Consumer learning behavior in choosing electric motorcycles

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.