Title: Pricing analysis of decision-making software: modelling and Artificial Intelligence approaches

Authors: Dinesh S. Dave, Ajay K. Aggarwal, Chandrashekar D. Challa

Addresses: Department of Computer Information Systems, John A. Walker College of Business, Appalachian State University, Boone, NC 28608, USA. ' Else School of Management, Millsaps College, 1701 North State Street, Jackson, MS 39210, USA. ' Sapthagiri Consulting, 200 Westgate Parkway, Suite 103, Richmond, VA 23233, USA

Abstract: Despite the lucrative worldwide software market, little pricing guidance is available in the literature to assist the software marketers. This paper attempts to create models for pricing software using both statistical and Artificial Intelligence (AI) techniques. All approaches utilise the OR/MS Today|s 2004 Decision Analysis Software Survey data. The paper concludes that the models produced using AI techniques, with 41 attributes each, show the most promise. The model-building approaches developed can be applied in analysing the software prices world-wide. Software designers and software purchasing managers will be able to evaluate the pricing decisions based upon the significant factors identified.

Keywords: software pricing; decision making software; artificial intelligence; AI; neural networks; pricing decisions; software marketing.

DOI: 10.1504/IJCAT.2006.010762

International Journal of Computer Applications in Technology, 2006 Vol.26 No.4, pp.175 - 181

Published online: 30 Aug 2006 *

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