Project portfolio selection criteria in the oil & gas industry and a decision support tool based on fuzzy Multimoora

被引:1
|
作者
Er, Akin [1 ]
Ozkale, Celal [2 ]
Coskun, Safa Bozkurt [3 ]
机构
[1] Investments Dept, Project, TUPRAS Headquarters, Istanbul, Turkiye
[2] Kocaeli Univ, Dept Ind Engn, TR-41001 Kocaeli, Turkiye
[3] Kocaeli Univ, Dept Civil Engn, TR-41001 Kocaeli, Turkiye
关键词
Oil refinery projects; Project portfolio selection; Investment criteria; Multi-criteria decision making; Fuzzy Multimoora; Decision support tool; MAKING METHOD; OPTIMIZATION; UNCERTAINTY; TOPSIS; MOORA;
D O I
10.5267/j.jpm.2024.5.002
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Considering the acceleration in the development of alternative energy sources due to climate change and the net zero carbon commitments made in this direction, there are different assessments of how the capacity of the refining industry will change in the next two decades. Refinery companies are trying to adapt to altering conditions while also trying to determine their investment strategies. Project portfolio selection problem is one of the relevant issues to be considered in line with these changes. In this article, research has been undertaken to determine which criteria refinery companies take into consideration while selecting their project portfolios. Based on the identified criteria, it is also aimed to carry out a study that will guide sector practitioners in project selection. For this purpose, interviews were conducted with industry experts. The criteria were accredited by applying categorical content analysis to the data obtained and their importance weights were identified accordingly. The most deterministic criteria were abstracted from the findings and applied to a multi -criteria decision -making (MCDM) framework, namely fuzzy MULTIMOORA to suggest a decision support tool that ranks the projects against themselves. Some of the prominent outcomes of the study are also discussed, along with the previous studies and comparative results of the proposed decision support tool. (c) 2024 Growing Science Ltd. All rights reserved.
引用
收藏
页码:197 / 212
页数:16
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