Other Articles by Author(s)

Mohamed Tarek Chahid

Author(s) and WSEAS

Mohamed Tarek Chahid

WSEAS Transactions on Computers

Print ISSN: 1109-2750
E-ISSN: 2224-2872

Volume 18, 2019

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Improvement of the Scor Model by the Use of the Performance Measurement System and an Aggregation Approach based on the Nonadditive Fuzzy Sugeno Integral: A Case Study for the Selection of Automotive Suppliers

AUTHORS: Mohamed Tarek Chahid

Download as PDF

ABSTRACT: This study aims to extend the SCOR model used in the supply chain (SC) context; we propose to extend here the proposed approaches for expressing the overall performance of an SC. The aggregation of appropriate Key Performance Indicators (KPI) in the global performance formula is based on a Sugeno integral operator, according to the fuzzy set theory, in order to deal with the nonlinearity of this model, makes data ambiguous in the process of multicriteria decision-making. Therefore, this work aims to help managers to select a suitable supplier in the Supply Chain context. The approach is used to evaluate the best contractors by using the Sugeno Integral to deal with the interrelationships aspects between KPI

KEYWORDS: Performance aggregation; Sugeno integral; Supply chain; SCOR model


[ 1]. M.Hlyal, M.T.Chahid, J. El Alami, A. Soulhi and N. El Alami, “Supplier’s Selection for the Moroccan Textile Sector by Using Performance Measurement System”, Modern Applied Science, vol. 9, No 3, 2015, doi: 10.5539/mas.v9n3p102.

[2]. L. Berrah,. and V. Clivelle, “Towards an aggregation performance measurement system model in a supply chain context”, Computers in Industry, vol. 58, 2007, pp 709-719.

[3]. L. Berrah, G. Mauris, and J. Montmain, “Monitoring the Improvement of an overall industrial performance based on a Choquet integral aggregation”, Omega, Vol. 36, 2008, pp 340-351.

[4]. J. Michalska, “The usage of the balanced scorecard for the estimation of the enterprise’s effectiveness”, Journal of materials processing technology, vol. 162-163, 2005, pp 751-758.

[5]. U.S. Bititci, P. Suwignjo, and A.S. Carrie, “Strategy management through quantitative modeling of performance measurement system ”, International Journal of Production Economics, vol. 69, 2001, pp 15-22.

[6]. S.A. Melnyk, U.S. Bititci, K. Platts, J. Tobias and B. Anderson, “Is performance measurement and management fit for the future?” Management Accounting Research, Vol. 25, No. 2, 2014, pp 173-186.

[7]. P. Kueng, A.J. Krahn, “Building a process performance measurement system: some early experiences”, Journal of Scientific, and Industrial Research, vol. 58, 1999, pp 149–59.

[8]. Y. Ducq, B. Vallespir, and G. Doumeingts, “Coherence analysis methods for production systems by performance aggregation”, International Journal of Production Economics. Vol. 7, 2001, pp 23–37.

[9]. V. Clivelle, L. Berrah and G. Mauris, ” Quantitative expression and aggregation of performance measurements based on the MACBETH multi-criteria method”, International Journal of Production Economics, vol. 105, 2006, pp 171-189.

[10]. A. Neely, “The performance measurement revolution: why now and what next?” International Journal of Operations & Production Management, vol. 19, No. 2, 1999, pp 205–228.

[11]. T. Takagi, and M. Sugeno, “Fuzzy Identification of Systems and Its Applications to Modeling and Control”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. smc15, No. 1, 1985, pp 116-132.

[12]. G. Buyukozkan, and D. Ruan, “Choquet integral based aggregation approach to software development risk assessment”, Information Sciences, Vol. 180, 2010, pp 441-451.

[13]. M. Grabisch, “A Constructive approach to multicriteria decision making”, Traitement du signal, Vol. 22, No. 4, 2005, pp 321-338.

[14]. D. J. Jeng, “Selection of an Improvement Strategy in Internal Service Operations: The MCDM Approach with Fuzzy AHP and Nonadditive Fuzzy Integral”, International Journal of Innovative Computing, Information and Control, Vol. 8, No. 8, 2011, pp 5917- 5933.

[15] M.T. Chahid, J. El Alami, A. Soulhi and N. El Alami, “Performance Measurement Model for Moroccan Automotive Suppliers Using PMQ and AHP”, Modern Applied Science, vol. 8, No 6, 2014, doi:10.5539/mas.v8n6p13.

WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 18, 2019, Art. #30, pp. 231-238

Copyright © 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

Bulletin Board


The editorial board is accepting papers.

WSEAS Main Site