Sealed-bid Auction Research Articles

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

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

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

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.

Boundedly rational bidding decision for land auctions during the transformation of real estate markets

Real estate developers in China exhibit different boundedly rational behaviors when bidding in different land auction formats, resulting in deviation from fully rational bidding, and the transformation of China’s real estate industry has intensified this deviation. To address this problem, this study establishes a reference utility model and a subjective decision probability model under the framework of incomplete information game to characterize developers’ utility distortion and winning probability distortion in open-bid auctions and sealed-bid auctions for land, respectively. The results show that the deviation between bounded rational bidding and fully rational bidding increases as developer competition intensifies. The equilibrium bidding of cost-disadvantaged developers in the boundedly rational model deviates less from the standard model. Moreover, in sealed-bid auctions, the "hiding degree" of cost-advantaged developers is greater, showing size effects, while the bids in open-bid auctions are more complex and affected by market conditions and developers’ risk preferences. Thus, this study characterizes boundedly rational bidding in land auctions and interprets the deviation from fully rational bidding, which can provide a more real basis for land auction mechanism design.

A Trustable and Secure Usage-Based Insurance Policy Auction Mechanism and Platform Using Blockchain and Smart Contract Technologies.

This study presents an architectural framework for the blockchain-based usage-based insurance (UBI) policy auction mechanism in the internet of vehicles (IoV) applications. The main objective of this study is to analyze and design the specific blockchain architecture and management considerations for the UBI environment. An auction mechanism is developed for the UBI blockchain platform to enhance consumer trust. The study identifies correlations between driving behaviors and associated risks to determine a driver's score. A decentralized bidding algorithm is proposed and implemented on a blockchain platform using elliptic curve cryptography and first-price sealed-bid auctions. Additionally, the model incorporates intelligent contract functionality to prevent unauthorized modifications and ensure that insurance prices align with the prevailing market value. An experimental study evaluates the system's efficacy by expanding the participant pool in the bidding process to identify the winning bidder and is investigated under scenarios where varying numbers of insurance companies submit bids. The experimental results demonstrate that as the number of insurance companies increases exponentially, the temporal overhead incurred by the system exhibits only marginal growth. Moreover, the allocation of bids is accomplished within a significantly abbreviated timeframe. These findings provide evidence that supports the efficiency of the proposed algorithm.

A New Quantum Sealed-Bid Auction Protocol with a Set of Local Indistinguishable Orthogonal Product States

Quantum sealed-bid auction (QSA) is a special form of transaction with significant applications in the economic and financial fields. Using a unique set of locally indistinguishable orthogonal product (LIOP) states, we propose a new QSA protocol in this paper. In the protocol, the bid message is encoded as a quantum sequence of LIOP states, and the different particles of LIOP states are transmitted separately. Even though an attacker obtains a portion of the particles, they cannot recover the entire bid message because of the local indistinguishability of LIOP states. Once the auctioneer announces the winner’s bid, all bidders are able to confirm the authenticity of their bid. With the help of a semi-honest third party, collusion between the auctioneer and a malicious bidder can be discovered. Finally, our protocol is capable of meeting all requirements for secure sealed-bid auctions through security and completeness analysis. Additionally, the proposed protocol does not require any entangled resources and complicated operations, so it can be easily implemented in practice.

The Use and Performance of Sealed Bid versus Oral Timber Auctions by State Forestry Agencies: A Minnesota Case Study

Abstract State governments are responsible for the stewardship and management of more than 28 million ha of forest land in the United States. This study presents the findings of an in-depth examination of the characteristics and performance of sealed bid and oral auctions using records from more than a thousand tracts offered for sale by the Minnesota Department of Natural Resources, which administers one of the nation’s most robust state timber sale programs. The study found that although tracts offered for sale through oral and sealed bid auctions sold at the same rate and are undifferentiated with respect to nearly all characteristics, sealed bid tracts generated significantly higher winning prices and additional revenue per hectare than tracts sold using oral auctions. Logging businesses were more likely to win sealed auctions than oral auctions, and their portfolio of purchased tracts contained a higher proportion acquired through sealed bid auctions than the portfolio of sealed bid tracts purchased by mills. The study adds to the limited body of literature on public agency timber auctions and is the first to provide a detailed analysis of the auction methods used by a state forest management agency. Study Implications: Public agencies use sealed bid and oral auctions to sell timber rights. This study of the nation’s largest state timber sale program found that the auction method used affects winning bid prices, the likelihood certain categories of bidders will win the auction, the allocation of timber to mills and logging businesses, and revenue generated for each hectare of timber sold. State timber sale program administrators may be able to use these findings to better understand how the choice of auction method affects the financial performance of their timber sale program as well as the allocation of timber among the major types of bidders.

On the role of optical materials in the realization of schemes for secure quantum communication

We introduce a prescription using optical materials to perform a quantum sealed-bid auction using an n-partite cluster state, produced using an optical parametric oscillator (OPO) through the process of spontaneous parametric down-conversion (SPDC) and an array of Beam splitters whose properties define the amount of correlation in the corresponding state. We further establish the role of optical materials in performing quantum communication protocols and analyse the effect of noise on the state.