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Soft and Hard Total Quality Management Practices Promote Industry 4.0 Readiness: A SEM-Neural Network Approach

Author

Listed:
  • Kashif Ali

    (Department of Management Sciences, Universiti Teknologi Petronas, Seri Iskandar 32160, Malaysia)

  • Satirenjit Kaur Johl

    (Department of Management Sciences, Universiti Teknologi Petronas, Seri Iskandar 32160, Malaysia)

  • Amgad Muneer

    (Department of Computer and Information Sciences, Universiti Teknologi Petronas, Seri Iskandar 32160, Malaysia
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA)

  • Ayed Alwadain

    (Computer Science Department, Community College, King Saud University, Riyadh 145111, Saudi Arabia)

  • Rao Faizan Ali

    (Department of Software Engineering, University of Management and Technology, Lahore 54728, Pakistan)

Abstract

Industry 4.0 (I4.0) is a technological development in the manufacturing industry that has revolutionized Total Quality Management (TQM) practices. There has been scant empirical research on the multidimensional perspective of TQM. Thus, this study aims to empirically examine the effect of the multidimensional view of TQM (soft and hard) on I4.0 readiness in small and medium-sized (SMEs) manufacturing firms. Based on the sociotechnical systems (STS) theory, a framework has been developed and validated empirically through an online survey of 209 Malaysian SMEs manufacturing firms. Unlike the existing TQM studies that used structural equation modeling (SEM), a two-stage analysis was performed in this study. First, the SEM approach was used to determine which variable significantly affects I4.0 readiness. Second, the artificial neural network (ANN) technique was adopted to rank the relative influence of significant predictors obtained from SEM. The results show that the soft and hard TQM practices have supported the I4.0 readiness. Moreover, the results highlight that hard TQM practices have mediating role between soft TQM practices and I4.0 readiness. The ANN results affirmed that customer focus is considered an important TQM factor for I4.0 managerial readiness, advanced manufacturing technology for operational readiness and top management commitment for technology readiness. In a nutshell, the SEM-ANN approach uniquely contributes to the TQM and I4.0 literature. Finally, the findings can help managers to prioritize firms’ soft and hard quality practices that promote I4.0 implementation, especially in emerging economies.

Suggested Citation

  • Kashif Ali & Satirenjit Kaur Johl & Amgad Muneer & Ayed Alwadain & Rao Faizan Ali, 2022. "Soft and Hard Total Quality Management Practices Promote Industry 4.0 Readiness: A SEM-Neural Network Approach," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:11917-:d:921319
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    References listed on IDEAS

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    Cited by:

    1. Zengjian Huang & Amna Shahzadi & Yaser Daanial Khan, 2022. "Unfolding the Impact of Quality 4.0 Practices on Industry 4.0 and Circular Economy Practices: A Hybrid SEM-ANN Approach," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
    2. Qining Deng & K. Noorliza, 2023. "Integration, Resilience, and Innovation Capability Enhance LSPs’ Operational Performance," Sustainability, MDPI, vol. 15(2), pages 1-22, January.
    3. Rahman Aulia Fuad & Agusti Rosalita Rachma & Kurniawati Desi Tri, 2024. "Mediating Role of Sustainability Reporting Quality on the Relationship Between Green Banking and Firm Value," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 34(4), pages 105-129.
    4. Katherine Roth & Kambiz Farahmand, 2023. "A Socio-Technical Study of Industry 4.0 and SMEs: Recent Insights from the Upper Midwest," Sustainability, MDPI, vol. 15(16), pages 1-19, August.

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