Universität zu Köln

Park, Eun Hee, Werder, Karl ORCID: 0000-0001-8481-1596, Cao, Lan and Ramesh, Balasubramaniam (2022). Why do Family Members Reject AI in Health Care? Competing Effects of Emotions. Journal of Management Information Systems, 39 (3). pp. 765-789. Taylor & Francis.

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Abstract

Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find that anxiety about health care monitoring and anxiety about health outcomes reduce the rejection of AI monitoring, whereas surveillance anxiety and delegation anxiety increase rejection. We also find that for individual-level risks, perceived controllability moderates the relationship between surveillance anxiety and the rejection of AI monitoring. We contribute to the theory of Information System rejection by identifying the competing roles of emotions in AI monitoring decision making. We extend the literature on decision making for others by suggesting the influential role of anxiety. We also contribute to healthcare research in Information System by identifying the important role of controllability, a design factor, in AI monitoring rejection.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Park, Eun Hee UNSPECIFIED UNSPECIFIED UNSPECIFIED Werder, Karl werder@wiso.uni-koeln.de orcid.org/0000-0001-8481-1596 UNSPECIFIED Cao, Lan UNSPECIFIED UNSPECIFIED UNSPECIFIED Ramesh, Balasubramaniam UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-633271
DOI:	10.1080/07421222.2022.2096550
Journal or Publication Title:	Journal of Management Information Systems
Volume:	39
Number:	3
Page Range:	pp. 765-789
Date:	2022
Publisher:	Taylor & Francis
Language:	English
Faculty:	Faculty of Management, Economy and Social Sciences
Divisions:	Faculty of Management, Economics and Social Sciences > Business Administration > Information Systems > Chair for Information Systems and Systems Development
Subjects:	Data processing Computer science Psychology Technology (Applied sciences) Management and auxiliary services
Related URLs:	Data
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/63327