Utilizing Stated Preference in Electric Vehicle Research; Evidence from the Literature

TLDR: In this paper, stated preference surveys in the context of electric vehicle (EV) research have been analyzed and a number of strategies have been discussed to minimize hypothetical bias associated with SP survey, which will be discussed in this paper.

Abstract: The existing literature on stated preference (SP) surveys in the context of electric vehicle (EV) research has emphasized data analysis and the mathematical side of choice modeling, while some important elements of SP surveys such as procedures relating to alternatives/attributes/levels selection have been under-emphasized. This study aims to fill in this gap while analyzing the previous practice of SP surveys in the context of EV research. Even though, SP surveys have become the standard practice for evaluation of a new product such as the EVs, there are a number of associated disadvantages. SP data are hypothetical and may be affected by the degree of ‘contextual realism’ one establishes for the respondents. As a consequence, they may not necessarily represent actual behavior of respondents in the real market. A number of strategies however exist to minimize hypothetical bias associated with SP survey, which will be discussed in this paper. To make the choice scenarios as close as possible to real world situation, special attention must be paid to identifying factors influencing choices. The purpose of this review is to identify factors that have been found consistently in the previous research to affect consumer choice. This is followed by highlights of some limitations within the existing literature. Knowing these limitations opens windows for future work, and allows for more accurate interpretation of estimation results with regard to forecasting and policy analysis. Finally, a discussion on how to overcome these limitations is presented following by a number of recommendations regarding SP survey design.