Circulise, a model-driven framework to build and align socio-technical systems for the twin transition: Fanyatu’s case of sustainability in reforestation
IF 7.5 1区 计算机科学Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
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引用次数: 0
Abstract
Building circular economic systems is crucial to address ecological challenges like climate change. The twin transition suggests that, to maximize the impact of sustainable solutions, humans and (disruptive) technologies need to be effectively integrated. Methods to conceptually build such (eco)systems integrating these and assess their ecological impact before implementation are lacking. This paper addresses this gap by proposing the Circulise framework, a model-driven method designed to build circular systems and evaluate their environmental performance. The approach promotes design-thinking to create socio-technical ecosystems that can be evaluated at the light of their alignment with circular economy and/or sustainability principles and be used to generate operational software behavior. The Circulise framework was developed following the methodological guidance of design science research. It is applied in this paper to the case of Fanyatu, a non-profit organization focused on reforestation in the Congo Basin, showing its ability to create a circular ecosystem not only supporting the creation of regenerative CO-absorbing forests but also empowering and improving the quality of life of the local communities involved in the planting of trees. In Fanyatu’s case, Circulise’s strategic planning and technology integration lead to virtuous cycles, enabling a snowball effect in forest creation and the promotion of sustainable projects. The framework’s scalability and versatility allow it to be applied across various contexts, enabling the creation of customized circular ecosystems for sustainability tailored to specific human and technological needs.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.