期刊
DIGITAL INNOVATION AND ENTREPRENEURSHIP (AMCIS 2021)
卷 -, 期 -, 页码 -出版社
ASSOC INFORMATION SYSTEMS
关键词
Algorithmic transparency; contact-tracing apps; mobile app adoption; COVID-19; online experiment
Empirical evidence proves that the level of algorithmic transparency in contact-tracing apps is positively associated with users' adoption behavior, comprehension, and trust.
Contact-tracing apps are considered one of the core information technologies to help contain the spread of the COVID-19 pandemic. However, they need to be adopted broadly to be effective. In this study, we apply the concept of algorithmic transparency (AT) to contact-tracing apps and hypothesize that users prefer apps with a high level of disclosure of information about the app's inner workings (referred to as transformation AT) and that disclosure increases user comprehension and trust. We empirically validate our hypotheses through an online experiment with 116 participants. We find that the level of transformation AT of a contact-tracing app is positively related to users' adoption behavior, comprehension, and trust.
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