Fare revenue forecast in public transport: A comparative case study

Jonas Krembsler, Sandra Spiegelberg, Richard Hasenfelder, Nicki Lena Kämpf, Thomas Winter, Nicola Winter and Robert Knappe

Research in Transportation Economics, 2024, vol. 105, issue C

Abstract: This paper presents results from a case study of fare revenue prediction in public transportation in Berlin using machine learning and time series analysis. Our work aims to aid in the implementation of automated revenue controlling and data-driven decision support within existing controlling processes.

Keywords: Public transport; Forecast; Revenue; Time series; Regression; Revenue controlling; Machine learning (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.retrec.2024.101445

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