This study aims to identify latent classes among shared e-scooter users based on their characteristics and analyze the differences in personal and usage characteristics across these classes. Specifically, the study has the following key objectives: (1) to select variables related to the personal and usage characteristics of shared e-scooter users; (2) to collect data on the personal and usage characteristics of shared e-scooter users; (3) to derive the latent classes of shared e-scooter users; and (4) to test the differences in personal and usage characteristics across the identified latent classes. Variables related to the personal and usage characteristics of shared e-scooter users were selected based on a literature review. Through a survey, data on the personal and usage characteristics of shared e-scooter users were collected. A latent class analysis (LCA) was performed to derive the latent classes of shared e-scooter users. Finally, a chi-square analysis was conducted to test the differences in personal and usage characteristics across the latent classes of shared e-scooter users. The results of this study are as follows. The personal characteristics of shared e-scooter users were identified as age and sex, whereas the usage characteristics were identified as usage frequency, time periods of e-scooter usage, return/rental zones, return/rental places, and types of roads used. Data on sex, age, usage frequency, periods of e-scooter usage, and return/rental locations were collected from 278 shared e-scooter users. Based on information criterion, statistical validation, and the entropy index, four latent classes of shared e-scooter users were identified: “male users with a commuting purpose in business zones,” “male users with a homeward commuting purpose in residential zones,” “female users with a leisure purpose in park/green zones,” and “users in their 20s with a commuting purpose in residential zones.” The results of a chisquare analysis revealed statistically significant differences (p < 0.05) in the personal and usage characteristics across the latent classes. Shared e-scooter user types were classified through Latent Class Analysis (LCA), and differences in personal and usage characteristics were identified across the classes. The preferred usage environments and conditions for each class of shared e-scooter users are determined. Variables related to the return/rental zone and periods of e-scooter usage showed the most significant differences among the classes. These findings can contribute to the development of customized user policies and the improvement of services based on the characteristics of shared e-scooter users.

In this study, we analyze the design preferences of parking spaces for shared e-scooters. The detailed purposes are to develop the attributes and attribute levels for the design of shared e-scooter parking spaces, derive profiles by combining the attributes and attribute levels of parking space design, collect preference data on parking-space design from shared e-scooter users, and analyze the preferences for parking space design. The attributes and attribute levels for the design of shared e-scooter parking spaces were developed based on a literature review and an investigation of shared e-scooter parking spaces. Using the full profile method and orthogonal design, the profiles were derived by combining the attribute levels. Preference data for parking space profiles were collected from shared e-scooter users using survey cards to visualize the profiles. Preferences for parking-space design were analyzed using conjoint analysis. Through a literature review and case studies, three attributes: parking angle and direction, parking unit, and parking method, along with their attribute levels were developed. By combining the attributes and their levels, 16 profiles for parking spaces were created. Preference data for these parking-space profiles were collected from 278 shared e-scooter users using a 10-point Likert scale. Using conjoint analysis, the utility and importance of the attributes and attribute levels for parking space design were analyzed. A parking-space design plan that considers the preferences of shared e-scooter users was proposed. The utilities of the attribute levels for shared e-scooter parking space design were derived. Among the attribute levels, the 'compact parking unit' showed the highest utility for the parking unit, whereas 'head-in parking' had the highest utility for the parking method. For parking angle and direction, 'perpendicular parking' had the highest utility, followed by '45°, direction toward the facility’s passageway.' The importance of the attributes for shared e-scooter parking space design was also derived, with 'parking angle and direction' being the most important attribute. Finally, a parking space design plan for shared e-scooters was proposed using visualized survey cards.

PURPOSES : This study presents a formula for calculating the parking capacity of shared e-scooter parking spaces using the dimensions of the clearance spaces of sidewalks. The details are as follows: First, the discontinuity angle of the parking unit placement is derived. Second, the parameters of the sidewalk clearance lengths are derived. Third, a formula for calculating the parking capacity of shared e-scooter parking spaces is derived. Finally, we examine the applicability of the parking capacity calculation formula to actual sidewalk clearance spaces. METHODS : Based on literature reviews, a formula for the discontinuity angle of parking unit placement was derived using the sidewalk clearance widths and the geometric structure of parking units. Formulas for the parameters of the sidewalk clearance lengths were derived using the sidewalk clearance lengths and the geometric structure of the parking units. A formula for parking capacity calculation was derived using the formula for the parameters of the sidewalk clearance lengths and the discontinuity angle. Examples of the application of the parking capacity calculation formula to actual sidewalk clearance spaces are presented. RESULTS : The results of this study are listed as follows: The discontinuity angle for the placement of standard shared e-scooter parking units was derived. Additionally, a formula for the sidewalk clearance lengths was derived. Moreover, a formula for calculating the parking capacity of shared e-scooter parking spaces based on sidewalk clearance lengths and widths was derived. Finally, examples of the application of the parking capacity calculation formula to actual sidewalk clearance spaces are presented. CONCLUSIONS : A formula for calculation of the parking capacity of shared e-scooter parking spaces using the dimensions of the clearance space of sidewalks was derived and proposed. The parking capacity calculation formula presented in this study can contribute to the design of parking spaces to accommodate dockless shared e-scooters on sidewalks. Furthermore, it can also contribute to accommodating other types of dockless mobility. Future research can focus on designing parking spaces that consider the parking demands for shared e-scooters.