Role of GHG information presentation in shaping EV preferences: machine learning approach
研究了温室气体信息的不同呈现方式如何影响不同人群对电动汽车的偏好，发现合适的呈现方式可将选择概率提高20%以上。
• The influence of vehicle labels on EV preferences was tested. • Different framings should be applied to communicate with different populations. • Appropriate communication can increase the probability of EV choice by over 20%. • Younger populations are more sensitive to GHG information presentation. One of the factors significantly contributing to EV preferences is how greenhouse gas (GHG) information is presented. This study aimed to identify the best GHG information presentation to communicate with different populations. Therefore, seven new framings for GHG information presentation were tested based on theories such as psychological distancing. The performance of these framings was compared with the GHG information presentation applied to current vehicle labels in Canada. A survey of over 2000 participants was administered. The optimal label for communicating with different populations was identified, and the influence of different framings on EV preference probability was calculated. The results confirmed the importance of GHG information presentation on EV preference/choice. Further, it was postulated that different framings should be applied to communicate with various populations. Some of the framings developed in this study could increase the EV preference probability by over 20% (e.g., disaster-based framing for residents of Alberta).