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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 in adopting digitalization, several perceived barriers stymied them. However, in the interest of its smooth adoption, these perceived barriers mus...

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Autores principales: Gadekar, Rimalini, Sarkar, Bijan, Gadekar, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9362972/
http://dx.doi.org/10.1007/s13198-022-01691-5
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author Gadekar, Rimalini
Sarkar, Bijan
Gadekar, Ashish
author_facet Gadekar, Rimalini
Sarkar, Bijan
Gadekar, Ashish
author_sort Gadekar, Rimalini
collection PubMed
description Industry 4.0 (I4.0) adoption is becoming predominant in manufacturing industries due to its limitless opportunities. Even though companies are interested in adopting digitalization, several perceived barriers stymied them. However, in the interest of its smooth adoption, these perceived barriers must be addressed urgently. This research aims to analyze the broader spectrum of possible barriers that impede the implementation of I4.0 and converge them into the most prominent inhibitors, further assessing these inhibitors to develop contextual relationships among them. A comprehensive literature review and an empirical research-based survey considering a large sample size are used to address the study’s research objectives. Industry and academia experts’ inputs are considered to derive the I4.0 implementation barrier’s current prominence. The interrelationship among extracted twelve significant inhibitors through principle component analysis (PCA) is modeled using interpretive structural modeling (ISM) to manifest each inhibitor’s direct and indirect effect. Fuzzy matriced’ impacts croise’s multiplication applique’e a’ un classement (MICMAC) analysis is further considered to classify these inhibitors into drivers and dependents. The study depicts inadequate organizational strategies, uncertainty about financial decision making, limited employee readiness, inconsistent legal and government policies, Insufficient IT and automation infrastructure as the most prominent driver inhibitors of the I4.0 adoption. An integrated novel PCA-ISM Fuzzy MICMAC model developed in this research paper is unique and used for the first time to establish the hierarchical relationship among I4.0 implementation inhibitors considering the post-COVID-19 scenario. This study offers practical insights and outcomes that will help researchers, decision-makers, and practitioners in unlocking the potential of I4.0 by dealing with its inhibitors efficaciously.
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spelling pubmed-93629722022-08-10 Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach Gadekar, Rimalini Sarkar, Bijan Gadekar, Ashish Int J Syst Assur Eng Manag Original Article Industry 4.0 (I4.0) adoption is becoming predominant in manufacturing industries due to its limitless opportunities. Even though companies are interested in adopting digitalization, several perceived barriers stymied them. However, in the interest of its smooth adoption, these perceived barriers must be addressed urgently. This research aims to analyze the broader spectrum of possible barriers that impede the implementation of I4.0 and converge them into the most prominent inhibitors, further assessing these inhibitors to develop contextual relationships among them. A comprehensive literature review and an empirical research-based survey considering a large sample size are used to address the study’s research objectives. Industry and academia experts’ inputs are considered to derive the I4.0 implementation barrier’s current prominence. The interrelationship among extracted twelve significant inhibitors through principle component analysis (PCA) is modeled using interpretive structural modeling (ISM) to manifest each inhibitor’s direct and indirect effect. Fuzzy matriced’ impacts croise’s multiplication applique’e a’ un classement (MICMAC) analysis is further considered to classify these inhibitors into drivers and dependents. The study depicts inadequate organizational strategies, uncertainty about financial decision making, limited employee readiness, inconsistent legal and government policies, Insufficient IT and automation infrastructure as the most prominent driver inhibitors of the I4.0 adoption. An integrated novel PCA-ISM Fuzzy MICMAC model developed in this research paper is unique and used for the first time to establish the hierarchical relationship among I4.0 implementation inhibitors considering the post-COVID-19 scenario. This study offers practical insights and outcomes that will help researchers, decision-makers, and practitioners in unlocking the potential of I4.0 by dealing with its inhibitors efficaciously. Springer India 2022-08-09 /pmc/articles/PMC9362972/ http://dx.doi.org/10.1007/s13198-022-01691-5 Text en © The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Gadekar, Rimalini
Sarkar, Bijan
Gadekar, Ashish
Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach
title Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach
title_full Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach
title_fullStr Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach
title_full_unstemmed Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach
title_short Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach
title_sort model development for assessing inhibitors impacting industry 4.0 implementation in indian manufacturing industries: an integrated ism-fuzzy micmac approach
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9362972/
http://dx.doi.org/10.1007/s13198-022-01691-5
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