2019
DOI: 10.1016/j.jtrangeo.2019.102486
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Smart cycling futures: Charting a new terrain and moving towards a research agenda

Abstract: Smart cycling futures: Charting a new terrain and moving towards a research agenda Nikolaeva, A.; te Brömmelstroet, M.; Raven, R.; Ranson, J. A B S T R A C TThe future of cycling is about to change. At least, this is apparent if we are to believe the multitude of innovators, start-ups, incumbent industries, policy actors and consultants proposing to harness the power of digital techniques to improve and transform cycling experiences, infrastructures, and gadgets. This 'smartification of cycling' is a phenomeno… Show more

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Cited by 36 publications
(15 citation statements)
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“…For the content analysis, this article 'measure[ed] the frequency and variety of messages' (Merriam and Tisdell 2016, 179), in combination with a qualitative element (summative content analysis) that is concerned with 'latent and more context depended meaning' (Schreier 2014, 173) and 'the evidence is provided in context, and by using words and examples from the text and its pictures rather than simple numbers' (Merriam and Tisdell 2016, 180) to understand how keywords are used in the documents. This was supported by a combination of NVIVO (analysis software for qualitative and mixed-method research, see (QSR International 2018)) and Excel (spreadsheet program and analysis tool, see (Microsoft 2018)). The following keywords that would reflect the focus of this article were selected so they could be used for easy discovery of relevant sections in the (often long) documents, and they were combined into four categories (a)-(d): (a) bicycle, cycling, bike, cyclist (b) car, automotive, vehicle, (c) IoT, Internet of Things, (d) transport, mobility.…”
Section: Methodsmentioning
confidence: 99%
“…For the content analysis, this article 'measure[ed] the frequency and variety of messages' (Merriam and Tisdell 2016, 179), in combination with a qualitative element (summative content analysis) that is concerned with 'latent and more context depended meaning' (Schreier 2014, 173) and 'the evidence is provided in context, and by using words and examples from the text and its pictures rather than simple numbers' (Merriam and Tisdell 2016, 180) to understand how keywords are used in the documents. This was supported by a combination of NVIVO (analysis software for qualitative and mixed-method research, see (QSR International 2018)) and Excel (spreadsheet program and analysis tool, see (Microsoft 2018)). The following keywords that would reflect the focus of this article were selected so they could be used for easy discovery of relevant sections in the (often long) documents, and they were combined into four categories (a)-(d): (a) bicycle, cycling, bike, cyclist (b) car, automotive, vehicle, (c) IoT, Internet of Things, (d) transport, mobility.…”
Section: Methodsmentioning
confidence: 99%
“…The main benefits are the reduction of traffic jams and expenditure on energy and the reduction of costs and time spent traveling for citizens [4]. However, this type of solution requires planning that integrates the different alternatives and ensures user safety [37].…”
Section: Definitions Of Smart Mobility Authorsmentioning
confidence: 99%
“…Innovations such as electronically assisted bikes (e-bikes) and bike-sharing systems (BSS) are rapidly adopted the use of conventional bikes and, to a lesser extent, car trips (Bigazzi & Wong, 2020;Ma, Yuan, Van Oort, & Hoogendoorn, 2020). Smart cycling technologies are getting more attention at different levels of governance, as they alter how this mode of travel is experienced, understood and governed (Nikolaeva et al 2019). Urban planning practice and mobility research share a growing need for understanding better the spatial, temporal and social aspects of cycling to respond to the rapidly changing scene in cities and attract more people on bikes.…”
Section: Introductionmentioning
confidence: 99%
“…2018), video recording (Pokorny & Piterna 2019) and virtual reality simulators (Leeuw & Kruijf 2015). Furthermore, tracking the use of bikes is increasingly integrated into the Internet of Things (IoT) fabric of smart cities through smart applications and devices such as smart wearables (Nikolaeva et al 2019), which further add to the increasing data flux.…”
Section: Introductionmentioning
confidence: 99%