02-2018-0066.
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Purpose This study aims to investigate – theoretically and empirically – if call auctions incorporate asymmetric information into prices. Design/methodology/approach First, this study introduces a new model of price formation in a call auction with insider information. In this call auction model, insider trading gives rise to an asymmetric information component of transaction costs. Next, this study estimates the model using 20 stocks from Euronext Paris and investigates if the asymmetric information component is present. Findings The theoretical analysis reveals that call auctions incorporate asymmetric information into prices. The empirical analysis finds strong evidence for the asymmetric information component. Testable implications provide further support for the model. Practical implications Call auctions have recently been proposed as an alternative to continuous limit order book markets to overcome problems associated with high-frequency trading. However, it is still an open question whether call auctions efficiently aggregate asymmetric information. The findings of this study imply that call auctions facilitate price discovery and, therefore, are a viable alternative to continuous limit order book markets. Originality/value There is no generally accepted measure of trading costs for call auctions. Therefore, the measure introduced in this study is of great value to anyone who wants to quantify trading costs in call auctions, understand the determinants of trading costs in call auctions or compare trading costs and their components between continuous markets and call auctions. This study also contributes to the literature devoted to estimating the probability of information-based trading.
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Bajari, Patrick, and Ali Hortaçsu. "Economic Insights from Internet Auctions." Journal of Economic Literature 42, no. 2 (May 1, 2004): 457–86. http://dx.doi.org/10.1257/0022051041409075.
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This paper surveys recent studies of internet auctions. Four main areas of research are summarized. First, we survey several studies that document and attempt to explain the frequently observed sniping, or last-second bidding behavior, in these auctions. Second, we summarize several methods proposed to quantify the distortions caused by asymmetric information in these markets, most notably due to the winner's curse. Third, we explore research about the role of reputation mechanisms installed to help combat these distortions. Finally, we discuss what internet auctions have to teach us about auction design.
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Sharma, Gaurav, Denis Verstraeten, Vishal Saraswat, Jean-Michel Dricot, and Olivier Markowitch. "Anonymous Sealed-Bid Auction on Ethereum." Electronics 10, no. 19 (September 24, 2021): 2340. http://dx.doi.org/10.3390/electronics10192340.
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In a competitive market, online auction systems enable optimal trading of digital products and services. Bidders can participate in existing blockchain-based auctions while protecting the confidentiality of their bids in a decentralized, transparent, secure, and auditable manner. However, in a competitive market, parties would prefer not to disclose their interests to competitors, and to remain anonymous during auctions. In this paper, we firstly analyze the specific requirements for blockchain-based anonymous fair auctions. We present a formal model tailored to study auction systems that facilitate anonymity, as well as a generic protocol for achieving bid confidentiality and bidder anonymity using existing cryptographic primitives such as designated verifier ring signature. We demonstrate that it is secure using the security model we presented. Towards the end, we demonstrate through extensive simulation results on Ethereum blockchain that the proposed protocol is practical and has minimal associated overhead. Furthermore, we discuss the complexity and vulnerabilities that a blockchain environment might introduce during implementation.
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Beranek, Ladislav. "Uncertain Reasoning for Detection of Selling Stolen Goods in Online Auctions Using Contextual Information." Advances in Decision Sciences 2014 (November 25, 2014): 1–14. http://dx.doi.org/10.1155/2014/891954.
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This work describes the design of a decision support system for detection of fraudulent behavior of selling stolen goods in online auctions. In this system, each seller is associated with a type of certification, namely “proper seller,” “suspect seller,” and “selling stolen goods.” The certification level is determined on the basis of a seller’s behaviors and especially on the basis of contextual information whose origin is outside online auctions portals. In this paper, we focus on representing knowledge about sellers in online auctions, the influence of additional information available from other Internet source, and reasoning on bidders’ trustworthiness under uncertainties using Dempster-Shafer theory of evidence. To demonstrate the practicability of our approach, we performed a case study using real auction data from Czech auction portal Aukro. The analysis results show that our approach can be used to detect selling stolen goods. By applying Dempster-Shafer theory to combine multiple sources of evidence for the detection of this fraudulent behavior, the proposed approach can reduce the number of false positive results in comparison to approaches using a single source of evidence.
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Tayaran, Hojat, and Mehdi Ghazanfari. "A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer." Mathematical Problems in Engineering 2020 (October 6, 2020): 1–13. http://dx.doi.org/10.1155/2020/5604246.
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The online reverse auction is considered as a new e-commerce approach to purchasing and procuring goods and materials in the supply chain. With the rapid and ever-expanding development of information technology as well as the increasing usage of the Internet around the world, the use of an online reverse auction method to provide the required items by organizations has increased. Accordingly, in this paper, a new framework for the online reverse auction process is provided that takes both sides of the procurement process, namely, buyer and seller. The proposed process is a multiattribute semisealed multiround online reverse auction. The main feature of the proposed process is that an online market maker facilitates the seller’s bidding process by the estimation of the buyer’s scoring function. For this purpose, a multilayer perceptron neural network was used to estimate the scoring function. In this case, in addition to hiding the buyer’s scoring function, sellers can improve their bids using the estimated scoring function and a nonlinear multiobjective optimization model. The NSGA II algorithm has been used to solve the seller model. To evaluate the proposed model, the auction process is simulated by considering three scoring functions (additive, multiplicative, and risk-aversion) and two types of open and semisealed auctions. The simulation results show that the efficiency of the proposed model is not significantly different from the open auction, and in addition, unlike the open auction, the buyer information was not disclosed.
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Asli, Larbi, Méziane Aïder, and El-Ghazali Talbi. "Solving a dynamic combinatorial auctions problem by a hybrid metaheuristic based on a fuzzy dominance relation." RAIRO - Operations Research 53, no. 1 (January 2019): 207–21. http://dx.doi.org/10.1051/ro/2018051.
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This paper introduces a bi-objective winner determination problem which is based on English auctions. Most models of combinatorial auctions (winner determination problem) do not allow the bidder to update his offer, due to the fact that these mechanisms are static. However in reality bidders are in rough competition while there is time for auction. In this work we give a mathematical formulation of the dynamic model of the bi-objective winner determination problem, where the objectives are: (i) maximization of the total income, (ii) maximization of the number of items sold. This problem is based on the English auction mechanism, which allows bidders to renew their bids until the end of the exercise period. Then the solution is proposed by giving an algorithm based on an hybridization of a metaheuristic with a fuzzy dominance relation. A numerical experimentation using this algorithm on simulated data gives rise to satisfactory results.
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Liu, De, and Adib Bagh. "Preserving Bidder Privacy in Assignment Auctions: Design and Measurement." Management Science 66, no. 7 (July 2020): 3162–82. http://dx.doi.org/10.1287/mnsc.2019.3349.
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Motivated by bidders’ interests in concealing their private information in auctions, we propose an ascending clock auction for unit-demand assignment problems that economizes on bidder information revelation, together with a new general-purpose measure of information revelation. Our auction uses an iterative partial reporting design such that for a given set of prices, not all bidders are required to report their demands, and when they are, they reveal a single preferred item at a time instead of all. Our design can better preserve bidder privacy while maintaining several good properties: sincere bidding is an ex post Nash equilibrium, ending prices are path independent, and efficiency is achieved if the auction starts with the auctioneer’s reservation values. Our measurement of information revelation is based on Shannon’s entropy and can be used to compare a wide variety of auction and nonauction mechanisms. We propose a hybrid quasi–Monte Carlo procedure for computing this measure. Our numerical simulations show that our auction consistently outperforms a full-reporting benchmark with up to 18% less entropy reduction and scales to problems of over 100,000 variables. This paper was accepted by Chris Forman, information systems.
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Bhargava, Hemant K., Gergely Csapó, and Rudolf Müller. "On Optimal Auctions for Mixing Exclusive and Shared Matching in Platforms." Management Science 66, no. 6 (June 2020): 2653–76. http://dx.doi.org/10.1287/mnsc.2019.3309.
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Platforms create value by matching participants on alternate sides of the marketplace. Although many platforms practice one-to-one matching (e.g., Uber), others can conduct and monetize one-to-many simultaneous matches (e.g., lead-marketing platforms). Both formats involve one dimension of private information, a participant’s valuation for exclusive or shared allocation, respectively. This paper studies the problem of designing an auction format for platforms that mix the modes rather than limit to one and, therefore, involve both dimensions of information. We focus on incentive-compatible auctions (i.e., where truthful bidding is optimal) because of ease of participation and implementation. We formulate the problem to find the revenue-maximizing incentive-compatible auction as a mathematical program. Although hard to solve, the mathematical program leads to heuristic auction designs that are simple to implement, provide good revenue, and have speedy performance, all critical in practice. It also enables creation of upper bounds on the (unknown) optimal auction revenue, which are useful benchmarks for our proposed auction designs. By demonstrating a tight gap for our proposed two-dimensional reserve-price-based mechanism, we prove that it has excellent revenue performance and places low information and computational burden on the platform and participants. This paper was accepted by Chris Forman, information systems.
