title: Leader identification in a research collaborative network
metadata.name: dc.contributor.author
metadata.value: Kazemi, Sajad
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2021-08-24T21:08:27Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2021-08-24T21:08:27Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2021-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Kazemi S. 2021. Leader identification in a research collaborative network. Vestnik of Saint Petersburg University. Management 20 (1): 58–85.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu08.2021.103
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/32914
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: There is considerable empirical evidence on the advantages of interorganizational research
  collaborative networks across societies and research institutes such as research and development
  (R&D) centers and universities. Identifying a leader in this contexts is important both theoretically
  for doing leadership studies, and practically for effective governmental funding allocation
  and private investments. Inconsistent definitions and non-homogeneous attributes with unidimensional
  measurement approaches such as subjective measuring of power or considering a
  central company as the leader made the previous efforts inefficient for identifying leaders in an
  interorganizational setting. This research aims to identify a leading organization among a set of
  homogenous R&D centers in a research collaborative network context through implementing the
  main leader’s attributes in different dimensions. The article presents a multidimensional common
  weight model based on the data envelopment analysis (DEA) approach in a parallel system
  with several operational dimensions each of which consumes a set of inputs (budget, lecturers,
  and students) to produce a set of outputs (scientific meetings and conferences, national and
  international papers). Centrality and visibility are two main leaders’ attributes combined with
  efficiency influence the contributions and outcomes of each collaborative network partner. It is
  demonstrated how the proposed model performs its high-efficiency score in the most influential
  R&D center named the “leader” among 47 R&D centers in medical universities in Iran. The
  comparative analysis of managerial results showed that reputation has a greater impact on leader
  identification than centrality. The results based on mathematical calculations showed a robust
  discriminating power for efficiency measurement of the proposed model.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Management;Volume 20; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: research collaborative network
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: leader
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: data envelopment analysis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: common weights
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: non-discretionary variables
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: efficiency
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: network centrality
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: reputation
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Leader identification in a research collaborative network
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 58-85.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/32914/1/58-85.pdf
resources.format: Adobe PDF
resources.size: 1,42 MB