From Industry 4.0 Readiness to Sustainable Manufacturing: An IMPULS-Informed PLS-SEM Analysis of Organisational and Technological Capabilities
Adnan, Muhammad and Butt, Javaid and Khan, Md Ashikul Alam and Sohail, Aamir and Sair, Shrafat Ali (2026) From Industry 4.0 Readiness to Sustainable Manufacturing: An IMPULS-Informed PLS-SEM Analysis of Organisational and Technological Capabilities. Journal of Manufacturing and Materials Processing, 10 (8). p. 273. ISSN 2504-4494
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Abstract
The transition towards Industry 4.0 has significantly heightened the need for manufacturing firms to assess their organisational readiness for the digital transformation of production systems while aligning with sustainable manufacturing goals. Despite increasing scholarly attention to Industry 4.0, there is limited evidence of how organisational and technological capabilities, through readiness, translate into sustainable manufacturing outcomes in emerging economies such as Pakistan. This study addresses this gap by examining the relationships among the six IMPULS dimensions, namely strategy and organisation, smart factory, smart operations, smart product, data-driven services, and employees, together with additional organisational and technological readiness factors, Industry 4.0 readiness, and sustainable manufacturing in the context of Pakistani manufacturing firms. A quantitative cross-sectional design was used, while data were collected from 470 respondents across various manufacturing sectors using a structured questionnaire constructed on validated measurement scales. This study develops and empirically tests an extended IMPULS-informed readiness-to-sustainability framework that integrates established Industry 4.0 readiness dimensions with additional organisational and technological capability factors relevant to sustainable manufacturing. The study makes a methodological distinction by operationalising an IMPULS-informed framework that connects its six dimensions with Industry 4.0 readiness and sustainable manufacturing within a single empirical model. The proposed model was examined using partial least squares structural equation modelling (PLS-SEM). The findings reveal that strategy and organisation, employees, smart products, and smart operations substantially contribute to Industry 4.0 readiness. Conversely, smart factories and data-driven services do not have a significant direct impact on readiness. Sustainable manufacturing is strongly influenced by Industry 4.0 readiness, smart operations, and the smart factory. Mediation analysis further indicates that Industry 4.0 readiness serves as a significant transmission mechanism linking strategy and organisation, employees, smart products, and smart operations to sustainable manufacturing. The study extends the IMPULS framework by validating its relevance in an emerging economy and by demonstrating that sustainability gains from digital transformation rely more on coordinated organisational and operational readiness than on isolated technology adoption. The results provide evidence-based prioritisation guidance for managers and policymakers seeking to prioritise strategic alignment, workforce skills, and operational integration for successful, sustainable industrial transformation.
| Item Type: | Article |
|---|---|
| Identification Number: | 10.3390/jmmp10080273 |
| Dates: | Date Event 26 July 2026 Accepted 1 August 2026 Published Online |
| Uncontrolled Keywords: | Industry 4.0 readiness, IMPULS-informed framework, sustainable manufacturing, digital transformation, PLS-SEM, Pakistani manufacturing sector |
| Subjects: | CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific) CAH17 - business and management > CAH17-01 - business and management > CAH17-01-02 - business studies |
| Divisions: | Architecture, Built Environment, Computing and Engineering > Engineering Business School > Management, Business and Marketing |
| Depositing User: | Gemma Tonks |
| Date Deposited: | 12 Aug 2026 12:16 |
| Last Modified: | 12 Aug 2026 12:16 |
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/17159 |
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