Publication Status

Accepted/In press

Document Type

Journal article

Department / Unit

Department of Computing and Decision Sciences

Journal Title

European Journal of Operational Research

Publication Date

11-18-2013

Language

English

Volume

235

First Page

329

Last Page

333

Keywords

Electric vehicle, Supply chain, Price discount, Incentive scheme

Abstract

We investigate an automobile supply chain where a manufacturer and a retailer serve heterogeneous consumers with electric vehicles (EVs) under a government’s price-discount incentive scheme that involves a price discount rate and a subsidy ceiling. We show that the subsidy ceiling is more effective in influencing the optimal wholesale pricing decision of the manufacturer with a higher unit production cost. However, the discount rate is more effective for the manufacturer with a lower unit production cost. Moreover, the expected sales are increasing in the discount rate but may be decreasing in the subsidy ceiling. Analytic results indicate that an effective incentive scheme should include both a discount rate and a subsidy ceiling. We also derive the necessary condition for the most effective discount rate and subsidy ceiling that maximize the expected sales of EVs, and obtain a unique discount rate and subsidy ceiling that most effectively improve the manufacturer’s incentive for EV production.

DOI

10.1016/j.ejor.2013.11.021

ISSN

0377-2217

Fulltext file version

Accepted author manuscript

Comment

For this research, the first author (Chunlin Luo) is supported by the National Natural Science Foundation of China under Grant No. 71261006. The second author (Mingming Leng) is supported by the General Research Fund of the Hong Kong Research Grants Council under Research Project No. LU341012. The third author (Jian Huang) is supported by the National Natural Science Foundation of China under Grant Nos. 70901036, 71371089, and 71101067, and is also supported by the Jiangxi University of Finance and Economics’s Excellent Young Researcher Support Scheme under Grant No. 00252025.

Pure ID

5664084

Pure UUID

a44e045c-afc8-42b7-8ca7-a8dbc710a5e3

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