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Sidnal, Nandini S., and Sunilkumar S. Manvi. "Intelligent Agent Based Model for Auction Service Discovery in Mobile E-Commerce." International Journal of E-Business Research 8, no. 1 (January 2012): 76–97. http://dx.doi.org/10.4018/jebr.2012010105.
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Internet enabled auctions are one of the popular application which basically require a web service discovery mechanism that is efficient in all perspectives. This paper focuses on auction service discovery and building repository of services for the use of E-customers. The auction service directory (repository) is developed based on the customer’s desires. Agent based Belief Desire Intention (BDI) architecture is used in this model, not only to support the service discovery process in spotty or no connectivity network environment but also to automate the process so that it enables the mobile users to complete the discovery process successfully without continuous on-line presence. The simulation results depict that the performance parameters like customer satisfaction, availability of requested services and stability in fetching the services are better in the proposed service discovery model as compared to auction based advertisement facilitated service discovery mechanism.
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Lin, Hanmi, Yongqiang Chen, Changping Liu, Jie Xie, and Baixiu Ni. "The Cross-Entropy Method for the Winner Determination Problem in Combinatorial Auctions." Mathematical Problems in Engineering 2020 (October 12, 2020): 1–7. http://dx.doi.org/10.1155/2020/5691719.
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The combinatorial auction is one of the important methods used for multi-item auctions, and the solution to the winner determination problem (WDP) is the key factor in the widespread application of combinatorial auctions. This paper explores the use of the cross-entropy method to solve the WDP, which is an NP problem. The performance of the proposed approach is evaluated on the basis of two well-known benchmark test cases. The experimental results show that, compared with the genetic algorithm and the particle swarm optimization algorithm, the cross-entropy（CE）method has the advantages of a higher success rate and a shorter time for solving the WDP. Therefore, the CE method provides a high-quality solution for the effective solution of the problem of determining winning bids in combined auctions.
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Brusco, Sandro, Giuseppe Lopomo, and Leslie M. Marx. "The Economics of Contingent Re-Auctions." American Economic Journal: Microeconomics 3, no. 2 (May 1, 2011): 165–93. http://dx.doi.org/10.1257/mic.3.2.165.
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We consider an auction environment where an object can be sold with usage restrictions that generate benefits to the seller but decrease buyers' valuations. In this environment, sellers such as the FCC have used “contingent re-auctions,” offering the restricted object with a reserve price, but re-auctioning it without restrictions if the reserve is not met. We show that contingent re-auctions are generally neither efficient nor optimal for the seller. We propose an alternative “exclusive-buyer mechanism” that can implement the efficient outcome in dominant strategies. In certain environments, parameters can be chosen so the seller's surplus is maximized across all selling procedures. (JEL D44, D82, H82)
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Fox, Jeremy T., and Patrick Bajari. "Measuring the Efficiency of an FCC Spectrum Auction." American Economic Journal: Microeconomics 5, no. 1 (February 1, 2013): 100–146. http://dx.doi.org/10.1257/mic.5.1.100.
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We propose a method to structurally estimate the deterministic component of bidder valuations in FCC spectrum auctions, and apply it to the 1995–1996 C block auction. We base estimation on a pairwise stability condition: two bidders cannot exchange two licenses in a way that increases the sum of their valuations. Pairwise stability holds in some theoretical models of simultaneous ascending auctions under intimidatory collusion and demand reduction. Pairwise stability results in a matching game approach to estimation. We find that a system of four large regional licenses would raise the allocative efficiency of the C block outcome by 48 percent. (JEL D44, D45, H82, L82)
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Zhang, Mingwu, and Bingruolan Zhou. "PP-VCA: A Privacy-Preserving and Verifiable Combinatorial Auction Mechanism." Wireless Communications and Mobile Computing 2020 (October 19, 2020): 1–11. http://dx.doi.org/10.1155/2020/8888284.
