Optimising Warehouse Order Picking: Real Case Application in the Shoe Manufacturing Industry DOI Creative Commons
Rodrigo Furlan de Assis, William de Paula Ferreira,

Alexandre Frias Faria

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 170868 - 170888

Опубликована: Янв. 1, 2024

Язык: Английский

Roadmap to reach global net-zero emissions for developing regions by 2085 DOI Creative Commons

Garima Acharya,

Pramish Paudel,

D. J. Arent

и другие.

Cell Reports Sustainability, Год журнала: 2025, Номер unknown, С. 100306 - 100306

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

A systematic review of Agent-based modelling in the Circular Economy: Insights towards a general model DOI Creative Commons
Massimiliano Rizzati, Matteo Landoni

Structural 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

5

Impact of optimized gas-liquid separator on temperature and frost distribution in electric vehicle heat pump AC DOI
Kang Li,

Miao Yanming,

Dingyu Xia

и другие.

Applied Thermal Engineering, Год журнала: 2024, Номер 248, С. 123282 - 123282

Опубликована: Апрель 26, 2024

Язык: Английский

Процитировано

5

Electric Vehicle (EV) Market Penetration in Countries with Rising Motorization Rates DOI
Hediye Tuydes-Yaman, Ege Cem Saltık, Hediye Tüydeş-Yaman

и другие.

International Journal of Civil Engineering, Год журнала: 2024, Номер unknown

Опубликована: Окт. 9, 2024

Язык: Английский

Процитировано

5

Promoting the Diffusion of Sustainable Innovations through Customer Education—A Case of the Cosmetic Industry DOI Open Access
Hongyi Chen, Turuna S. Seecharan, Chen Feng

и другие.

Sustainability, 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

3

Prospects for the development of hydrogen fuel cell vehicles in China DOI
Xiaopeng Guo, Wenjing Li, Dongfang Ren

и другие.

Renewable Energy, Год журнала: 2024, Номер unknown, С. 122231 - 122231

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

3

Synergies Between Virtual Commissioning and Digital Twins DOI Creative Commons

Hermann Boris Djeulezeck Tanegue,

William de Paula Ferreira, Rodrigo Furlan de Assis

и другие.

Опубликована: Фев. 24, 2025

Язык: Английский

Процитировано

0

How demand-side incentive policies drive the diffusion of forest wellness tourism products: An agent-based modeling analysis DOI
Ying Li, Yuxin Liu, Wenlong Wang

и другие.

Forest Policy and Economics, Год журнала: 2025, Номер 174, С. 103496 - 103496

Опубликована: Апрель 25, 2025

Язык: Английский

Процитировано

0

Agent-based modelling of electric vehicle adoption: A multidimensional perspective assessment DOI Creative Commons
Lorella Cannavacciuolo,

Vincenzo Maione,

Cristina Ponsiglione

и другие.

Research in Transportation Business & Management, Год журнала: 2025, Номер 61, С. 101407 - 101407

Опубликована: Май 13, 2025

Язык: Английский

Процитировано

0

Impacts of Consumers’ Heterogeneity on Decision-Making in Electric Vehicle Adoption: An Integrated Model DOI Open Access
Wen Xu, Irina Harris, Jin Li

и другие.

Sustainability, 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

0