Volume 56, Number 4, July-August 2022
|Page(s)||2139 - 2158|
|Published online||11 July 2022|
Causal modelling of the enablers of CPFR for building resilience in manufacturing supply chains
Management Division, ABV-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India
2 Operations Management Area, Indian Institute of Management Lucknow, Lucknow, India
Accepted: 14 May 2022
Supply chain resilience is widely receiving attention during the past decade. Collaboration and visibility enhancement in supply chains is a key to achieve resilience and robustness in supply chains. Collaborative Planning, Forecasting and Replenishment (CPFR) is always been one of the difficult, yet powerful tool for collaboration in supply chains. Companies, in general attempt to address the technological side of changes, but avoid addressing the non-technological side of it, while implementing CPFR. This paper aims to explore the technological and non-technological enablers of CPFR, separately considering the Indian manufacturing industries and study their causal relations, using the Interpretive Structural Modeling (ISM). The results are beneficial, as managers can concentrate on causal enablers, while implementing CPFR. The success factors for implementation can slightly vary across different industries, but the applicability of the result is wider due to several common issues that arise during its implementation. Thus, the paper aims to provide directions for considering the most influencing enablers that can act as critical factors in the successful implementation of the CPFR. These influential enablers can be given much focus to reduce the vulnerabilities and to enhance the resilience capabilities of firms and their supply chains.
Mathematics Subject Classification: 62D20 / 68U01 / 90B90 / 90B50
Key words: Supply chain resilience / Collaborative Planning, Forecasting and Replenishment (CPFR) / information sharing / interpretive structural modeling (ISM)
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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