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Modelling the SCM enablers: an integrated ISM‐fuzzy MICMAC approach

S.J. Gorane (Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India)
Ravi Kant (Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India)

Asia Pacific Journal of Marketing and Logistics

ISSN: 1355-5855

Article publication date: 29 March 2013

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Abstract

Purpose

The purpose of this paper is to identify the supply chain management enablers (SCMEs) and establish relationships among them using interpretive structural modeling (ISM) and find out driving and dependence power of enablers, using fuzzy MICMAC (Matriced' Impacts Croisés Multiplication Appliquée á un Classement) analysis.

Design/methodology/approach

A group of experts from industries and academics was consulted and ISM is used to develop the contextual relationship among various SCMEs for each dimension of SCM implementation. The results of ISM are used as an input to fuzzy MICMAC analysis, to identify the driving and dependence power of SCMEs.

Findings

This paper has identified 24 key SCMEs and developed an integrated model using ISM and the fuzzy MICMAC approach, which is helpful to identify and classify the important SCMEs and reveal the direct and indirect effects of each SCME on the SCM implementation. The integrated approach is developed, since the ISM model provides only binary relationship among SCMEs, while fuzzy MICMAC analysis provides precise analysis related to driving and dependence power of SCMEs.

Research limitations/implications

The weightage for ISM model development and fuzzy MICMAC are obtained through the judgment of academicians and a few industry experts. It is only subjective judgment and any biasing by the person who is judging the SCMEs might influence the final result. A questionnaire survey can be conducted to catch the insight on these SCMEs from more organizations.

Practical implications

This study has strong practical implications, for both practitioners as well as academicians. The practitioners need to concentrate on identified SCMEs more cautiously during SCM implementation in their organizations and the top management could formulate strategy for implementing these enablers obtained through ISM and fuzzy MICMAC analysis.

Originality/value

This is first kind of study to identify 24 SCMEs and further, to deploy ISM and fuzzy MICMAC to identify and classify the key SCMEs that influence SCM implementation in the organization.

Keywords

Citation

Gorane, S.J. and Kant, R. (2013), "Modelling the SCM enablers: an integrated ISM‐fuzzy MICMAC approach", Asia Pacific Journal of Marketing and Logistics, Vol. 25 No. 2, pp. 263-286. https://doi.org/10.1108/13555851311314059

Publisher

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Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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