Three essays on the role of proximity in science and innovation

This thesis proposes three studies that provide novel empirical evidence on how different types of proximity can affect innovation and science activities through various mechanisms and in different contexts. In the first study (second chapter of this thesis), in collaboration with Julio Raffo, we analyze the relationship between geography and the likelihood of duplication in inventive activities. We argue that the uneven diffusion of knowledge means that the duplication of inventions will not be randomly distributed geographically and over time. First, as knowledge diffuses over time and competitive incentives decrease, the probability of a claimed invention duplicating an existing one will decrease in the time distance between the two. Second, for recent and upcoming inventions, competitive incentives are high, and localized knowledge flows increase the probability of duplication. Therefore, over a brief time period, the probability of duplication decreases with geographic distance. Conversely, the duplication of less recent inventions is more likely to occur at long distances as a consequence of less awareness of a technology existing due to missing knowledge flows. We test our hypotheses on European Patent Office (EPO) patent bibliographical data on patent citation categories. Geographic distance matters significantly less in sectors in which patents are known to be more effective as a source of information such as discrete technologies. In the second study (third chapter), in collaboration with Annamaria Conti and Fabiana Visentin, we investigate the effects of professorsâ social proximity with external universities on the level of productivity of PhD students hired from these universities. Researchers hired from external environments tend to have high scientific productivity compared to those who completed their studies in the same institution where they are employed. In a population of 4,666 PhD students, we further study the scientific productivity of external students from professorsâ networks, defined as students with a master's degree from a different university from that of their PhD, and also from a university with which their supervisors' co-authors are affiliated. We find that these students are significantly more productive, both compared to other students with a master's degree from a different university, and to students with a master's degree from the same university as that of their PhD. In our analyses, we control for the heterogeneity of supervisors and the heterogeneity of institutions where the students obtained their master's degrees, including proxies for the specific relevance of these universities for a given supervisor. Thus, we conclude that professors hire students with higher scientific productivity from universities where their co-authors are affiliated. Additional analyses further suggest that the reduction of information asymmetries is the main mechanism to explain this finding. In the third study (fourth chapter), in collaboration with Guillaume Burghouwt, we investigate the role of interregional knowledge integration as a driver of firm innovative performance. We adopt an unbalanced panel of 3,871 innovative companies in Germany between 1992 and 2010, for a total of 15,819 observations, and we study their innovative productivity. [...]

Institutions and Incentives in Knowledge Production and Diffusion: From Science to Innovation

Charles Chadi Ayoubi

This thesis presents four essays providing novel empirical and theoretical insights on the incentives and institutional structures that favor knowledge production and diffusion. The first two studies analyze these processes in the realm of scientific research, while the last two essays evaluate broader applications with vast social welfare implications. The first essay (chapter 2) of this dissertation, in collaboration with Michele Pezzoni and Fabiana Visentin, exploits a dataset on all applicants to a prestigious Swiss grant to explore a central process in academic life: the application for funds. The results suggest that scientists applying to a grant significantly increase their publicationsâ quality and quantity, learn more, and extend their collaboration network. Beyond the effect of applying, receiving the research funds increases the probability of co-authoring with co-applicants, but it does not have any additional effect on other scientific outcomes. These results justified the title of the chapter since, as it is the case in the Olympics, in research grants, âthe important thing is not to win, it is to take part.â The second essay (chapter 3), also in collaboration with Michele Pezzoni and Fabiana Visentin, uses the same empirical context to explore the determinants of knowledge flows among collaborating scientists. The chapter proposes a novel methodology based on journal references to track knowledge flows among researchers working together. The results suggest that geographical distance does not significantly affect the knowledge flows between team members, but the cognitive distance separating two members does. More specifically, there is an inverted U-curve effect of cognitive distance on the learning among team members: the higher the distance between two scientists in terms of subjects studied, the more they exchange knowledge, up to the point when the distance becomes detrimental because they have too little common ground to communicate. The third essay (chapter 4), in collaboration with Boris Thurm, goes beyond the exploration of the determinants for scientistsâ knowledge production and diffusion to delve into the incentives of all individuals to exchange knowledge. The chapter has two major contributions. First, it acts as a literature review of the empirical evidence on non-financial incentives for knowledge diffusion, such as social recognition, career prospects, and moral considerations. Second, the chapter proposes a simple economic model with heterogeneous agents holding both selfish and moral motives to derive some novel policy implications. The last essay (chapter 5), in collaboration with Dominique Foray, delves into a specific case of knowledge diffusion, the integration of machine learning technologies in healthcare. The analysis suggests that machine learning has the potential for spurring innovation in healthcare but faces several institutional levers. Collecting quantitative data on patents and publications, and qualitative data on hospitals, the results show that machine learning affects healthcare in different ways than older information and communication technologies. The apparition of new business models encourages tech giants to enter the healthcare sector. These patterns have the potential to increase social welfare by reducing externalities in terms of innovation complementarities, but they pose new challenges such as competition policy and human capital formation.

