This paper examines the evolution of auction design from ancient traditions to modern digital markets, focusing on the development of strategy-proof mechanisms that incentivize truthful bidding. The research analyzes classical formats including first-price and English auctions, highlighting their strategic limitations, before exploring the Vickrey-Clarke-Groves (VCG) mechanism which achieves dominant-strategy incentive compatibility through externality pricing. The study then empirically contrasts Google's Generalized Second-Price (GSP) auction with Meta's VCG-inspired approach in digital advertising markets. Cost-per-click analysis reveals an average premium of $1.52 in GSP auctions, with industry-specific variations reaching $3.88. A computational complexity analysis demonstrates that GSP achieves O(n log n) time complexity compared to VCG's O(nk), providing algorithmic justification for GSP's prevalence in latency-sensitive real-time bidding environments. These findings suggest that real-world mechanism selection depends critically on the interplay between theoretical properties, market structure, and computational constraints. CCS CONCEPTS Theory of computation~Theory and algorithms for application domains~Algorithmic game theory and mechanism design~Computational pricing and auctions.

Abstract In this work we are concerned with the design of efficient mechanisms while eliciting limited information from the agents. First, we study the performance of sampling approximations in facility location games. Our key result is to show that for any $$\epsilon > 0$$ ϵ > 0 , a sample of size $$c(\epsilon ) = \varTheta (1/\epsilon ^2)$$ c ( ϵ ) = Θ ( 1 / ϵ 2 ) yields in expectation a $$1 + \epsilon $$ 1 + ϵ approximation with respect to the optimal social cost of the generalized median mechanism on the metric space $$(\mathbb {R}^d, \Vert \cdot \Vert _1)$$ ( R d , ‖ · ‖ 1 ) , while the number of agents $$n \rightarrow \infty $$ n → ∞ . Moreover, we study a series of exemplar environments from auction theory through a communication complexity framework, measuring the expected number of bits elicited from the agents; we posit that any valuation can be expressed with k bits, and we mainly assume that k is independent of the number of agents n . In this context, we show that Vickrey’s rule can be implemented with an expected communication of $$1 + \epsilon $$ 1 + ϵ bits from an average bidder, for any $$\epsilon > 0$$ ϵ > 0 , asymptotically matching the trivial lower bound. As a corollary, we provide a compelling method to increment the price in an English auction. We also leverage our single-item format with an efficient encoding scheme to prove that the same communication bound can be recovered in the domain of additive valuations through simultaneous ascending auctions, assuming that the number of items is a constant. Finally, we propose an ascending-type multi-unit auction under unit demand bidders; our mechanism announces at every round two separate prices and is based on a sampling algorithm that performs approximate selection with limited communication, leading again to asymptotically optimal communication. Our results do not require any prior knowledge on the agents’ valuations, and mainly follow from natural sampling techniques.

Simultaneous ascending auctions find extensive applications in spectrum licensing and advertising space allocation. However, existing quantum sealed-bid auction protocols suffer from dual limitations: they cannot support multi-item simultaneous bidding scenarios, and their reliance on complex quantum resources along with requiring full quantum operational capabilities from bidders fails to accommodate practical constraints of quantum resource-limited users. To address these challenges, this paper proposes a multi-party semi-quantum simultaneous ascending auction protocol based on single-particle states. The protocol employs a trusted honest third party (HTP) responsible for quantum state generation, distribution, and security verification. Bidders determine their groups through quantum measurements and privately encode their bid vectors. Upon successful HTP authentication, each bidder obtains a unique identity code. During the bidding phase, HTP dynamically updates quantum sequences, allowing bidders to submit bids for multiple items by performing only simple unitary operations. HTP announces the highest bid for each item in real time and iteratively generates auction sequences until no new highest bid emerges, thereby achieving simultaneous ascending auctions for multiple items. It acts as a quantum-secured signaling layer, ensuring unconditional security for bid transmission and identity verification while maintaining classical auction logic. Quantum circuit simulations validate the protocol’s feasibility with current technology while satisfying critical security requirements, including anonymity, verifiability, non-repudiation, and privacy preservation. It provides a scalable semi-quantum auction solution for resource-constrained scenarios.

