Abstract
The theoretical literature on managing R&D pipeline is largely based on real
option theory, which has been the workhorse for assessing R&D projects and
making decisions about undertaking, continuing, or terminating projects. The
theory typically assumes that each project or causally related set of projects
is independent. Yet, casual observation suggests that this assumption is not
valid in many circumstances. For instance, firms expend much effort on
“managing” and “balancing” its R&D pipeline, where managing appears to be
related to the choice of R&D selection thresholds and balancing is related to
finding projects perhaps from different sources to fill the pipeline. Not only
do these rule appear to differ across firms, they also appear that they can vary
over time for the same firm. Such managing suggests there may be some type of
interdependency among R&D projects and that the choice of R&D selection rules is
a strategic decision. In this paper we develop a model using dynamic programming
techniques that explains why firms vary in their R&D project selection rules.
The novelty and value of our model derives from the central insight that some
firms invest in downstream co-specialized activities that would incur
substantial adjustment costs if R&D efforts are unsuccessful while other firms
have no such investment. If transaction costs in technology markets are
positive, which implies that accessing the market for projects is costly, these
investments lead to state-contingent project selection rules that create a
dynamic interdependency among R&D activities and product mix. The existence of a
dynamic interdependency fundamentally implies that a firm's current project
selection decision will affect future state conditions and future profit and
that the project selection prescription for assessing each project independently
is never correct. We describe how strategic management of the R&D pipeline
optimally changes in response to a variety of state conditions. We conclude that
our model can be extended to address several additional research questions
associated with R&D portfolio management, joint ventures, and mergers and
acquisitions.