Abstract: In order to reveal the demand distribution mechanism of shared electric vehicles, this paper explores the impact of latent variables such as personal carbon trading, risk, and habits on travel location choice behavior of shared electric vehicles. Based on the questionnaire data of Beijing City, this paper establishes a multiple indicators multiple causes (MIMIC) model to quantify the unobserved latent variables in the framework of the theory of planned behavior, and integrates the latent variable model and Mixed Logit model to construct a hybrid choice model. The results of the model estimation show that gender, education, occupation, car ownership and driving age all have great influence on psychological latent variables. Personal carbon trading, risk, subjective norms, behavioral intention and perceived behavioral control have significant influence on the choice of travel location. Parking lots, subway stations and shopping malls all have significant influence on the choice of travel location, while bus routes have no significant influence. According to the model results, relevant suggestions are put forward to develop shared electric vehicles in different travel locations.
Keywords: traffic engineering; demand distribution mechanism; hybrid choice model; shared electric vehicle; psychological latent variable; multiple indicators multiple causes(MIMIC) model
合肥工业大学学报自科版