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

doi:10.1080/0144929X.2019.1624826

CNU IR > College of Smart Living > Dept. of Hospital and Health (including master's program) > Periodical Articles > Item 310902800/32711

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/32711

Title:	Understanding the performance impact of the epidemic prevention cloud: an integrative model of the task-technology fit and status quo bias
Authors:	Pi-Jung Hsieh(謝碧容) Weir-Sen Lin(林為森)
Contributors:	Chia Nan Univ Pharm & Sci, Dept Hosp & Hlth Care Adm
Keywords:	Post-adoption resistance task-technology fit status quo bias communicable disease surveillance report system utilisation performance impact
Date:	2019-08
Issue Date:	2020-08-25 15:07:51 (UTC+8)
Publisher:	TAYLOR & FRANCIS LTD
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 < .01) and technology-related characteristics (p < .001) influence task-technology fit. Task-technology fit has a positive effect on both utilisation (p < .001) and performance (p < .001), while it appears to have a negative effect on resistance to use (p < .001). Our results showed that resistance to use was caused by uncertainty costs (p < .01) and perceived value (p < .01). The results indicate the significant effect of utilisation on performance (p < .01). Further, the results indicate a significant negative effect of resistance to use on utilisation (p < .05). This study illustrates the importance of incorporating post-adoption resistance in technology adoption studies
Relation:	Behaviour & Information Technology, v.39, n.8, pp.899-916
Appears in Collections:	[Dept. of Hospital and Health (including master's program)] Periodical Articles

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