Skip navigation

Subsidising an electric vehicle supply chain with imperfect information

Subsidising an electric vehicle supply chain with imperfect information

Gu, Xiaoyu, Ieromonachou, Petros ORCID: 0000-0002-5842-9585 and Zhou, Li ORCID: 0000-0001-7132-5935 (2019) Subsidising an electric vehicle supply chain with imperfect information. International Journal of Production Economics, 211. pp. 82-97. ISSN 0925-5273 (doi:https://doi.org/10.1016/j.ijpe.2019.01.021)

[img] PDF (Acceptance Email)
23386 IEROMONACHOU_Acceptance_Email_2019.pdf - Additional Metadata
Restricted to Repository staff only

Download (10kB) | Request a copy

Abstract

This paper studies a four-echelon vehicle supply chain consisting of government, an electric/gasoline vehicle manufacturer, a retailer and consumers. The purpose is to understand how government subsidies should be allocated in order to maximise total profit of the whole supply chain. By adopting Stackelberg game theory based on conditions of imperfect information, a mathematical model was developed. The results suggest that allocation of a subsidy in the electric vehicle supply chain should first be allotted for electric vehicle customers. Specifically, in the early development stage, if the subsidy budget is limited, all of them should be given to the purchasers of electric vehicle customer. With an increasing budget available for subsidies, more allocation to the electric vehicle manufacturer is expected. However, more subsidies does not necessarily lead to more electric vehicle purchases as there is a ceiling on the market for electric vehicles. In the later development stage, subsidies may not be important in promoting electric vehicle uptake.

Item Type: Article
Uncontrolled Keywords: Electric vehicle, Supply chain, Energy price, Subsidy policy, Stackelberg game, Imperfect information
Subjects: H Social Sciences > HB Economic Theory
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group
Faculty of Business > Department of Systems Management & Strategy
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Last Modified: 19 May 2019 21:57
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 3
URI: http://gala.gre.ac.uk/id/eprint/23386

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics