Abstract
Purpose: Despite the growing interest in closed-loop manufacturing, there is a lack of comprehensive frameworks that integrate the Product development, Production Processes, People, and Policies (4Ps) to optimize sustainable manufacturing performance. This study investigates the influence of the four Ps of closed-loop manufacturing systems (product development, production processes, people, and policies) on sustainable manufacturing performance (SMP).
Design/methodology/approach: To investigate the influence of the four Ps on sustainable manufacturing performance (SMP), a hybrid analytical model was employed, combining Structural Equation Modeling (SEM) with Artificial Neural Networks (ANN). Data was collected through a structured survey administered to 353 manufacturing firms in Malaysia. SEM was used to assess the relationships between the variables, while ANN was employed to capture non-linear relationships and improve prediction accuracy.
Findings: The research findings demonstrate that product development practices, including eco-design, life cycle assessment, and resource planning, exert the most significant influence on sustainable manufacturing performance (SMP). Furthermore, implementing green and lean manufacturing techniques, energy modeling, and material utilization/toxicity planning significantly enhances sustainability outcomes. While the social setting (employee motivation, turnover, work life quality) does not directly impact SMP, it plays a pivotal role in facilitating the implementation of internal environmental policies. Moreover, environmental management practices, both mandatory and voluntary, serve as intermediaries between the four Ps and SMP within closed-loop manufacturing systems.
Originality/value: This study contributes to the literature by providing a comprehensive framework for understanding the factors that drive sustainable manufacturing performance. The hybrid SEM-ANN model offers a robust and innovative approach to analyzing the complex relationships between the four Ps and SMP.
Practical Implications: The findings offer valuable insights for policymakers, industry leaders, and manufacturing organizations. By prioritizing product development, implementing green and lean manufacturing practices, and fostering a positive social setting, organizations can significantly enhance their sustainable performance. Additionally, the study highlights the importance of effective environmental management practices in mediating the relationship between other factors and SMP.
Design/methodology/approach: To investigate the influence of the four Ps on sustainable manufacturing performance (SMP), a hybrid analytical model was employed, combining Structural Equation Modeling (SEM) with Artificial Neural Networks (ANN). Data was collected through a structured survey administered to 353 manufacturing firms in Malaysia. SEM was used to assess the relationships between the variables, while ANN was employed to capture non-linear relationships and improve prediction accuracy.
Findings: The research findings demonstrate that product development practices, including eco-design, life cycle assessment, and resource planning, exert the most significant influence on sustainable manufacturing performance (SMP). Furthermore, implementing green and lean manufacturing techniques, energy modeling, and material utilization/toxicity planning significantly enhances sustainability outcomes. While the social setting (employee motivation, turnover, work life quality) does not directly impact SMP, it plays a pivotal role in facilitating the implementation of internal environmental policies. Moreover, environmental management practices, both mandatory and voluntary, serve as intermediaries between the four Ps and SMP within closed-loop manufacturing systems.
Originality/value: This study contributes to the literature by providing a comprehensive framework for understanding the factors that drive sustainable manufacturing performance. The hybrid SEM-ANN model offers a robust and innovative approach to analyzing the complex relationships between the four Ps and SMP.
Practical Implications: The findings offer valuable insights for policymakers, industry leaders, and manufacturing organizations. By prioritizing product development, implementing green and lean manufacturing practices, and fostering a positive social setting, organizations can significantly enhance their sustainable performance. Additionally, the study highlights the importance of effective environmental management practices in mediating the relationship between other factors and SMP.
Original language | English |
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Number of pages | 29 |
Journal | Business Process Management Journal |
Early online date | 3 Dec 2024 |
DOIs | |
Publication status | Early online - 3 Dec 2024 |
Keywords
- Closed loop manufacturing
- sustainable manufacturing
- environmental management
- structural equational modelling
- artificial neural network