
IEEE Access, Год журнала: 2024, Номер 12, С. 170868 - 170888
Опубликована: Янв. 1, 2024
Язык: Английский
IEEE Access, Год журнала: 2024, Номер 12, С. 170868 - 170888
Опубликована: Янв. 1, 2024
Язык: Английский
Cell Reports Sustainability, Год журнала: 2025, Номер unknown, С. 100306 - 100306
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1Structural Change and Economic Dynamics, Год журнала: 2024, Номер 69, С. 617 - 631
Опубликована: Апрель 4, 2024
Circular Economy (CE) is a popular topic for governments and businesses around the world; yet, only few comprehensive economy-wide frameworks exist, consequences of CE on economic systems stay unclear. With this systematic review, we put under scrutiny existing contributions to that apply Agent-based modelling methodology. There an open gap in literature regarding use ABM. The research question guides review concerns potential benefit ABM how methodology context CE. We evidence three thematic areas, two agents one process, namely producers, i.e. firms industrial systems, consumers, households waste disposal, diffusion innovation. infer former strands can be further synthetized together form general model Economy. This development crucial properly evaluate agent's heterogeneity affects adoption practices economy. Research has widely applied simulations consider impact among individuals their behavioural interactions evolution complex yet very little did it systematically about Our results complement those Computable General Equilibrium models. provides interpretative framework, suggests valuable future directions within new area, contributes theoretical managerial discussion agent-based circular
Язык: Английский
Процитировано
5Applied Thermal Engineering, Год журнала: 2024, Номер 248, С. 123282 - 123282
Опубликована: Апрель 26, 2024
Язык: Английский
Процитировано
5International Journal of Civil Engineering, Год журнала: 2024, Номер unknown
Опубликована: Окт. 9, 2024
Язык: Английский
Процитировано
5Sustainability, Год журнала: 2024, Номер 16(6), С. 2583 - 2583
Опубликована: Март 21, 2024
This article investigates whether customer education about the sustainability advantage of a sustainable innovation helps promote diffusion such using survey and an experimental study in cosmetic industry. Educating customers to equip them with awareness, know-how, principal knowledge promotes their motivation toward adoption thus facilitates innovation. Specifically, results show that educating product ingredients, definition, green certification increases customers’ intention towards checking products for avoiding contain harmful purchasing next two years. Customers will also have more trust adopt certified products, they regard is truly as factor important than its price purchase decisions. Finally, comprehensive list factors contribute customer’s perception product, well ranking given by participants, are discussed.
Язык: Английский
Процитировано
3Renewable Energy, Год журнала: 2024, Номер unknown, С. 122231 - 122231
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
3Опубликована: Фев. 24, 2025
Язык: Английский
Процитировано
0Forest Policy and Economics, Год журнала: 2025, Номер 174, С. 103496 - 103496
Опубликована: Апрель 25, 2025
Язык: Английский
Процитировано
0Research in Transportation Business & Management, Год журнала: 2025, Номер 61, С. 101407 - 101407
Опубликована: Май 13, 2025
Язык: Английский
Процитировано
0Sustainability, Год журнала: 2025, Номер 17(11), С. 4981 - 4981
Опубликована: Май 29, 2025
Understanding consumer heterogeneity is crucial for analysing attitude formation and its role in innovation diffusion. Traditional top-down models struggle to reflect the nuanced characteristics activities of population, while bottom-up approaches like agent-based modelling (ABM) offer ability simulate individual decision-making social networks. However, current ABM applications often lack a strong theoretical foundation. This study introduces novel, theory-driven framework examine formation, focusing on electric vehicle (EV) adoption across segments. The model incorporates non-linear rules grounded established theories, incorporating Rogers’s Diffusion Innovations, Social Influence Theory, Theory Planned Behaviour. agents are characterised using UK empirical data, segmented into early adopters, majority, late laggards. interactions simulated, micro-validated, optimised supervised machine learning (SML) approaches. results reveal that adopters majority highly responsive influences, environmental beliefs, external events such as pandemic war conflict performing pro-EV attitudes. In contrast, laggards show more stable or delayed responses. These findings provide actionable insights targeting segments enhance EV strategies.
Язык: Английский
Процитировано
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