Abstract
We aim to provide insights into what makes bus service more reliable by analyzing a detailed data set from Butler, Pennsylvania. We employ multiple regression methodology to reduce omitted variables bias. Our dependent variable is run time deviation from schedule and our explanatory variables are drivers, vehicles, trips, months, and days of the work week. We find that problem drivers, lunch hour and afternoon peak times, November, and Fridays, are the variables that reduce bus reliability the most. Our study speaks to the critical need for information-intensive design and delivery of reliable bus service. Analyses of such databases help the public, in general, and the transit authorities, in particular, in providing efficient and effective bus service systems.
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