EconPapers    
Economics at your fingertips  
 

Consumer learning behavior in choosing electric motorcycles

Yen-Ching Sung

Transportation Planning and Technology, 2010, vol. 33, issue 2, 139-155

Abstract: The purpose of this paper is to understand the effect of the learning process on consumers' choice behavior for electric motorcycles in Taiwan. The electric motorcycle is a new technological product so consumers need to gather all kinds of information -- performance, operating cost, government subsidy policy, etc. -- to reduce their uncertainty about the product. In this paper, a four-stage stated preference experiment is designed and a survey applied. At each stage, the survey gives respondents new information about the electric motorcycle. In this process, respondents gather information and update their expectation about electric motorcycles in a Bayesian manner. This paper calibrates a Bayesian learning process model to the data. The results show that respondents have a higher quality perception of the electric motorcycle than the gasoline motorcycle and there is heterogeneous learning across respondents. The manufacturers can use these to target specific consumers to promote the electric motorcycle.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/03081061003643747 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:transp:v:33:y:2010:i:2:p:139-155

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GTPT20

DOI: 10.1080/03081061003643747

Access Statistics for this article

Transportation Planning and Technology is currently edited by Dr. David Gillingwater

More articles in Transportation Planning and Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:transp:v:33:y:2010:i:2:p:139-155