Sealed-bid Auction Research Articles

Practical Trustworthy Sealed-Bid Auctions in Wireless Networks

Practical Trustworthy Sealed-Bid Auctions in Wireless Networks

THE GENERAL SOLUTION OF THE ENGLISH AUCTION WITH CONTINUOUS EQUAL DISTRIBUTION OF ORDERS WITHIN THE FRAMEWORK OF STRUCTURAL DESIGN THEORY / ԿԱՐԳԵՐԻ ԱՆԸՆԴՀԱՏ ՀԱՎԱՍԱՐԱՉԱՓ ԲԱՇԽՄԱՄԲ ԱՆԳԼԻԱԿԱՆ ԱՃՈՒՐԴԻ ԸՆԴՀԱՆՈՒՐ ԼՈՒԾՈՒՄԸ ԿԱՌՈՒՑԱԿԱՐԳԵՐԻ ՆԱԽԱԳԾՄԱՆ ՏԵՍՈՒԹՅԱՆ ՇՐՋԱՆԱԿՆԵՐՈՒՄ

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.

Enhancing infrastructure project outcomes through optimized contractual structures and long-term warranties

PurposeThis study delves into the influence of contractual frameworks on infrastructure project timelines and evaluates the role of long-term warranty agreements in maintenance efficacy. It underscores the correlation between construction contract structures and prevalent project delays, advocating for a revision in the allocation of responsibilities to mitigate such delays effectively.Design/methodology/approachWhile previous research has explored individual aspects of construction management, such as contractor incentives and risk allocation, our study uniquely integrates these elements to develop a comprehensive model that includes the effects of long-term warranty agreements and penalty clauses.FindingsThe findings advocate for contract revisions that entail clearly articulated responsibilities and thorough impact assessments, aimed at enhancing the efficiency of project execution and optimizing infrastructure investment returns. Concrete examples are provided from large-scale infrastructure and public works maintenance projects, illustrating the benefits of well-defined penalty clauses in curbing delays and ensuring sustained quality through long-term warranties. Our results demonstrate that optimized contractual structures can significantly reduce project delays and enhance maintenance effectiveness.Originality/valueThis study addresses significant gaps in understanding construction contract management dynamics, especially in transportation infrastructure. It rigorously analyzes how penalty clauses and long-term warranties impact contractor behavior and project outcomes. Key findings show that the benefits of long-term warranties, including social advantages, depend heavily on the strictness of penalty clauses. Innovatively, it employs a First-Price Sealed-Bid Auction framework with empirical data from various case studies, enhancing contract structure optimization for better stakeholder alignment and infrastructure integrity. These insights notably advance construction contract management methodologies.

First-price auction with a stochastic head start

AbstractWe consider a two-player first-price sealed-bid auction for an item with a common value, where one player has a head start with a stochastic value. We show that under mild conditions, there exists a unique Bayesian Nash equilibrium in pure strategies in which the player with the head start buys the item at a price equal to its value minus the minimal value of the head start rather than its expected value. Thus, the seller extracts an information rent. Applications of the results in professional sports are considered.

Payoff equivalence in sealed bid auctions and the dual theory of choice under risk: A correction

Payoff equivalence in sealed bid auctions and the dual theory of choice under risk: A correction

FACT: Sealed-Bid Auction With Full Privacy via Threshold Fully Homomorphic Encryption

FACT: Sealed-Bid Auction With Full Privacy via Threshold Fully Homomorphic Encryption

Practical Verifiable Time-Lock Puzzle: Pre- and Post-Solution Verification

A time-lock puzzle encapsulates a secret message such that the receiver needs to perform a sequential computation, which takes a specified amount of time, to recover the message. Time-lock puzzles can be used in various scenarios, such as sealed-bid auctions, fair contract signing, and so on. The time required to generate a time-lock puzzle and the time needed to solve it are asymmetric, making the verification of a time-lock puzzle crucial. Before solving the puzzle, the solver needs to verify the validity of the puzzle to avoid computing invalid time-lock puzzles. After the puzzle has been solved, it is essential for a third party to confirm the correctness of the solution. This paper proposes a framework for time-lock puzzles, providing both pre-verification and post-verification functionalities, and outlines the security requirements of this framework. Furthermore, we present a practical construction based on iterated squaring in the RSA group and analyze the security of the specific construction. Finally, we implement this construction in Python and demonstrate its efficiency in different settings when implemented in practice.