EPFL2020

The geography of duplicated inventions: evidence from patent citations

Stefano Horst Baruffaldi, Julio Diego Salvador Raffo

The geography of duplicated inventions: evidence from patent citations. Regional Studies. Innovators often claim inventions that turn out to duplicate, at least in part, existing ones. This paper advances the claim that for recent and upcoming inventions, competitive incentives are high, and localized knowledge flows increase the probability of duplication. Therefore, over a brief period of time the probability of duplication is higher at short geographical distance. Conversely, the duplication of less recent inventions is more likely at long distance as a consequence of a lower awareness of the existence of a technology. This claim is supported by coherent descriptive and multivariate evidence using data on patent citation categories from the European Patent Office (EPO).

Routledge Journals, Taylor & Francis Ltd2017

Corporate Science and Voluntary Disclosure

Markus Simeth

The dissertation investigates the phenomenon of firms that make voluntary contributions to the stock of scientific knowledge. Such a firm behaviour appears counterintuitive from a traditional viewpoint, since no direct financial returns can be expected while the disclosure of research outcomes may lead to knowledge spillovers to competing firms. This raises the questions why firms engage in those boundary-spanning activities, how scientific disclosure strategies are implemented, and to what extent scientific disclosure strategies affect the firm performance. The dissertation provides empirical evidence on these questions using representative firm-level data and econometric analysis techniques. The first chapter of the dissertation reviews the relevant literature, underlines the relevance of doing research on this topic by providing descriptive evidence on the amounts of scientific contributions by firms, and includes some novel insights from interviews which I conducted at several large R&D performing firms. I discuss the potential benefits, costs and organizational challenges of scientific disclosure strategies and position scientific publications as an expression of openness in the light of alternative openness definitions prevalent in innovation research. The second chapter focuses on the question why firms publish in scientific journals using a cost-benefit framework. In particular, I analyse whether scientific contributions of firms are used as an instrument to get access to academic knowledge networks. Moreover, I explore environmental conditions by considering the effectiveness of appropriation instruments and the spillover levels in a sector that may impact the firms’ decision-making process. The analysis relies on data from the French Innovation survey and provides evidence for the predictions that firms show reciprocal behaviour in exchange of obtaining valuable academic knowledge. However, the propensity of firms to publish is rather sensitive to the spillover threats. The third chapter examines how are firms able to publish by testing the requirements and origins of scientific contributions by firms. I explicitly consider the heterogeneity of scientific outputs and provide a complementary view on the requirements for the creation of inventive outcomes. The requirements considered can be classified according to the research orientation and the demographic composition of the R&D labs. The analysis revealed that scientific disclosure strategies require specific resource allocations and capabilities, which are in part not necessary for the generation of inventive outcomes. The findings support the view that disclosure strategies can be costly and are not only a by-product of the “usual” R&D activities. The fourth chapter addresses the performance effects of scientific activities of firms. More specifically, I examine whether scientific publications stocks provide valuable information to the financial markets, potentially leading to different valuations. I consider the heterogeneity of scientific and inventive outcomes and found evidence for a positive impact of scientific contributions on the firm’s Tobin’s Q beyond the effects of R&D stocks, patent stocks and patent quality.