Understanding the relations between crowd density, safety perception and risk-taking behavior on train station platforms: A case study from Switzerland

Schneider, Andrea; Krueger, Eva; Vollenwyder, Beat; Thurau, Jasmin; Elfering, Achim

doi:10.1016/j.trip.2021.100390

Cited by 6 publications

(13 citation statements)

References 17 publications

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“…However, the indicated LOS correlated with the indicated comfort level as anticipated; a higher indicated LOS corresponded with a lower comfort level. These findings are consistent with those from previous studies, which found a relation between crowd density and perceived comfort (Cullen & Cullen, 2001;Schneider et al, 2021).…”

Section: Experienced Crowd Density and Comfortsupporting

confidence: 93%

“…Previous studies have mainly reported on the negative effects of crowding (an aggregation of people in the same space at the same time) (Adrian et al, 2019), including its effects on humans in rail contexts (Schneider et al, 2021). "Crowding" is frequently used to describe psychological tensions experienced in crowded areas.…”

Section: Crowding and Wayfindingmentioning

confidence: 99%

“…Evans and Wener (2007) describe crowding as a state that occurs when the regulation of social interaction is unsuccessful, and the desired level of social interaction is exceeded by the actual amount of social interaction experienced. Hence, crowding is often associated with negative impacts on experience, including psychological or physical discomfort, perceptions of risk to personal safety or security or actual risks to safety (Cox et al, 2006;Cullen & Cullen, 2001;Schneider et al, 2021).…”

Section: Crowding and Wayfindingmentioning

confidence: 99%

“…Customer experience management aims towards a better understanding of customer experience wherever a customer-company interaction occurs; therefore, different methods to generate customer insights are applied. This is a part of the applied user-or human-centered approach (e.g., Boy, 2017), which has been pursued by the SBB in various areas (e.g., train station platform design (Schneider et al, 2018;Schneider et al, 2021), websites, in-house applications (e.g., Schneider et al, 2016;Vol-lenwyder et al, 2018), and accessible mobile applications (Vollenwyder et al, 2020). Current discussions on methods to gather customer insights include suggestions to collect retrospective data or data from a subjective perspective (Said et al, 2015) in real-time and using newer innovative methods (Schneider et al, 2018;Schneider et al, 2021).…”

Section: Customer Experience and Understanding The Customer Perspectivementioning

confidence: 99%

“…This is a part of the applied user-or human-centered approach (e.g., Boy, 2017), which has been pursued by the SBB in various areas (e.g., train station platform design (Schneider et al, 2018;Schneider et al, 2021), websites, in-house applications (e.g., Schneider et al, 2016;Vol-lenwyder et al, 2018), and accessible mobile applications (Vollenwyder et al, 2020). Current discussions on methods to gather customer insights include suggestions to collect retrospective data or data from a subjective perspective (Said et al, 2015) in real-time and using newer innovative methods (Schneider et al, 2018;Schneider et al, 2021). Furthermore, Said et al (2015) contend that while there is significant literature on the necessity and influence of customer insights on decision-making, there is a lack of literature exploring the generation of customer insights in real environments.…”

Section: Customer Experience and Understanding The Customer Perspectivementioning

confidence: 99%

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Mobile eye tracking applied as a tool for customer experience research in a crowded train station

Schneider¹,

Vollenwyder²,

Krueger³

et al. 2023

JEMR

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Train stations have increasingly become crowded, necessitating stringent requirements in the design of stations and commuter navigation through these stations. In this study, we explored the use of mobile eye tracking in combination with observation and a survey to gain knowledge on customer experience in a crowded train station. We investigated the utilization of mobile eye tracking in ascertaining customers’ perception of the train station environment and analyzed the effect of a signalization prototype (visual pedestrian flow cues), which was intended for regulating pedestrian flow in a crowded underground passage. Gaze behavior, estimated crowd density, and comfort levels (an individual’s comfort level in a certain situation), were measured before and after the implementation of the prototype. The results revealed that the prototype was visible in conditions of low crowd density. However, in conditions of high crowd density, the prototype was less visible, and the path choice was influenced by other commuters. Hence, herd behavior appeared to have a stronger effect than the implemented signalization prototype in conditions of high crowd density. Thus, mobile eye tracking in combination with observation and the survey successfully aided in understanding customers’ perception of the train station environment on a qualitative level and supported the evaluation of the signalization prototype the crowded underground passage. However, the analysis process was laborious, which could be an obstacle for its practical use in gaining customer insights.

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Section: Experienced Crowd Density and Comfortsupporting

confidence: 93%

Section: Crowding and Wayfindingmentioning

confidence: 99%