Modelling the SCM implementation barriers: An integrated ISM-fuzzy MICMAC approach

Abstract

Purpose

The purpose of this paper is to develop the relationships among the identified supply chain management barriers (SCMBs) and understand mutual influences of these SCMBs on supply chain implementation. Further, this paper seeks to identify driving and dependent SCMBs using an interpretive structural modelling (ISM) and fuzzy MICMAC (Matrix of Cross-Impact Multiplications Applied to Classification) analysis.

Design/methodology/approach

The methodology used in the paper is the ISM with a view to evolving mutual relationships among SCMBs. The identified SCMBs have been classified further, based on their driving and dependence power using fuzzy MICMAC analysis.

Findings

This paper has identified 15 key SCMBs which hinder the successful supply chain management (SCM) implementation in an organization and has developed the relationships among the SCMBs using the ISM methodology. Further, this paper analyses the driving and dependent SCMBs using fuzzy MICMAC analysis. The integrated approach is developed here, as the ISM model provides only binary relationship among SCMBs. The fuzzy MICMAC analysis is adopted here, as it is useful in specific analysis related to driving and the dependence power of SCMBs.

Research limitations/implications

The weightage for the ISM model development and fuzzy MICMAC is obtained through the judgement of academics and industry experts. Further, validation of the model is necessary through questionnaire survey.

Practical implications

The identification of SCMBs, ISM model development and fuzzy MICMAC analysis provide academics and managers a macro picture of the challenges posed by the SCM implementation in an organization.

Originality/value

The results will be useful for business managers to understand the SCMBs and overcome these SCMBs during the SCM implementation in an organization.

Citation

Gorane, S.J. and Kant, R. (2015), "Modelling the SCM implementation barriers: An integrated ISM-fuzzy MICMAC approach", Journal of Modelling in Management, Vol. 10 No. 2, pp. 158-178. https://doi.org/10.1108/JM2-08-2012-0026