Correspondence: Clarence Wardell III, School of Industrial and Systems Engineering, Tennenbaum Institute, Georgia Institute of Technology, 760 Spring Street NW, Atlanta GA 30332-0210, USA. Tel: +1 248 214 4048; Fax: +1 404 385 6127; E-mail: cwardell@isye.gatech.edu

¹Clarence L. Wardell III is a doctoral student in the School of Industrial and Systems Engineering at the Georgia Institute of Technology concentrating in economic decision analysis. At Georgia Tech he conducts research with the Tennenbaum Institute, which focuses on topics related to enterprise transformation. Working in conjunction with IBM Research he has presented his work at the INFORMS Revenue Management and Pricing Conference.

²Laura Wynter is a research scientist at IBM's Watson Research Center specialising on optimisation, network equilibrium, pricing and forecasting. Dr Wynter is actively working on projects related to transportation modelling and to financial revenue forecasting. She was previously a researcher at INRIA and the Université de Versailles, in France. Dr Wynter has published and presented her work in numerous journals and conferences.

³Mary Helander is an IBM research scientist specialising in applications of operations research to supply chains and software engineering. Dr Helander was previously an Associate Partner in IBM's Business Consulting Services, and a Research Fellow and faculty member at Linköping University, in Sweden. She has published in journals such as Networks, Transportation Science, Computers and O&R, and IEEE Transactions on Software Engineering.

Received 14 February 2008; Revised 14 February 2008; Published online 18 April 2008.

Abstract

The capacity and value-based pricing (CVBP) model for professional services was derived out of a need for a new way to think about how professional service 'products' should be priced in a competitive marketplace. Moving away from 'cost-plus' pricing, the CVBP model attempts to incorporate the 'stand-alone' value of a service, along with other variables, to arrive, systematically, at a set of improving prices. A multinomial logit model is used to model the discrete choice decision making. The model and its output can be used in negotiating services contracts, increasing profits, and smoothing demand.