Abstract: A method of computing at least one solution to an auction winner-determination problem includes receiving a plurality of bids in an auction and computing at least one solution to an auction winner-determination problem for the auction using the plurality of bids.

Abstract: An embodiment in accordance with the present invention provides a method for determining a demand function for an item. For example, the method includes determining a first estimate of the demand function for the item by utilizing a first auction having a first set of auction parameters. Additionally, the method includes determining a second estimate of the demand function for the item by utilizing a second auction using auction data from the first auction. The second auction has a second set of auction parameters based on the first estimate of the demand function.

Abstract: A computer-implemented automated decision support system for designing an auction for a given item includes a structure extractor that estimates unknown elements of market structure of the auction based on auction characteristics data extracted from historical auctions for similar items and a bidding model matching the extracted auction characteristics data. The decision support system also includes a bidding behavior predictor that predicts bidding behaviors of bidders in the auction based on the estimated unknown elements of market structure and characteristics of the auction. In addition, the system includes an optimizer that employs an evaluation criterion to generate an evaluation of the auction based on (1) the estimated unknown elements of market structure and (2) the predicted bidding behavior of bidders. A method of providing an automated auction analysis is also described.

Abstract: An embodiment in accordance with the present invention provides a method for determining a demand function for an item. For example, the method includes determining a first estimate of the demand function for the item by utilizing a first auction having a first set of auction parameters. Additionally, the method includes determining a second estimate of the demand function for the item by utilizing a second auction using auction data from the first auction. The second auction has a second set of auction parameters based on the first estimate of the demand function.

Abstract: A method and related system for predicting, possibly a software program executing on a computer system, an online auction outcome for each of a plurality of feedback rules.

Abstract: An automated estimation and optimization solution for selecting the best auction format by determining the latent elements of the auction environment taking into account the strategic and information conditions with minimal assumptions on the distributions of unobserved random elements. Structural analysis of bid data from prior auctions is used to identify and estimate the distributions of bidders' private signals conditional on observable bidder characteristics. The estimated signal distributions, identified by the structural analysis, are used to evaluate alternative auction formats and to select the best format from among a given set of candidates. The present invention provides decision support tools to select an auction format based on structural econometric analysis of available data on the market environment. A decision-maker may estimate the unobservable private signals of the bidders and to determine the best auction format the decision maker can employ to sell a given set of items.

Abstract: A method for extracting an implied value of a component associated with a plurality of product packages is disclosed. One embodiment of the method includes receiving data associated with a plurality of product packages. It is noted that the data comprises product package price data associated with the plurality of product packages. The data is processed utilizing a mathematical optimization to produce first output data. The first output data is processed with a statistical regression to produce second output data. The second output data includes an estimated value and its standard error of a component associated with the plurality of product packages.

Abstract: The present invention provides an automated estimation and optimization solution for selecting the optimal bid for an item in an auction. The characteristics of the auction are selected (e.g., auction format, reserve price). A relevant bidding model, based on the characteristics of the auction, is selected. The structure of the auction is estimated based on the relevant bidding model. A bid function is determined based on the auction structure and user inputs regarding the item being bid on and the characteristics of the rival bidders. An optimal bid is determined based on the bid function and user-defined evaluation criterion. An embodiment of the present invention provides a method and system that determines the latent elements of the auction environment taking into account the strategic and information conditions with minimal assumptions on the distributions of unobserved random elements.

Abstract: One embodiment of the present invention provides a method and system that computes the optimal level of the reserve price for an auction, with respect to a multiplicity of possible evaluation criteria that the end user of the system may specify. In one embodiment, structural elements characterizing the auction situation are estimated from bid data available on past auctions. The estimated structural elements are then used in the formulation of the user's expected payoff as a function of the reserve price. This objective function is then optimized to obtain the best level of the reserve price. In one embodiment, this method is implemented by a process executed on a computer system, under the control of software and firmware directing the operation of its processors and components. In one embodiment, a computer readable medium causes a computer system to execute the steps in a process for implementing the method.

