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. Keywords: Bayesian learningelectric motorcyclesstated preference experimentTaiwan Acknowledgements The author thanks Professor Liang-Shyong Duann for his considerable help on the earlier draft of this paper as well as Professor Michael Keane for his extensive and helpful comments on a later version of this paper. The author is grateful to the Faculty of Business in the University of Technology, Sydney for providing the research assistance to pursue more advanced research and finish this paper.