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Deployment of Interpretive Structural Modeling in Barriers to Industry 4.0: A Case of Small and Medium Enterprises

Authors: Pankaj Goel; Raman Kumar; Harish Kumar Banga; Swapandeep Kaur; Rajesh Kumar; Danil Yurievich Pimenov; Khaled Giasin;

Deployment of Interpretive Structural Modeling in Barriers to Industry 4.0: A Case of Small and Medium Enterprises

Abstract

Small and medium enterprises (SMEs) are vital contributors and significant drivers of any manufacturing sector. The Industry 4.0 (I 4.0) revolution has made the global economy highly competitive and automated, requiring Indian SMEs to adapt more quickly. Therefore, this study aimed to identify the barriers to implementing I 4.0, simplifying the complex interrelationship among such barriers with the help of a suitable model, categorizing them as independent and dependent ones, and, ultimately, leveling the same drivers, autonomous linkages, and dependent forces. The present investigation thoroughly examined the existing literature and summarized the list of barriers into fifteen significant barriers to the smooth establishment of Industry 4.0 in India. The identified barriers were analyzed with the help of Interpretive Structural Modeling (ISM) Diagraph and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. This study was able to explore the interrelationship among these barriers. The study has found found a lack of support from stakeholders, and insufficient managerial support emerged as a major factor neglected by Indian SMEs. However, uncertainty in the predicted demand for products, the lack of an alternate solution to the technological breakdown, and doubt about the sustainability of Industry 4.0 (relating to its potential to lead to unemployment in society, etc.) are significant contingent barriers. These barriers can impact the other strategic choices related to the successful implementation of Industry 4.0. This study’s observations can help decision-makers make strategic decisions to manage the barriers affecting Industry 4.0 in Indian SMEs. This research revealed a scope that can be extended to other South Asian and developing nations. The results of the present work can be further studied with structural equation modeling (SEM) and multiple regression analysis (MRA).

Keywords

interpretive structural modeling (ISM), MICMAC analysis, ddc:650, barriers, Industry 4.0; small and medium enterprises (SMEs); interpretive structural modeling (ISM); MICMAC analysis; barriers; sustainability, Industry 4.0, sustainability, small and medium enterprises (SMEs)

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%
gold