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OV-fiets: where to go? : a study on OV-fiets user characteristics and destinations

Pluister, Bas (2022) OV-fiets: where to go? : a study on OV-fiets user characteristics and destinations.

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Abstract:Not much is known about OV-fiets (a Station-Based Round-Trip bikesharing scheme (SBRT)) destinations and users, although OV-fiets have existed since 2008 with yearly increasing trips. The OV-fiets is operated by NS Stations (a subsidiary of the Nederlandse Spoorwegen (NS)) and allow for the station-to-door part of the trip and improves the door-to-door trip. This accommodates the change of public transport from station-to-station mobility to door-to-door trips. The NS is the Netherlands' national railway operator and a major public transport actor. The NS also changes from a pure railway company to a mobility company. The knowledge gap on OV-fiets makes strategic decisions, such as capacity planning, difficult to make. The research aims to get insights on OV-fiets user characteristics and OV-fiets user destinations. A revealed preference survey collected 1538 responses with individual characteristics (e.g. socio-economic characteristics, and preferences and habits) and trip characteristics (e.g. destinations, frequencies and purposes). The survey was representative of weekday peak hours, which were around 70% of all weekly trips. With the individual characteristics, a multinomial logit model was estimated to determine the purpose of an OV-fiets user. With the destinations and built environment characteristics, a binomial logistic regression model was estimated to determine the probability of a destination being chosen by an OV-fiets user. The OV-fiets user in the collected sample was highly educated, young, and regularly travel with OV-fiets to and from work. The median of an OV-fiets trip is 3 kilometres or 10 minutes. High-density areas and facilities with work or business functions, such as offices or meeting locations, increased the probability of a destination being chosen. The distance between 1150 and 3800 meters had the strongest influence on the destination probability. The results of the models for the example case of the city Eindhoven showed that the main hotspots for destinations were visible in the industrial/office area De Hurk, the offices of Eindhoven Airport, the city centre and the university locations. Contributors of those locations were the high density of buildings and work-focused facilities. In more detail to user characteristics, trips with student travel cards were attracted by the high-tech campus university location more than other card types. Moreover, business card trips were more spatially distributed, while on-balance card trips were more clustered in the area, despite their equal trip amounts. The research results show the key statistics of OV-fiets trips and the general OV-fiets user for weekday peak hours. Furthermore, it showed the main predictors for the destination of OV-fiets users, which were the distance between 1150 and 3800 metres and a high-density built environment.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
Link to this item:https://purl.utwente.nl/essays/93399
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