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Combinatorial auctions can be employed in the fields such as spectrum auction, network routing, railroad segment, and energy auction, which allow multiple goods to be sold simultaneously and any combination of goods to be bid and the maximum sum of combinations of bidding prices to be calculated. However, in traditional combinatorial auction mechanisms, data concerning bidders’ price and bundle might reveal sensitive information, such as personal preference and competitive relation since the winner determination problem needs to be resolved in terms of sensitive data as above. In order to solve this issue, this paper exploits a privacy-preserving and verifiable combinatorial auction protocol (PP-VCA) to protect bidders’ privacy and ensure the correct auction price in a secure manner, in which we design a one-way and monotonically increasing function to protect a bidder’s bid to enable the auctioneer to pick out the largest bid without revealing any information about bids. Moreover, we design and employ three subprotocols, namely, privacy-preserving winner determination protocol, privacy-preserving scalar protocol, and privacy-preserving verifiable payment determination protocol, to implement the combinatorial auction with bidder privacy and payment verifiability. The results of comprehensive experimental evaluations indicate that our proposed scheme provides a better efficiency and flexibility to meet different types of data volume in terms of the number of goods and bidders.
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Bernardes, Fernando, Douglas Vieira, Vasile Palade, and Rodney Saldanha. "Winds of Change: How Up-To-Date Forecasting Methods Could Help Change Brazilian Wind Energy Policy and Save Billions of US$." Energies 11, no. 11 (October 29, 2018): 2952. http://dx.doi.org/10.3390/en11112952.
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This paper proposes a revaluation of the Brazilian wind energy policy framework and the energy auction requirements. The proposed model deals with the four major issues associated with the wind policy framework that are: long-term wind speed sampling, wind speed forecasting reliability, energy commercialization, and the wind farm profitability. Brazilian wind policy, cross-checked against other countries policies, showed to be too restrictive and outdated. This paper proposes its renewal, through the adoption of international standards by Brazilian policy-makers, reducing the wind time sampling necessary to implement wind farms. To support such a policy change, a new wind forecasting method is designed. The method is based on fuzzy time series shaped with a statistical significance approach. It can be used to forecast wind behavior, by drawing the most-likely wind energy generation intervals given a confidence degree. The proposed method is useful to evaluate a wind farm profitability and design the biding strategy in auctions.
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Li, Ao, Zhaoman Wan, and Zhong Wan. "Optimal Design of Online Sequential Buy-Price Auctions with Consumer Valuation Learning." Asia-Pacific Journal of Operational Research 37, no. 03 (April 29, 2020): 2050012. http://dx.doi.org/10.1142/s0217595920500128.
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Buy-price auction has been successfully used as a new channel of online sales. This paper studies an online sequential buy-price auction problem, where a seller has an inventory of identical products and needs to clear them through a sequence of online buy-price auctions such that the total profit is maximized by optimizing the buy price in each auction. We propose a methodology by dynamic programming approach to solve this optimization problem. Since the consumers’ behavior affects the seller’s revenue, the consumers’ strategy used in this auction is first investigated. Then, two different dynamic programming models are developed to optimize the seller’s decision-making: one is the clairvoyant model corresponding to a situation where the seller has complete information about consumer valuations, and the other is the Bayesian learning model where the seller makes optimal decisions by continuously recording and utilizing auction data during the sales process. Numerical experiments are employed to demonstrate the impacts of several key factors on the optimal solutions, including the size of inventory, the number of potential consumers, and the rate at which the seller discounts early incomes. It is shown that when the consumers’ valuations are uniformly distributed, the Bayesian learning model is of great efficiency if the demand is adequate.
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Aghajani, Mojtaba, and S. Ali Torabi. "A mixed procurement model for humanitarian relief chains." Journal of Humanitarian Logistics and Supply Chain Management 10, no. 1 (October 16, 2019): 45–74. http://dx.doi.org/10.1108/jhlscm-10-2018-0067.
