What Do We Know of the Mobility of Research Scientists and of its Impact on Scientific Production

Fernández-Zubieta, Ana; Geuna, Aldo; Lawson, Cornelia

doi:10.2139/ssrn.2611203

Cited by 19 publications

(18 citation statements)

References 154 publications

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“…Among the less tangible factors, the literature on academic mobility has stressed: the individual's preference for adventure and intercultural exposure and a greater than average appetite for life change among academics (Lee & Kuzhabekova, 2018); the possibility of improving performance, visibility, and credibility through mobility and, also, the development of more fruitful patterns of collaboration (Fernandez-Zubieta, Geuna, & Lawson, 2015); the positive symbolic capital-a sort of prestige-associated with international mobility (Bauder et al, 2017); the opportunity to acquire social, cultural, and symbolic capital through the acquisition of new skills and competences, the creation of new networks, and gains in terms of reputation (aka "mobility capital"; Bauder et al, 2017); increased access to international research networks and funding (Cañibano, Otamendi, & Andújar, 2008); "intrinsic rewards": greater work satisfaction, particularly in relation to the working environment, the possibility of collaborating with "star scientists," the possibility of being funded, the freedom in choosing research topics (Pellens, 2012); the institutional framework that eases access to visas, residence permits, and even acquisition of citizenship (Bauder, Lujan, & Hannan, 2018;Komatsu & Staniscia, 2005).…”

Section: Academic Mobility Versus the Migration Of Academics: A Litmentioning

confidence: 99%

“Knowledge migrants” or “economic migrants”? Patterns of academic mobility and migration from Southern Europe to Mexico

Mendoza

Staniscia

Guitart

2019

Population Space and Place

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Because mobility has been described as a key element of the academic habitus and a well‐established norm in scientific life, people moving within academia have been generally considered to be “knowledge migrants” and “talent migrants.” Indeed, the literature rarely takes a labour market perspective when analysing academic mobility. However, Southern European academia is largely characterised by challenging working conditions, low wages, and a lack of fair competition for positons, all of which negatively affecting job prospects. Based on 25 in‐depth interviews, this paper explores the reasons behind the migration of a group of Spanish and Italian academics in Mexico with a view to bringing into focus the role of economic/labour and career‐related reasons in migration decisions. We find that their experiences fall along three main academic trajectories, which are distinguished by the stage in the participants' careers at which they decided to migrate and the channels by which they entered Mexican academia. Common to all three groups is the identification of the economic crisis and a lack of institutional support as strong motivating factors in their decision. Underlying this is the question of whether the studied group is best viewed as “knowledge”/“talent” migrants who have followed certain institutional channels or “economic migrants” who are somehow pushed to work abroad by the lack of good employment in their countries of origin. The paper also challenges mainstream ideas about academic mobility, in the sense that the literature has not considered the attractive power of universities/research centres located in the Global South.

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Section: Academic Mobility Versus the Migration Of Academics: A Litmentioning

confidence: 99%

“Knowledge migrants” or “economic migrants”? Patterns of academic mobility and migration from Southern Europe to Mexico

Mendoza

Staniscia

Guitart

2019

Population Space and Place

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“…There is an expanding literature on the mobility of scientists. Many works have been focusing on the relationship between movements and scientific impact (Scellato et al, 2017;Franzoni et al, 2014;Fernandez-Zubieta et al, 2015). Other works analyzed scientists mobility across countries to determine the effects of policy (Czaika and Parsons, 2017) and to investigate aspects of the brain circulation phenomenon (Bénassy and Brezis, 2013;Saxenian, 2005;Agrawal et al, 2011;Verginer and Riccaboni, 2018).…”

Section: Introductionmentioning

confidence: 99%

Reproducing Scientists’ Mobility: A Data-Driven Model

2018

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This paper makes two important contributions to understand the mobility patterns of scientists. First, by combining two large-scale data sets covering the publications of 3.5 mio scientists over 60 years, we are able to reveal the geographical "career paths" of scientists. Each path contains, on the individual level, information about the cities (resolved on real geographical space) and the time (in years) spent there. A statistical analysis gives empirical insights into the geographical distance scientists move for a new affiliation and their age when moving. From the individual career paths, we further reconstruct the world network of movements of scientists, where the nodes represent cities and the links in-and outflow of scientists between cities. We analyze the topological properties of this network with respect to degree distribution, local clustering coefficients, path lengths and assortativity. The second important contribution is an agent-based model that allows to reproduce the empirical findings, both on the level of scientists and of the network. The model considers that agents have a fitness and consider potential new locations if they allow to increase this fitness. Locations on the other hand rank agents against their fitness and consider them only if they still have a capacity for them. This leads to a matching problem which is solved algorithmically. Using empirical data to calibrate our model and to determine its initial conditions, we are able to validate the model against the measured distributions. This allows to interpret the model assumptions as microbased decision rules that explain the observed mobility patterns of scientists.

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“…Prior studies have focused mainly on academic employees within science and engineering, and we will expand the perspective by looking at academic careers within all fields of science. There has lately been a call for research on crosssector mobility, particularly how experience from sectors outside academe influences academic work (Fernandez-Zubieta et al, 2015). We contribute here by investigating in detail the possible effects of non-academic work experience among academics.…”

Section: Introductionmentioning

confidence: 99%

The effects of non-academic work experience on external interaction and research performance

Gulbrandsen

Thune

2017

J Technol Transf

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We ask whether academic employees with non-academic work experience differ from their colleagues with respect to interaction with external stakeholders and research performance. We use a science and technical human capital perspective and address the question through an analysis of 4,400 survey responses from academic employees in Norwegian universities and colleges. Non-academic work experience is common in all academic fields; it characterises more than half of the tenured academic staff members in Norway. Our analysis indicates that, in general, external interaction is positively influenced by non-academic work experience, in line with prior research. Contrary to expectations, we find few signs of a trade-off or a "punishment" effect of non-academic work experience on scientific productivity. Non-academic work experience is neither significantly related to publication productivity nor share of publications in highly ranked journals, but there are important differences based on the type of previous work experience.

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What Do We Know of the Mobility of Research Scientists and of its Impact on Scientific Production

Cited by 19 publications

References 154 publications

“Knowledge migrants” or “economic migrants”? Patterns of academic mobility and migration from Southern Europe to Mexico

“Knowledge migrants” or “economic migrants”? Patterns of academic mobility and migration from Southern Europe to Mexico

Reproducing Scientists’ Mobility: A Data-Driven Model

The effects of non-academic work experience on external interaction and research performance

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