Auctions with costly information acquisition Constrained Bidders

We consider auction environments in which bidders must incur a cost to learn their valuations and study the optimal selling mechanisms in such environments. These mechanisms specify for each period, as a function of the bids in previous periods, which new potential buyers should be asked to bid. In addition, these mechanisms must induce buyers to both acquire and to reveal truthfully their valuations. Using a generalized Groves principle, we prove a very general “full extraction of the surplus” result: the seller can obtain the same profit as if he had full control over the buyers’ acquisition of information and could have observed directly their valuations once they are informed. We also present appealing implementations of the optimal mechanism in special cases.mechanism design, selling mechanisms, auctions, information acquisition, search procedures

Auctions with Costly Information Acquisition

We characterize optimal selling mechanisms in auction environments where bidders must incur a cost to learn their valuations. These mechanisms specify for each period, as a function of the bids in previous periods, which new potential buyers should be asked to bid. In addition, these mechanisms must induce the bidders to acquire information about their valuations and to reveal this information truthfully. Using a generalized Groves principle, we prove a very general full extraction of the surplus result: the seller can obtain the same profit as if he had full control over the bidders' acquisition of information and could have observed directly their valuations once they are informed. We also present appealing implementations of the optimal mechanism in special cases.

Pricing and Market Segmentation Using Opaque Selling Mechanisms

In opaque pricing certain characteristics of the product or service are hidden from the consumer until after purchase, transforming a differentiated good into somewhat of a commodity. Opaque pricing has become popular in service pricing as it allows firms to sell their differentiated products at higher prices to regular brand loyal customers while simultaneously selling to non loyal customers at discounted prices. We develop a stylized model of consumer model a monopolist selling a product via three selling channels: a regular full information channel, an opaque posted price channel and an opaque bidding channel where consumers specify the price they are willing to pay. We illustrate the segmentation created by opaque pricing as well as compare optimal revenues and prices for sellers using regular full information channels with those using opaque selling mechanisms in conjunction with regular channels. We also study the segmentation and policy changes induced by capacity constraints

The Power of Simple Menus in Robust Selling Mechanisms

We study a robust selling problem where a seller attempts to sell one item to a buyer but is uncertain about the buyer's valuation distribution. Existing literature indicates that robust mechanism design provides a stronger theoretical guarantee than robust deterministic pricing. Meanwhile, the superior performance of robust mechanism design comes at the expense of implementation complexity given that the seller offers a menu with an infinite number of options, each coupled with a lottery and a payment for the buyer's selection. In view of this, the primary focus of our research is to find simple selling mechanisms that can effectively hedge against market ambiguity. We show that a selling mechanism with a small menu size (or limited randomization across a finite number of prices) is already capable of deriving significant benefits achieved by the optimal robust mechanism with infinite options. In particular, we develop a general framework to study the robust selling mechanism problem where the seller only offers a finite number of options in the menu. Then we propose a tractable reformulation that addresses a variety of ambiguity sets of the buyer's valuation distribution. Our formulation further enables us to characterize the optimal selling mechanisms and the corresponding competitive ratio for different menu sizes and various ambiguity sets, including support, mean, and quantile information. In light of the closed-form competitive ratios associated with different menu sizes, we provide managerial implications that incorporating a modest menu size already yields a competitive ratio comparable to the optimal robust mechanism with infinite options, which establishes a favorable trade-off between theoretical performance and implementation simplicity. Remarkably, a menu size of merely two can significantly enhance the competitive ratio, compared to the deterministic pricing scheme

The failure of the revenue equivalence principle: multiple objects, information acquisition and favoritism

A celebrated result of auction theory is the revenue equivalence principle which states that with independent private values and a single unit for sale all selling (or procurement) mechanisms that give the object to the bidder with the highest valuation generate the same revenue. The present thesis explores in each chapter a different deviation from the revenue equivalence princi- ple and compares selling (or procurement) mechanisms that would be equivalent otherwise. In chapter two the equivalence between the first-price auction and the descending auction fails if more than one unit is for sale. In chapter three and four the equivalence between all four of the standard auction formats fails in the case that bidders are not fully informed about their private valuation and may acquire additional information in the course of the auction. The fifth chapter theoretically analyzes the differences between optimal auctions and negotiations that can only arise in the presence of favoritism

Third-Party Data Providers Ruin Simple Mechanisms

Motivated by the growing prominence of third-party data providers in online marketplaces, this paper studies the impact of the presence of third-party data providers on mechanism design. When no data provider is present, it has been shown that simple mechanisms are "good enough" -- they can achieve a constant fraction of the revenue of optimal mechanisms. The results in this paper demonstrate that this is no longer true in the presence of a third-party data provider who can provide the bidder with a signal that is correlated with the item type. Specifically, even with a single seller, a single bidder, and a single item of uncertain type for sale, the strategies of pricing each item-type separately (the analog of item pricing for multi-item auctions) and bundling all item-types under a single price (the analog of grand bundling) can both simultaneously be a logarithmic factor worse than the optimal revenue. Further, in the presence of a data provider, item-type partitioning mechanisms---a more general class of mechanisms which divide item-types into disjoint groups and offer prices for each group---still cannot achieve within a $\log \log$ factor of the optimal revenue. Thus, our results highlight that the presence of a data-provider forces the use of more complicated mechanisms in order to achieve a constant fraction of the optimal revenue

Multi-item quick response system with budget constraint

Cataloged from PDF version of article.Quick response mechanisms based on effective use of up-to-date demand information help retailers to reduce their inventory management costs. We formulate a single-period inventory model for multiple products with dependent (multivariate normal) demand distributions and a given overall procurement budget. After placing orders based on an initial demand forecast, new market information is gathered and demand forecast is updated. Using this more accurate second forecast, the retailer decides the total stocking level for the selling season. The second order is based on an improved demand forecast, but it also involves a higher unit supply cost. To determine the optimal ordering policy, we use a computational procedure that entails solving capacitated multi-item newsboy problems embedded within a dynamic programming model. Various numerical examples illustrate the effects of demand variability and financial constraint on the optimal policy. It is found that existence of a budget constraint may lead to an increase in the initial order size. It is also observed that as the budget available decreases, the products with more predictable demand make up a larger share of the procurement expenditure. & 2012 Elsevier B.V. All rights reserved