Sustainable Partner Selection in Collaborative Networked Organisations

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Serval ID
serval:BIB_C52AA6BEB5C0
Type
Unpublished: a document having an author and title, but not formally published.
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Publications
Institution
Title
Sustainable Partner Selection in Collaborative Networked Organisations
Author(s)
Badulescu Yvonne, Soltan Ezzeddine, Hameri Ari-Pekka, Cheikhrouhou Naoufel
Language
english
Number of pages
16
Notes
Structured Abstract
Purpose: Collaborative Networked Organisations (CNO) are a means of ensuring longevity and business continuity in the face of a global crisis such as COVID-19. This paper presents a multicriteria decision making method for sustainable partner selection based on the three sustainability pillars and Risk.
Design/methodology/approach: A combined Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach to evaluate and rank potential partners based on known conditions and predicted conditions at a future time based on uncertainty to support sustainable partner selection.
Findings: It is integral to include Risk criteria as an addition to the three Sustainability pillars: economic, environmental, and social, to build a robust and sustainable CNO. One must combine the AHP and Fuzzy-AHP weightings to ensure the most appropriate sustainable partner selection for the current as well as predicted future period.
Originality: The paper presents a novel approach to the partner selection process for a sustainable CNO under current known conditions and future uncertain conditions, highlighting the risk of a force majeure occurring such as COVID.
Research implications: The approach proposed in the paper is intended to support existing CNO, as well as individual firms wanting to create a CNO, to build a more robust and sustainable partner selection process in the context of a force majeure such as COVID-19.
Keywords
Fuzzy AHP, Partner selection, CNO, Sustainability, TOPSIS, Group decision making
Funding(s)
Swiss National Science Foundation / Programmes / 100018_176349
Create date
08/10/2021 13:45
Last modification date
26/05/2022 6:36
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