Title: A global performance analysis methodology using Taguchi approach: case of cloud computing and supply chain
Authors: Awatif Ragmani; Amina El Omri; Noreddine Abghour; Khalid Moussaid; Mohammed Rida
Addresses: Department of Computer Science and Mathematics, Faculty of Sciences Ain-Chock, Hassan II University of Casablanca, B.P. 5366 Maarif, Casablanca, Morocco ' Department of Computer Science and Mathematics, Faculty of Sciences Ain-Chock, Hassan II University of Casablanca, B.P. 5366 Maarif, Casablanca, Morocco ' Department of Computer Science and Mathematics, Faculty of Sciences Ain-Chock, Hassan II University of Casablanca, B.P. 5366 Maarif, Casablanca, Morocco ' Department of Computer Science and Mathematics, Faculty of Sciences Ain-Chock, Hassan II University of Casablanca, B.P. 5366 Maarif, Casablanca, Morocco ' Department of Computer Science and Mathematics, Faculty of Sciences Ain-Chock, Hassan II University of Casablanca, B.P. 5366 Maarif, Casablanca, Morocco
Abstract: Nowadays, performance optimisation is identified as the major asset to maximise the quality-cost ratio of a given system. Particularly, the performance analysis of a complex system involving several processes and a multitude of stakeholders cannot be done without an efficient methodology. During this paper, we aim at the implementation of a generic methodology for performance analysis taking as a framework the case of cloud computing and supply chain. The proposed methodology is based on the fundamental idea of transforming a complex system into a black box which will be analysed through different inputs corresponding to the influential factors and outputs which translate the key performance indicators. The analysis of the interactions between influential factors and key performance indicators is carried out on the basis of the Taguchi concept. The conclusions of the proposed methodology make it possible to identify diverse perspectives in order to enhance the performance of the entire system.
Keywords: cloud computing; performance methodology; key performance indicator; KPI; balanced scorecard; Taguchi; supply chain.
DOI: 10.1504/IJLSM.2020.110559
International Journal of Logistics Systems and Management, 2020 Vol.37 No.2, pp.252 - 284
Received: 25 Mar 2017
Accepted: 18 Jun 2018
Published online: 26 Oct 2020 *