Optimal social welfare:A many-to-many data transaction mechanism based on double auctions

With the development of Big Data and the Internet of Things(IoT),the data value is more significant in both academia and industry.Trading can achieve maximal data value and prepare data for smart city services.Due to data's unique characteristics,such as dispersion,heterogeneity and distributed storage,an unbiased platform is necessary for the data trading market with rational trading entities.Meanwhile,there are multiple buyers and sellers in a practical data trading market,and this makes it challenging to maximize social welfare.To solve these problems,this paper proposes a Social-Welfare-Oriented Many-to-Many Trading Mechanism(SOMTM),which integrates three entities,a trading process and an algorithm named Many-to-Many Trading Algorithm(MMTA).Based on the market scale,market dominated-side and market fixed-side,simulations verify the convergency,economic properties and efficiency of SOMTM.

Evolutionary Techniques for Reverse Auctions

Winner determination is one of the main challenges in combinatorial auctions. However, not much work has been done to solve this problem in the case of reverse auctions using evolutionary techniques. This has motivated us to propose an improvement of a genetic algorithm based method, we have previously proposed, to address two important issues in the context of combinatorial reverse auctions: determining the winner(s) in a reasonable processing time, and reducing the procurement cost. In order to evaluate the performance of our proposed method in practice, we conduct several experiments on combinatorial reverse auctions instances. The results we report in this paper clearly demonstrate the efficiency of our new method in terms of processing time and procurement cost.

Strategic Analysis of High-tech Auctions

This paper deals with the security voting structure in an auction mechanism used to sell an item Of high-tech. The design of security voting structure allows the seller to choose between two objectives that are not mutually consistent. However, if the seller wants to maximize his revenue, he should retain some shares to benefit from the future dividends generated by the acquirer. In addition, if he wants to sell his high-tech to the most efficient candidate, he should sell all the shares.

Cotton Reserves Auctions Touch 57% of Release Plan but Prices Rally

With manufacturing slowly recovering amid improving economic conditions, cotton demand has increased prompting more orders among mills. However, with a deficient supply of cotton in the market, prices extend gains since Oct. 2009.

A New Protocol for Multi-Item Electronic Auctions

The authors propose a new protocol for muhizzitem electronic auctions. It has the following advantages： first, the protocol is more applicable and flexible than the previous protocols, in this protocol, each bidder can decide how many items to buy according to diiferent bidding prices, which are set by the seller at the beginning of the auction; second, privacy is well preserved, no third parties are needed in the protocol and the auction outcome is jointly computed by the bidders on their own without uncovering any additional information.

Multi-Dimensional Customer Data Analysis in Online Auctions

In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.

A Few Notes on Auctions:The Boom in the Asymmetric Art Auction Market

The art market,following the example of financial markets,is divided into a primary market,where works are traded directly from artists,and a secondary market that is mainly the auction market.COVID-19 and galloping inflation have influenced the creation of a bull market in artwork.The high incomes of some buyers and inflation have influenced the emergence of the so-called“glittery”art market.Works by neglected artists have“very much taken on a life of their own”:fantasy art,works by young poster artists,casting“nightmares”-have been selling well for more than a year.People terrified of inflation are putting their money“in works of art”.The auction market dominates the primary market because anonymity makes it easier to enter the art market.The gallery market does not guarantee this anonymity.Very often,the auction market for works of art is used for money laundering.The purpose of this paper is to show that auction mechanisms are a good tool for the efficient allocation of goods and money in an era of galloping inflation,including non-standard objects such as works of art.These mechanisms,due to the information asymmetry,often lead to the generation of all kinds of pathologies and the increasing incidence of the phenomenon known as the winner’s curse.

What Drives Up Land Price in China?Evidence from Bidding Processes of Land Auctions in Beijing

The land price in big cities draws much attention and discussion for its skyrocketing appreciation.Most researches are from the macro perspective due to data restriction.This paper aims to investigate the critical factors in the price formation process of a land auction,using the listing auction micro bidding-level data in Beijing from 2013 to 2018.We construct a model for the relationship between quitting price and land,bidder's characteristics,housing market conditions and competitive intensity(including private and public signals),then we use OLS for identification.We find that competitive intensity increases the quitting price by causing competition and interaction between bidders.More importantly,we find evidence of cheating behavior in the land market.Results show that bidders have higher quitting prices when they are in a joint venture,and when a central SOE developer or a top 10 developer exist in the joint venture.We also find different behavior of developers in the short run and long run.Our research contributes to the literature of land auctions by analyzing the price formation process and developers'behavior.We also provide supporting evidence for the government to make adjustments of the auction system and identify the cheating developers.

The cost of privacy on blockchain:A study on sealed-bid auctions

In order to preserve privacy in a blockchain ecosystem,the main objective is to keep a transaction's data private,such as the sender,the receiver,and the amount transferred.The current work studies the cryptographic tools commonly used to achieve this type of privacy,primarily focusing on the Ethereum blockchain.Such tools usually require many computational and storage resources,leading to additional fees.An anonymous auction protocol was developed as a case study to explore these costs,where hiding the identity and the amount of the bids utilizes a variety of cryptographic primitives.The proposed implementation was compared against three sealed-bid auction protocols,which utilize similar cryptographic tools for preserving privacy throughout the auction process.The results show that providing an additional level of anonymity,such as hiding someone's identity,can increase the gas cost significantly,up to 2.5 times,depending on the choice of the cryptographic tools,which determine the usage of the blockchain's storage and computational resources.By adjusting the level of decentralization on the application level by moving some operations off-chain and maintaining the role of the auctioneer,we show that we can maintain anonymity while reducing the gas cost by 40%.

Will Contextual Factors and Providing the Maximum Price Information Affect People's Actual Willingness-to-pay in BDM Auctions? Evidence from Three Asian Countries

The purpose of this study was to measure the effect of maximum price information and contextual factors on people＇s bidding behaviors in a controlled Becker-DeGroot-Marschak （BDM） experimental auctions. 354 respondents from three Asian countries （China, Cambodia and the Philippines） participated in this study. In each country, both households with piped water connection and households without piped water connection were investigated. The sample in each country was then randomly assigned to two groups： one group was provided with a maximum price of a water filter and the other group was not provided with the maximum price information. The results show that the treatment group with maximum price information had a higher actual willingness-to-pay than the control group without maximum price information, but they were not significantly different. Our results also indicate that contextual and socioeconomic factors did play a role in participants＇ bid results for the water filter.

A WEIGHTED PRODUCT METHOD FOR BIDDING STRATEGIES IN MULTI-ATTRIBUTE AUCTIONS

To eliminate computational problems involved in evaluating multi-attribute bids with differentmeasures,this article first normalizes each individual component of a bid,and then makes use ofthe weighted product method to present a new scoring function that converts each bid into a score.Twokinds of multi-attribute auction models are introduced in terms of scoring rules and bidding objectivefunctions.Equilibrium bidding strategies,procurer's revenue comparisons and optimal auction designare characterized in these two models.Finally,this article discusses some improvement of robustnessof our models,with respect to the assumptions.

OPTIMAL STARTING PRICE FOR EBAY-LIKE ONLINE AUCTIONS

Reserve price auctions are one of hot research issues in traditional auction theory. Here we study the starting price in an online auction, the counterpart of the public reserve price in a traditional auction. By considering three features of eBay-like online auctions： stochastic entry of bidders （subject to Poisson process）, insertion fee proportional to the starting price, and time discount, we have analyzed the properties of extremum points of the starting price for maximizing the seller＇s expected revenue, and found that, under certain conditions, the optimal starting price should be at the lowest Mlowable level, which is contrary to the results from the classic auction theory and finds its optimality in reality. We have also developed a general extended model of multistage auctions and carried out analysis on its properties. At last, some directions for further research are also put forward.

基于拍卖理论的动态多代理同类机调度算法

This paper addresses a multi-agent scheduling problem with uniform parallel machines owned by a resource agent and competing jobs with dynamic arrival times that belong to different consumer agents.All agents are self-interested and rational with the aim of maximizing their own objectives,resulting in intense resource competition among consumer agents and strategic behaviors of unwillingness to disclose private information.Within the context,a centralized scheduling approach is unfeasible,and a decentralized approach is considered to deal with the targeted problem.This study aims to generate a stable and collaborative solution with high social welfare while simultaneously accommodating consumer agents’preferences under incomplete information.For this purpose,a dynamic iterative auction-based approach based on a decentralized decision-making procedure is developed.In the proposed approach,a dynamic auction procedure is established for dynamic jobs participating in a realtime auction,and a straightforward and easy-to-implement bidding strategy without price is presented to reduce the complexity of bid determination.In addition,an adaptive Hungarian algorithm is applied to solve the winner determination problem efficiently.A theoretical analysis is conducted to prove that the proposed approach is individually rational and that the myopic bidding strategy is a weakly dominant strategy for consumer agents submitting bids.Extensive computational experiments demonstrate that the developed approach achieves high-quality solutions and exhibits considerable stability on largescale problems with numerous consumer agents and jobs.A further multi-agent scheduling problem considering multiple resource agents will be studied in future work.

