A literature review of over fifty worldwide studies on bicycle-transit yielded nearly forty factors. These influential factors can be grouped along the trip chain: transit, first/last-mile and the larger context. The three groups are composed of the following elements:
Transit related: System and operating service, journey, and station typology
First/last-mile: Regional climate, bicycle journey, and competition other modes
Context: Culture and attitude, and user characteristics
This paper first describes each group briefly and then presents the related factors in a table. Each factor’s relative influence on bicycle-transit demand is captured with a ++/+/−/− − symbol as a rough indication for a, respectively, (very) positive or (very) negative impact. We have not used a quantitative benchmark but followed the sources’ qualitative reflection. These indicators are compared among each other to help provide higher-level guidance on interpreting the factors. Note that correlations between factors will exist. For example, high levels of employment will closely correlate to more commuters on public transport.
For a more detailed description of the literature review we refer to the work of Leferink (2017), and for more understanding of the factors we refer to the original studies in the sources mentioned in the table and text.
It is not surprising that many of the factors for good bicycle-rail integration focus on the transfer area: the transit stop or station. This part of the transit journey is typically valued lowest by travellers (Peek and Van Hagen 2002).
The literature has a rich vocabulary related to transit networks, stations or stops, and the transit journey itself. For this research, the following definition of transit is used: a shared transport mode, in a network (connecting stops) that operates on an interval or timetable.
In the introduction, two types of bicycle-transit trip chains were presented. For the transit leg of a journey, bike-and-ride travellers are similar to other transit users after they have parked or collected their bicycle. The differences in transfers and transit may, therefore, mostly be experienced by bike-on-board travellers. This counts particularly for those with a fixed frame bicycle compared to a foldable bike.
Table 1 shows the influential factors related to the transit, their effect and main sources. They are discussed in more detail in the consecutive paragraphs.
Typically, the largest part of the bicycle-transit combination is the transit journey, both in terms of time and distance. Still on average 30–50% of the travel time of bicycle-transit is spent on access and egress according to a Dutch study using active travel diary information (Krygsman et al. 2004), with similar findings in the US (Flamm and Rivasplata 2014). It may be concluded that to compensate for the inconvenience and extra time required to collect, park or board a bicycle, the transit journey must be of significant length. Another study looking at the Dutch railway system stated that for bicycle-rail in particular, the total travel distance must be at least 10–15 km (Van der Loop 1997). For short trips, people may be more inclined to cycle the whole trip or use the car for a more convenient journey. The stated choice study described in the second section of this paper looks directly from a traveller’s point of view.
Transit stop typology
There are many studies on capturing general transit station’s attractiveness and accessibility. The relevant factors range from its cleanliness to location in the network, and from the feeling of security to the number of benches according to a Dutch literature study (Groenendijk et al. 2018). Not surprisingly, ensuring a good integration of bicycle-rail at the local station or transit stop level is a requirement. There are various ways to improve bicycle-transit trips directly. Guidelines from an EU knowledge and practice sharing project called BiTiBi mention six vital services: bicycle parking, public bicycles (see examples in Ma et al. 2020), integrated payment systems (e.g. smartcard schemes), collaborations of bicycle-rail organisations, positive communication and safe cycling infrastructure (BiTiBi 2017). These bicycle-transit ‘services’ are included in this overview to ensure completeness of influential factors, but their effects are not described in more detail here due to large local variation.
The location of a station relates closely to its operating services (see Sect. 3.1.3), but also greatly influence the share of cyclists it attracts and produces. From data presented in a stated travel choice study among railway passengers in the Netherlands it can be noted that particularly semi-urban stations see a relatively high percentage of bicycle-transit users (Van Hagen and Exel 2014). Another Dutch study indicated that the main growth of bicycle-rail use at the turn of the century occurred at the commuter towns (so-called ‘voorstadstations’) (Van Boggelen and Tijssen 2007).
Similar research was undertaken by Cervero et al. (2013), who divided the 42 light rail stations in the San Francisco Bay Area in five categories based on urban setting and parking provisions. The ‘urban with parking’ station type was found to have the largest share of access by bicycle (7% in 2008), where the transit service offered at each station was identical (same frequencies, fares, etcetera). Note that in all these studies the availability of alternative forms of transport play a large role.
Transit system and operating service
There are different types of public transport services as well as network typologies. Some systems or stations seem to be more likely to attract cyclists. Both the study by Bachand-Marleau et al. (2011) as well as by Heinen and Bohte (2014) found that if people are able to substitute one leg of their (primarily higher level) transit journey currently undertaken by another form of public transport with the use of a bicycle, they are more keen to switch. As bicycle-transit is already a multimodal trip by definition, any additional transfers are valued more negatively. Thus, stops with more direct services are more attractive. Furthermore, other studies indicate that people will cycle greater distances to higher service level transit stops and stations (Brand et al. 2017; Rijsman et al. 2019; Blainey 2010; Martens 2004; Verschuren 2016). Note that these system-wide factors trickle down into the transit station factors of Sect. 3.1.1.