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Purpose The purpose of this paper is to improve the relief procurement process as one of the most important elements of humanitarian logistics. For doing so, a novel two-round decision model is developed to capture the dynamic nature of the relief procurement process by allowing demand updating. The model accounts for the supply priority of items at response phase as well. Design/methodology/approach A mixed procurement/supply policy is developed through a mathematical model, which includes spot market procurement and a novel procurement auction mechanism combining the concepts of multi-attribute and combinatorial reverse auctions. The model is of bi-objective mixed-integer non-linear programming type, which is solved through the weighted augmented e-constraint method. A case study is also provided to illustrate the applicability of the model. Findings This study demonstrates the ability of proposed approach to model post-disaster procurement which considers the dynamic environment of the relief logistics. The sensitivity analyses provide useful managerial insights for decision makers by studying the impacts of critical parameters on the solutions. Originality/value This paper proposes a novel reverse auction framework for relief procurement in the form of a multi-attribute combinatorial auction. Also, to deal with dynamic environment in the post-disaster procurement, a novel two-period programming model with demand updating is proposed. Finally, by considering the priority of relief items and model’s applicability in the setting of relief logistics, post-disaster horizon is divided into three periods and a mixed procurement strategy is developed to determine an appropriate supply policy for each period.
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Anthony, Patricia, and Edwin Law. "Autonomous Seller Agent for Multiple Simultaneous English Auctions." International Journal of Agent Technologies and Systems 4, no. 2 (April 2012): 1–21. http://dx.doi.org/10.4018/jats.2012040101.
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The growth of online auction is due to the flexibility and convenience that it offers to consumers. In the context of online auction, deriving the best reserve price can be associated to the seller’s optimization problem. Determining this reserve price is not straightforward due to the dynamic and unpredictable nature of the auction environment. Setting the price too high will lead to the possibility of no sale outcome. Putting the price too low may produce a sale with less profit due to its lower selling price. The authors propose a strategy to derive the best reserve price based on several selling constraints such as the number of competitors (sellers), the number of bidders, the auction duration, and the profit the seller desired when offering an item to be auctioned. However, to obtain the best performance, the strategy must be tuned to the prevailing auction environment where the agent is situated. This paper describes the seller agent’s performance under varying auction environments. The purpose of the experimental evaluation is to assess the ability of the agent to identify its environments accurately to enable it to come up with the best reserve price.
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Schellhorn, Henry. "A formulation of combinatorial auction via reverse convex programming." Journal of Applied Mathematics and Decision Sciences 2005, no. 1 (January 1, 2005): 19–32. http://dx.doi.org/10.1155/jamds.2005.19.
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In combinatorial auctions, buyers and sellers bid not only for single items but also for combinations (or “bundles”, or “baskets”) of items. Clearing the auction is in general an NP-hard problem; it is usually solved with integer linear programming. We proposed in an earlier paper a continuous approximation of this problem, where orders are aggregated and integrality constraints are relaxed. It was proved that this problem could be solved efficiently in two steps by calculating two fixed points, first the fixed point of a contraction mapping, and then of a set-valued function. In this paper, we generalize the problem to incorporate constraints on maximum price changes between two auction rounds. This generalized problem cannot be solved by the aforementioned methods and necessitates reverse convex programming techniques.
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Gurtuev, Alim, and Zaur Ivanov. "Comparison of different land distribution mechanisms for a land-hungry region." E3S Web of Conferences 164 (2020): 07017. http://dx.doi.org/10.1051/e3sconf/202016407017.
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This paper proposes an approach to the development an efficient land distribution mechanism for a particular land-hungry region. We separate budgetary and allocative efficiency and use general utility approach during evaluation of particular distribution mechanisms. We propose a model of potential land users, which allows quantifying the efficiency of a number of mechanisms of land distribution for land-hungry regions. Land users are represented as economic agents with bounded rationality and subjective utility functions. The model calculates allocation efficiency and budgetary efficiency as independent values and thus is more precise. It also has considerable flexibility and can be adjusted to specific agricultural technology and soil types. An analysis of the efficiency of various mechanisms for the test region showed that lottery mechanisms leads to losses of allocative efficiency compared with auction mechanisms. As for the budget revenues, the use of lottery mechanisms leads to much smaller losses of budgetary efficiency in comparison with simultaneous closed auctions of the first and second prices. But of all the mechanisms considered in the paper, the repetitive Vickrey auction leads to the smallest losses of budget efficiency in the model.
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Lu, Yixin, Alok Gupta, Wolfgang Ketter, and Eric van Heck. "Dynamic Decision Making in Sequential Business-to-Business Auctions: A Structural Econometric Approach." Management Science 65, no. 8 (August 2019): 3853–76. http://dx.doi.org/10.1287/mnsc.2018.3118.
