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Public preference for data privacy - A pan-European study on metro/train surveillance

Patil, Sunil, Patruni, Bhanu, Potoglou, Dimitris and Robinson, Neil 2016. Public preference for data privacy - A pan-European study on metro/train surveillance. Transportation Research Part A: Policy and Practice 92 , pp. 145-161. 10.1016/j.tra.2016.08.004

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Abstract

This paper presents a pan-European application of a stated preference discrete choice experiment for eliciting respondents’ preferences for various data-privacy settings in the context of security and surveillance of train/metro facilities in Europe. Results show that respondents across the 27 European Union Member States (EU27) prefer some Closed Circuit Television Cameras (CCTV) surveillance across in all countries, except Sweden where the most advanced type of CCTV with face recognition capabilities is preferred. Most respondents prefer that CCTV data is stored for future use rather than just being used for real-time monitoring, with the exception of respondents in Greece. However, an intermediate period of storage (15 days) is preferred over a shorter or longer duration (45 days). Respondents across the EU27 are averse to police force outside their home country having access to CCTV data. Respondents prefer the presence of unarmed security personnel over absence of security personnel. The majority of respondents are averse to any kind of security checks. However, in Belgium, France, Italy, Spain and the UK there is a preference for randomly selected people to go through a metal detector or full body scanner. Further this study shows that preferences also vary by age and gender. Overall, analysis of the data illustrates the complexity of the privacy over security debate as it pertains to transportation infrastructures. In particular, the increased use of transportation user data for various reasons (efficiency, safety and security) can pose complex social and ethical challenges to users, especially around perceptions of consent, accountability and transparency.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Geography and Planning (GEOPL)
Publisher: Elsevier
ISSN: 0965-8564
Date of First Compliant Deposit: 22 August 2016
Date of Acceptance: 2 August 2016
Last Modified: 13 Mar 2020 15:03
URI: http://orca.cf.ac.uk/id/eprint/93974

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