Greek chemical engineers. Are they static or mobile? Evidence from the national archive of PhD theses
| DOI | https://doi.org/10.1108/CC-06-2020-0017 |
| Published date | 04 November 2020 |
| Date | 04 November 2020 |
| Pages | 87-96 |
| Subject Matter | Library & information science,Collection building & management |
| Author | Evi Sachini,Konstantinos Sioumalas-Christodoulou,Charalampos Chrysomallidis,Galatios Siganos,Nikolaos Karampekios |
Greek chemical engineers. Are they static or
mobile? Evidence from the national archive of
PhD theses
Evi Sachini, Konstantinos Sioumalas-Christodoulou, Charalampos Chrysomallidis, Galatios Siganos and
Nikolaos Karampekios
National Documentation Centre, Athens, Greece
Abstract
Purpose –The purpose of this paper is to identify the geographical location of researchers.
Design/methodology/approach –Combine standard bibliometric databases with social media data.
Findings –The majority of the population of the sample (71.8%) –Greek chemical engineers –are static. A significant portion of the mobile
researchers (28.2%) returned to their country of origin (25.6%). Performing network analysis, the cluster of countries corresponding to the mobil e
category of researchers is identified and depicted.
Originality/value –Herein, this study introduce a new, national data set on doctorate holders that will allow multiple biblio metric analyses in the
future. Also, this study is among the few (Gendronneau et al., 2019) that combines standard bibliometric databases with social media data. In cases
where multiple affiliations per year pose a difficulty in understanding the geographical location of each individual, Linked In data were used. The
analysis sheds light on a field of science that is not extensively examined in terms of brain circulation. While similar publications focus on physician s
(i.e. cardiologists –Dyachenko and Mironenko, 2018), this paper focus on a subset of doctorate holders in engineering.
Keywords Greece, Mobility, Bibliometrics, Chemical engineers, PhD holders, Social data
Paper type Research paper
1. Introduction
The geographical mobility of the highly educated is a theme of
increased interest,as it gives rise to a number of considerations.
For example, in relation to the international flow of human
capital (Hunter, 2013) or to the realisationthat open countries
(as opposed to closed ones) have a strong science system
(Wagner and Jonkers,2017). This is associated with the finding
that scientistshave the most impact when they are free to move,
according to Sugimotoet al. (2017).
The theme is of interest not only for academic reasons but
also for policy ones, as domestic education considerations
consider this outward mobility a loss of national resources, as
migrated scientists eventuallywork in another, hosting country
that has probably not bear the cost of their education and
training (Cervantes and Guellec, 2002). Others view the
phenomenon as making countries lose a dynamic part of their
human capital such as young and talented scientists, that may
be regarded to be a prerequisite for society’s and economy’s
further development and growth (Martineauet al., 2004). This
is an argument worth considering especially in the case of
Greece, which onlyvery recently started bouncing back from an
extreme decline of macroeconomicindicators during the 2009–
2016 crisis that forced its educated workforce to emigrate
abroad (Labrianidis and Pratsinakis, 2014;Labrianidis, 2017).
To restore economic growth –a potential that has been just
scaled back due to the 2020 Covid-19 pandemic –a country
needs all the help it can get from its educated science diaspora.
While luring them back is unfounded, as top-notch positions
are highly paid globallyand go against the intrinsic nature of the
scientific endeavour that gives a premium to mobility and
network creation, establishing a digitally-enabled, knowledge-
and/or entrepreneurial-based relations is a potential middle
ground (Labrianidis et al., 2019). Especially, as the majority of
scientists do not sever tieswith their homeland but may build a
chain of affiliations, benefittingit, in an indirect way (Sugimoto
et al.,2017).
However, no analysis nor policy implementation is possible
without the mapping and identification of the highly educated
that would shed light on their geographical, knowledge, etc.,
mobility. Short of nation-wide, periodical censuses that probe
into the mobility of researchers and scientists, existing large
data sets on the outputs produced by those highly educated
stands as the main sources of understanding this mobility.
Analysis of the bibliometric output of these populations is
central to this identification process (Laudel, 2003;Moed and
Halevi, 2014;Robinson-Garcia, 2019). Tech-based data sets
such as patents and trademarks, as well as the exploitation of
the trove of data found in social media, stand as parallel
avenues.
The current issue and full text archiveof this journal is available on Emerald
Insight at: https://www.emerald.com/insight/2514-9326.htm
Collection and Curation
41/3 (2022) 87–96
© Emerald Publishing Limited [ISSN 2514-9326]
[DOI 10.1108/CC-06-2020-0017]
Received 12 June 2020
Revised 17 July 2020
Accepted 26 July 2020
87
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