Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-27T15:11:24.755Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic investment strategies for a risky R and D project

Published online by Cambridge University Press:  14 July 2016

S. D. Deshmukh  and
S. D. Chikte
S. D. Deshmukh
Affiliation:
Northwestern University
S. D. Chikte
Affiliation:
Polytechnic Institute of New York
Get access Rights & Permissions [Opens in a new window]

Abstract

During the course of an R and D project, it is often meaningful and possible to evaluate its status, so that this information may be used for making better financing decisions over time. The project status changes stochastically due to the internal (technological) and the external (market) uncertainties, the former being partially controlled by expenditure of resources. In addition to the resource expenditure strategy, the manager must also decide when to terminate the project. Once the project is terminated, a terminal return is collected, whose value depends on the final project status. It is shown that the project should be terminated if the current status is either too low or too high to make further expenditure worthwhile. Otherwise, for an intermediate (promising) status of the project, an aggressive investment strategy is shown to be optimal. Thus, the model unifies the problems of optimally undertaking, financing and terminating an R and D project in face of various uncertainties.

Keywords

STOCHASTIC R AND D PROJECTSEMI-MARKOV DECISION PROCESSOPTIMAL RESOURCE ALLOCATIONOPTIMAL STOPPING
Type
Research Papers
Information
Journal of Applied Probability , Volume 14 , Issue 1 , March 1977 , pp. 144 - 152
Copyright
Copyright © Applied Probability Trust 1977 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Aldrich, C. and Morton, T. E. (1975) Optimal funding paths for a class of risky R and D projects. Management Sci. 21, 491–500.Google Scholar
[2] Davis, O. L. (1962) Some statistical considerations in the selection of research projects in the pharmaceutical industry. Appl. Statist. 2, 170–183.Google Scholar
[3] Gaver, D. P. and Srinivasan, V. (1972) Allocating resources between research and development: A macro analysis. Management Sci. 18, 492–501.Google Scholar
[4] Gittins, J. C. (1969) Optimal resource allocation in chemical research. Adv. Appl. Prob. 1, 238–270.CrossRefGoogle Scholar
[5] Gittins, J. C. (1972) Some problems of stochastic resource allocation. J. Appl. Prob. 9, 360–369.Google Scholar
[6] Gittins, J. C. (1974) Resource allocation in speculative chemical research. J. Appl. Prob. 11, 255–265.Google Scholar
[7] Hess, S. W. (1963) A dynamic programming approach to R and D budgeting and project selection. IRE Trans. Engineering Management EM-9, 170–178.Google Scholar
[8] Kamien, M. I. and Schwartz, N. L. (1971) Expenditure patterns for risky R and D projects. J. Appl. Prob. 8, 60–73.Google Scholar
[9] Kamien, M. I. and Schwartz, N. L. (1974) Risky R and D with rivalry. Ann. Econ. Soc. Measurement 3, 266–277.Google Scholar
[10] Laska, E., Meinser, M. and Siegel, C. (1972) Contributions to the theory of optimal resource allocation. J. Appl. Prob. 9, 337–359.CrossRefGoogle Scholar
[11] Lippman, S. A. (1975) On dynamic programming with unbounded rewards. Management Sci. 21, 1225–1233.CrossRefGoogle Scholar
[12] Lippman, S. A. (1976) Countable state continuous time dynamic programming with structure. Opns. Res. 24, 477–490.CrossRefGoogle Scholar
[13] Lucas, R. E. (1971) Optimal management of an R and D project. Management Sci. 17, A679–A697.Google Scholar
[14] Radner, R. and Rothschild, M. (1975) On the allocation of effort. J. Econ. Theory 10, 358–376.Google Scholar
[15] Scherer, F. M. (1967) Research and development resource allocation under rivalry. Quart. J. Econ. 81, 359–394.Google Scholar