UM Data Science Research Seminar
Fabiana Visentin, Mario Gonzalez Sauri, A joint seminar of Institute of Data Science (UM) and UNU-MERIT
The UM Data Science Research Seminar Series are monthly sessions organised by the Institute of Data Science, on behalf of the UM Data Science Community, in collaboration with different departments across UM with the aim to bring together data scientists from Maastricht University to discuss breakthroughs and research topics related to Data Science.
This event is free and open to everyone. Please register by 15 October.
Time: 12:00 - 12:30
Speaker: Fabiana Visentin
Abstract: Despite the high interest of scholars in identifying inventions that have a big technological impact, little attention has been devoted to investigating how (fast) novel technologies embodied in these inventions are re-used in follow-on inventions. We overcome this limitation by empirically identifying novel technologies and mapping their re-use trajectories. We identify novel technologies as those that originate from new combinations of existing technological functionalities and trace these new combinations in follow-on inventions. We map each trajectory as S-shaped, defining its take-off time and full technological impact. Using patent data, we identify the trajectories of 10,782 novel technologies.
In searching for the antecedent characteristics of the novel technologies shaping their trajectories, we find that more complex novel technologies combining for the first time technological functionalities with a stronger science-based nature generate trajectories with a higher technological impact, but a somewhat longer take-off time. In contrast, combining for the first time technological functionalities that are similar to each other and familiar to the inventors’ community have a shorter take-off time but a lower technological impact.
Time: 12:30 - 13:00
Speaker: Mario Gonzalez Sauri
Abstract: Prestige and mobility are important aspects of academic life that play a critical role during early-career. After PhD graduation, scholars have to compete for positions in the labour market. Unfortunately, many of them have few research products such that their inherent ability and skills remain mostly unobserved for hiring committees. Institutional prestige in this context is a key mechanism that signals the quality of candidates, and many studies have shown that a "good" affiliation can confer many opportunities for future career development. We know little, however, about how changes of scholar's institutional prestige during early-career relate to future academic performance.
In this paper, we use an algorithm to rank universities based on hiring networks in Mexico. We distinguish three groups of scholars that move Up, Down or Stay in the prestige hierarchy between PhD graduation and first job. After controlling for individual characteristics by matching scholars with equal training or the same first job institution, we find that scholars hired by their existing faculty sustain higher performance over their career in comparison to other groups. Interestingly, we find that scholars that move up the hierarchy exhibit, on average, lower academic performance than the other groups. We argue that the negative relation between upward ranking mobility and performance is related to the difficulties in changing research teams at an early-career stage and to the so-called "big-fish-small-pond" effect. We observe a high stratification of universities by prestige and a negative association between mobility and performance that can hinder the flows of knowledge throughout the science system.
About the speaker
Fabiana Visentin received her Ph.D. degree in Economics and Organisation from the Advanced School of Economics of Ca’ Foscari University in Venice, Italy. She was a Visiting Research Fellow at the University of Lugano, Lugano, Switzerland, and at the Goizueta Business School, Atlanta, USA. Before joining UNU-MERIT and Maastricht University, she worked as Senior Research Fellow at the Chair of Economics and Management of Innovation at Ecole Polytechnique Fédérale de Lausanne (EPFL), in Switzerland. Her research interests focus on the microeconomics of innovation and on the economics of science area. In these topics, her contributions have appeared in the American Sociological Review, Journal of Economic Behavior & Organization, Research Policy, IEEE Transactions on Engineering Management and PlosOne.
Mario Gonzalez Sauri applies econometric, bibliometric, network analysis and algorithms to study science systems, particularly in Latin America and Mexico. He is interested in the analysis of science dynamics for development and policymaking. His research focuses on estimating the impact of research collaboration and network structure on scientific productivity and impact. Furthermore, he studies how the stratification of universities by prestige affects the future career of scholars. His current research is centred on estimating the effect of foreign versus local PhD training and its effect on scientific achievement.
Date: 15 October 2020
Time: 12:00 - 13:00 CET