Abstract: A system including a service provider server receives product specification data sets or price data sets. The service provider server invokes an evaluation service that causes a metric application to obtain metric data including market reference price data for responsive items at a particular time or period of time. Attribute data for responsive items is algorithmically processed to dynamically identify any differences. The identified differences are used to contextually determine which of the predefined instructions are applicable to the responsive item. One or more adjustment values are generated and applied to the market reference price data for a responsive item that differs by at least one parameter value, transforming the market reference price data into normalized metric data that is used to generate a normalized metric value. One or more of the received data sets and the respective normalized metric value are communicated to a remotely located user-agent computing device.

Abstract: A computer system including a service provider server receives price data sets responsive to one or more product specification data sets. The service provider server invokes an evaluation service that causes a metric application to obtain metric data including market reference price data for items responsive to attributes of an item identified in a price data set. The attribute data for each responsive item is algorithmically processed to dynamically identify differences. One or more adjustment values are generated and applied to the market reference price data for a responsive item that differs from the item identified in the price data set, transforming the market reference price data into normalized metric data that is used to produce a normalized metric value. At least a subset of the price data sets and the respective normalized metric values are communicated via a network interface to a remotely located buyer-agent computing device.

Abstract: A computer system including a service provider server invokes an evaluation service that causes a metric application to obtain a plurality of market transaction data sets responsive to attributes of at least one item identified in a product specification data set and/or a price data set. Each market transaction data set is defined by at least one parameter value and represents market reference price data of a particular time or period of time. At least one adjustment value is generated and applied to the market reference price data associated with the at least one item in one or more of the market transaction data sets, transforming the market reference price data and producing normalized market reference price data sets. A synthetic market value is generated for the at least one item in the product specification data set and/or the price data set, and one or more evaluation metrics generated therefrom are communicated via a network interface.

Abstract: An automated system for evaluating the market value of items includes invoking an evaluation service that causes a metric application to obtain a plurality of market transaction data sets responsive to attributes of at least one item identified in a product specification data set and/or a price data set. Each obtained market transaction data set is defined by at least one parameter value and represents market reference price data of a particular period of time. At least one adjustment value is calculated and applied to the market reference price data having parameter values that vary from the at least one item identified in the product specification data set, transforming the market reference price data and generating a plurality of normalized market reference price data sets. A synthetic market value is determined for the at least one item in the product specification data set and/or the price data set.

Abstract: Methods and computer storage media provide for evaluating the market value of items. A product specification data set identifies an item defined by two or more parameters, or items that differ in accordance with at least one parameter. For at least one item, transaction data sets that include previously-exposed transaction data between buyers and sellers are obtained. The transaction data represents market reference price data of a particular period of time. The market reference price data is adapted by applying one or more pre-defined rules, variables, or criteria operably associated with the item, a parameter of the item, and/or the one or more databases, to the market reference price data, transforming the transaction data sets into normalized market price data sets that are used to calculate a market value for the item, and communicate the market value to an output. In additional embodiments, price data sets are received and evaluated.

Abstract: To disaggregate a single combined price of a bundled product, a computer receives a price data set comprised of component parts that correspond to the component parts of the bundled product. At least one component part differs in accordance with at least one parameter value of another component part. A price for a component part is calculated by obtaining metric data that includes one or more market reference prices responsive to the component part. Using the metric data, a market value is computed for each component part and the computed market values are summed to compute a market value total. A proportional value for at least one component part is generated by dividing the market value of the component part by the market value total. A price for the component part is calculated by multiplying the price data set's single combined price by the component part's proportional value.

Abstract: A computer-readable storage medium contains instructions that cause one or more computing devices to receive a product specification data set identifying one or more items, and price data sets that include one or more items and corresponding price data. For each price data set, metric data is obtained which includes one or more market reference prices for the items in the price data set. A market value of the items is calculated for comparison to the price data in the price data set. The instructions may also cause the one or more computing devices to compare the price data in the price data set to the calculated market value to generate a comparison value. In another embodiment, metric data is obtained for each item in a product specification data set, and a market value of each item is calculated for comparison to the price data in the price data sets.

Abstract: One or more price metrics are generated by retrieving, from a database, one or more price data sets representing a specified time period. Each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item, and is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items. In at least one embodiment, a combined item price total is divided by a combined item unit total to generate a metric price per unit for each item in the product specification data set. In another embodiment, a summed individual metric price per unit is divided by the number of individual metric prices to generate an overall metric price per unit for each item in the product specification data set.

Abstract: A method for evaluating price data includes receiving a product specification data set that identifies different items. Also received are price data sets that include items and corresponding price data. For each price data set, metric data for each item is obtained. The metric data includes one or more market reference prices for the items in the price data set. Using the metric data, a market value of each item in the price data set is calculated for comparison to the price data in the price data set. The method may also include comparing the price data in the price data set to the calculated market value to generate a comparison value. In another embodiment, metric data is obtained for each item in the product specification data set, and a market value of each item is calculated for comparison to the price data in the price data sets.

Abstract: A method for evaluating price data includes receiving a product specification data set that identifies different items. Also received are price data sets that include items and corresponding price data. For each price data set, metric data for each item is obtained. The metric data includes one or more market reference prices for the items in the price data set. Using the metric data, a market value of each item in the price data set is calculated for comparison to the price data in the price data set. The method may also include comparing the price data in the price data set to the calculated market value to generate a comparison value. In another embodiment, metric data is obtained for each item in the product specification data set, and a market value of each item is calculated for comparison to the price data in the price data sets.

