Understanding the performance impact of the epidemic prevention cloud: an integrative model of the task-technology fit and status quo bias

Pi-Jung Hsieh and Weir-Sen Lin

Behaviour and Information Technology, 2020, vol. 39, issue 8, 899-916

Abstract: The epidemic prevention cloud allows infection control professionals to streamline many of their reporting procedures, thereby improving patient safety in a cost-effective manner. Based on task-technology fit and status quo bias perspectives, this study develops an integrated model to explain individuals’ health information technology usage behaviour. We conducted a field survey in 30 Taiwan hospitals to collect data from infection control professionals with using experience of the epidemic prevention cloud. A total of 167 questionnaires were sent out, and 116 were returned from 18 hospitals. To test the proposed research hypothesis, we employed a structural equation model by the partial least squares method. The results found that both task – (p

Date: 2020
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DOI: 10.1080/0144929X.2019.1624826

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