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<p>This study examines how manufacturing companies can enhance their waste reduction performance (WRP) and waste management effectiveness (WME) by implementing extended producer responsibility policy stringency (EPRS), corporate compliance with EPR (CCEPR), and sustainability initiatives in production (SIP). Based on the institutional theory paradigm, a comprehensive framework was developed to investigate the moderating effect of government incentives for EPR compliance (GIEC) and the mediating role of recycling infrastructure development (RID). A structural equation modeling and artificial neural network (SEM-ANN) hybrid technique was used to analyze data from 398 manufacturing companies. The SEM results reveal that EPRS, CCEPR, and SIP positively impact WME and WRP. The different efficacy of environmental regulations in waste management is highlighted by the fact that RID partially mediates these associations, whereas GIEC moderates EPRS and SIP but not CCEPR. ANN results demonstrate that SIP is the primary predictor for WRP, whereas RID is the most significant element for WME. This study adds to the body of knowledge on sustainability by illustrating nonlinear interactions in the context of institutional theory. There is also a discussion of theoretical contributions, practical implications, and potential avenues for future research.</p>

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Evaluating the impact of extended producer responsibility policies on waste management

  • 期刊论文

  • 发表日期：

    2026年3月7日

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  • Yunfei Lu,
  • Ahmed Muneeb Mehta,
  • Muhammad Farrukh Shahzad,
  • Muhammad Asif

摘要

This study examines how manufacturing companies can enhance their waste reduction performance (WRP) and waste management effectiveness (WME) by implementing extended producer responsibility policy stringency (EPRS), corporate compliance with EPR (CCEPR), and sustainability initiatives in production (SIP). Based on the institutional theory paradigm, a comprehensive framework was developed to investigate the moderating effect of government incentives for EPR compliance (GIEC) and the mediating role of recycling infrastructure development (RID). A structural equation modeling and artificial neural network (SEM-ANN) hybrid technique was used to analyze data from 398 manufacturing companies. The SEM results reveal that EPRS, CCEPR, and SIP positively impact WME and WRP. The different efficacy of environmental regulations in waste management is highlighted by the fact that RID partially mediates these associations, whereas GIEC moderates EPRS and SIP but not CCEPR. ANN results demonstrate that SIP is the primary predictor for WRP, whereas RID is the most significant element for WME. This study adds to the body of knowledge on sustainability by illustrating nonlinear interactions in the context of institutional theory. There is also a discussion of theoretical contributions, practical implications, and potential avenues for future research.