Efficiency Guarantees in Auctions with Budgets

In settings where players have a limited access to liquidity, represented in the form of budget constraints, efficiency maximization has proven to be a challenging goal. In particular, the social welfare cannot be approximated by a better factor then the number of players. Therefore, the literature has mainly resorted to Pareto-efficiency as a way to achieve efficiency in such settings. While successful in some important scenarios, in many settings it is known that either exactly one incentive-compatible auction that always outputs a Pareto-efficient solution, or that no truthful mechanism can always guarantee a Pareto-efficient outcome. Traditionally, impossibility results can be avoided by considering approximations. However, Pareto-efficiency is a binary property (is either satisfied or not), which does not allow for approximations. In this paper we propose a new notion of efficiency, called \emph{liquid welfare}. This is the maximum amount of revenue an omniscient seller would be able to extract from a certain instance. We explain the intuition behind this objective function and show that it can be 2-approximated by two different auctions. Moreover, we show that no truthful algorithm can guarantee an approximation factor better than 4/3 with respect to the liquid welfare, and provide a truthful auction that attains this bound in a special case. Importantly, the liquid welfare benchmark also overcomes impossibilities for some settings. While it is impossible to design Pareto-efficient auctions for multi-unit auctions where players have decreasing marginal values, we give a deterministic $O(\log n)$-approximation for the liquid welfare in this setting

Signal-Jamming in a Sequential Auction

In a recurring auction early bids may reveal bidders’ types, which in turn affects bidding in later auctions. Bidders take this into account and may bid in a way that conceals their private information until the last auction is played. The present paper analyzes the equilibrium of a sequence of ?rst-price auctions assuming bidders have stable private values. We show that signal-jamming occurs and explore the dynamics of equilibrium prices

Statistical Arbitrage Mining for Display Advertising

We study and formulate arbitrage in display advertising. Real-Time Bidding (RTB) mimics stock spot exchanges and utilises computers to algorithmically buy display ads per impression via a real-time auction. Despite the new automation, the ad markets are still informationally inefficient due to the heavily fragmented marketplaces. Two display impressions with similar or identical effectiveness (e.g., measured by conversion or click-through rates for a targeted audience) may sell for quite different prices at different market segments or pricing schemes. In this paper, we propose a novel data mining paradigm called Statistical Arbitrage Mining (SAM) focusing on mining and exploiting price discrepancies between two pricing schemes. In essence, our SAMer is a meta-bidder that hedges advertisers' risk between CPA (cost per action)-based campaigns and CPM (cost per mille impressions)-based ad inventories; it statistically assesses the potential profit and cost for an incoming CPM bid request against a portfolio of CPA campaigns based on the estimated conversion rate, bid landscape and other statistics learned from historical data. In SAM, (i) functional optimisation is utilised to seek for optimal bidding to maximise the expected arbitrage net profit, and (ii) a portfolio-based risk management solution is leveraged to reallocate bid volume and budget across the set of campaigns to make a risk and return trade-off. We propose to jointly optimise both components in an EM fashion with high efficiency to help the meta-bidder successfully catch the transient statistical arbitrage opportunities in RTB. Both the offline experiments on a real-world large-scale dataset and online A/B tests on a commercial platform demonstrate the effectiveness of our proposed solution in exploiting arbitrage in various model settings and market environments.Comment: In the proceedings of the 21st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2015

A Model of Vertical Oligopolistic Competition

This paper develops a model of successive oligopolies with endogenous market entry, allowing for varying degrees of product differentiation and entry costs in both markets. Our analysis shows that the downstream conditions dominate the overall profitability of the two-tier structure while the upstream conditions mainly affect the distribution of profits. We compare the welfare effects of upstream versus downstream deregulation policies and show that the impact of deregulation may be overvalued when ignoring feedback effects from the other market. Furthermore, we analyze how different forms of vertical restraints influence the endogenous market structure and show when they are welfare enhancing

