Contributions published at Performance Management

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We observe the eects of ICT solutions, categorised by digital resource, on Swiss companies' performance. Using several methods to regress on revenue, productivity and innovation, we nd that the industry sector strongly denes the adoption of specic digital resources in companies, as well as the employees predisposition to ICT. Process-related digital resources have the most signicant positive in uence throughout all dependent variables. We nd security resources to be highly correlated with process ICT solutions due to the high sensitivity of data within them. Communication tools enable companies to further their innovation development and the sale of new or improved products. Cloud computing, still at an early stage of adoption within the business world, does not yield any signicant results. An element of complementarity is found within companies that cumulate several ICT solutions, although the marginal positive eect diminishes in a concave quadratic production function for revenue and productivity.

The economic return to public and private R&D is of enormous interest to academics and policy makers. First, private returns to R&D appear to be large and larger than the returns to alternative investments. Second, private R&D and R&D subsidies are positively correlated and there is no evidence for crowding out effects. Third, R&D cooperation increases private R&D. Fourth, there appear to exist complementarities between alternative sources of funding. Fifth, the mobility of R&D workers, particularly of university scientists is positively related to an increase in innovation. Sixth, there are many university spinoffs but these are no more successful than non-university spinoffs. Seventh, scientists with a migration background outperform domestic ones. Eights, universities constitute important collaboration partners. Ninth, clusters enhance collaboration, patents and productivity. A problem for economic policy is that little is known about the optimal design of policy measures since most studies analyze a single policy measure only.

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This study investigates the impact and effectiveness of a public R&D support policy. In a policy design that aims at incentivizing radical as well as incremental innovations, we test where the policy impact is highest. While the privately motivated R&D expenditures are significant for both types of innovation, the policy-induced part is significant only for radical innovation. Furthermore, given that the funding agency encourages collaboration, and particularly industry-science collaboration, we further test whether effects are enhanced in collaborating firms. We do not find any evidence pointing to increased effects for the latter.

This study focuses on how firms form and sequentially adapt their inter organizational knowledge sourcing structures within research and development (R&D) alliances and how this process impacts their innovation performance. In contrast to the previous literature that mainly ignores the dynamic aspects of how firms adapt their search strategies, our approach accounts for sequential adaptation. Our proposed framework explores the role of simultaneous diversification and sequential adaptation of collaboration partners within R&D alliances according to specific innovation outcomes. The results emphasize that firms should not remain within the same search activities indefinitely, as non-adapting interorganizational knowledge transfer structures lead to inferior performance. Notably, this study highlights important partner-type selectivity and identifies appropriate simultaneous diversification and sequential adaptation strategies in relation to specific innovation outcomes and firm sizes.

The growing complexity of the problems faced by managers and policy makers means that new, accessible methods for finding accurate and effective policy solutions are required. System dynamics (SD) has proven useful in effectively handling a complex environment. Nevertheless, an extensive quantitative analysis is often not an option for those managers who lack the necessary time. Furthermore, a purely qualitative analysis is very limited in terms of its expressiveness. The semi-quantitative system dynamics approach elaborated by Beck, Schenker-Wicki, and Schoenenberger (2015) tries to build a middle ground be-tween a too restrained qualitative and a too intensive quantitative analysis. The methodolo-gy is especially designed for practical usage in a fast changing and complex organizational environment. In this paper, this new semi-quantitative SD method has been compared with classic quantitative SD on the basis of three established and well-known models: the basic maintenance model (Thun, 2006), the simplified inventory-workforce model (Saleh et al., 2010), and the dynamic world model (Forrester, 1971). Especially in small and medium-size models, the semi-quantitative system dynamics method has proven to be an effective policy-finding tool that enables a fast and accurate detection of potential levers. By helping both inexperienced and experienced users to improve their policy-finding processes this novel approach can be seen as complementary to classic system dynamics analysis. Furthermore, in smaller settings, the methodology was able to arrive at the same policy rec-ommendations as those generated by a complete quantitative analysis and might therefore be used as a stand-alone tool when the cost and risks of the implementation are manageable.

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This thesis examines how diversity in R&D cooperation partners affects the innovation performance of research- and development-oriented firms, as measured by each firm’s sales share of innovative products. To address this question, a large-scale sample of firm-level microdata from six waves (1999, 2002, 2005, 2008, 2011 and 2013) of the Swiss innovation survey is examined using a heteroscedastic-robust Tobit subsample regression method. Results suggest that diversity positively affects the innovation performance of both firm types, but that the effects are strongest for research-oriented firms. In line with theoretical predictions, a clear inverted U-shaped relationship between partner diversity and innovation performance is detected only for development-oriented firms and differences in effects are most pronounced for new-to-the-market innovations. In light of these results and further findings on the output effects of various partner combinations, the thesis stresses the importance of partner diversity for research-oriented firms and (vertical) partner selectivity for development-oriented firms.

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This study investigates the efficacy of public R&D support. Compared to most existing studies, we do not stop at substitution effects or general innovation outcome measures, but we are interested in knowing where the policy effect is highest: on innovation close to the market (i.e. incremental innovation) or on innovation that is still far from the market and hence more risky and radical. Using firm level data from the period 1999 to 2011, we find that the policy hits where the market failure is highest, that is, for radical innovation. Taking into account that the Swiss funding agency encourages collaboration, we find no evidence that the impact of the policy is positively effected by various R&D collaboration patterns.

This study focuses on the effectiveness of sequential adaption of diversification strategies of R&D collaboration to improve firms’ innovation performance. While accounting for the firm’s initial simultaneous collaboration pattern, we investigate if certain sequential adaption strategies of firms’ collaboration patterns are more beneficial to achieve specific innovation objectives. Our panel data analysis method uses firm level data from five waves of the Swiss innovation survey covering a period from 1999 to 2011. Our analysis confirms the results of previous empirical studies regarding simultaneous R&D collaboration, though our findings shed light on the importance of sequential adaption of firms’ collaboration strategies, and indicate a careful selection of partner types in line with the firm’s needs and objectives.

This study investigates the efficacy of public R&D support. Compared to most existing studies, we do not stop at substitution effects or general innovation outcome measures, but we are interested in knowing where the policy effect is highest: on innovation close to the market (i.e. incremental innovation) or on innovation that is still far from the market and hence more risky and radical. Using firm level data from the period 1999 to 2011, we find that the policy hits where the market failure is highest, that is, for radical innovation. Taking into account that the Swiss funding agency encourages collaboration, we find no evidence that the impact of the policy is positively effected by various R&D collaboration patterns.