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We develop a dynamic structural model of competitive bidding in multiunit sequential business-to-business auctions. Our model accounts for two notable characteristics of these auctions: (i) bidders have multiple purchase opportunities for the same product, and (ii) winning bidders in each round can acquire multiple units of the same product. We apply the model to bidding data from the world’s largest flower wholesale market at which trades are facilitated through fast-paced, sequential, Dutch auctions. Using a two-step estimation approach, we are able to recover the structural parameters effectively and efficiently. We then conduct policy counterfactuals to evaluate the performance of alternative design choices. The results suggest that the current auction practice still has ample room for improvement. In light of this, we propose an optimization framework that can facilitate auctioneers’ decisions in making the trade-off between revenue maximization and operational efficiency. This paper was accepted by Lorin Hitt, information systems.
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Windle, Jill, John Rolfe, Juliana McCosker, and Andrea Lingard. "A conservation auction for landscape linkage in the southern Desert Uplands, Queensland." Rangeland Journal 31, no. 1 (2009): 127. http://dx.doi.org/10.1071/rj08042.
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Conservation auctions are a type of market-based instrument (MBI) that can achieve a more cost-efficient allocation of public funds than approaches such as devolved grants. In this paper, the conduct of a multiple round conservation auction to improve biodiversity management in a rangelands area is outlined. The auction was designed to develop a wildlife corridor across the southern Desert Uplands bioregion in Queensland and to improve management of rangelands areas. The conservation auction incorporated two important new design features. First, there was a need to promote landholder cooperation so that proposed areas for better land management were aligned and connected across the region. The second innovative design feature was to hold multiple bidding (three) rounds, which differs from the standard application of a single bidding round. The auction outcomes resulted in conservation contracts covering 85 000 ha of remnant vegetation awarded at an average cost of $2* per hectare per annum. Although complete landscape connectivity across the Desert Uplands was not achieved, over 70% of the successful bids, accounting for over 62 000 ha (77% of the total bid area), were part of a group that formed a distinct corridor or landscape linkage with only single or part-property gaps. The results also indicate that multiple bidding rounds improved auction efficiency (for the government), although there was little improvement in connectivity. Sixty-six percent more environmental benefit units could be purchased for the given budget of $350 000 between rounds one and three.
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Carroll, Gabriel, and Ilya Segal. "Robustly Optimal Auctions with Unknown Resale Opportunities." Review of Economic Studies 86, no. 4 (July 30, 2018): 1527–55. http://dx.doi.org/10.1093/restud/rdy041.
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Abstract The standard revenue-maximizing auction discriminates against a priori stronger bidders so as to reduce their information rents. We show that such discrimination is no longer optimal when the auction’s winner may resell to another bidder, and the auctioneer has non-Bayesian uncertainty about such resale opportunities. We identify a “worst-case” resale scenario, in which bidders’ values become publicly known after the auction and losing bidders compete Bertrand-style to buy the object from the winner. With this form of resale, misallocation no longer reduces the information rents of the high-value bidder, as he could still secure the same rents by buying the object in resale. Under regularity assumptions, we show that revenue is maximized by a version of the Vickrey auction with bidder-specific reserve prices, first proposed by Ausubel and Cramton (2004). The proof of optimality involves constructing Lagrange multipliers on a double continuum of binding non-local incentive constraints.
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Gostomczyk, Waldemar. "System aukcyjny jako nowy sposób wspierania OZE." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 18(33), no. 3 (September 28, 2018): 113–33. http://dx.doi.org/10.22630/prs.2018.18.3.71.
