A multivariate stochastic model to assess research performance (Articolo in rivista)

Type
Label
  • A multivariate stochastic model to assess research performance (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/s11192-014-1474-5 (literal)
Alternative label
  • Abramo G.; Costa C.; D'Angelo C.A. (2014)
    A multivariate stochastic model to assess research performance
    in Scientometrics (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Abramo G.; Costa C.; D'Angelo C.A. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84910070318&partnerID=q2rCbXpz (literal)
Rivista
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Laboratory for Studies of Research and Technology Transfer at the Institute for System Analysis and Computer Science (IASI-CNR), National Research Council of Italy, Rome, Italy; Consiglio per la Ricerca e la sperimentazione in Agricoltura (CRA), Unità di ricerca per l'Ingegneria Agraria, Rome, Italy; Department of Engineering and Management, University of Rome \"Tor Vergata\", Rome, Italy (literal)
Titolo
  • A multivariate stochastic model to assess research performance (literal)
Abstract
  • There is a worldwide trend towards application of bibliometric research evaluation, in support of the needs of policy makers and research administrators. However the assumptions and limitations of bibliometric measurements suggest a probabilistic rather than the traditional deterministic approach to the assessment of research performance. The aim of this work is to propose a multivariate stochastic model for measuring the performance of individual scientists and to compare the results of its application with those arising from a deterministic approach. The dataset of the analysis covers the scientific production indexed in Web of Science for the 2006-2010 period, of over 900 Italian academic scientists working in two distinct fields of the life sciences. (literal)
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