Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/8447
Title: A New Fuzzy Risk Management Model for Production Supply Chain Economic and Social Sustainability
Authors: Durić G.
Todorovic G.
Đorđević, Aleksandar
Borota-Tisma A.
Issue Date: 2019
Abstract: © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. The issues of operational, organisational and process risk assessment in supply chains (SCs) are the most usually analysed, while other risk groups (like economic and social risks) are not taken into account, even though they have a critical effect on the competitive advantage and SCs sustainability over long time periods. The determination of risk value that may arise due to the materialisation of each defined risk factor (RF) is based on the assessment of the severity of RF consequences and frequency of RF occurrence. These judgments are obtained by decision makers and modelled by using fuzzy set theory. The relative importance of RFs are stated by fuzzy pair-wise comparison matrices in compliance with fuzzy analytical hierarchy process (FAHP). The risk level of SCs could be obtained in an exact way by applying fuzzy logic. The proposed model, to be presented in this paper, provides a possibility to easily and simply determine risk level from the automotive industry SC and to propose appropriate management initiatives that should lead to a reduction or elimination of RF influence.
URI: https://scidar.kg.ac.rs/handle/123456789/8447
Type: article
DOI: 10.1080/1331677X.2019.1638287
ISSN: 1331-677X
SCOPUS: 2-s2.0-85069770511
Appears in Collections:Faculty of Engineering, Kragujevac

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