'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY. / Thiée, Lukas-Walter; Petrowsky, Hannes M.; Frech, Marie-Lena et al.
ECIS 2021 Proceedings: Human Values Crisis in a Digitizing World. ed. / Association for Information Systems (AIS). AIS eLibrary, 2021. 1655.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - 'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY
AU - Thiée, Lukas-Walter
AU - Petrowsky, Hannes M.
AU - Frech, Marie-Lena
AU - Loschelder, David D.
AU - Funk, Burkhardt
N1 - ECIS 2021 Proceedings Collection: Research Papers, Beitrag 123
PY - 2021/5/11
Y1 - 2021/5/11
N2 - The release of the Corona-Warn-App (CWA), a governmental pandemic tracing app to track infection chains related to COVID-19 in Germany, marks an unprecedented situation that offers a unique opportunity for investigating population-wide adoption of novel technology. We develop a conceptual model to investigate the effects and path relationships of multiple constructs related to technology adoption, data security, morality, social influence, trust, and COVID-19 to predict behavioral intentions and actual usage behavior. We use structural equation modelling with the partial least squares method and identify effort expectancy, social influence, prevailing opinions on COVID-19 and the CWA, as well as moral and ethical considerations as the most influential predictors. We are able to explain moderate to high amounts of variance with our model. Our results offer valuable insights for the technology ac- ceptance literature and enable practical recommendations for improving the public communication and elevating user numbers of pandemic tracing apps in Germany.
AB - The release of the Corona-Warn-App (CWA), a governmental pandemic tracing app to track infection chains related to COVID-19 in Germany, marks an unprecedented situation that offers a unique opportunity for investigating population-wide adoption of novel technology. We develop a conceptual model to investigate the effects and path relationships of multiple constructs related to technology adoption, data security, morality, social influence, trust, and COVID-19 to predict behavioral intentions and actual usage behavior. We use structural equation modelling with the partial least squares method and identify effort expectancy, social influence, prevailing opinions on COVID-19 and the CWA, as well as moral and ethical considerations as the most influential predictors. We are able to explain moderate to high amounts of variance with our model. Our results offer valuable insights for the technology ac- ceptance literature and enable practical recommendations for improving the public communication and elevating user numbers of pandemic tracing apps in Germany.
KW - Business informatics
UR - https://aisel.aisnet.org/ecis2021_rp/123/
M3 - Article in conference proceedings
BT - ECIS 2021 Proceedings
A2 - , Association for Information Systems (AIS)
PB - AIS eLibrary
T2 - European Conference on Information Systems
Y2 - 14 June 2021 through 16 June 2021
ER -