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Real option games with R&D and learning spillovers

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  • Martzoukos, Spiros H.
  • Zacharias, Eleftherios

Abstract

We demonstrate to decision makers how to optimally make costly strategic pre-investment R&D decisions in the presence of spillover effects in an option pricing framework with analytic tractability. Decisions are modeled as impulse-type controls with random outcome. Two firms face two decisions that are solved interdependently in a two-stage game. The first-stage decision is: What is the optimal level of coordination (optimal policy/technology choice)? The second-stage decision is: What is the optimal effort for a given level of the spillover effects and the cost of information acquisition? The framework is extended to a two-period closed-loop stochastic game with (path-dependency inducing) switching costs that make strategy revisions harder. When conditions of learning-by-doing exist, we find that strategy shifts are easier to observe in market environments of high growth and high volatility.

Suggested Citation

  • Martzoukos, Spiros H. & Zacharias, Eleftherios, 2013. "Real option games with R&D and learning spillovers," Omega, Elsevier, vol. 41(2), pages 236-249.
    • Handle: RePEc:eee:jomega:v:41:y:2013:i:2:p:236-249
    DOI: 10.1016/j.omega.2012.05.005
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    More about this item

    Keywords

    Cost benefit analysis; Real options; Game theory; R&D;
    All these keywords.

    JEL classification:

    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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