Research on parking app choice behavior based on MNL

Abstract

As a kind of intelligent parking mode, shared parking mode has been widely promoted, and parking app, as a product of the development of sharing economy in the field of transportation, is also being vigorously advocated. However, there are not many people who use parking app to find and reserve parking space in practice, which is largely caused by insufficient information provided by the parking apps. In order to better explain, predict and improve drivers’ choice of parking apps, a multinomial logit model was established to analyze the relationship between drivers’ parking app choice behavior and the influential factors. The influential factors include drivers’ individual characteristics and parking app’s attributes, which were extracted from a questionnaire and typical parking apps currently in operation. The results show that the reservation and shared parking spaces, available parking spaces, parking charges and distance to the destination are the main factors that determine the drivers’ choice of parking app. This paper provides a reference for the development of Ningbo parking apps.