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A Sequential Model of R&D Investment Over an Unbounded Time Horizon

Author

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  • Wallace J. Hopp

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60201)

Abstract

A Markov model of sequential R&D investment, where successful firms are assumed to have an advantage in related follow-on R&D, is formulated and a solution approach is given. Under this assumption, profit maximizing firms must consider the effect of R&D investments on their future market position as well as the direct monetary returns from innovation. Under certain conditions, free entry is shown to lead to excessive competition and overinvestment by the firms. This market failure can be corrected through a three-part policy of restricted patent lives, subsidies to firms for consecutive successes, and entry taxes. In addition to these policy conclusions, the modeling and solution approaches presented here provide a framework for further research efforts to incorporate market position into project selection and budget allocation models.

Suggested Citation

  • Wallace J. Hopp, 1987. "A Sequential Model of R&D Investment Over an Unbounded Time Horizon," Management Science, INFORMS, vol. 33(4), pages 500-508, April.
    • Handle: RePEc:inm:ormnsc:v:33:y:1987:i:4:p:500-508
    DOI: 10.1287/mnsc.33.4.500
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    Cited by:

    1. Johnston, Iain G., 2022. "Optimal strategies in the fighting fantasy gaming system: Influencing stochastic dynamics by gambling with limited resource," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1272-1281.
    2. A. Prinzie & D. Van Den Poel, 2003. "Investigating Purchasing Patterns for Financial Services using Markov, MTD and MTDg Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/213, Ghent University, Faculty of Economics and Business Administration.
    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. Boaz Golany & Moshe Kress & Michal Penn & Uriel G. Rothblum, 2012. "Resource allocation in an asymmetric technology race with temporary advantages," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(2), pages 128-145, March.
    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. A. Prinzie & D. Van Den Poel, 2005. "Incorporating sequential information into traditional classification models by using an element/position- sensitive SAM," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/292, Ghent University, Faculty of Economics and Business Administration.
    7. Pelin G. Canbolat & Boaz Golany & Inbal Mund & Uriel G. Rothblum, 2012. "A Stochastic Competitive R&D Race Where “Winner Takes All”," Operations Research, INFORMS, vol. 60(3), pages 700-715, June.
    8. Prinzie, Anita & Van den Poel, Dirk, 2006. "Investigating purchasing-sequence patterns for financial services using Markov, MTD and MTDg models," European Journal of Operational Research, Elsevier, vol. 170(3), pages 710-734, May.
    9. Suresh Chand & Vernon Ning Hsu & Suresh Sethi, 2002. "Forecast, Solution, and Rolling Horizons in Operations Management Problems: A Classified Bibliography," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 25-43, September.

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