In the Internet age, e-commerce provides customers global reach to a wide variety of products and plays a dominant role in business activity and competition. Competition is especially aggressive in the online travel domain where wholesalers, e.g. brokerage companies, contract through their contract managers with thousands of hotel brands and trade hotel products (usually hotel nights) for travel businesses or end customers. In order to conclude a profitable contract, a contract manager should be able to compare all the particulars of the prospective partner hotel with those of the competing hotels in the target city. Given that the number of contract managers is comparatively small compared to the large number of hotels, the possible knowledge base is limited. Thus, the hotel brokerage companies are only able to bargain with a relatively limited number of hotels, and the contract profitability relies heavily on the contract managers' expertise and communication skills. In this paper we present a price management decision support system (DSS) for hotel brokers that allows analysis of hotel prices using spatial and non-spatial characteristics, estimation of the objective relative hotel prices, and determination of the profitability of the existing or future contracts. We built our system using free and open source tools including geographic information system and data mining frameworks that allow companies with limited money resources or manpower to implement such a prototype. We show the effectiveness of our tool by covering all the major components of the DSS such as data selection and integration, model management and user interface. We demonstrate our tool on the area of Barcelona, Spain using a real data of 168 hotels provided by one of the travel service providers.