Identification and analysis of enablers of SCM by using MCDM approach

Abstract

PurposeThe purpose of this paper is to differentiate the empowering influences of critical enablers of supply chain management (SCM) along with their interrelationships. These empowering enablers are significant, as they encourage productive execution to improve organizational performance and stakeholder's satisfaction.Design/methodology/approachFrom the literature review, incidence of a number of SCM enablers were found and they were subjected to critical scrutiny by a considerable number of experts engaged in SCM research and application to identify significant and applicable empowering enablers by grounded interactions. By using Impact Matrix Cross-Reference Multiplication Applied to a Classification analysis, the driving and dependence power were analyzed and the empowering enablers were ordered. This was pursued by building up a structural model of the empowering enablers using interpretive structure modeling, followed with measuring cause–effect relationship using decision-making trial and evaluation laboratory (DEMATEL).FindingsAmong these identified enablers of SCM, operational performance, green SCM, employee empowerment and motivation and strategic association came out to be strategic enablers.Research limitations/implicationsThe findings may help the practicing professionals to develop clarity in understanding of these essential enablers and their contextual as well as cause–effect relationship in SCM. The practicing professionals need to focus on all these enablers during implementation of SCM for enhancing the organizational performance and stake holders' satisfaction.Originality/valueThis study is of practical utility in real-life implementation of SCM. The algorithm used in applying the multi-criteria decision-making approach is very user-friendly, and the application of DEMATEL is an innovation compared to previous research. Further, the findings can be used as a benchmark for improving the performance of SCM by considering the cause–effect relationship.