Correspondence: Sameer Kumar, Opus College of Business, University of St Thomas, Mail no. TMH 343, 1000 LaSalle Avenue, Minneapolis, Minnesota 55403-2005, USA

¹is currently a professor of Decision Sciences and Qwest Endowed Chair in Global Communications and Technology Management in the Opus College of Business, University of St Thomas, Minneapolis, Minnesota. His major areas of research interests include optimisation concepts applied to various aspects of global supply chain management, revenue management, health-care applications, information systems, technology management, product and process innovation, and capital investment justifications.

²is an associate professor in Decision Sciences Department at the Opus College of Business, University of St Thomas. He has a PhD degree in Operations Research from the University of Minnesota, Minneapolis. He has taught for over 20 years in both graduate and undergraduate programs at the University of St Thomas, where he has been named Outstanding Professor in the Graduate School of Business. He has experience in the application of statistics and mathematics for management decision-making.

³has been an instructor for 15 years in the Quantitative Methods and Computer Science Department at St Thomas, and 14 years with the Graduate School of Business. Previously he taught at the University of Minnesota, 6 years with the School of Physics and 7 years with the School of Mathematics. He has a BS degree in Engineering Science (1975) from Illinois Institute of Technology, a Master of Mathematics (1977) from the University of Waterloo, Ontario.

Received 22 September 2008; Revised 22 September 2008; Published online 28 November 2008.

Abstract

This study proposes an integrated risk and revenue management decision model for a business venture, from both the entrepreneur's and venture capitalist's perspectives. The four-step methodology includes a creative step using mind-maps to crystallise ideas, a consideration of the forces that affect the goals of each, a decision tree of possibilities and a model-building process using at risk to assess economic and market feasibility. The decision support model enables the selection of an optimal product configuration for a new business venture using different methods of performing subjective evaluations of revenue and risk options.