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.

ABSTRACT
1. 서론
    1.1. 연구배경 및 목적
    1.2. 연구수행절차
2. 문헌연구
    2.1. 공유형 전동킥보드 이용특성에 대한 검토
    2.2. 잠재계층분석(LCA)에 대한 검토
3. 연구 방법
    3.1. 변수선정 방법
    3.2. 데이터 수집 방법
    3.3. 잠재계층분석(LCA) 방법
    3.4. 잠재계층간 공유형 전동킥보드 이용자의 특성차이검증 방법
4. 결과
    4.1. 변수선정 결과
    4.2. 데이터 수집 결과
    4.3. 잠재계층분석(LCA) 결과
    4.4. 잠재계층간 공유형 전동킥보드 이용자의 특성차이검증 결과
5. 결론
REFERENCES

• 구건형(경기대학교 도시, 교통공학과 석사과정) | Gu Gun-hyeong
• 오흥운(경기대학교 도시, 교통공학과 교수) | Oh Heung-un