A KPI System to Measure Bicycle Attractiveness of a City

Johannes Schering (), Jorge Marx Gómez () and Frank Köster ()
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Johannes Schering: University of Oldenburg
Jorge Marx Gómez: University of Oldenburg
Frank Köster: Institute for AI Safety and Security

A chapter in Smart and Secure Embedded and Mobile Systems, 2024, pp 105-116 from Springer

Abstract: Abstract Many municipalities want to become more bicycle friendly. More people should be convinced to use the bike more often to strengthen the location as an attractive city. In this process bicycle data has become available from many regions and use cases to support decision making processes. One research problem is how different data sources and related Key Performance Indicators (KPIs) can be meaningful connected. It can be expected that there will be data sources that are more relevant than others. In addition, many of the calculated numbers will be depending from other indicators (e.g. number of bike connections and number of trips). Decision makers would like to know more about the attractiveness of the bicycle infrastructure. As part of this contribution we suggest a KPI system that is inspired by the DuPont System of financial control as a solution. There are many data sources available as smartphone app data, mobile sensor data, parking and counting data, cycling path and road conditions data (e.g. surface types, length, width), citizen reporting data or (near) accident data. We suggest to classify these data sources and related KPIs according to the categories Bicycle Use, Bicycle Infrastructure and Traffic safety. In the conclusion further development steps on the path to an interconnected cycling KPI system will be described.

Keywords: KPI system; Bicycle infrastructure; Bicycle attractiveness; Bicycle data (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-56603-5_10

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