Hanne, Thomas

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Hanne, Thomas

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2020 - 20212
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Autor:in: Yazdi, Amir Karbassi × Dateien dazu vorhanden?: Nein ×

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  • Vorschaubild nicht verfügbar
    Publikation
    A hybrid model for ranking critical successful factors of lean six sigma in the oil and gas industry
    (Emerald, 2021) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan Carlos [in: The TQM Journal]
    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 implicationsThe 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.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    A decision-support approach under uncertainty for evaluating reverse logistics capabilities of healthcare providers in Iran
    (Emerald, 2020) Yazdi, Amir Karbassi; Fernandes Wanke, Peter; Hanne, Thomas; Bottani, Eleonora [in: Journal of Enterprise Information Management]
    Purpose – This paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran. Design/methodology/approach – To identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied. Findings – First, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers. Originality/value - The contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.
    01A - Beitrag in wissenschaftlicher Zeitschrift