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European Journal of Operational ResearchVolume 284, Issue 3, 1 August 2020, Pages 1154-1166

Multiple criteria decision aiding as a prediction tool for migration potential of regions(Article)

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  • aDepartment of Economics and Business, University of Catania, Catania, Italy
  • bUniversity of Belgrade – Faculty of Economics, Belgrade, Serbia

Abstract

This study presents the potential of multiple criteria decision aiding (MCDA) as a tool for prediction analysis. We apply MCDA methodology for the determination of internal migration potential of regions within a country. The ELECTRE Tri-C together with the Multiple Criteria Hierarchy Process (MCHP), the imprecise SRF method and the Stochastic Multicriteria Acceptability Analysis (SMAA) will be applied to investigate the case of the internal migrations in Serbia. We shall give recommendations regarding the migration potential of Serbian municipalities in the following years. In particular, the ELECTRE Tri-C will be applied to classify the regions in four classes ordered with respect to regions’ migration potential, MCHP will be used to take into account the hierarchical structure of criteria on which the municipalities are evaluated. Finally, the imprecise SRF method, as well as the SMAA methodology, will be used to take into account the preferences of numerous economic agents. © 2020 Elsevier B.V.

Author keywords

ELECTRE Tri-CInternal migrationMultiple criteria decision aidingMultiple Criteria Hierarchy ProcessRobustness concerns

Indexed keywords

Engineering controlled terms:Stochastic systems
Engineering uncontrolled termsEconomic agentsELECTRE TRIHierarchical structuresInternal migrationMultiple Criteria Decision AidingMultiple criteria hierarchy processPrediction toolsStochastic multicriteria acceptability analyses (SMAA)
Engineering main heading:Decision support systems

Funding details

Funding sponsor Funding number Acronym
Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja179005,179065MPNTR

  • 1

    Salvatore Corrente wishes to acknowledge the funding by the research project “Data analytics for entrepreneurial ecosystems, sustainable development and well-being indices” of the Department of Economics and Business of the University of Catania. This work was supported by the Ministry of Education and Science of the Republic of Serbia, under Grant numbers 179005 and 179065.

  • ISSN: 03772217
  • CODEN: EJORD
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1016/j.ejor.2020.01.046
  • Document Type: Article
  • Publisher: Elsevier B.V.

  Stamenković, M.; University of Belgrade – Faculty of Economics, Belgrade, Serbia;
© Copyright 2020 Elsevier B.V., All rights reserved.

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