Barriers to adopt industry 4.0 in supply chains using interpretive structural modeling

Abstract

This research aims at exploring barriers of adopting Industry 4.0 in manufacturing supply chains. Data were collected based on a review of extant literature on barriers Industry 4.0 adoption, individual interviews with a panel consisted of academic and industry experts. Following numerous previous studies, interpretive structural modeling (ISM) and matrix multiplication applied to classification (MICMAC) analysis were conducted to order 10 barriers based on their importance and impacts. The results excluded one barrier “cyber security challenges”, categorized another one as a dependent barrier “lack of digital strategy”, and eight barriers as linkage barriers “lack of infrastructure”, “personnel resistance to adopt new technologies”, “high investment requirements”, “data management and quality challenges”, “uncertainty of economic benefits”, “low maturity level of technology”, “lack of adequate skills”, and “job disruptions”. Henceforward, it was concluded that mitigating these eight barriers is very critical to ensure a successful adoption of Industry 4.0 technologies in supply chains. Further studies are required to categorize these eight barriers based on their importance and relationships.