The Partial Solution of First Price Sealed Bid Auction in the Scope of Mechanism Design Theory and With Uniformly Distributed Types

In the article the first price sealed bid auction has been analysed within the scope of mechanism design theory and with uniformly distributed types. The sealed bid auction consisting of two of agents has been observed finding the partial solution to the auction. Bayesian Nash equilibrium strategies, the equilibrium state, and the implemented social choice function for the auction have been evaluated. The mechanism has been designed to truthfully implement the social choice function for the auction consisting of two agents. The variables such as the probability of an agent to win, the expected utility of an agent and the expected revenue of the seller have been evaluated.

Efficiency of Public Procurement Function in Moroocco

Public procurement, involving the public sector’s purchase of goods, services, or works from the pri-vate sector, accounts for 13-20% of global GDP (The World Bank, 2020). In Morocco, this sector rep-resents 17% of GDP (The World Bank, 2014) and is a crucial source of business for SMEs, which make up 95% of all businesses (Augier, Castel & El Malki, 2019). The efficiency of public procure-ment is a central issue in research due to its strategic, economic, and managerial impact (Kakwezi & Nyeko, 2019). While past research often focused on practical assessments (Flynn & Davis, 2014) and overlooked the market structure (KLEMPERER, 1999), based on a renewal of the game auction model for first price sealed bid auctions, along with both a qualitative and quantitative empirical research , this paper examines Moroccan public procurement efficiency from a market-based, game auction model perspective. It demonstrates that Morocco’s predominant open tender procedure exhibits pat-terns of an efficient game auction model with a Bayesian Nash equilibrium expression , suggesting opportunities for maintaining and improving the open tender meachnism itself and the surrounding procurement mechanisms.

A Sealed-Bid Auction with Fund Binding: Preventing Maximum Bidding Price Leakage

A Sealed-Bid Auction with Fund Binding: Preventing Maximum Bidding Price Leakage

Towards trustworthy and privacy-preserving decentralized auctions

Blockchain smart-contracts can be used as service mappers, connecting a contractor with the service provider best fitting desired service requirements (e.g., price or quality of service). The allocation consists of comparing competitive bids using a smart-contract. However, in competitive environments, service providers may be reluctant to share sensitive information offers with the blockchain as it makes any transaction implicitly public. To reconcile data privacy imperatives with the benefits of blockchain, we propose to leverage fully homomorphic encryption (FHE) for blockchain-based sealed-bid auctions. More precisely (i) FHE enables the processing of bids without decrypting them, (ii) smart-contracts gather and orchestrate bids comparison, and (iii) a computation oracle carries on comparisons over ciphered data. Collusion attempts may occur between bidders and the computation oracle. To prevent this, we combine FHE with hybrid RSA/AES encryption to preserve the privacy of the onchain bid contents. Hence, our protocol prevents information leakage onchain and on the service providers’ side during bids comparison. We validate this approach through an implemented prototype.

A Privacy-preserving Auction Mechanism for Learning Model as an NFT in Blockchain-driven Metaverse

The Metaverse, envisioned as the next-generation Internet, will be constructed via twining a practical world in a virtual form, wherein Meterverse service providers (MSPs) are required to collect massive data from Meterverse users (MUs). In this regard, a critical demand exists for MSPs to motivate MUs to contribute computing resources and data while preserving user privacy. Federated learning (FL), as a privacy-preserving collaborative machine learning paradigm, can support distributed intensive computation in the Metaverse. In this work, we first investigate minting the machine learning models into NFT with FL assistance (referred to as FL-NFT), such that MUs as stakeholders can control the ownership and share the economic value of user-generated content (UGC). Specifically, MUs are encouraged to establish a decentralized autonomous organization (i.e., MU-DAO) to aggregate local models and mint FL-NFT. MUs and MSPs optimize the strategies by formulating an imperfect information Stackelberg game to trade off the cost and benefit. We apply the backward induction to derive the equilibrium solution. Then, we construct a privacy-preserving multi-winner sealed-bid auction mechanism (PMS-AM), in which the Hidden Markov Model assists MSPs in choosing rational bidding strategies according to historical bids, and the double auction mechanism determines the winners and price of FL-NFT. Finally, the numerical results based on theoretical analysis and simulations demonstrate that the proposed PMS-AM can increase the quality of FL-NFT and achieve the economic properties of incentive mechanisms such as individual rationality and incentive compatibility.

