Bus or Rail: An Approach to Explain the Psychological Rail Factor

Scherer, Milena; Dziekan, Katrin

doi:10.5038/2375-0901.15.1.5

Cited by 41 publications

(20 citation statements)

References 7 publications

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“…In the United States and other developed countries, rail transit is assumed to attract a higher ridership than does bus, all other factors being equal. This is known in the literature as "rail bias" (Scherer and Dziekan, 2012). We would assume this would be the case in the PRD.…”

Section: Strategy St1: Enhance Competitiveness Of Bus and Rail Througmentioning

confidence: 99%

Quality of Life Indicators and Policy Strategies to Advance Sustainability in the Pearl River Delta

Knopman¹,

Zmud²,

Ecola³

et al. 2015

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Section: Strategy St1: Enhance Competitiveness Of Bus and Rail Througmentioning

confidence: 99%

Quality of Life Indicators and Policy Strategies to Advance Sustainability in the Pearl River Delta

Knopman¹,

Zmud²,

Ecola³

et al. 2015

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“…The stronger weighting of rail stations is in line with existing studies. For example, Scherer and Dziekan [28] were able to prove the existence of a rail factor through face-to-face interviews. They showed that rail is preferred as a means of transport over bus.…”

Section: Choosing the Variables To Measure Urbanitymentioning

confidence: 99%

Spatial Factor—Using a Random Forest Classification Model to Measure an Internationally Comparable Urbanity Index

et al. 2020

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Travel behavior can be determined by its spatial context. If there are many shops and restaurants in close proximity, various activities can be done by walking or cycling, and a car is not needed. It is also more difficult (e.g., parking space, traffic jams) to use a car in high-density areas. Overall, travel behavior and dependencies on travel behavior are influenced by urbanity. These relationships have so far only been examined very selectively (e.g., at city level) and not in international comparison. In this study we define an Urbanity Index (UI) at zip code level, which considers factors influencing mobility, international comparability, reproducibility as well as practical application and the development of a scalable methodology. In order to describe urbanity, data were collected regarding spatial structure, population, land use, and public transport. We developed the UI using a supervised machine learning technique which divides zip codes into four area types: (1) super-urban, (2) urban, (3) suburban/small town, (4) rural. To train the model, the perception from experts in known zip codes concerning urbanity and mobility was set as ground truth. With the UI, it is possible to compare countries (Germany and France) with a uniform definition and comparable datasets.

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“…Transport researchers are seemingly becoming more mindful of the role of culture in travel behaviour: Kuhnimhof and Wulfhorst (2013) described 'perceptions and lifestyle orientations' (one of their four critical aspects of urban mobility culture) as being heavily influenced by cultural background. Scherer and Dziekan (2012) state that any psychological biases in favour of rail over bus will be influenced by local conditions so cannot be generalised and applied to different regions. Ger et al (1999) touched on the symbolic values of both the car and the bicycle in different cultures; Miller 2001suggests an overemphasis on the 'consequences' of transport rather than an account of its importance in different cultural contexts; and recent research by Syam (2014) examined the role of culture in modal choice for different migrant groups within Auckland and concluded that national culture was a strong motivator of how public transport is perceived differently by different national groups within a city (see also Oliver and Lee, 2010;Syam et al, 2011;Syam et al, 2013).…”

Section: Symbolic Transport Motivation Across Different Groups and Cumentioning

confidence: 99%

Using thematic analysis to explore symbolism in transport choice across national cultures

et al. 2018

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A recently empirically isolated latent variable in transport choice is symbolism, which examines what people believe their transport choices say to others about them and how they are judged in a social context. Whilst it is well established that symbolism differs vertically across different socioeconomic groups within a country, very little work has been done on how symbolism in transport may differ between similar individuals across nations as a function of national cultural values, and how this may manifest itself in transport choices. If significant differences were to be found then this could have impacts for transport policy formulation and transfer. This paper explores and discusses these issues and concludes that the initial goal of any research into symbolic transport choices across cultures is theoretical fertility, and this is best achieved by adopting the research philosophy of Imre Lakatos, using theory-driven thematic analysis to develop theoretical models for testing. Keywords: latent choice motivation, transport symbolism, national culture, Lakatosian research programmes, mixed methods research, thematic analysis many months first brought the possibility of symbolic transport choices differing across national culture to light. Secondly Dr Alvin Lee at Deakin University for introducing the principal author to the cultural models quoted in this paper. Thirdly Professor David Hensher, Professor Kay Axhausen, and Dr Luis Willumsen, for their insights into latent variables and social segmentation. Finally it would be remiss not to thank the staff of the Centre for Transport studies for their support and feedback during the earlier phases of this work. However, views expressed in this paper belong only to the authors. Disclosure statement No potential conflict of interest was reported by the authors. Funding bodies There are no funding bodies for this research.

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Bus or Rail: An Approach to Explain the Psychological Rail Factor

Cited by 41 publications

References 7 publications

Quality of Life Indicators and Policy Strategies to Advance Sustainability in the Pearl River Delta

Quality of Life Indicators and Policy Strategies to Advance Sustainability in the Pearl River Delta

Spatial Factor—Using a Random Forest Classification Model to Measure an Internationally Comparable Urbanity Index

Using thematic analysis to explore symbolism in transport choice across national cultures

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