2023
DOI: 10.5267/j.uscm.2022.9.013
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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 on… Show more

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Cited by 79 publications
(12 citation statements)
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“…The final challenges selected in the study were classified into four categories: (i) Internal, (ii) External, (iii) Apprehensive, and (iv) Prospective challenges. Internal challenges included challenges that were specific to the automobile industry, such as an outdated infrastructure, lack of strategy and standards, lack of knowledge and awareness, the reluctance of top management, lack of support from employees and stakeholders, lack of skilled workers [19], poor internet connectivity and an inability to collect and identify data. External challenges were factors outside the control of the automobile industry, such as lack of government support [20], lack of financial aid, lack of customer awareness, and recession due to the COVID-19 pandemic.…”
Section: Delphi-based Expert Consensusmentioning
confidence: 99%
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“…The final challenges selected in the study were classified into four categories: (i) Internal, (ii) External, (iii) Apprehensive, and (iv) Prospective challenges. Internal challenges included challenges that were specific to the automobile industry, such as an outdated infrastructure, lack of strategy and standards, lack of knowledge and awareness, the reluctance of top management, lack of support from employees and stakeholders, lack of skilled workers [19], poor internet connectivity and an inability to collect and identify data. External challenges were factors outside the control of the automobile industry, such as lack of government support [20], lack of financial aid, lack of customer awareness, and recession due to the COVID-19 pandemic.…”
Section: Delphi-based Expert Consensusmentioning
confidence: 99%
“…External challenges were factors outside the control of the automobile industry, such as lack of government support [20], lack of financial aid, lack of customer awareness, and recession due to the COVID-19 pandemic. Apprehensive challenges included fears and concerns of stakeholders, such as concern for data security [19], fear of loss of employment [21], uncertainty about financial benefits [19], and changes in work organisation. Prospective challenges included challenges inherently expected to deter the implementation of Industry 4.0 tools in the automobile industry, such as the absence of an IT and R&D department, lack of research and collaboration with academia, high initial investment cost, and low maturity level Industry 4.0 tools [19].…”
Section: Delphi-based Expert Consensusmentioning
confidence: 99%
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“…In another manuscript, the following classification of barriers is mentioned: economic and financial, cultural, competence, legal, technical, and related to the implementation process (Orzes et al, 2018). It seems that these classifications are only a matter of convention since most authors list mostly the same barriers in their studies and, depending on the topic, focus on selected or more of them (Attiany et al, 2023;Vigneshvaran and Vi-nodh, 2021;Raj et al, 2020). The indicated technical barriers include, among others: insufficient information and communication technology infrastructure (Kumar et al, 2021;Andro-niceanu et al, 2021), lack of standards, uncertainty about the reliability of systems, and difficult interoperability/compatibility of devices.…”
Section: Literature Reviewmentioning
confidence: 99%
“…However, the implementation of modern technologies in enterprises also brings specific barriers. Among the most common, we can rank lack of infrastructure, personnel resistance, high investment requirements, lack of digital strategy, uncertainty, lack of adequate skills (Attiany et al, 2023), doubt about sustainability, lack of alternate solutions (Goel et al, 2022), lack of trust, lack of business model or lack of government support (Kumar et al, 2023).…”
Section: Introductionmentioning
confidence: 99%