다중회귀분석을 활용한 도시철도 이용승객 더움민원에 관한 분석 및 감소방안에 관한 연구

Abstract

Using multiple regression analysis, this study attempted to identify causality between variables based on four variables: daily passenger demand using urban railways, daily outdoor average temperature, daily number of hot complaints, and daily precipitation and suggest improvement measures to reduce hot complaints in trains. As a result of the study, in the regression analysis considering seasonal temperatures, the necessity of setting a more realistic appropriate temperature was identified than now because the average daily outside temperature absolutely did not directly affect the number of daily hot complaints. In particular, during the change of seasons and precipitation, active efforts are needed to come up with effective countermeasures against hot complaints that are more active in the recommended temperature in the train cabin than in the current response method.