Abstract The superiority of an obviously strategy-proof (OSP) mechanism relative to its direct revelation form is largely justified on experimental results between the English auction and the strategically equivalent second-price auction. We examine this result in a very different environment, uniform rationing problems, where OSP mechanisms have only recently been devised. In contrast to previous experimental evidence, we find similar performance between the direct revelation uniform mechanism and its OSP counterpart. Two other mechanisms that alleviate strategic uncertainty in different ways fare better. A strategically equivalent mechanism that provides non-binding feedback during the reporting period greatly improves performance. A sequential revelation mechanism produces modest improvements despite not possessing dominant strategies. We characterize each alternative to the direct mechanism, finding general lessons about the advantages of real-time feedback and sequentiality of play, as well as the potential shortcomings of OSP mechanisms.

This study extends the understanding of jump bidding in ascending auctions by introducing a multi-round dynamic framework. While traditional theories suggest jump bidding reduces seller revenue, recent work by Lim and Xiong (2021) demonstrated its potential to increase revenue with risk-averse bidders. Our research proposes a theoretical model for dynamic jump bidding with multiple signaling stages and empirically tests its implications through a laboratory experiment incorporating an Amended Random Payment (ARP) design. We hypothesize that dynamic jump bidding, by allowing for sustained risk premium extraction from risk-averse bidders, will lead to significantly higher seller revenue compared to static jump bidding or no jump bidding. experimental results provide compelling evidence supporting this hypothesis, highlighting the crucial role of bidder risk aversion and the dynamic nature of bidding in enhancing auction outcomes for sellers.

Commodity Auction Markets (PLK) serve as a platform for interactions between sellers and buyers to conduct transactions through a price-bidding system. Traditionally, these auctions are held offline to facilitate transactions between farmers, farmer groups, traders, businesses, and other commodity buyers. However, conventional auctions face multiple challenges, including inefficiencies in execution time, limited access to information for buyers, and high operational costs. This study aims to design and develop an Integrated e-Auction Market System (PLT) based on the English Auction model. The system supports the entire auction process from preparation, announcement, and bidding, to winner determination and transaction finalization. System development was conducted using the Rapid Application Development (RAD) approach for planning, analysis, design, and implementation phases. Unified Modeling Language (UML) tools were utilized to model system design components.The web-based PLT system successfully integrates all auction processes efficiently and transparently. It provides stakeholders with access to commodity catalogs, session schedules, and detailed transaction information, while enabling real-time online auctions. The implementation of this system is expected to broaden commodity marketing networks, increase local government revenues, and significantly reduce auction operational costs particularly venue rental expenses.

For decades, simultaneous ascending auction (SAA) has been the most popular mechanism used for spectrum auctions. It has recently been employed by many countries for the allocation of 5G licences. Although SAA presents relatively simple rules, it induces a complex strategic game for which the optimal bidding strategy is unknown. Considering the fact that sometimes billions of euros are at stake in an SAA, establishing an efficient bidding strategy is crucial. In this work, we model the auction as a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-player simultaneous move game with complete information and propose the first efficient bidding algorithm that tackles simultaneously its four major strategic issues: the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">exposure problem</i>, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">own price effect</i>, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">budget constraints</i>, and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eligibility management problem</i>. Our solution, called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{SMS}^\alpha$</tex-math></inline-formula>, is based on simultaneous move Monte Carlo Tree Search and relies on a new method for the prediction of closing prices. By introducing a new reward function in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$SMS^\alpha$</tex-math></inline-formula>, we give the possibility to bidders to define their own level of risk-aversion. Through extensive numerical experiments on instances of realistic size, we show that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{SMS}^\alpha$</tex-math></inline-formula> largely outperforms state-of-the-art algorithms, notably by achieving higher expected utility while taking less risks.