Hidden in plain sight: Payoffs, probability, space, and time in isomorphic tasks

Highest stoppage games in economics—first price sealed bid auction and Dutch auction, among others—have produced striking puzzles, including violation of revenue equivalence between auctions and adjustment of behavior across interfaces. The latter is also observed in risk elicitation. Here, we use existing puzzles to shed light on each other, by nesting auction and risk tasks in a common environment. We find behavior consistent with a spatial interface imparting the same relevant auction-theoretic surplus and probability information as does an interactive numerical calculation tool. Empirical revenue equivalence (respectively, risky choice) can thus be altered by design.

Improving Farmers’ Income on Online Agri-Platforms: Evidence from the Field

Problem definition: To improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched online agri-platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and, more generally, how they can be leveraged to enable more efficient agricultural supply chains and markets. This paper describes work conducted in close collaboration with the state government of Karnataka, India, to design, implement, and assess the impact of a new two-stage auction on the state’s online agri-platform, the United Market Platform (UMP). Methodology/results: To ensure implementability and protect farmers’ revenue, the auction design is guided by practical operational considerations, as well as semistructured interviews with a majority of the traders in the field. A new behavioral auction model informed by the field insights is developed to determine when the proposed two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By the end of May 2019, commodities worth more than $6 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 3.6% price increase (corresponding to a 55%–94% profit gain) for over 10,000 farmers who traded in the treatment market. Managerial implications: The results from this paper offer tangible lessons on how innovative price discovery mechanisms could be enabled by online agri-platforms in resource-constrained environments. Importantly, the success of these designs critically depends on careful considerations of systemic operational and behavioral factors that affect trades in the physical markets. History: This paper has been accepted as part of the 2023 Manufacturing & Service Operations Management Practice-Based Research Competition. Funding: Financial support from the Tata Center for Technology and Design at MIT and the National Science Foundation [Grant 1452875] is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0437 .

A Dual Formulation of Bidding Behaviour in Sealed Bid Auctions

A Dual Formulation of Bidding Behaviour in Sealed Bid Auctions

A Blockchain-based Privacy-Preserving Scheme for Sealed-bid Auction

A Blockchain-based Privacy-Preserving Scheme for Sealed-bid Auction

A Decentralized Auction Model for Sustainable Housing Rental Market

The Internet of Things has driven the transformation of the traditional offline rental model to online rental platforms such as Zillow, Zigbang, and Lianjia. These platforms provide abundant housing options, detailed information, convenient communication, and greater price transparency. However, existing online rental platforms are still centralized and rely on third-party intermediaries for settlement, which raises concerns about the integrity of real estate data, transaction security, and price transparency. To improve the real estate leasing business, we propose leveraging the decentralized nature of blockchain technology. By eliminating intermediaries, we can ensure customer privacy and reduce transaction costs. This strategy revolves around smart contracts as a core component, automatically matching landlords and tenants based on their offers, achieving transparency, and maintaining anonymity for both parties. We introduce a novel auction system that combines the features of interactive auctions and sealed-bid auctions, enabling landlords and tenants to engage in range bidding. In this study, we developed a detailed algorithm to define how smart contracts function during the auction process. Through a cost analysis, we demonstrate the economic feasibility and provide a secure, transparent, and reliable approach for online auctions.

Nonparametric estimation of English auctions with selective entry: An application to online judicial auctions

AbstractThis 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.

Auction design and order of sale with budget-constrained bidders

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.

A machine learning-based Biding price optimization algorithm approach

Trading companies of used product market are struggling to gain customers attentaion and to sell the products. The aim of this research is to develop a mechanism that can maximize the sale of products while considering profit implications. The literature review classifies the procurement mechanism. Given the limited-supply nature, that also includes unpredictable quality levels and a procurement mechanism that perceives the company offering prices to suppliers on a single-item basis. The academic literature has not covered such a mechanism. Techniques like those that improve the required bidding strategy are reviewed and considered fit to be included in the support tool as the procedures intention to maximize an objective function depending on the bidding price and contain the probability of winning the auction and the profit made from the proceeding, the motivation laid on the approach that predicts the probability. It is determined that this assembles a Response to Reverse Request for Quotation that meets the assumptions of a First-Price Sealed-Bid(FPSD) auction that potentially includes a hidden reservation price.