Real option games with R&D and learning spillovers
AbstractWe 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Omega.
Volume (Year): 41 (2013)
Issue (Month): 2 ()
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Other versions of this item:
- Martzoukos, Spiros H & Zacharias, Eleftherios, 2008. "Real Option Games with R&D and Learning Spillovers," MPRA Paper 12686, University Library of Munich, Germany.
- 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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