Quick abnormal-bid-detection method for construction contract auctions

Noncompetitive bids have recently become a major concern in both public and private sector construction contract auctions. Consequently, several models have been developed to help identify bidders potentially involved in collusive practices. However, most of these models require complex calculations and extensive information that is difficult to obtain. The aim of this paper is to utilize recent developments for detecting abnormal bids in capped auctions (auctions with an upper bid limit set by the auctioner) and extend them to the more conventional uncapped auctions (where no such limits are set). To accomplish this, a new method is developed for estimating the values of bid distribution supports by using the solution to what has become known as the German Tank problem. The model is then demonstrated and tested on a sample of real construction bid data, and shown to detect cover bids with high accuracy. This paper contributes to an improved understanding of abnormal bid behavior as an aid to detecting and monitoring potential collusive bid practices

Shallow Flaws Under Biaxial Loading Conditions, Part II: Application of a Weibull Stress Analysis of the Cruciform Bend Specimen Using a Hydrostatic Stress Criterion

Cruciform beam fracture mechanics specimensl have been developed in the Heavy Section Steel Technology (HSST) Program at Oak Ridge National Laboratory (ORNL) to introduce a prototypic, far- field, out-of-plane biaxird bending stress component in the test section that approximates the nonlinear biaxial stresses resulting from pressurized-thernxd-shock or pressure-temperature loading of a nuclear reactor pressure vessel (RPV). Matrices of cruciform beam tests were developed to investigate and quantify the effects of temperature, biaxial loading, and specimen size on fracture initiation toughness of two-dimensional (constant depth), shtdlow, surface flaws. Tests were conducted under biaxial load ratios ranging from uniaxial to equibiaxial. These tests demonstrated that biaxial loading can have a pronounced effect on shallow-flaw fracture toughness in the lower transition temperature region for RPV materials. Two and three- parameter Weibull models have been calibrated using a new scheme (developed at the University of Illinois) that maps toughness data from test specimens with distinctly different levels of crack-tip constraint to a small scale yielding (SSY) Weibull stress space. These models, using the new hydrostatic stress criterion in place of the more commonly used maximum principal stress in the kernel of the OW integral definition, have been shown to correlate the experimentally observed biaxiaI effect in cruciform specimens, thereby providing a scaling mechanism between uniaxial and biaxial loading states

Social Media Technologies' Use for the Competitive Information and Knowledge Sharing, and Its Effects on Industrial SMEs' Innovation

The effective use of technologies supporting decision making is essential to companies? survival. Recent studies analyzed social media technologies (SMT) in the context of small- and medium-sized enterprises (SMEs), contributing to the discussion on SMT benefits from the marketing perspective. This article focuses on the effects of SMT use on innovation. Our findings provide empirical evidence on the positive effects of SMT use for acquiring external information and for sharing knowledge and innovation performance

Fracture assessment of HSST Plate 14 shallow-flaw cruciform bend specimens tested under biaxial loading conditions

A technology to determine shallow-flaw fracture toughness of reactor pressure vessel (RPV) steels is being developed for application to the safety assessment of RPVs containing postulated shallow surface flaws. Matrices of cruciform beam tests were developed to investigate and quantify the effects of temperature, biaxial loading, and specimen size on fracture initiation toughness of two-dimensional (constant depth), shallow, surface flaws. The cruciform beam specimens were developed at Oak Ridge National Laboratory (ORNL) to introduce a far-field, out-of-plane biaxial stress component in the test section that approximates the nonlinear stresses resulting from pressurized-thermal-shock or pressure-temperature loading of an RPV. Tests were conducted under biaxial load ratios ranging from uniaxial to equibiaxial. These tests demonstrated that biaxial loading can have a pronounced effect on shallow-flaw fracture toughness in the lower transition temperature region for an RPV material. The cruciform fracture toughness data were used to evaluate fracture methodologies for predicting the observed effects of biaxial loading on shallow-flaw fracture toughness. Initial emphasis was placed on assessment of stress-based methodologies, namely, the J-Q formulation, the Dodds-Anderson toughness scaling model, and the Weibull approach. Applications of these methodologies based on the hydrostatic stress fracture criterion indicated an effect of loading-biaxiality on fracture toughness; the conventional maximum principal stress criterion indicated no effect. A three-parameter Weibull model based on the hydrostatic stress criterion is shown to correlate the experimentally observed biaxial effect on cleavage fracture toughness by providing a scaling mechanism between uniaxial and biaxial loading states