More abstractly, Brand et al. (2017) mention physical and network integration, an integrated ticket system (for paid cycle parking, bike share and the transit journey, such as the Dutch OV-card) and high-quality information system as preconditions of bicycle-transit use. The researchers expect that the quality of Bike-on-Board facilities and availability will also influence the amount of bicycle-transit use. However, no existing literature has been found on this topic particularly. It may be expected that in evaluation reports of train operators such information may be of hand. These literature sources were not part of this research scope.
First-/last mile factors
The bicycle leg of the bicycle-transit journey can make up nearly half of the total trip time as indicated earlier in Sect. 3.1.1. This group of factors contains three subgroups: generic ‘regional climate’ of a place, quality of the bicycle journey and competition with other modes. Competition applies to both access and egress trips to the train station (competition bicycle), as well as the complete door-to-door journey (competition bicycle-rail). Table 2 shows these factors, their relationship and main sources.
There are a number of geographical features that describe bicycle uptake in general and bicycle-rail levels in particular. At a local level these characteristics include the weather, hilliness and city size.
The influence of weather is considered in various studies and even defined as “main external factor” by a study in Taiwan of Cheng and Liu (2012), although user experience can differ. Weather conditions were defined by rain, wind, and temperature. Rainy weather has a “large impact” according to a stated preference survey among rail users in the Netherlands (Molin and Timmermans 2010) and ranked high as well by Van Boggelen and Tijssen (2007). A small but much-quoted empirical research by Bickelbacher in 2001 found a decrease in the share of cyclists to a Munich metro station from 16 to 6% on rainy days. Seasonal differences indicated a doubling of bicycle-rail use in summertime in the study. The type of users may, however, differ too, as Bachand-Marleau et al. (2011) describe how users cycle more in summer but increase their overall public transport use during the winter—capturing a predictable substitute.
In a survey in the US among bicycle-rail users, 33% of the participants stated to use bicycle-rail for “avoiding bad weather or riding in the dark” (Flamm and Rivasplata 2014). Note that this was possibly the alternative to cycling the whole trip. Their study also indicated that hilliness may actually increase the use of bicycle-rail compared to bicycle-only trips—arguably trips that otherwise may not have been made at all.
The bicycle journey to or from a train station shares many characteristics with other bicycle journeys: an attractive and safe bicycle route will also be attractive and safe for bicycle-transit users. A Dutch study considers the bicycle journey to railway stations in particular. Scheltema (2012) formulated the “bicycle-rail traveller’s pyramid of needs”. The fundamental conditions of any bicycle(-rail) route are safety and directness including elements like lighting along the route and right of way. The extra value comes from comfort and attractiveness, where elements as liveliness and bicycle parking are included. The importance of directness becomes clear when considering that railway passengers attach much value to reliability (Brons and Rietveld 2009). The cyclist has a train to catch and wishes to have as few traffic lights as possible.
Good cycling infrastructure in quality and quantity has been mentioned in a number of cycle-rail studies to greatly affect bicycle-rail usage. Research in the San Francisco Bay Area, US (Cervero et al. 2013) mentions how “[a number of infrastructure changes] clearly benefited rail stations (…) in attracting cyclists”. Bicycle infrastructure was ranked among the top-3 most influential factors in the study by (Krizek and Stonebraker 2010).
Competition with other modes
Bicycle-transit can be a faster, cheaper, more comfortable or convenient alternative to other transport mode options. Public transport services and systems vary in the world from minivans to metro, BRT and high-speed rail. Railway services can typically be classified among the higher-service level forms of public transport. The previous section showed that (more) people are willing to cycle (further) to more direct transit services. Therefore, this section will mainly include studies that look into bicycle-rail trips.
A main indicator for mode choice is trip distance. The exact distance that people are willing to cycle can vary, depending on aforementioned factors like station type and geographic characteristics as well as individual preferences. Roughly speaking, the bicycle is most popular between 1 and 3, up to 5 km distance. Note that travel time and the attractiveness (e.g. safety) of a bicycle route can describe a catchment area better as, for example, the study of Cervero et al. (2013) shows. Typically people will cycle further on the home-bound side of the journey (Krygsman et al. 2004; Meng et al. 2016; Shelat et al. 2018). An overall preference for walking over both cycling and bus to a higher-level transit system seems international, up to a distance of 1 km (Chen et al. 2012; KiM 2015). The financial costs for the alternatives is also a clear indicator of the attractiveness of the alternative modes (La Paix Puello and Geurs 2016).
