Innovation and learning performance implications of free revealing and knowledge brokering in competing communities: insights from the Netflix Prize challenge

Firms increasingly use open competitions to extend their innovation process and access new diverse knowledge. The Netflix Prize case we study in this paper is a multi-stage repeat-submission open competition involving the creation of new knowledge from across knowledge domains, a process which benefits from knowledge sharing across competing communities. The extant literature says little about the effects of different types and levels of knowledge sharing behavior on the learning and innovation outcomes of such a competitive system, or what the performance boundaries may be for the system as a result of such differences. Our research explores those boundaries unveiling important tradeoffs involving free revealing behavior-defined as voluntarily giving away codified knowledge and making it into a 'public good'aEuro"and knowledge brokering behavior-defined as using knowledge from one domain to innovate in another-on the learning performance of competing communities. The results, analyzing the system-level average and volatility of learning outcomes, lead to three conclusions: (i) greater knowledge sharing, as portrayed by greater free revealing and knowledge brokering, helps achieve better average learning for the system as a whole, however, (ii) achieving the best overall outcome possible from the system actually requires controlling the amount of knowledge brokering activity in the system. The results further suggest that (iii) it should not be possible to simultaneously achieve both the best overall outcome from the system and the best average learning for the system. The tradeoffs that ensue from these findings have important implications for innovation policy and management. This research contributes to practice by showing how it is possible to achieve different learning performance outcomes by managing the types and levels of knowledge sharing in open competitive systems.

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 sources of process innovation in user firms

Marcellus Bogers

Previous research has shown that innovation can have various sources and different forms. Innovation can thus be developed by different types of organizations or individuals for several reasons, and it can be related to product or process technologies. One particular stream of research has explored the role of users as a source of innovation. Examples of user innovations can be found in a variety of fields and settings such as mountain biking, snowboarding, open source software, scientific instruments, oil refining, semiconductor manufacturing, and even the World Wide Web. What these innovations have in common is that they were all initially developed by people or organizations that wanted to solve a specific need and benefited from using their innovation rather than selling it. A particular type of user innovator is a "user firm" which develops new or improved production technology for its own internal use. Such process innovation is characterized by determinants and outcomes, which are fundamentally different from for example product innovation. In particular, process innovation may be driven by learning-by-doing, which is a form of problem-solving or experimentation that takes place on the production floor rather than in research and development (R&D). However, the exact drivers and consequences of process innovation in general and learning-by-doing in particular are not yet fully explored. Therefore, the objective of this thesis is to increase the understanding of the antecedents and impact of process innovation in user firms by exploring the role of non-R&D activities and learning-by-doing. This thesis consists of four parts. Each of them addresses a specific aspect related to the sources of process innovation in user firms. The first paper particularly argues that process innovation relies on different learning mechanisms than product innovation. Using data from the Swiss Innovation Survey of the Swiss Institute of Business Cycle Research (KOF) at ETH Zürich, the paper shows which are the external and internal knowledge sources (related to R&D, manufacturing and marketing) that lead to innovation. The second paper further investigates R&D and non-R&D activities as sources of innovation and develops two measures to quantify the magnitude of non-R&D innovation. The results show that a substantial part of the firms develop innovations without R&D and that non-R&D process innovation has a very large impact on the overall cost reductions in the Swiss economy. In order to better understand the sources and attributes of process innovation in user firms, a questionnaire was conducted in a sample of Swiss manufacturing firms. Based on the results, the third paper shows the pervasiveness of major and especially minor process innovation. It also explores the sources of process innovation within the firms and identifies the practices related to the accounting, protection, appropriation, and monitoring of process innovation, which are often of an informal nature. The fourth paper investigates in more detail how such practices drive learning-by-doing and process innovation. The findings firstly show which complementary systems of practices are implemented in user firms to promote the innovative contribution of production floor workers and secondly how these practices drive learning-by-doing for either major or minor process innovation.

EPFL2009

Three essays on the role of proximity in science and innovation

Stefano Horst Baruffaldi

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. [...]

EPFL2015