Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach

Industry 4.0 (I4.0) adoption is becoming predominant in manufacturing industries due to its limitless opportunities. Even though companies are interested adopting digitalization, several perceived barriers stymied them. However, the interest of smooth adoption, these must be addressed urgently. This research aims analyze broader spectrum possible that impede implementation I4.0 and converge them into most prominent inhibitors, further assessing inhibitors develop contextual relationships among A comprehensive literature review an empirical research-based survey considering a large sample size used address study’s objectives. academia experts’ inputs considered derive barrier’s current prominence. The interrelationship extracted twelve significant through principle component analysis (PCA) modeled using interpretive structural modeling (ISM) manifest each inhibitor’s direct indirect effect. Fuzzy matriced’ impacts croise’s multiplication applique’e a’ un classement (MICMAC) classify drivers dependents. study depicts inadequate organizational strategies, uncertainty about financial decision making, limited employee readiness, inconsistent legal government policies, Insufficient IT automation infrastructure as driver adoption. An integrated novel PCA-ISM MICMAC model developed this paper unique for first time establish hierarchical relationship post-COVID-19 scenario. offers practical insights outcomes will help researchers, decision-makers, practitioners unlocking potential by dealing with efficaciously.