Artikel

Risk assessment in PPP projects by applying different MCDM methods and comparative results analysis

Recently, risk assessment has become one of the most challenging issues in the areas of construction and public-private partnerships (PPPs). To address risk assessment issues, various decision-making techniques have been proposed, each with its own specific disadvantages and advantages. This paper investigates step-wise weight assessment ratio analysis (SWARA), complex proportional assessment (COPRAS), fuzzy analytic network process (FANP), fuzzy analytic hierarchy process (FAHP), fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS), simple additive weighting (SAW) and evaluation based on distance from average solution (EDAS) in order to define how various multi-attribute decision-making (MADM) methods compare when used for risk assessment in PPP projects. For this study, 5 risk assessment criteria and 10 types of risk used in Iranian highway PPP projects were selected. Four suitability and applicability tests were used to measure agreement between the rankings derived from the MADM methods. Final results show that all techniques had approximately the same rankings of risk assessment, with the SWARA, COPRAS, and EDAS methods performing slightly better. The findings of this study will help the parties in PPP and construction projects to select the best risk assessment method.

Sprache
Englisch

Erschienen in
Journal: Administrative Sciences ; ISSN: 2076-3387 ; Volume: 8 ; Year: 2018 ; Issue: 4 ; Pages: 1-17 ; Basel: MDPI

Klassifikation
Öffentliche Verwaltung
Thema
risk assessment
SWARA
COPRAS
FANP
FAHP
FTOPSIS
SAW
EDAS
PPP project

Ereignis
Geistige Schöpfung
(wer)
Valipour, Alireza
Sarvari, Hadi
Tamošaitiene, Jolanta
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2018

DOI
doi:10.3390/admsci8040080
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Valipour, Alireza
  • Sarvari, Hadi
  • Tamošaitiene, Jolanta
  • MDPI

Entstanden

  • 2018

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