Clearly, when both the levels of cycling and rail use are high, the absolute number of bicycle-rail users increases (Kuhnimhof et al. 2010; Martens 2007). This logical reasoning is integrated in various bicycle-rail demand modelling studies (Ensor and Slason 2011; Geurs et al. 2016; Krizek and Stonebraker 2010). Note that this study only includes literature where the combined use of bicycle and public transport is considered. The factors described are part of the larger, complex system of our daily choices. Thus, additional relations between the factors will exist. One may expect that high car ownership will typically result in lower levels of cycling and transit use on their own, and with high shares of full-time employment in an area, a higher share of commuters is very likely.
For the complete door-to-door journey, the car will generally be the main competitor. Car ownership among bicycle-rail commuters is slightly lower according to various studies (Heinen and Bohte 2014; Meng et al. 2016), as among cyclists in general (Parkin et al. 2008). Nevertheless, bicycle-rail users often still own a car (Shelat et al. 2018; Sherwin and Parkhurst 2010), just like other rail users (Givoni and Rietveld 2007), indicating they are not ‘captive’ public transport users per se.
To complete this section on competing modes, the study of Singleton and Clifton (2014) in the US is of interest. The researchers challenged the concept that cycling is a competitor for transit services. On particularly shorter journeys, the bicycle is likely to replace lower-level and lower-frequency public transport services such as bus rides. Meanwhile, as a sustainable long-term alternative to the car, the competition can become a synergy. Whenever a tire is flat or the rain is pouring one can opt for the bus and when the trains are striking the bike is a reliable mode of transport. Their research indicates that transit are short-term mode substitutes, but might be long-term complements. Increases in urban area bicycle commuting were positively associated with transit ridership. More research in this field is recommended by them.
Before we zoom into individuals’ travel purposes of the stated choice model in the next section, we give the larger context of a cycling culture and attitude towards cycling and typical user-characteristics. How is bicycle and rail use perceived? What characteristics do bicycle-rail-users share? How do transportation alternatives affect the share of bicycle-rail? What transport policy is in place? Answers to these questions will vary depending on where and to whom they are asked. Note that these factors are often more qualitative, making it harder to assign a direct relation. Table 3 shows these factors, their relationship and main sources.
High levels of rail use and bicycle use are not mentioned as factors explicitly in this overview but are assumed to be captured by a ‘positive attitude towards rail’ and a ‘positive attitude towards cycling’.
Culture and attitude towards transport modes
The culture around, perceptions of and attitude towards various modes of transport, are all contextual factors which influence a traveller’s choice. Particularly the perception of cycling seems to differ per country or social group.
Part of the perception is an interpretation of the actual number and type of cyclists or transit users. If only affluent white males can be spotted cycling on expensive road bikes (dubbed Mamil in some places: a middle-aged man in lycra) or contrarily, only students are going around on cheap and rusty bicycles, cycling will be perceived accordingly (Aldred and Jungnickel 2014). The same counts for expensive train travel that only affluent people can afford or vice versa, where the train (or bicycle) is a poor man’s mode of transport for those who cannot afford a car. Negative or stereotypical perceptions can become a barrier to changing people’s travelling habits. The phrase ‘cycling for all ages and abilities’ used by various pro-cycling groups, indicates work is being done on changing perception and hopefully practice.
Bicycle-transit user characteristics
Traffic flows are the sum of travel choices made by individuals. Research on who are travelling by bicycle, by transit and even by bicycle-transit has accumulated over the years. The literature review focuses on factors for the combination of the two modes only.
Particularly in this group of factors, large differences between places were found. Where some local studies indicated that income or gender may highly correlate with bicycle(-rail), in other locations these appeared to be insignificant. This should be kept in mind when studying these factors. There remains much work to be done in this field.
Mostly socio-economic factors have been identified in the literature. The differentiation of users lays in age, gender and household size, as well as many travel or occupational themes including trip purpose, education levels, employment rate or types and income but also riding frequencies, route knowledge and even clothing. There are clearly correlations between these factors which are outside the scope of this literature review.
Reflection on factors from literature review
The relatively most influential factors determining the demand of bicycle-transit use emerging from this review are the first/last-mile-distance (most people will cycle up to five km), current bicycle and rail use, competition of other modes, safe and high-quality bicycle routes to the station, the share of commuters among railway passengers and number of rainy days. The positive feedback loops (and potentially negative loops) between all the stated factors should be studied in more detail to develop our understanding further. These feedback loops are, however, evident: good bicycle infrastructure will increase cycling levels and in turn high cycling levels will push cycling measures on the agenda (e.g. safer cycling routes) which might increase demand for bicycle trains even further, and so forth.
On a system-wide level, good public transportation and high-quality cycling infrastructure can provide a reliable and flexible alternative to the car. People are then less reliant on their car. On an individual’s trip choice level, however, there is a competition for the first and last mile between the bicycle and its alternatives to reach or leave a railway station. Then, for bicycle-rail in particular, bus, tram and metro systems will work as a competitor.
As bicycle-rail literature is limited and considering these large variations, more than a generic overview cannot be given. It may be assumed that a combination of the factors can give a first indication of the potential for bicycle-rail use.