Interpretive Structural Modelling (ISM) Methodology and its application in Supply Chain Research
Nilesh Wankhade1, Gautam Kumar Kundu2

1Nilesh Wankhade*, Research Scholar – VITBS, VIT University, Vellore, TN, India.
2Gautam Kumar Kundu, Professor – VITBS, VIT University, Vellore, TN, India.
Manuscript received on January 14, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 1101-1109 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1607029420/2020©BEIESP | DOI: 10.35940/ijitee.D1607.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: The horizon of the supply chain (SC) in the business in increasing continuously and becoming complex with its expanding role, which is result of technological advancement, ever increasing customer expectation, regulatory compliances and changing business models. Researchers used various methods to understand SC complexity and decipher the factors impacting the SC processes and concepts. Interpretive Structural Modelling (ISM) is one of the methods which is widely used in literature to transforms complex and abstract business phenomenon or vaguely defined business processes into clearly articulated, visual, structured models. This method includes interactive technique which helps to structure and build the comprehensive systematic model for set of different but related elements. The objective of this paper is to review the literature on ISM as methodology for understanding the complexity of SC challenges, issues, barriers and enablers of various processes or functions and their classifications based on SC processes using a structured approach. This study further elaborates the process for modelling structure and presented ISM as a modelling approach by elaborating steps and important features. Discussion and managerial implications of using and extending ISM in SC are provided to conclude the review. 
Keywords: Supply Chain Management, Interpretive Structural Modelling, ISM, SSIM, Research Methodology in SC, Modelling in SC
Scope of the Article: Data Management