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Abstract：
The significance of accurate energy production prediction cannot be overstated, especially in the context of achieving carbon neutrality and balancing traditional and clean energy sources. Unlike conventional models with simplified assumptions or limited data inputs hindering energy usage optimization, waste reduction and efficient resource allocation, we introduced a novel structural equation modelling approach to eight manufacturing industries\' sustainable waste management practices (SWMPs) in Iraq. This comprehensive analysis, conducted with Smart PLS software on 375 responses aims to enhance energy production predictions\' accuracy and support sustainability goals contribute to achieving carbon neutrality goals and promote a balanced energy mix that supports sustainability and environmental stewardship. The findings reveal noteworthy insights: notably, chemical manufacturing companies exhibit a substantial advantage from green accounting practices, witnessing a 78.1 % and 45.8 % improvement in environmental auditing oversight and SWMPs, respectively, compared to other manufacturing sectors. Compared to conventional grey models, our model demonstrates that a 1-unit improvement in CSR enhances environmental auditing oversight effectiveness by 33.4 % and sustainable waste management by 56.9 % across industries. By leveraging these data-driven insights and innovative approaches, we can drive positive change towards a more sustainable and resilient energy future, collectively contributing to a more resilient, efficient, and sustainable energy ecosystem that benefits societies, economies, and the environment. The heightened accuracy of energy production prediction facilitated by our novel model empowers stakeholders at regional and global levels to make informed decisions, mitigate risks, support policy development, achieve sustainability goals, formulate effective policies and foster collaboration.
摘要：
准确的能源产量预测的重要性怎么强调都不为过,特别是在实现碳中和和平衡传统和清洁能源的背景下。与具有简化假设或有限数据输入阻碍能源使用优化的传统模型不同，减少浪费和有效的资源分配，我们将一种新颖的结构方程建模方法引入了伊拉克八个制造业的可持续废物管理实践（SWMP）。综合分析,与SmartPLS软件进行的375响应旨在提高能源生产预测的准确性和支持可持续发展目标有助于实现碳中和目标，促进平衡的能源组合，支持可持续性和环境管理。这些发现揭示了值得注意的见解：特别是，化工制造公司从绿色会计实践中表现出巨大的优势，见证了环境审计监督和SWMP的78.1%和45.8%的改善，分别,与其他制造业相比。与传统的灰色模型相比，我们的模型表明，企业社会责任的1个单位改进可使各行业的环境审计监督效率提高33.4％，可持续废物管理提高56.9％。通过利用这些数据驱动的见解和创新方法，我们可以推动积极的变化，朝着更可持续和更有弹性的能源未来发展，共同为更有弹性的人做出贡献，高效,以及造福社会的可持续能源生态系统，经济,和环境。我们的新模型提高了能源生产预测的准确性，使区域和全球层面的利益相关者能够做出明智的决策。减轻风险，支持政策制定,实现可持续发展目标，制定有效的政策，促进合作。
