Abstract: A solution for automatically adjusting a webpage. According to the method of the present invention it can be automatically learned what the user's historical browsing behaviors is and thereby predict which block in the webpage would concerned the user more so that it would be the one to be browsed and then adjust display of the block accordingly. Thus, with the present invention, limited screen sources can be utilized to more efficiently display the content that would concern a user when the user browses a webpage. A system for automatically adjusting a webpage and a computer readable article of manufacture tangibly embodying non-transitory computer readable instructions which, when executed, cause a computer to carry out the steps of a method for automatically adjusting a webpage are also provided.

Abstract: System and method for service pricing optimization enables analysis of multi-phased, multi-business unit, multi-process, multi-geo/country deal structure with its parts and phases having different pricing implications, and provides a flexible composite pricing schedule optimized for both service provider and receiver by gain and risk sharing. In one aspect, elementary pricing models and pricing parameters are established and a composite pricing model is constructed based on the elementary pricing models and pricing parameters. An optimizer optimizes the composite pricing model to minimize risk and maximize one or more selected criteria. Price is generated using the optimized composite pricing model.

Abstract: A method and system for generating bill payment schedule utilizes a composite pricing module to generate payment schedule over a predetermined period of time. In one aspect, a fraction of each pricing model attributing to the composite pricing model is determined. A charge fee associated with said each pricing model based on said fraction and said total price to charge is determined. Price to charge during each time unit of the time period is allocated, based on budget over the time period, discount rate, target profit margin and risk affordance. Bill schedule is generated using the allocated price.

Abstract: A method and system for generating bill payment schedule utilizes a composite pricing module to generate payment schedule over a predetermined period of time. In one aspect, a fraction of each pricing model attributing to the composite pricing model is determined. A charge fee associated with said each pricing model based on said fraction and said total price to charge is determined. Price to charge during each time unit of the time period is allocated, based on budget over the time period, discount rate, target profit margin and risk affordance. Bill schedule is generated using the allocated price.

Abstract: System and method for determining maximal price for projects are provided. A project scope of a project based on a plurality of selected criteria is defined, and total cost of the project is estimated. A value model of the project is generated and estimated value of the project is determined using the value model. A composite object function that includes cumulative distributive functions of the total cost and of the estimated value is computed to determine potential maximal price or share rate or combinations thereof.

Abstract: A method and system for generating bill payment schedule utilizes a composite pricing module to generate payment schedule over a predetermined period of time. In one aspect, a fraction of each pricing model attributing to the composite pricing model is determined. A charge fee associated with said each pricing model based on said fraction and said total price to charge is determined. Price to charge during each time unit of the time period is allocated, based on budget over the time period, discount rate, target profit margin and risk affordance. Bill schedule is generated using the allocated price.

Abstract: System and method for determining maximal price for projects are provided. A project scope of a project based on a plurality of selected criteria is defined, and total cost of the project is estimated. A value model of the project is generated and estimated value of the project is determined using the value model. A composite object function that includes cumulative distributive functions of the total cost and of the estimated value is computed to determine potential maximal price or share rate or combinations thereof.

Abstract: System and method for determining piecewise pricing, in one aspect, generate a distribution function of transactions based on a plurality of data records associated with said transactions. One or more correlations between total cost and one or more performance measures are analyzed. Demand model is generated based on the distribution function. Piecewise pricing or level-price pairs are determined for a plurality of levels of performance measure, based on said one or more correlations between total cost and one or more performance measures, said demand model, and desired profit margin.

Abstract: System and method for service pricing optimization enables analysis of multi-phased, multi-business unit, multi-process, multi-geo/country deal structure with its parts and phases having different pricing implications, and provides a flexible composite pricing schedule optimized for both service provider and receiver by gain and risk sharing. In one aspect, elementary pricing models and pricing parameters are established and a composite pricing model is constructed based on the elementary pricing models and pricing parameters. An optimizer optimizes the composite pricing model to minimize risk and maximize one or more selected criteria. Price is generated using the optimized composite pricing model.

Abstract: A method, system and service for using a Component Business Model (CBM) of an enterprise to support value based pricing of business solutions. Business solutions are composed from, and are described in terms of, services exposed by business components. Pricing is represented as the product of iterative negotiations between a solution provider and a solution consumer. Both the provider and the consumer are analyzed in terms of constituent services. Value based pricing is applied to the constituent services, and a value based pricing schedule for the provider or the consumer is constructed from an evaluation of pricing schedules for the respective constituent services. The value based pricing schedules are themselves configured from a plurality of pricing strategies, the configuration being designed to optimize a pricing schedule for the mutual benefit of the provider and consumer.