Abstract: One embodiment of the present invention provides a method and system that determines the optimal preference policy for a market, such as an auction, with respect to a multiplicity of possible evaluation criteria that auction participants or other end users specify. In one embodiment, a method and system that configures the optimal preference policies that can be implemented in any market, particularly an auction, applicable to any auction format a market decision maker may wish to conduct. An embodiment of the present invention estimates bidders' private information and correspondingly identifies exploitable asymmetries to implement a preferential treatment policy. In one embodiment, this method is implemented on a computer system, under the control of software and firmware directing the operation of its processor and other components. In one embodiment, a computer readable medium causes a computer system to execute the method.

Abstract: An initial external bid of an enterprise that is based on initial component bids of plural entities is received by a tool. The tool receives margin values representing margins acceptable to the entities. A new external bid is received that is different from the initial bid, and adjusted component bids of the plural entities are generated by the tool according to the new external bid and the margins of the entities.

Abstract: A method and apparatus for determining private information and risk attitudes of bidders at auctions. By varying auction formats, the underlying risk attitudes and joint distribution of bidders' private information is extracted. Bids submitted in utility-independent auctions are used to determine the bidders private information. Risk attitudes for bidders are determined using utility-dependent auctions and using the determined bidders' private information. When there is insufficient auction data for determining private information and risk attitudes, additional auctions are conducted to obtain the needed auction data. The results can then be used for designing auctions and for determining bids to be made by buyers.

Abstract: A system and method comprises simulating a multiple lot auction using a sequencing rule until bidding on all lots is closed, simulating the multiple lot auction using a different sequencing rule until bidding on all lots is closed, and comparing results of the simulated auctions with both sequencing rules.

Abstract: A method and related system for predicting, possibly a software program executing on a computer system, an online auction outcome for each of a plurality of feedback rules.

Abstract: Methods and associated apparatus comprise, among other features, organizing previously acquired auction data into a plurality of sub-samples, each sub-sample comprising bid data associated with auctions having a common number of bidders, applying an inverse bid function to at least two sub-samples, pooling results from applying the inverse bid function to form a first pool, applying a direct bid function on the first pool to generate sample bids, matching bids from at least one sub-sample to the sample bids, and pooling results from the matching with the first pool to form a second pool.

Abstract: A method and associated system comprise obtaining historical auction data, determining, from the historical auction data, a first parameter that is a function of a joint bid distribution and a density function related to the joint bid distribution, selecting a bidder, obtaining a value distribution for the selected bidder, and solving an equation. The equation may include the first parameter and the selected bidder's value distribution, and not the value distribution of other bidders. The equation computes a bid value associated with the selected bidder for a given bid.

Abstract: A method and system for selecting feedback rules for an online auction. An exemplary method may comprise controlling feedback by customizing feedback rules for an online auction substantially no earlier than entry of auction rules into an auction program by an end-user, storing the customized feedback rules for future use by the auction program, and conducting the online auction by the auction program using the feedback rules.

Abstract: A computer-implemented method for automatic contract monitoring. An electronic version of a contract comprising at least one term and at least one penalty is received. Information relevant to enforcement of contract is monitored. A transaction related to the contract is received. Using the information, it is automatically determined whether the transaction is compliant with the contract.

Abstract: A method for extracting an implied value of a component associated with a plurality of product packages is disclosed. One embodiment of the method includes receiving data associated with a plurality of product packages. It is noted that the data comprises product package price data associated with the plurality of product packages. The data is processed utilizing a mathematical optimization to produce first output data. The first output data is processed with a statistical regression to produce second output data. The second output data includes an estimated value and its standard error of a component associated with the plurality of product packages.

Abstract: A computer-implemented method for determining a bid for a auction. A valuation for the auction, a risk preference, and a rate of change of the risk preference are received. A joint distribution is determined based on historical auction information and at least one updated valuation for an historical auction. A density of the joint distribution is determined. The bid is determined based on the risk preference, the rate of change of the risk preference, the valuation, the joint distribution, and the density of the joint distribution.