'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY

Lukas-Walter Thiée; Hannes M. Petrowsky; Marie-Lena Frech; David D. Loschelder; Burkhardt Funk

'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY

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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. Hrsg. / Association for Information Systems (AIS). AIS eLibrary, 2021. 1655.

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Bibtex

@inbook{2000ef0c1c5c4cecaa7bb23cba66335f,

title = "'SPREAD THE APP, NOT THE VIRUS{\textquoteright} – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY",

abstract = "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.",

keywords = "Business informatics",

author = "Lukas-Walter Thi{\'e}e and Petrowsky, {Hannes M.} and Marie-Lena Frech and Loschelder, {David D.} and Burkhardt Funk",

note = "ECIS 2021 Proceedings Collection: Research Papers, Beitrag 123; European Conference on Information Systems : Human Values Crisis in a Digitizing World , ECIS 2021 ; Conference date: 14-06-2021 Through 16-06-2021",

year = "2021",

month = may,

day = "11",

language = "English",

editor = "{Association for Information Systems (AIS)}",

booktitle = "ECIS 2021 Proceedings",

publisher = "AIS eLibrary",

address = "United States",

url = "https://www.ecis2021.com/",

}

RIS

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 -

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