Performance evaluation research on supply chain based on AHP and modified grey relational analysis

Performance evaluation is one of the most important problems for retail chains and may have effect on tactical and strategic decisions. This paper proposes a grey-based multi-criteria performance evaluation model for retail sector. This model integrates Decision-Making Trial and Evaluation Laboratory (DEMATEL) and modified Grey Relational Analysis (GRA) methods. First, the grey-based DEMATEL method is used for determining the importance of performance indicators to be used in GRA based on the experts’ assessments. Then, the proposed modified GRA method is used for the performance evaluation and ranking of retail stores with respect to the predetermined performance indicators. Finally, the effectiveness and the applicability of the developed approach are illustrated with a case study with the actual data taken from a retail chain in Turkey.

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Integrated analytical hierarchy process and grey relational analysis approach to measure supply chain complexity

Benchmarking An International Journal ◽

10.1108/bij-03-2020-0108 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Sujan Piya ◽

Ahm Shamsuzzoha ◽

Mohammed Khadem ◽

Mahmoud Al Kindi

Keyword(s):

Mathematical Model ◽

Supply Chain ◽

Analytical Hierarchy Process ◽

Grey Relational Analysis ◽

Extensive Literature ◽

Content Type ◽

Relational Analysis ◽

Grey Relational ◽

Hierarchy Process

PurposeThe purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC).Design/methodology/approachThrough extensive literature review, the authors discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study.FindingsThe authors identified 22 drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing and company culture.Originality/valueIn this paper, the authors propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors' knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC.

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A Pythagorean fuzzy ANP-QFD-Grey relational analysis approach to prioritize design requirements of sustainable supply chain

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-212131 ◽

2022 ◽

pp. 1-15

Author(s):

Zhenxing Peng ◽

Lina He ◽

Yushi Xie ◽

Wenyan Song ◽

Jue Liu ◽

...

Keyword(s):

Supply Chain ◽

Grey Relational Analysis ◽

Quality Function Deployment ◽

Sustainable Supply Chain ◽

Pythagorean Fuzzy Set ◽

Fuzzy Anp ◽

Uncertain Environment ◽

Relational Analysis ◽

Design Requirements ◽

Grey Relational

A sustainable supply chain (SSC) is vital for company’s sustainability success, so it is imperative to identify and prioritize SSC’s design requirements (DRs) for better SSC planning. For customer-centric markets, the customer requirements (CRs) need to be integrated into SSC’s DRs. This paper thus proposes a customer-centric approach based on Analytic Network Process (ANP), Quality Function Deployment (QFD), Grey Relational Analysis (GRA), and Pythagorean Fuzzy Set (PFS) to rank SSC’s DRs, considering CRs and information ambiguity. The PFS is combined with ANP, QFD, and GRA to better handle uncertainty in the SSC. The Pythagorean fuzzy ANP is applied to analyze the correlations among the sustainable CRs and determine the corresponding weights. The sustainable CRs are transformed into the DRs using the Pythagorean fuzzy QFD. The relationships among the resulting DRs are analyzed through Pythagorean fuzzy GRA to prioritize DRs. The approach is validated through a case study. The results obtained in this paper shows that the proposed method is efficient to prioritize DRs of SSC with the consideration of sustainable CRs under uncertain environment. The novelties of proposed method are that it not only offers a customer-oriented SSC planning method through the integration of ANP, QFD and GRA, but also can reflect the uncertain information with a broader membership representation space via PFSs. Based on the proposed method, the decision-maker can conduct comprehensive analysis to prioritize DRs and design appropriate SSC to fulfill CRs under uncertain environment.

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