A hybrid model for ranking critical successful factors of Lean Six Sigma in the oil and gas industry
Purpose: The aim of this paper is to find and prioritise multiple critical success factors (CSFs) for the implementation of LSS in the oil and gas industry. Design/methodology/approach: Based on a preselected list of possible CFSs, experts are involved in screening them with the Delphi method. As a result, 22 customised CSFs are selected. To prioritise these CSFs, the step-wise weight assessment ratio analysis (SWARA) method is applied to find weights corresponding to the decision-making preferences. Since the regular permutation-based weight assessment can be classified as NP-hard, the problem is solved by a metaheuristic method. For this purpose, a genetic algorithm (GA) is used. Findings: The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. The less important factors can be neglected and thus do not require limited resources. Research limitations/implications: Only a specific set of methods have been considered. Practical implications: The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. Social implications: The methodology supports respective evaluations in general. Originality/value: The paper contributes to the very limited research on the implementation of LSS in the oil and gas industry, and, in addition, it suggests the usage of SWARA, a permutation method and a GA, which have not yet been researched, for the prioritisation of CSFs of LSS.
Year of publication: |
2021
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Authors: | Yazdi, Amir Karbassi ; Hanne, Thomas ; Osorio Gómez, Juan Carlos |
Published in: |
The TQM Journal. - Emerald, ISSN 1754-2731, ZDB-ID 2420151-0. - Vol. 33.2021, 8 (17.03.), p. 1825-1844
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Publisher: |
Emerald |
Saved in:
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