An application of fuzzy AHP to SCOR performance measures: a case study of an Egyptian naturalbottled water company

Purpose This paper proposes a method which incorporates the fuzzy analytic hierarchy process approach (Fuzzy AHP) and the supply chain operations reference-model (SCOR) to evaluate and improve the performance of supply chain operations. Research Approach The performance of supply chain operations was measured using a performance measurement tool that combines SCOR Model and the fuzzy AHP technique. To demonstrate the applicability of the proposed approach, a case study of an Egyptian Natural Bottled Water Company was conducted. Findings and Originality This paper developed a method to quantify the SC performance through quantifying: SC measurement criteria, environmental uncertainty, and subjective judgments of SC performance evaluators. Applying this method can be an objective tool to evaluate and improve the performance of SC operations. Research Impact The proposed method is based on quantifying the SC performance through: (i) describing the characteristics and the structure of the supply chain (ii) identifying the main processes and sub processes in the supply chain and mapping these processes to SCOR Model process IDs, (iii) identifying the corresponding performance measurement attributes for the previous mapped processes based on the SCOR Model standard performance metrics, (iv) determining the relative importance weight of each attribute using fuzzy pair wise comparison, (v) assigning a performance rate for each attribute using performance rating scale. (vi) consequently, calculating the weighted rate for each attribute by multiplying the importance weight of each attribute by its performance rate. (vii) Finally, aggregating the weighted rate for each attribute across all SC performance measurement attributes using the weighted averaging aggregation method to determine the performance index of the company’s supply chain. Since each SC performance measurement attribute has weighted rate and corresponds to certain processes in the SC, SC processes that need improvement can be identified and the overall SC performance, in terms of SC index, can be evaluated. Practical Impact This method allows organisations to assess and improve the effectiveness and efficiency of supply chain operations in meeting supply chain goals and to contribute to overall improvement in the company’s performance through identifying SC processes that are working well and areas where the supply chain might need improvement.

[1]  Ahmed Farouk,et al.  Fuzzy Genetic Prioritization in Multi-Criteria Decision Problems , 2008 .

[2]  Sunil K. Sheoran,et al.  A review and analysis of supply chain operations reference (SCOR) model , 2004 .

[3]  Ludmil Mikhailov,et al.  A fuzzy approach to deriving priorities from interval pairwise comparison judgements , 2004, Eur. J. Oper. Res..

[4]  Adisak Theeranuphattana,et al.  A conceptual model of performance measurement for supply chains: Alternative considerations , 2007 .

[5]  Kamal M. Al‐Subhi Al‐Harbi,et al.  Application of the AHP in project management , 2001 .

[6]  Felix T.S. Chan,et al.  Feasibility of performance measurement system for supply chain: a process‐based approach and measures , 2003 .

[7]  Wendy L. Tate,et al.  Understanding and Managing the Services Supply Chain , 2004 .

[8]  Jung Lyu,et al.  The performance evaluation of SCOR sourcing process--The case study of Taiwan's TFT-LCD industry , 2008 .

[9]  Cheng-Ru Wu,et al.  Applying fuzzy hierarchy multiple attributes to construct an expert decision making process , 2009, Expert Syst. Appl..

[10]  Oliver Meixner,et al.  FUZZY AHP GROUP DECISION ANALYSIS AND ITS APPLICATION FOR THE EVALUATION OF ENERGY SOURCES , 2009 .

[11]  Gin-Shuh Liang,et al.  Extensions of the multicriteria analysis with pairwise comparison under a fuzzy environment , 2006, Int. J. Approx. Reason..

[12]  Nikolaos F. Matsatsinis,et al.  MCDA and preference disaggregation in group decision support systems , 2001, Eur. J. Oper. Res..

[13]  C. Kahraman,et al.  Multi‐criteria supplier selection using fuzzy AHP , 2003 .

[14]  A. Gunasekaran,et al.  Performance measures and metrics in a supply chain environment , 2001 .

[15]  Kevin McCormack,et al.  Linking SCOR planning practices to supply chain performance: An exploratory study , 2004 .

[16]  Samuel H. Huang,et al.  Computer-assisted supply chain configuration based on supply chain operations reference (SCOR) model , 2005, Comput. Ind. Eng..

[17]  Hing Kai Chan,et al.  A CONCEPTUAL MODEL OF PERFORMANCE MEASUREMENT FOR SUPPLY CHAINS , 2003 .

[18]  Ludmil Mikhailov,et al.  Deriving priorities from fuzzy pairwise comparison judgements , 2003, Fuzzy Sets Syst..

[19]  L. C. Leung,et al.  On consistency and ranking of alternatives in fuzzy AHP , 2000, Eur. J. Oper. Res..

[20]  Mark Johnson,et al.  Supply chain management for servitised products: A multi-industry case study , 2008 .

[21]  Hepu Deng Multicriteria analysis with fuzzy pairwise comparison , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).