Efforts to improve the accessibility of rail services for all users have been ongoing in the industry and academia for many years. The British government and key industry organisations such as the Rail Safety and Standards Board (RSSB), Network Rail, and the Rail Delivery Group (RDG) are keen to continue to improve the accessibility of services across the rail travel sector in support of the Department for Transport’s (DfT, 2018) Inclusive Transport Strategy. Whilst progress has been made towards improving the accessibility of the built environment over recent years (examples include Network Rail, 2019; RSSB, 2020a); these projects have tended to focus on improving access to stations and trains through structural works as well as the implementation of various digital systems like real-time passenger prediction services (Chick, 2020) and data-driven timetabling projects which have emerged via industry sponsored innovation competitions such as the RSSB Data Sandbox (RSSB, 2020b). By contrast, research projects that have sought to understand and improve digital technologies within the travel sector have largely been focused on the management and service provider facing systems (Anaya and Lehto, 2020, 317). As a result, there are several avenues within the passenger experience that have received less attention in industry and academic research. For example, whilst there are several projects aimed at improving the efficiency and usability of rail sector digital systems, the benefits of using such systems are most often seen by the provider rather than directly by the passenger (see RSSB, 2019a; RSSB 2019b). Similarly, little consideration has been given to assessing how and why some passengers do (not) adopt technological innovations designed to assist and enhance their journey experience.
To address these gaps, this PhD project will adopt ideas and concepts from the areas of tourism, disability studies, human factors, and transport studies to explore how digital systems used (or not used) by passengers can be improved or adapted to better suit the needs of users with later technology adopting tendencies. Rogers’ (2003) theory of the diffusion of innovation suggests that individuals within a social system do not adopt new ideas or products simultaneously, rather they adopt over time depending upon various personal characteristics. The focus of this PhD will be on the latter half of society which are later to adopt new ideas and technologies, namely late adopters and laggards (Essen and Ostlund, 2011, 90). The overarching research question driving this project is: What are the barriers to rail travel for late technology adopting passengers and to what extent is this explained by the social privilege dimension of constraints negotiation theory and the diffusion of technology theory? The findings of this research will generate recommendations for the rail sector related to improving accessibility policies and industry standards to remove technological, psychological, or physical barriers in both the digital and built environment. This will contribute towards the overall objective of making the rail more appealing and accessible for all passengers.
References:
Anaya, G. and Lehto, X. (2020) Traveller-Facing Technology in the Tourism Experience: A Historical Perspective. Journal of Travel and Tourism Management. 37 (3) 317-331.
Chick, D. (2020) Using Machine Learning to Predict Delays and Build Passenger Trust. Birmingham: ZipAbout. Available from https://www.zipabout.com/news/using-machine-learning-to-predict-delays-and-build-passenger-trust [accessed 27 April 2021].
Department for Transport. (2018) Policy Paper: Inclusive Transport Strategy. London: Department for Transport. Available from https://www.gov.uk/government/publications/inclusive-transport-strategy [accessed 30 March 2021].
Essen, A. and Ostlund, B. (2011) Laggards as Innovators? Old Users as Designers of New Services & Service Systems. International Journal of Design, 5 (3) 89-99.
Network Rail. (2019) Major Project to Improve Accessibility at Lincolnshire Railway Station Completed. London: Network Rail. Available from https://www.networkrailmediacentre.co.uk/news/major-project-to-improve-accessibility-at-lincolnshire-railway-station-completed [accessed 29 March 2021].
Rogers, E. (2003) Diffusion of Innovations, 5th edition. New York: Free Press.
RSSB. (2019a) Utilising Deep Analytics to Predict Reactionary Delays and Dwell Time Variation in the New Accessible Railway. London: Rail Safety and Standards Board. Available from https://rssb.wavecast.io/data-sandbox-plus/utilising-deep-analytics-to-predict-reactionary-delays-and-dwell-time-variation-in-the-new-accessible-railway [accessed 27 April 2021].
RSSB. (2020a) The Economic Case for Removing the Gap and Step Between Trains and Platforms: The Case of Kneeling Trains Report (COF-ECO-02). London: Rail Safety and Standards Board. Available from https://www.rssb.co.uk/research-catalogue/CatalogueItem/COF-ECO-02 [accessed 30 March 2021].
RSSB. (2020b) Data Sandbox+: New Opportunities to Collaborate with Innovators. London: Rail Safety and Standards Board. London: Rail Safety and Standards Board. Available from https://www.rssb.co.uk/what-we-do/Key-Industry-Topics/Performance/Value-from-data/Future-Sandbox [accessed 29 March 2021].