A model for replacing human labor with industrial robots in the industrial production sector to promote sustainable growth

The study aims to develop a model for replacing human labor with industrial robots in the industrial production sector to promote sustainable growth. A mixed-methods approach was employed, combining qualitative interviews with nine experts and quantitative analysis based on survey data from 500 industrial enterprises. Structural Equation Modeling (SEM) confirmed that government policies, industrial Readiness, integration cooperation, and production potential are key determinants of successful robot adoption. Government policy exerted the most substantial direct influence on industrial Readiness and integration cooperation, which, in turn, positively affected production potential. The results emphasize the importance of collaborative strategies between public institutions, educational organizations, and private enterprises to enhance workforce capability and technological preparedness. The proposed Automated Robot–Human Labor Industrial Replacement (ARHLIR) Model offers both theoretical and practical implications for policymakers and industry leaders. The integration of policy support, organizational Readiness, and cooperative networks ensures that automation drives competitiveness, innovation, and long-term sustainability.

Publication Details

Journal
Decision Science Letters
Published
2025-12-17
DOI
https://doi.org/10.5267/j.dsl.2025.10.009
Citations
1
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
1.24
Controls
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article

A model for replacing human labor with industrial robots in the industrial production sector to promote sustainable growth

1 citations
Decision Science Letters
Digital Transformation in Industry
1.24
article

A model for replacing human labor with industrial robots in the industrial production sector to promote sustainable growth

article en
1 citations

Abstract

The study aims to develop a model for replacing human labor with industrial robots in the industrial production sector to promote sustainable growth. A mixed-methods approach was employed, combining qualitative interviews with nine experts and quantitative analysis based on survey data from 500 industrial enterprises. Structural Equation Modeling (SEM) confirmed that government policies, industrial Readiness, integration cooperation, and production potential are key determinants of successful robot adoption. Government policy exerted the most substantial direct influence on industrial Readiness and integration cooperation, which, in turn, positively affected production potential. The results emphasize the importance of collaborative strategies between public institutions, educational organizations, and private enterprises to enhance workforce capability and technological preparedness. The proposed Automated Robot–Human Labor Industrial Replacement (ARHLIR) Model offers both theoretical and practical implications for policymakers and industry leaders. The integration of policy support, organizational Readiness, and cooperative networks ensures that automation drives competitiveness, innovation, and long-term sustainability.

Decision Science LettersVol. 15(1)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Digital Transformation in Industry
1.24
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