Article ID: | iaor20032169 |
Country: | Netherlands |
Volume: | 37 |
Issue: | 1 |
Start Page Number: | 15 |
End Page Number: | 27 |
Publication Date: | Mar 2003 |
Journal: | Socio-Economic Planning Sciences |
Authors: | Heidenberger Kurt, Schillinger Alexander, Stummer Christian |
Keywords: | artificial intelligence: decision support, research |
The research and development (R&D) budgeting decision is crucial for at least two reasons: if too much is spent, short-term financial stability is at risk, while, if the budget is too small, long-term competitiveness is threatened. Nevertheless, many enterprises simply extrapolate the past without further reflection. This paper presents a computer-based dynamic stochastic simulation model that allows one to assess the impact of alternative R&D budgeting policies on corporate development. The core decisions to be evaluated concern timing and funding of investments in R&D. Our approach substantially expands earlier work by Brockhoff. In particular, it distinguishes between product and process innovation, considers market dynamics related to technical progress via a modifiable S-curve, integrates marketing, and takes into account essential financial aspects. As a result, our model is closer to reality than previous ones. A sample application with real company data illustrates its potential usage.