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Optimal Funding Paths for a Class of Risky R&D Projects

Author

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  • Carole Aldrich

    (Graduate School of Business Administration, Duke University)

  • Thomas E. Morton

    (Graduate School of Business, University of Chicago)

Abstract

The problem of financing risky R&D projects over time has been stated as an optimal control problem by Hess [Hess, S. W. 1962. A dynamic approach to R&D budgeting and project selection. IRE Transactions on Engineering Management EM-9 (December) 170-178.], Lucas [Lucas, Robert E. 1971. Optimal management of a research and development project. Management Sci. 17 (11, July) 679-697.], and Kamien and Schwartz [Kamien, M. I., N. L. Schwartz. 1971. Expenditure patterns for risky R&D projects. J. Appl. Probab. VIII (1, March) 60-72.]. In this paper, the model is extended to allow the possibility of time dependent returns. The authors restate the problem as a finite horizon continuous time dynamic programming problem, and demonstrate uniform convergence to a unique, autonomous (infinite horizon) solution for the present value of the project and optimal spending rate as a function of expended effort. Further conclusions are shown for the time dependent model with exponential completion probability and for the time independent model.

Suggested Citation

  • Carole Aldrich & Thomas E. Morton, 1975. "Optimal Funding Paths for a Class of Risky R&D Projects," Management Science, INFORMS, vol. 21(5), pages 491-500, January.
    • Handle: RePEc:inm:ormnsc:v:21:y:1975:i:5:p:491-500
    DOI: 10.1287/mnsc.21.5.491
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    Cited by:

    1. A. Messica & A. Mehrez & I. David, 2000. "Optimal Expenditure Patterns of a Double-Path Engineering Project," Journal of Optimization Theory and Applications, Springer, vol. 105(2), pages 441-455, May.
    2. S. D. Deshmukh & S. D. Chikte, 1976. "Stochastic Evolution and Control of an Economic Activity," Discussion Papers 197, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    3. Heidenberger, Kurt, 1996. "Dynamic project selection and funding under risk: A decision tree based MILP approach," European Journal of Operational Research, Elsevier, vol. 95(2), pages 284-298, December.
    4. Mehrez, Abraham & Justman, Moshe, 2001. "On the efficiency of the parallel path R&D approach: a stochastic game analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 57(1), pages 19-28.
    5. Scott A. Shane & Karl T. Ulrich, 2004. "50th Anniversary Article: Technological Innovation, Product Development, and Entrepreneurship in Management Science," Management Science, INFORMS, vol. 50(2), pages 133-144, February.
    6. S. D. Deshmukh & S. D. Chikte, 1976. "Dynamic Investment Strategies for a Risky R&D Project," Discussion Papers 198, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    7. S.D. Deshmukh & S.D.Chikte, 1975. "Optimal Stochastic Development Strategy," Discussion Papers 159, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    8. Supachart Iamratanakul, 2013. "The Selection of Project in Rapid Environment’s Industry Using Zero Based Budget," Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management,, ToKnowPress.
    9. Justman, Moshe, 2004. "Transitional dynamics of output, wages and profits in innovation-led growth: a general equilibrium analysis," Structural Change and Economic Dynamics, Elsevier, vol. 15(2), pages 183-205, June.

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