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Oliveira, P. S. P. C., Ferreira, F. A. F., Dabić, M., Ferreira, J. J. M. & Ferreira, N. C. M. Q. F. (2024). Analyzing the causal dynamics of circular-economy drivers in SMES using interpretive structural modeling. Energy Economics. 138
P. S. Oliveira et al., "Analyzing the causal dynamics of circular-economy drivers in SMES using interpretive structural modeling", in Energy Economics, vol. 138, 2024
@article{oliveira2024_1731867528552, author = "Oliveira, P. S. P. C. and Ferreira, F. A. F. and Dabić, M. and Ferreira, J. J. M. and Ferreira, N. C. M. Q. F.", title = "Analyzing the causal dynamics of circular-economy drivers in SMES using interpretive structural modeling", journal = "Energy Economics", year = "2024", volume = "138", number = "", doi = "10.1016/j.eneco.2024.107842", url = "https://www.sciencedirect.com/journal/energy-economics" }
TY - JOUR TI - Analyzing the causal dynamics of circular-economy drivers in SMES using interpretive structural modeling T2 - Energy Economics VL - 138 AU - Oliveira, P. S. P. C. AU - Ferreira, F. A. F. AU - Dabić, M. AU - Ferreira, J. J. M. AU - Ferreira, N. C. M. Q. F. PY - 2024 SN - 0140-9883 DO - 10.1016/j.eneco.2024.107842 UR - https://www.sciencedirect.com/journal/energy-economics AB - 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. ER -