Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach

Abstract

Purpose

Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion.

Design/methodology/approach

This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence.

Findings

The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain.

Practical implications

This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits.

Originality/value

This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.

Citation

Agrawal, P., Narain, R. and Ullah, I. (2020), "Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach", Journal of Modelling in Management, Vol. 15 No. 1, pp. 297-317. https://doi.org/10.1108/JM2-03-2019-0066