Abstract: One or more price metrics are generated by retrieving, from a database, one or more price data sets representing a specified time period. Each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item, and is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items. In at least one embodiment, a combined item price total is divided by a combined item unit total to generate a metric price per unit for each item in the product specification data set. In another embodiment, a summed individual metric price per unit is divided by the number of individual metric prices to generate an overall metric price per unit for each item in the product specification data set.

Abstract: One or more price metrics are generated by retrieving, from a database, one or more price data sets representing a specified time period. Each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item, and is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items. In at least one embodiment, a combined item price total is divided by a combined item unit total to generate a metric price per unit for each item in the product specification data set. In another embodiment, a summed individual metric price per unit is divided by the number of individual metric prices to generate an overall metric price per unit for each item in the product specification data set.

Abstract: Comparison values are calculated for evaluating a commercial transaction. A request for quote received from a buyer agent includes a product specification data set that identifies items that differ in accordance with at least one parameter. Price data sets received from seller agents identify items and prices in response to the product specification data set. At least one of the price data sets identifies an item having a different parameter value as compared to the item in another price data set. A comparison value for each price data set is generated by determining a price total from the price data set and calculating a summed market price total by summing market price totals for each of the items. Calculating market price totals includes obtaining metric data indicative of market prices. The summed market price total is compared to the price total for the price data set to generate the comparison value.

Abstract: Comparison values are calculated for evaluating a commercial transaction. A request for quote received from a buyer agent includes a product specification data set that identifies items that differ in accordance with at least one parameter. Price data sets received from seller agents identify items and prices in response to the product specification data set. At least one of the price data sets identifies an item having a different parameter value as compared to the item in another price data set. A comparison value for each price data set is generated by determining a price total from the price data set and calculating a summed market price total by summing market price totals for each of the items. Calculating market price totals includes obtaining metric data indicative of market prices. The summed market price total is compared to the price total for the price data set to generate the comparison value.

Abstract: Comparison values are calculated for evaluating a commercial transaction. A request for quote received from a buyer agent includes a product specification data set that identifies items that differ in accordance with at least one parameter. Price data sets received from seller agents identify items and prices in response to the product specification data set. At least one of the price data sets identifies an item having a different parameter value as compared to the item in another price data set. A comparison value for each price data set is generated by determining a price total from the price data set and calculating a summed market price total by summing market price totals for each of the items. Calculating market price totals includes obtaining metric data indicative of market prices. The summed market price total is compared to the price total for the price data set to generate the comparison value.

Abstract: Comparison values are calculated for evaluating a commercial transaction. A request for quote received from a buyer agent includes a product specification data set that identifies items that differ in accordance with at least one parameter. Price data sets received from seller agents identify items and prices in response to the product specification data set. At least one of the price data sets identifies an item having a different parameter value as compared to the item in another price data set. A comparison value for each price data set is generated by determining a price total from the price data set and calculating a summed market price total by summing market price totals for each of the items. Calculating market price totals includes obtaining metric data indicative of market prices. The summed market price total is compared to the price total for the price data set to generate the comparison value.

Abstract: Managing and evaluating commodities pricing, in one embodiment, includes retrieving and summing one or more price data sets exchanged between a buyer and seller agent in a specified time period. Additionally, metric data indicative of market prices for commodities indicated by the retrieved price data sets are summed. The summed totals are then compared to generate a comparison value. In another embodiment, one or more price data sets in a specified time period are retrieved, wherein commodities indicated by the price data sets meet a specified criterion. The retrieved price data sets and metric data indicative of market prices for the indicated commodities are summed and compared. In another embodiment, price data in one or more requests for quote are compared with metric data to normalize quoted prices. Accordingly, multi-value cross compilation of sales transactions and metric data for evaluation of commodities pricing is achieved.

Abstract: Managing and evaluating commodities pricing, in one embodiment, includes retrieving and summing one or more price data sets exchanged between a buyer and seller agent in a specified time period. Additionally, metric data indicative of market prices for commodities indicated by the retrieved price data sets are summed. The summed totals are then compared to generate a comparison value. In another embodiment, one or more price data sets in a specified time period are retrieved, wherein commodities indicated by the price data sets meet a specified criterion. The retrieved price data sets and metric data indicative of market prices for the indicated commodities are summed and compared. In another emobodiment, price data in one or more requests for quote are compared with metric data to normalize quoted prices. Accordingly, multi-value cross compilation of sales transactions and metric data for evaluation of commodities pricing is achieved.

Abstract: A method and system for managing and evaluating commodities purchasing over a network of distributed computing devices. In one embodiment, the method allows a plurality of buyers to generate one request for quote and, response to the request for quote, receive a quote from plurality of vendors. The system of the present invention provides a price normalization routine that allows buyers to evaluate and compare a normalized price for commodity products having different evaluation parameters. In an arrangement comprising a plurality of computers connected to a network said plurality of computers including at least one server, at least one buyer client computer and a plurality of seller client computers, the method for providing commodities exchange services first provides a web-based browsable display describing at least one commodities exchange service. The system then receives at least one request for quote from the buyer.