Abstract
This paper presents a novel fuzzy performance measurement model for supply chain based on hierarchical structure of metrics proposed in Supply Council Operations Reference (SCOR®) model (version 12.0). Performance measurement of supply chains predominantly suffers from uncertainty and vagueness due to the involvement of subjective judgement of the decision-makers. In the proposed model, the fuzzy set theoretic approach has been used to address the inherent vagueness and Mamdani fuzzy inference reasoning is employed to capture the causal relationship among the metrics proposed in SCOR model. The novelty of this study is the employment of newly defined metrics and their hierarchical structure suggested in the latest version of SCOR® model, SCOR® 12.0.
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Acknowledgements
This research was funded by University Grants Commission (UGC) Minor Research Project Grant Letter No. PSW-292/15-16 (ERO). The authors are grateful to the anonymous reviewers for their valuable comments and suggestions in improving the quality of the manuscript.
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Majumder, D., Bhattacharjee, R., Dam, M. (2020). Fuzzy Supply Chain Performance Measurement Model Based on SCOR 12.0. In: Solanki, V., Hoang, M., Lu, Z., Pattnaik, P. (eds) Intelligent Computing in Engineering. Advances in Intelligent Systems and Computing, vol 1125. Springer, Singapore. https://doi.org/10.1007/978-981-15-2780-7_116
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DOI: https://doi.org/10.1007/978-981-15-2780-7_116
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