حراج تأمین تجهیزات ترکیبی شامل قیمت بسته نرم افزاری بدون سواری رایگان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|16951||2008||20 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Decision Support Systems, Volume 44, Issue 3, February 2008, Pages 621–640
Combinatorial auctions are currently becoming a common practice in industrial procurement, allowing bidders (sellers of goods and services in the procurement setting) to avoid the risk of selling good or service bundles that are incomplete, inefficient, or excessively expensive to deliver. Two major concerns in combinatorial auction design are the revelation or discovery of market price information over the course of the auction, and the inherent computational difficulty (NP-hardness) of the underlying “winner-determination” problem. In this paper we describe a new general auction format maintaining the benefits of the adaptive user-selection approach without the problems of free-riding, inefficiency, or distortionary linear prices. This auction format is particularly well-suited to the largest combinatorial auctions for which winner-determination is computationally tractable, because it provides bundle synergy information that is computable in polynomial time for all interactive phases.
Early reports on the use of combinatorial procurement auctions (see ,  and  for examples) emphasize the robust ability of auction mechanisms to fairly price goods or services provided to a central buyer, allowing benefits on both sides of the market. Suppliers are able to pursue only combinations of goods or services that are cost-efficient to produce, while the buyer or procurer of services benefits from the price competition among several sellers. De-emphasized in the available literature is the complex interplay between the need for market revelation, allowing competing participants the ability to learn about one another, and the strategic leverage that becomes available when too much information about a bidder is made available through the auction's revelation environment. One of the main strengths of traditional single item auctions is that a bidder has the ability to learn about her own true preferences by observing the behavior of her opponents (see the text by Krishna ), a feature that is also beneficial in the combinatorial procurement setting. In the industrial procurement of food materials, for example (see the Mars Inc. procurement auction described in ), industrial growers of sugar may each hold some private knowledge on the yield of this year's crop, which in aggregate will determine the relative scarcity of the commodity and thus influence market behavior. Similarly, several transportation providers participating in a shipping lane auction (see the case of Sears Inc. described in ) may each have some (noisy) forecast of future oil prices, which in aggregate are much more accurate than if treated separately. Since the price of oil may heavily influence the value of future shipping contracts, these transportation firms would very much want to ascertain or estimate the beliefs of their opponents by observing their behavior in a multi-stage auction game. We may conclude from these simple examples that revelation of market information is quite beneficial in the procurement setting, and that a (one-shot) sealed-bid mechanism is undesirable for this reason. While the importance of revealed information and the potential for over-revelation have been only scarcely explored in the combinatorial auction literature, the issue that has been most discussed is the computational difficulty (NP-hardness) of the underlying “winner-determination” problem. Several approaches to this computational problem are discussed in the literature (see  and  for surveys), but here we focus instead on the adaptive user-selection techniques which address both the computational difficulties and the revelation properties simultaneously.
نتیجه گیری انگلیسی
We have presented a new auction design that incorporates features from both the PAUSE auction of Kelly and Steinberg  and the clock–proxy auction of Ausubel et al. . In particular, our method emphasizes revelation of price information on individual items in order to reduce the number of bundles for which bids will be necessary in the (NP-hard) winner-determination problem, and to allow for the revelation of aggregate information in common value settings. Unlike the clock–proxy auction and the dual-based pricing approaches, our mechanism for revealing prices on individual items does not incorporate non-linear (or non-additive) synergy information into linear item prices, as this leads to meaningless and distorted item prices. Unlike the PAUSE auction, free-riding is limited by a disciplined approach to bundle price revelation. We do, however, reveal price information over bundles, and as in the PAUSE auction this revelation takes place with only little computational burden to the auctioneer. (In contrast to PAUSE, this takes place through the repeated solution of assignment problems in our case, a polynomial-time procedure.) Like the clock–proxy auction, the use of a final sealed-bid round ensures efficiency and allows us to encourage truthful bidding throughout the auction with a “second-price” final payment mechanism. With the increasing use of combinatorial auctions for procurement (and other settings) the design of a computationally viable auction that incorporates price discovery (both for items and bundles), while mitigating many of the problems such as free-riding and the threshold problem, is of significant practical interest. The auction proposed in this paper addresses these issues in a novel and comprehensive way, building upon both PAUSE and the clock–proxy auction, yet avoiding some of the criticisms of each. To our knowledge, no other auction proposed so far is able to address all of the issues addressed by our auction. We look forward to experiments and practical implementations of our auction format in the future, in both the forward and reverse (procurement) auction contexts.