Real R&D options with time-to-learn and learning-by-doing

Abstract

We model R&D efforts to enhance the value of a product or technology before final development. Such efforts may be directed towards improving quality, adding new features, or adopting technological innovations. They are implemented as optional, costly and interacting control actions expected to enhance value but with uncertain outcome. We examine the interesting issues of the optimal timing of R&D, the impact of lags in the realization of the R&D outcome, and the choice between accelerated versus staged (sequential) R&D. These issues are also especially interesting since the history of decisions affects future decisions and the distributions of asset prices and induces path-dependency. We show that the existence of optional R&D efforts enhances the investment option value significantly. The impact of a dividend-like payout rate or of project volatility on optimal R&D decisions may be different with R&D timing flexibility than without. The attractiveness of sequential strategies is enhanced in the presence of learning-by-doing and decreasing marginal reversibility of capital effects.

Adoption of Innovation

“…From this perspective, real options is a learning and selection mechanism that enables firm to adopt changes. Continuous learning that is achieved from sequential investing is analogous to an internal 'learning-by-doing' mode (Koussis et al 2006). Moreover, in the high rapidly changing context, it will be more effective to engage in greater experimentation and prototyping with early testing of processes.…”

Value maximizing hurdle rates for R&D investment

“…Without diversity of business activity that large businesses often have, a greater proportion of shadow options expire unexercised. Current R&D has the attraction that it makes firms incrementally larger and better able to exploit shadow options with 'learning by doing' (Koussis, Martzoukos, and Trigeorgis 2007;Bergemann and Hege 1998;Grenadier and Weiss 1997;Childs and Triantis 1999). Third, past R&D success has a permanent effect on future R&D as internal management and external investors, including venture capital, acknowledge the franchise value of a track record for this success.…”

“…However, R&D is unlikely a solitary investment, and many firms consider 'continuous R&D' as a cornerstone of strategic planning and growth. There are many sequential investment features that the R&D literature uses to distinguish R&D from conventional investment: technology spillovers (Acs, Braunerhjelm, and Audretsch 2009), learning (Koussis, Martzoukos, and Trigeorgis 2007;Bergemann and Hege 1998;Grenadier and Weiss 1997;Childs and Triantis 1999), spawning (Kasanen 1993), follow-on investment success (Hopp 1987), wealth from failure (Banik and Westgren 2004), falling forward (McGrath 1999), staged investment (Bar-Ilan and Strange 1998; Roberts and Weitzman 1981;Weitzman, Whitney, and Rabin 1981;Pennings and Lint 1997), strategic timing (Smit and Trigeorgis 2006;Lint and Pennings 1999;Weeds 2002;Goel 1995;Miltersen and Schwartz 2004;De Liso and Filatrella 2008) and resolution of uncertainty (Kolbe, Morris, and Teisberg 1991;Lint and Pennings 1998). Given this reality, these features make solitary investment results unsuitable for R&D.…”

Rivalry and Uncertainty in Complementary Investments with Dynamic Market Sharing

“…The real options literature for monopoly markets neglects the effect of competition on firms' investment behavior, but it is very extensive and diverse in terms of practical applications (Martzoukos 2000;Smith 2005; Koussis et al 2007;Bastian-Pinto et al 2010;Franklin 2015;Chronopoulos and Siddiqui 2015;Farzan et al 2015). Smets (1993) initiated a new branch of literature, now named "real option game" models, which study firms' investment behavior considering uncertainty and (duopoly) competition (Dixit and Pindyck 1994, Ch.…”