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The article analyzes both existing and proposed legal acts in the field of promoting and generating energy from renewable sources. The model of energy management based on renewable sources is implemented differently in individual countries. With the increasing share of renewable energy and the level of objectives for the coming years, it is essential that they are achieved with the lowest possible cost of support from public funds. For this reason, many countries have decided to gradually move to the auction system, giving control over the costs, structure and capacity increase of new RES installations. The research problem is the evaluation of the effectiveness of the auction system against the background of the instruments used so far, both in terms of the increase in new generation capacities and the costs of achieving the intended objectives. These issues, due to the short period of functioning of the new system, have not been properly identified yet. The study uses data from the years 2010-2018. The spatial range was mainly in Poland, but examples from other countries around the world were also used. The research and analysis used a comparative method and a list of individual renewable energy production technologies according to the analyzed values. It has been hypothesized that an auction system based on competitive principles, more effectively and with lower support of public funds will allow for achieving goals related to the promotion of renewable energy sources. The aim of the article is to present the current and new RES support system, prices obtained in auctions and the first experience in its implementation. The research material were Eurostat and GUS statistical materials, documents from the European Commission, the Ministry of Energy, the Energy Regulatory Office, reports on support systems from European countries and Poland. Research methods used in the work include analysis of documents, normative acts, subsequent amendments to the Act on renewable energy sources and regulations issued on their basis. The assessment and recognition of the level of support in the auction system in countries that have been using this instrument for many years was also made. These analyses allowed the assessment of the effects of the auctions carried out, their advantages and disadvantages, and helped formulate conclusions in the field of organizational changes ensuring efficient functioning of the auction system.
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Hurtubia, Ricardo, Francisco Javier Martinez, and Michel Bierlaire. "A quasi-equilibrium approach for market clearing in land use microsimulations." Environment and Planning B: Urban Analytics and City Science 46, no. 3 (July 13, 2017): 445–68. http://dx.doi.org/10.1177/2399808317719071.
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A method for market clearing in land use models with a microsimulation approach for location choice of agents is proposed. The method, based on the Bid-auction theory and random utility models, assumes that agents individually adjust their perceived expected utility by observing market prices before entering auctions for a real estate good, hence modifying their overall willingness to pay for locations. The adjustment translates into a correction of each agent’s bid level that follows the direction of supply-demand equilibrium, as they attempt to ensure their location. In each period, auctions for each available real estate good are simulated and prices are computed as the expected maximum bid of all agents in the market. The proposed method is tested for the city of Brussels, validated against real data and compared with results obtained when the bid adjustment is not included. Simulation results reproduce price trends that were observed in reality between the year 2001 and 2008, outperforming results obtained without a quasi-equilibrium bid adjustment approach. The proposed method is feasible to be implemented in large scale microsimulations and agent-based models because it does not require solving large fixed-point equilibrium problems.
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Rong, Zhang, Liu Bin, and Liu Sifeng. "A multi-attribute auction model by dominance based rough sets approach." Computer Science and Information Systems 7, no. 4 (2010): 843–58. http://dx.doi.org/10.2298/csis090804025r.
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As an alternative to the price-based traditional auction model, the multi-attribute auction model is an integrated model requiring the simultaneous trade of different types of attributes as the sellers and buyers deal. As a result, the design and modeling of the auction mechanism have become very difficult. This paper proposes a multiattribute auction model using the dominance-based rough sets approach (DRSA). The multi-attribute decision method by DRSA can directly mine out the preference relations between the attributes of alternatives so that relevant auction mechanisms can be designed. This model uses a natural reasoning procedure similar to that of decision makers. Finally, a numerical example demonstrates the simplicity, efficiency, and feasibility of the proposed auction model.
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Gansterer, Margaretha, and Richard F. Hartl. "The Prisoners’ Dilemma in collaborative carriers’ request selection." Central European Journal of Operations Research 29, no. 1 (January 13, 2021): 73–87. http://dx.doi.org/10.1007/s10100-020-00717-2.
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AbstractLogistics providers have to utilize available capacities efficiently in order to cope with increasing competition and desired quality of service. One possibility to reduce idle capacity is to build coalitions with other players on the market. While the willingness to enter such coalitions does exist in the logistics industry, the success of collaborations strongly depends on mutual trust and behavior of participants. Hence, a proper mechanism design, where carriers do not have incentives to deviate from jointly established rules, is needed. We propose to use a combinatorial auction system, for which several properties are already well researched but little is known about the auction’s first phase, where carriers have to decide on the set of requests offered to the auction. Profitable selection strategies, aiming at maximization of total collaboration gains, do exist. However, the impact on individual outcomes, if one or more players deviate from jointly agreed selection rules is yet to be researched. We analyze whether participants in an auction-based transport collaboration face a Prisoners’ Dilemma. While it is possible to construct such a setting, our computational study reveals that carriers do not profit from declining the cooperative strategy. This is an important and insightful finding, since it further strengthens the practical applicability of auction-based trading mechanisms in collaborative transportation.
