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Identifying and Prioritizing Sustainable Outsourcing Risk with Fuzzy Type II Data
(Case Study: National Company for Southern Oilfields)
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Bijan Pishejoo1   , Saber Molaalizadeh Zavardehi * 2, Allahkaram Salehi1 , Reza Tehrani3 |
1- Islamic Azad University, Masjed Soleiman
2- Islamic Azad University, Masjed Soleiman , saber.alizadeh@gmail.com
3- Tehran University |
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Abstract: (2023 Views) |
The purpose of this research is Identifying and Prioritizing Sustainable Outsourcing Risk with Fuzzy Type II Data in National Company for Southern Oilfields. This research was a Mix methodology and used qualitative and quantitative analytical processes to collect and analyze data. In the qualitative part, meta-analysis was first used to identify its components and themes to assess the risk of sustainable outsourcing. Based on Delphi analysis, an attempt was made to confirm the theoretical consensus on the components and themes of sustainable outsourcing risk assessment. In the quantitative part, based on fuzzy logic, type-2 fuzzy data analysis and FAHP algorithm were used. The target population in this study was academic experts as panel members in the quality department and managers of organizational levels of the National Company for Southern Oilfields in the quantitative department. The results in the qualitative part indicated the existence of 3 main components and 22 themes of sustainable outsourcing risk assessment. Also in the quantitative part of the results showed that the economic risk of sustainable outsourcing was the most important component and the lack of environmental standards in waste control was identified as the most important assessment theme in the National Company for Southern Oilfields.
JEL Classification: K32, N71, P18, Q4
Keywords: Sustainable Outsourcing Risk; Fuzzy Type II; National Company for Southern Oilfields
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| Keywords: Sustainable Outsourcing Risk, Fuzzy Type II, National Company for Southern Oilfields |
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Full-Text [PDF 1627 kb]
(902 Downloads)
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Type of Study: Thesis(PhD.) |
Subject:
مديريت ريسك
Received: 2021/11/2 | Accepted: 2022/02/6 | Published: 2022/05/31 | ePublished: 2022/05/31
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