The sustainability strategy focuses on conscious production and consumption, with the circular economy (CE) as an innovative approach to maximize resource value and minimize waste. Industry 4.0 technologies like AI, robotics, and blockchain play a significant role in enhancing the competitiveness of businesses pursuing the CE. These advanced technologies help organizations achieve their sustainability goals, particularly within the CE framework. The study analyses how Industry 4.0‐driven CE practices impact sustainable business performance, using the Indian textile industry as a case study. The researchers developed a three‐stage hybrid decision‐making framework, integrating various methods to assess sustainable performance. A novel three‐stage hybrid decision‐making framework was developed by integrating Kendall's agreement test (Kendall's W), fuzzy Delphi, best–worst method (BWM), full consistency method (FUCOM), and combined compromise solution (CoCoSo) methods. The findings highlight positive outcomes such as enhanced incentives, government support, greener logistics, and improved monitoring of emissions, waste, and pollution. However, there is room for further improvements to address market demand and increase the profitability of green products.

中文翻译：

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用于衡量工业 4.0 驱动的纺织行业循环经济绩效的新型混合决策框架


可持续发展战略侧重于有意识的生产和消费，以循环经济（CE）作为最大化资源价值和最小化浪费的创新方法。人工智能、机器人和区块链等工业 4.0 技术在增强追求 CE 的企业的竞争力方面发挥着重要作用。这些先进技术帮助组织实现可持续发展目标，特别是在 CE 框架内。该研究以印度纺织行业为案例研究，分析了工业 4.0 驱动的 CE 实践如何影响可持续的业务绩效。研究人员开发了一个三阶段混合决策框架，整合了各种方法来评估可持续绩效。通过集成肯德尔一致性检验（Kendall's瓦）、模糊德尔菲法、最佳-最差法（BWM）、完全一致性法（FUCOM）和组合折衷解法（CoCoSo）。调查结果强调了积极的成果，例如加强激励措施、政府支持、绿色物流以及改进对排放、废物和污染的监测。然而，在满足市场需求和提高绿色产品的盈利能力方面还有进一步改进的空间。