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Ahmad, Maqbool, Muhammad Shafiq, Azeem Irshad, Muhammad Khalil Afzal, Dae Kim, and Jin-Ghoo Choi. "Adaptive and Economically-Robust Group Selling of Spectrum Slots for Cognitive Radio-Based Networks." Sensors 18, no. 8 (August 1, 2018): 2490. http://dx.doi.org/10.3390/s18082490.
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Auction theory has found vital application in cognitive radio to relieve spectrum scarcity by redistributing idle channels to those who value them most. However, countries have been slow to introduce spectrum auctions in the secondary market. This could be in part because a number of substantial conflicts could emerge for leasing the spectrum at the micro level. These representative conflicts include the lack of legislation, interference management, setting a reasonable price, etc. In addition, the heterogeneous nature of the spectrum precludes the true evaluation of non-identical channels. The information abstracted from the initial activity in terms of price paid for specific channels may not be a useful indicator for the valuation of another channel. Therefore, auction mechanisms to efficiently redistribute idle channels in the secondary market are of vital interest. In this paper, we first investigate such leading conflicts and then propose a novel Adaptive and Economically-Robust spectrum slot Group-selling scheme (AERG), for cognitive radio-based networks such as IoT, 5G and LTE-Advanced. This scheme enables group-selling behavior among the primary users to collectively sell their uplink slots that are individually not attractive to the buyers due to the auction overhead. AERG is based on two single-round sealed-bid reverse-auction mechanisms accomplished in three phases. In the first phase, participants adapt asks and bids to fairly evaluate uplink slots considering the dynamics of spectrum trading such as space and time. In the second phase, an inner-auction in each primary network is conducted to collect asks on group slots, and then, an outer-auction is held between primary and secondary networks. In the third phase, the winning primary network declares the winners of the inner-auction that can evenly share the revenue of the slots. Simulation results and logical proofs verify that AERG satisfies economic properties such as budget balance, truthfulness and individual rationality and improves the utilities of the participants.
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Kong, Xiang T. R., Ray Y. Zhong, Gangyan Xu, and George Q. Huang. "Robot-enabled execution system for perishables auction logistics." Industrial Management & Data Systems 117, no. 9 (October 16, 2017): 1954–71. http://dx.doi.org/10.1108/imds-03-2016-0114.
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Purpose The purpose of this paper is to propose a concept of cloud auction robot (CAR) and its execution platform for transforming perishable food supply chain management. A new paradigm of goods-to-person auction execution model is proposed based on CARs. This paradigm can shift the management of traditional manual working to automated execution with great space and time saving. A scalable CAR-enabled execution system (CARES) is presented to manage logistics workflows, tasks and behavior of CAR-Agents in handling the real-time events and associated data. Design/methodology/approach An Internet of Things enabled auction environment is designed. The robot is used to pick up and deliver the auction products and commends are given to the robot in real-time. CARES architecture is proposed while integrating three core services from auction workflow management, auction task management, to auction execution control. A system prototype was developed to show its execution through physical emulations and experiments. Findings The CARES could well schedule the tasks for each robot to minimize their waiting time. The total execution time is reduced by 33 percent on average. Space utilization for each auction studio is improved by about 50 percent per day. Originality/value The CAR-enabled execution model and system is simulated and verified in a ubiquitous auction environment so as to upgrade the perishable food supply chain management into a new level which is automated and real-time. The proposed system is flexible to cope with different auction scenarios, such as different auction mechanisms and processes, with high reconfigurability and scalability.
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Li, Tong, and Bingyu Zhang. "Affiliation and Entry in First-Price Auctions with Heterogeneous Bidders: An Analysis of Merger Effects." American Economic Journal: Microeconomics 7, no. 2 (May 1, 2015): 188–214. http://dx.doi.org/10.1257/mic.20110106.
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We study the effects of mergers in timber sale auctions in Oregon. We propose an entry and bidding model within the affiliated private value (APV) framework and with heterogeneous bidders, and establish existence of the entry equilibrium and existence and uniqueness of the bidding equilibrium when the joint distribution of private values belongs to the class of Archimedean copulas. We estimate the resulting structural model, and study merger effects through counterfactual analyses using the structural estimates. We evaluate how merger effects depend on affiliation, entry, and the auction mechanism and find that the seller may benefit from some mergers. (JEL C57, D44, G34, L11, L73)