Over the past fifteen years, a number of studies have examined the determinants of firm R&D spending. These studies, however, almost invariably focus on the role of firm or external ownership characteristics in predicting R&D spending while overlooking the attributes of the top managers involved in allocating corporate resources. In this study, we change that focus by empirically examining how R&D spending as compared to industry competitors varies at firms based on the characteristics of their CEOs. Using a sample of publicly traded firms, we find that CEO characteristics explain a significant proportion of the sample variance in firm R&D spending even when corporate strategy, ownership structure, and other firm-level attributes are controlled. In terms of individual CEO characteristics, we find that R&D spending is greater at firms where CEOs are younger, have greater wealth invested in firm stock and signifacant career experience in marketing and/or engineering/R&D. In contrast to existing theory, we find that the amount of a CEO's formal education had no significant association with R&D spending once a CEO has attained a college degree. However, significant R&D spending increases are found at firms where CEOs have advanced science-related degrees. From subgroup analyses, we further find that CEO effects on relative R&D spending increase with longer CEO tenure implying that CEOs, over time, may mold R&D spending to suit their own preferences. From these results, we make implications for both research on determinants of R&D spending and managerial practice.

Historically, commercial use of university research has been viewed in terms of spillovers. Recently, there has been a dramatic increase in technology transfer through licensing as universities attempt to appropriate the returns from faculty research. This change has prompted concerns regarding the source of this growth-specifically, whether it suggests a change in the nature of university research. We develop an intermediate input model to examine the extent to which the growth in licensing is due to the productivity of observable inputs or driven by a change in the propensity of faculty and administrators to engage in commercializing university research. We model licensing as a three-stage process, each involving multiple inputs. Nonparametric programming techniques are applied to survey data from 64 universities to calculate total factor productivity (TFP) growth in each stage. To examine the sources of TFP growth, the productivity analysis is augmented by survey evidence from businesses who license-in university inventions. Results suggest that increased licensing is due primarily to an increased willingness of faculty and administrators to license and increased business reliance on external R&D rather than a shift in faculty research.

New start-up companies, which are considered to be a vital ingredient in a successful economy, have a different objective than established companies: They want to maximise their chance of long-term survival. We examine the implications for their operating decisions of this different criterion by considering an abstraction of the inventory problem faced by a start-up manufacturing company. The problem is modelled under two criteria as a Markov decision process; the characteristics of the optimal policies under the two criteria are compared. It is shown that although the start-up company should be more conservative in its component purchasing strategy than if it were a well-established company, it should not be too conservative. Nor is its strategy monotone in the amount of capital it has available. The models are extended to allow for interest on investment and inflation.