Towards sustainable sustainability: exploring the impact of antecedents on industry 4.0 and sustainable performance of organizations—an empirical investigation

Mohammad Nurul Hassan Reza, Sreenivasan Jayashree, Chinnasamy Agamudai Malarvizhi, Angappa Gunasekaran, Muhammad Mohiuddin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study investigates the impact of influential antecedents on the adoption of Industry 4.0 and sustainable performance in organizations. It addresses the challenges organizations face in adopting Industry 4.0 and the limited research on the relationship between Industry 4.0 and organizational performance, particularly sustainability. The study analyzes direct effect of Industry 4.0 on sustainable outcomes and evaluates the mediating role of Industry 4.0 in the relationship between antecedents and sustainable performance. Data from 293 Malaysian companies was used to develop the higher-order model and disjoint two-stage approach in Partial Least Square Structural Equation Modeling (PLS-SEM) was employed to analyze the relationships. The results indicate that smart technologies, management support, human capital and the government’s role significantly influence Industry 4.0 implementation. These factors also have a significant impact on organizations’ sustainable performance. However, while human capital has emerged as an antecedent of Industry 4.0, its impact on sustainable performance is insignificant. The mediation of Industry 4.0 and its direct effect on sustainable performance were also confirmed. The validated model provides valuable insights for professionals and policy-makers to plan effectively and optimize resource utilization in implementing Industry 4.0 with a focus on sustainability. Recommendations for future research include longitudinal studies, cross-country validation, and exploring other antecedents and their impact on organizations’ digital innovation and sustainable performance.

Original languageEnglish (US)
JournalAnnals of Operations Research
DOIs
StateAccepted/In press - 2024

All Science Journal Classification (ASJC) codes

  • General Decision Sciences
  • Management Science and Operations Research

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