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
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - One app to trace them all?
T2 - Examining app specifications for mass acceptance of contact-tracing apps
AU - Trang , Simon
AU - Trenz, Maneul
AU - Weiger , Welf
AU - Tarafdar, Monideepa
AU - Cheung, Christy
PY - 2020/7/31
Y1 - 2020/7/31
N2 - 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
AB - 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
U2 - 10.1080/0960085X.2020.1784046
DO - 10.1080/0960085X.2020.1784046
M3 - Journal article
VL - 29
SP - 415
EP - 428
JO - European Journal of Information Systems
JF - European Journal of Information Systems
SN - 0960-085X
IS - 4
ER -