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공유 전동킥보드 이용 예측력에 대한 모형 및 영향요인에 관한 연구

A Study on the Inter-Model Comparison and Influencing Factors on the Use Predictive Power of Shared E-scooter

이동민|김대원
한국ITS학회 (The Korean Society of Intelligent Transport Systems)|2024.06|한국ITS학회 논문지 (Journal of Korean Society of Intelligent Transport Systems)|제23권 제3호|pp. 29-47|DOI https://doi.org/10.12815/kits.2024.23.3.29

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키워드

영향요인공유 전동킥보드영향권Geographically Weighted RegressionInfluencing factor모형 비교 분석지리가중회귀모형Shared E-scooterComparative analysis modelInfluencing Scope

초록

공유 전동킥보드 실적자료를 기반으로 공유 전동킥보드 이용에 유의미한 영향을 미치는 요인을 도출한 연구는 국내외 다수 존재하나, 이용 예측력을 활용하여 모형을 비교 분석하고 타지역에 대한 적용을 통해 최적의 예측모형을 구축한 연구는 아직 많이 이루어지지 않았다. 따라서 본 연구에서는 국내의 공유 전동킥보드 실적자료를 활용하여 광진구 및 강남구 지역에대한 세부적인 공유 전동킥보드 이용 영향요인 및 영향권을 명확히 정립함으로써 이용 예측력을 높이고, 공간적 자기상관성 검증을 통해 지역적 특성을 반영한 최적의 모형으로 지리가중회귀모형을 도출하였다. 본 결과를 바탕으로 지역적 차이에 따라 발생하는 구축 모형의 방향성을 제시하고, 실제 이용량과 모형 예측량의 차이에 따른 이용자 관점에서의 주요 시사점을도출하였다.

Abstract

Many domestic and foreign studies derive factors that significantly affect the use of shared E-scooters based on performance data, but few studies have been conducted with comparative analysis models using predictive power, applying them to other regions. Therefore, by clearly establishing detailed influencing factors and scope in Gwangjin-gu and Gangnam-gu by using domestic shared E-scooter performance data, this study enhances predictive power, and the Geographically Weighted Regression model is derived through spatial autocorrelation verification. Based on the results, the direction of a construction model created from regional differences was presented, and major implications from the user's perspective are derived based on the difference between actual use and the model’s prediction.

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