Intelligent Multi-Agent English Auction Interaction Protocol for Logistics Service Provider Selection

In this article, we tackle the problem of designing an efficient bidding strategy for simultaneous ascending auctions (SAA). SAA is a well-known mechanism for allocating spectrum to mobile networks operators and has been used for example to allocate 5G licenses in many countries. Although the rules are relatively simple, there is no known optimal bidding strategy for SAA. In a previous work, we proposed a Simultaneous move Monte Carlo Tree Search-based algorithm named <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$SMS^{\alpha }$</tex-math></inline-formula> that we extend here to an incomplete information framework. We consider and compare three determinization approaches of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$SMS^{\alpha }$</tex-math></inline-formula>, and show how they are able to tackle four key strategic issues of SAA, namely, the exposure problem, the own price effect, the budget constraints and the eligibility management. Extensive numerical experiments on instances of realistic size and including an uncertain framework show that our extensions of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$SMS^{\alpha }$</tex-math></inline-formula> outperform state-of-the-art algorithms by achieving higher expected utility while taking less risks.

In the article, the English auction was analyzed within the framework of the theory of structure design and under conditions of continuous distribution of types. The English auction is conducted by gradually increasing the initial announced price. The transaction is considered completed when only one buyer remains. The English auction consisting of N individuals was considered in the article, deriving the general solution of the auction. The dominant strategies of the auction, the state of equilibrium, the social choice function implemented by the mechanism were evaluated. In order to truthfully implement the social choice function of the auction, an appropriate mechanism has been designed. The variables of agent’s winning probability, expected utility and seller's expected return were also evaluated. The effect of increasing the number of agents on different variables of the model was evaluated: announced prices, dominant strategies, expected utility, expected revenue of the seller. As a result of the analysis, it was found that the second-price sealed bid auction and the English auction can be considered strategically the same game. As a result of the analysis, recommendations were made, as a result of the application of which and the demonstration of a scientific approach, it is possible to predict the results of the English auction in the case of N number of participants.

Rational Bidding Meets Emotional Viewing: The Landscape of English Auction Livestreams in The Age of Algorithms

Abstract This study investigates the role of starting prices in sequentially ascending (English) auctions. Applying binary logit and hedonic price models on a unique data set comprising 8217 auctioned lots of frozen saithe, an important species in Norwegian fisheries, we find support for three hypotheses; that low starting prices will lead to a higher share of successful auctions, a higher number of participating bidders, and higher final prices. These results indicate that starting prices in English auctions are important for both seller revenue and auction efficiency and are important with respect to strategic behavior in auction markets for food commodities.

PT Indra Karya is one of the state-owned companies in the field of construction consultants. PT Indra Karya, in carrying out its business processes, still uses traditional methods in documenting, For this reason, PT Indra Karya is trying to digitize existing business processes for the application of modern technology, in line with the president's appeal regarding IndustryOne of the efforts made to realize this is the auction inventory system. In designing the application, it requires an application framework with its model, namely Laravel as a framework used for design methods and using a prototyping model to facilitate the design and evaluation stages. In the design process, using the PHPMyadmin database, which functions as a storage medium and data that will be processed in the application activity, the result of the design is an auction inventory application that can run on an online platform by adhering to the English auction method. The process of transferring inventory items can be done easily and can bring value and instill a digital culture in employees.

