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Analyzing the causal dynamics of circular-economy drivers in SMES using interpretive structural modeling
Energy Economics ( IF 13.6 ) Pub Date : 2024-08-20 , DOI: 10.1016/j.eneco.2024.107842 Pedro S. Oliveira , Fernando A.F. Ferreira , Marina Dabić , João J.M. Ferreira , Neuza C.M.Q.F. Ferreira
Energy Economics ( IF 13.6 ) Pub Date : 2024-08-20 , DOI: 10.1016/j.eneco.2024.107842 Pedro S. Oliveira , Fernando A.F. Ferreira , Marina Dabić , João J.M. Ferreira , Neuza C.M.Q.F. Ferreira
The circular economy has emerged as a crucial way for companies to achieve their sustainability goals. Numerous businesses, especially small and medium-sized enterprises (SMEs), are integrating circular-economy projects into their operations. However, this undertaking presents multiple challenges as many managers must grapple with constraints in resources and expertise. This study’s primary objective is to develop a process-oriented decision-making system designed to deal with complex circular-economy scenarios. The proposed analysis system can help SMEs identify the driving forces behind circular-economy principles and evaluate the intricate connections between these determinants, using a unique combination of multiple criteria decision analysis methods (i.e. , cognitive mapping, and interpretive structural modeling). Collaborative sessions involving circular-economy experts were instrumental in refining the analysis system, and in-depth discussions with other specialists from the International Labor Organization further enriched this decision-support system. The findings include that circular-economy drivers can be grouped into five clusters: products , processes , policies/regulations , attitudes/behaviors , and communication/awareness . This structured breakdown provides SMEs with the tools to comprehend and address the pivotal factors that shape circular-economy initiatives. This pioneering study thus produced a comprehensive decision-making model attuned to the intricacies of the circular economy while highlighting the benefits of collaborative endeavors involving industry experts and global decision makers.
中文翻译:
使用解释性结构模型分析 SMES 中循环经济驱动因素的因果动态
循环经济已成为公司实现可持续发展目标的重要方式。许多企业,尤其是中小企业 (SME),正在将循环经济项目整合到其运营中。然而,这项任务带来了多重挑战,因为许多管理者必须努力克服资源和专业知识的限制。本研究的主要目标是开发一个以过程为导向的决策系统,旨在处理复杂的循环经济情景。所提出的分析系统可以帮助中小企业确定循环经济原则背后的驱动力,并使用多标准决策分析方法(即认知映射和解释性结构建模)的独特组合来评估这些决定因素之间的复杂联系。涉及循环经济专家的合作会议有助于完善分析系统,与国际劳工组织的其他专家的深入讨论进一步丰富了这一决策支持系统。研究结果包括,循环经济驱动因素可分为五类:产品、流程、政策/法规、态度/行为和沟通/意识。这种结构化的细分为中小企业提供了理解和解决影响循环经济计划的关键因素的工具。因此,这项开创性的研究产生了一个全面的决策模型,该模型与循环经济的复杂性相适应,同时强调了行业专家和全球决策者共同努力的好处。
更新日期:2024-08-20
中文翻译:
使用解释性结构模型分析 SMES 中循环经济驱动因素的因果动态
循环经济已成为公司实现可持续发展目标的重要方式。许多企业,尤其是中小企业 (SME),正在将循环经济项目整合到其运营中。然而,这项任务带来了多重挑战,因为许多管理者必须努力克服资源和专业知识的限制。本研究的主要目标是开发一个以过程为导向的决策系统,旨在处理复杂的循环经济情景。所提出的分析系统可以帮助中小企业确定循环经济原则背后的驱动力,并使用多标准决策分析方法(即认知映射和解释性结构建模)的独特组合来评估这些决定因素之间的复杂联系。涉及循环经济专家的合作会议有助于完善分析系统,与国际劳工组织的其他专家的深入讨论进一步丰富了这一决策支持系统。研究结果包括,循环经济驱动因素可分为五类:产品、流程、政策/法规、态度/行为和沟通/意识。这种结构化的细分为中小企业提供了理解和解决影响循环经济计划的关键因素的工具。因此,这项开创性的研究产生了一个全面的决策模型,该模型与循环经济的复杂性相适应,同时强调了行业专家和全球决策者共同努力的好处。