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  • Trang_et_al._OneTracingApp

    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in European Journal of Information Systems on 27 July 2020, available online: https://www.tandfonline.com/doi/full/10.1080/0960085X.2020.1784046

    Accepted author manuscript, 592 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License


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One app to trace them all?: Examining app specifications for mass acceptance of contact-tracing apps

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>31/07/2020
<mark>Journal</mark>European Journal of Information Systems
Issue number4
Number of pages14
Pages (from-to)415-428
Publication StatusPublished
Early online date27/07/20
<mark>Original language</mark>English


The current COVID-19 crisis has seen governments worldwide mobilising to develop and implement contact-tracing apps as an integral part of their lockdown exit strategies. The challenge facing policy makers is that tracing can only be effective if the vast majority of the population uses the one app developed; its specifications must therefore be carefully considered. We theorise on tracing apps and mass acceptance and conduct a full-factorial experiment to investigate how app installation intention is influenced by different app specifications based on three benefit appeals, two privacy designs, and two convenience designs. By applying quantile regression, we not only estimate the general effect of these app specifications but also uncover how their influence differs among citizens with different propensities for acceptance (i.e. critics, undecided, advocates)—a crucial insight for succeeding with mass acceptance. This study contributes to research in three ways: we theorise how mass acceptance differs from established app acceptance, we provide a fine-grained approach to investigating the app specifications salient for mass acceptance, and we reveal contextualised insights specific to tracing apps with multi-layered benefit structures. Our findings can guide policy makers by providing specification recommendations for facilitating mass acceptance of tracing apps during pandemics or other societal crises