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Decision maker friendly approach for pricing software

Techniques for predicting computer software prices are of interest to researchers. This paper reviews and extends the earlier contributions of the authors to the field. It illustrates a new approach for predicting software prices. The illustrated approach is superior to previous approaches in two ways. First, the authors employ a unique factoring technique based on variable context that makes the final results easy to interpret and use. Second, the authors use variable transformations that have worked successfully in pricing computer hardware. The paper discusses the model construction, accuracy and results and helps decision makers better understand and control software prices.