Information Revelation in Sequential Auctions with Uncertainties About Future Objects

In many auctions,buyers know beforehand little about objects to be sold in the future.Whether and how to reveal information about future objects is an important decision problem for sellers.In this paper,two objects are sold sequentially and each buyer's valuation for the second object is k times that for the first one,and the true value of k is sellers' private information.The authors identify three factors which affect sellers' revelation strategies: The market's competition intensity which is characterized by the number of buyers,buyers' prior information about the second object,and the difference degree between two objects which is characterized by k.The authors give not only conditions under which revealing information about the second object in advance benefits the seller,but also the optimal releasing amount of information in the market with two sellers and one seller,respectively.

The Changing of Common Priors in Sequential Auctions

In sequential auctions the phenomenon of declining prices is often observed, which in theory can be represented by a supermartingale. This paper employs the perspective that bidders' values may change over stages and the common priors are sequentially adjusted by the remaining bidders. It is shown that the declining price sequence can be explained by the adjustment of common priors between auctions. The adjustment of common priors is characterized by stochastic orders. Sufficient and necessary conditions for a supermartingale price sequence are derived.

BUDGET CONSTRAINTS IN HOMOGENOUS MULTI-UNIT AUCTIONS

A homogenous multi-unit auction model is studied in two conditions： One is that the bidders face budget constraints and another is that the bidders do not face budget constraints. Two equilibrium bidding strategies of each bidder are presented in these two conditions. By comparing them, the authors show that the equilibrium unit price bid in the presence of budget constraints will be less than that in the absence of budget constraints. The difference between the two equilibrium bids leads to the reduced revenue of the seller. And this difference will decrease as the number of the bidders increases.

t-Private and t-Secure Auctions

In most of the auction systems the values of bids are known to the auctioneer. This allows him to manipulate the outcome of the auction. Hence, one might be interested in hiding these values. Some cryptographically secure protocols for electronic auctions have been presented in the last decade. Our work extends these protocols in several ways. On the basis of garbled circuits, i.e., encrypted circuits, we present protocols for sealed-bid auctions that fulfill the following requirements： 1） protocols are information-theoretically t-private for honest but curious parties; 2） the number of bits that can be learned by malicious adversaries is bounded by the output length of the auction; 3） the computational requirements for participating parties are very low： only random bit choices and bitwise computation of the XOR-function are necessary. Note that one can distinguish between the protocol that generates a garbled circuit for an auction and the protocol to evaluate the auction. In this paper we address both problems. We will present a t-private protocol for the construction of a garbled circuit that reaches the lower bound of 2t ＋ 1 parties, and Finally, we address the problem of bid changes in an auction. a more randomness efficient protocol for （t ＋ 1）^2 parties

Application of Online Reverse Auctions in Revenue Management of Airline Company

Based On the online reverse auction formalism in Priceline.com, In this paper,the use of online reverse auctions in airline companies revenue management is highlighted.This research examines the process of online reverse auctions in detail, point out the potential benefits of online reverse auctions. At last we examines how the online reverse auction mechanism design for optimal allocation.

Cotton Reserves Auctions Touch 57% of Release Plan but Prices Rally

With manufacturing slowly recovering amid improving economic conditions, cotton demand has increased prompting more orders among mills. However, with a deficient supply of cotton in the market, prices

OPTIMAL RESERVE PRICE IN STATIC AND DYNAMIC SPONSORED SEARCH AUCTIONS

Sponsored search advertising is a significant revenue source for search engines. To ameliorate revenues, search engines often set fixed or variable reserve price to in influence advertisers＇ bidding. This paper studies the optimal reserve price for a generalized second-price auction （GSP） under both static and dynamic settings. We show that if advertisers＇ per-click value has an increasing generalized failure rate, the search engine＇s revenue rate is quasi-concave and hence there exists an optimal reserve price under both settings. Different from a static GSP auction where the optimal reserve price is proved to be constant, in a dynamic setting the optimal reserve price is dependent on not only advertisers＇ per-click values, but also the number of ad links sold. A search engine should gradually raise reserve price as more qualified advertisers arrive, and maintain the same threshold after all first-page positions are occupied.