The foreign experience of land banks in the USA, Germany, Poland, Latvia, Slovakia, Hungary and Lithuania was studied. The normative and legal framework regulating the conduct of land auctions and transactions with land has been studied. Information on how the Ukrainian Universal Exchange, the platform of LLC "Y.YUIZ", the Prozoro.Prodazhi system functions is highlighted. The mechanism of their functioning is substantiated. It is noted that the sale of land plots takes place through the E-Tender platform. The stages of conducting land auctions are presented, such as the formation of a list of land plots that are submitted for land auctions, the preparation of the technical passport of the land plot, the publication of an official announcement about conducting auctions, the submission of an application for participation in land auctions, the consideration of applications from individuals and legal entities, and the verification of receipts from funds for participation in land auctions, directly the process of conducting land auctions, summarizing the results of auctions (determining the winner), conducting calculations and registration of the ownership of the land plot. The mechanism of a three-round English auction is described. Opened prospects of the land bank in the land use system. The main ones are the possibility of increasing the value of land through online auctions, bringing land out of the shadows, developing one's own business, attracting investments into the agricultural sector, which will contribute to competition and efficiency in the field of the land market, transparency of operations in the field of the land bank, which makes it possible to improve the logistical and production processes of land management operations and operations with land plots, the increase in the value of the land plot, sales through online auctions, revitalization of sales on the land market, creation of new jobs, opening of new production and service structures, deposit of land as collateral, which indicates that land is a liquid asset. The outlined perspectives contribute to the transparency of doing business on land, as well as the successful functioning of land banks. We see the prospects for further research in the substantiation of design and estimate decisions in the land management field.

Information Asymmetry and Bidding Behavior in Common Value English Auction

The evolution of online auction systems has revolutionized the way products and services are bought and sold. Among various auction formats, the English auction model remains one of the most widely adopted due to its simplicity, scalability, and ability to accommodate a large number of participants in real-time. These systems, also known as e-Auctions or electronic auctions, have become increasingly prevalent across industrial and commercial sectors due to their efficiency, cost-effectiveness, and transparency.To enhance the predictive capabilities and decision-making accuracy of these systems, advanced machine learning techniques are integrated into the auction process. Specifically, Long Short-Term Memory (LSTM) networks are employed to capture temporal bidding patterns and forecast price trends over time. LSTMs are particularly effective in handling sequential data and learning complex dependencies, making them suitable for dynamic, time-sensitive auction environments.In addition, Kalman Filters are utilized to refine real-time predictions by continuously updating and correcting the forecasted price based on new observations. This hybrid approach—combining LSTM’s deep learning with Kalman filtering’s real-time estimation—enables more accurate and adaptive prediction of final auction prices, even in the presence of noisy or incomplete data.The system is capable of handling diverse product categories, from hardware items with quantifiable features (e.g., memory size, processing speed) to "soft" goods such as jewelry, which rely on subjective attributes like color, texture, and design. By leveraging these intelligent algorithms, the auction system improves the reliability of price prediction, enhances bidder engagement, and supports better-informed decision-making for both buyers and sellers

Identification in english auctions with shill bidding

Abstract This paper proposes an estimation approach following the constructive identification strategy of Athey and Haile, and Gentry and Li with adaption in the context of ascending auctions with selective entry. Our estimators are shown to be consistent in a large sample and to perform well in a finite sample by a simulation study. We apply our estimation approach to the Alibaba online judicial auctions of used cars to recover the bounds of conditional value distribution and the entry cost. The bounds estimates of both conditional value distribution and entry cost are quite tight (resp., relatively wide) for middle‐valued (resp., low‐valued or high‐valued) signal, and the cumulative distribution functions of conditional value distribution given signal comply with the law of ordered dominance. Finally, our counterfactual analysis indicates that (i) the ascending auction yields a higher revenue than the first‐price sealed bid auction, and (ii) the revenue can be improved significantly when the entry cost is cut by half.

The presence of financial constraints changes traditional auction theory predictions. In the case of multiple items, such constraints may affect revenue equivalence and efficiency of different auction formats. We consider a simple complete information setting with three financially constrained bidders and two items that have different values common to all the bidders. Using a laboratory experiment, we find that, as predicted by theory, it is more beneficial for the seller to sell the higher value item first. We then show that the first-price sealed-bid auction yields higher revenue than the English auction, with significant differences in learning of equilibrium strategies.

This study aims to show how experiencedregret influences the decisions made by bidders of differentgenders in an auction. - In this paper, the data is collected through a real-time recorded tv show about English auctions. In previous studies, female participants tend to be more risk-sensitive and rational than male bidders. Based on this trend, we hypothesized that female bidders would make quick decisions compared to male bidders after the bidder experience regret.