The present study aims to reveal the contributing factors for train delays in Tokyo metropolitan area by conducting statistical analyses, focusing on passenger trains, and using a variety of information by including data concerning train cars, stations, passengers, tracks and working timetables as explanatory variables. The present study conducted 2 types of statistical analyses including the standard multiple regression analysis and the logistic regression analysis by setting “average delay time” which indicates the quantitative conditions of delays, and “occurrence of delays” which indicates the qualitative condition, as objective variables. According to the results of the logistic regression analysis, the possibility of direct operations increasing the delay occurrence rate was quantitatively indicated. Therefore, direct operations are regarded as a contributing factor for train delays concerning metropolitan areas in recent years. Additionally, it was confirmed that the concentration of demand on terminal stations is also a contributing factor for train delays. On the other hand, it is certain that direct operations contribute to improv ing the convenience of passengers as well as the operational efficiency of train cars. Therefore, it would be ideal to resolve delays by easing the concentration of demands which may be accomplished by recommending off-peak commuting as well as adjustments to the working timetables .
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