Task-technology adaptation and decision-making in hospitals

Abstract

In recent years IS research has given attention to the topic of adaptation strategies or task technology adaptation in the information systems. However, what is missing in those studies are the reasons behind users making those adaptations and how those adaptations will benefit them. By focusing on the usage of the EMR in a health care setting and how it can lead to a more effective decision-making process, this thesis proposes a research model including behavioral EMR adaptation. To gain an understanding of behavioral adaptation, a sample of 133 doctors, nurses, doctor assistants, and other medical professionals that use the EMR for their daily work tasks has been collected. PLS-SEM was used to analyze the dataset. Outcomes demonstrate that behavioral EMR adaptation has a significant effect on decision-making effectiveness. Furthermore, people that are open to new technologies score higher on behavioral EMR adaptation. No mediating effects have been found for behavioral EMR adaption due to the absence of a direct correlation between the independent variables (computer self-efficacy and personal innovativeness) and the dependent variable (decision-making effectiveness). There have been no significant effects found for facilitating conditions as moderator. This suggests that facilitating conditions is better suitable as an independent variable.

Date of Award	30 Jun 2020
Original language	English
Supervisor	Rogier van de Wetering (Examiner) & Rik Bos (Co-assessor)