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Evaluation of Criteria for the Implementation of High-Performance Computing (HPC) in Danube Region Countries Using Fuzzy PIPRECIA Method

Author

Listed:
  • Milovan Tomašević

    (Faculty of Information Studies in Novo Mesto, Ljubljanska cesta 31a, 8000 Novo Mesto, Slovenia)

  • Lucija Lapuh

    (Faculty of Information Studies in Novo Mesto, Ljubljanska cesta 31a, 8000 Novo Mesto, Slovenia)

  • Željko Stević

    (Faculty of Transport and Traffic Engineering, University of East Sarajevo, Vojvode Mišića 52, 74000 Doboj, Bosnia and Herzegovina)

  • Dragiša Stanujkić

    (Department of Management, Technical Faculty in Bor, University of Belgrade, Vojske Jugoslavije 12, 19210 Bor, Serbia)

  • Darjan Karabašević

    (Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, Serbia)

Abstract

The use of computers with outstanding performance has become a real necessity in order to achieve greater efficiency and sustainability for the accomplishment of various tasks. Therefore, with the development of information technology and increasing dynamism in the business environment, it is expected that these computers will be more intensively deployed. In this paper, research was conducted in Danube region countries: Austria, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Germany, Hungary, Moldova, Montenegro, Romania, Serbia, Slovakia, Slovenia, and Ukraine. The aim of the research was to determine what criteria are most significant for the introduction of high-performance computing and the real situation in each of the countries. In addition, the aim was to establish the infrastructure needed to implement such a system. In order to determine the partial significance of each criterion and thus the possibility of implementing high-performance computing, a multi-criteria model in a fuzzy environment was applied. The weights of criteria and their rankings were performed using the Fuzzy PIvot Pairwise RElative Criteria Importance Assessment—fuzzy PIPRECIA method. The results indicate different values depend on decision-makers (DMs) in the countries. Spearman’s and Pearson’s correlation coefficients were calculated to verify the results obtained.

Suggested Citation

  • Milovan Tomašević & Lucija Lapuh & Željko Stević & Dragiša Stanujkić & Darjan Karabašević, 2020. "Evaluation of Criteria for the Implementation of High-Performance Computing (HPC) in Danube Region Countries Using Fuzzy PIPRECIA Method," Sustainability, MDPI, vol. 12(7), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:3017-:d:343446
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    Cited by:

    1. Željko STEVIĆ & Dajana NUNIĆ & Ibrahim BADI & Darjan KARABAŠEVIĆ, 2022. "Evaluation of dimensions of SERVQUAL model for determining quality of processes in reverse logistics using a Delphi – Fuzzy PIPRECIA model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 139-159, April.

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