How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure

This paper develops an agent-based model with linking variables (ABML) to investigate the influencing factors for the new energy vehicles (NEVs) market in China. The ABML is a framework with three-level variables including micro, linking, and macro variables, which can reduce the complexity of the s...

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Autores principales:	Mo Chen, Rudy X. J. Liu, Chaochao Liu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	new energy vehicles agent-based model linking variables China market penetration Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/14255dc3157344a79b7a299c28de0bc1
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spelling	oai:doaj.org-article:14255dc3157344a79b7a299c28de0bc12021-11-11T19:51:03ZHow to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure10.3390/su1321123072071-1050https://doaj.org/article/14255dc3157344a79b7a299c28de0bc12021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/12307https://doaj.org/toc/2071-1050This paper develops an agent-based model with linking variables (ABML) to investigate the influencing factors for the new energy vehicles (NEVs) market in China. The ABML is a framework with three-level variables including micro, linking, and macro variables, which can reduce the complexity of the simulation. The emergence from bottom to top occurs between linking and macro variables, while the best–worst scaling describes the mapping between micro and linking variables. In the case study, Rookie, Veteran, and New Generation consumers are assumed as the three types of consumers in China’s market. A specification of the three types of variables is presented, where the value of linking variables obeys uniform distribution. By introducing the population density and the interaction frequency, the number of agents is determined with an experiment. All parameters in the model are estimated by calibrating the realistic vehicle sales. We compare different scenarios and obtain some management insights for improving the market penetration of NEVs in China.Mo ChenRudy X. J. LiuChaochao LiuMDPI AGarticlenew energy vehiclesagent-based modellinking variablesChinamarket penetrationEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12307, p 12307 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	new energy vehicles agent-based model linking variables China market penetration Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	new energy vehicles agent-based model linking variables China market penetration Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Mo Chen Rudy X. J. Liu Chaochao Liu How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure
description	This paper develops an agent-based model with linking variables (ABML) to investigate the influencing factors for the new energy vehicles (NEVs) market in China. The ABML is a framework with three-level variables including micro, linking, and macro variables, which can reduce the complexity of the simulation. The emergence from bottom to top occurs between linking and macro variables, while the best–worst scaling describes the mapping between micro and linking variables. In the case study, Rookie, Veteran, and New Generation consumers are assumed as the three types of consumers in China’s market. A specification of the three types of variables is presented, where the value of linking variables obeys uniform distribution. By introducing the population density and the interaction frequency, the number of agents is determined with an experiment. All parameters in the model are estimated by calibrating the realistic vehicle sales. We compare different scenarios and obtain some management insights for improving the market penetration of NEVs in China.
format	article
author	Mo Chen Rudy X. J. Liu Chaochao Liu
author_facet	Mo Chen Rudy X. J. Liu Chaochao Liu
author_sort	Mo Chen
title	How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure
title_short	How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure
title_full	How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure
title_fullStr	How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure
title_full_unstemmed	How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure
title_sort	how to improve the market penetration of new energy vehicles in china: an agent-based model with a three-level variables structure
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/14255dc3157344a79b7a299c28de0bc1
work_keys_str_mv	AT mochen howtoimprovethemarketpenetrationofnewenergyvehiclesinchinaanagentbasedmodelwithathreelevelvariablesstructure AT rudyxjliu howtoimprovethemarketpenetrationofnewenergyvehiclesinchinaanagentbasedmodelwithathreelevelvariablesstructure AT chaochaoliu howtoimprovethemarketpenetrationofnewenergyvehiclesinchinaanagentbasedmodelwithathreelevelvariablesstructure
_version_	1718431392394641408

How to Improve the Market Penetration of New Energy Vehicles in China: An Agent-Based Model with a Three-Level Variables Structure

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