Mitigating Resistance in Smart Health Monitoring Systems: The Role of Data Governance and Privacy Concerns
Date
Authors
Zhang, J
Hassandoust, F
Johnston, AC
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Emerald
Abstract
Purpose – Smart health monitoring systems (SHMSs) have encountered resistance and limited adoption by various stakeholders. This study aims to investigate the impact of data governance on the associated privacy concerns in relation to barriers, thereby mitigating users' resistance to SHMSs. Design/methodology/approach – This mixed-methods study draws on innovation resistance theory and data governance mechanisms. We developed a research model based on 20 qualitative interviews with individuals from multiple stakeholder groups and empirically tested the model using 277 valid responses from potential and current SHMS users, collected through an online questionnaire survey. Findings – The findings reveal that data governance mechanisms–incorporating legislative protection, cultural and religious differences (procedural data governance mechanisms), transparency, and trust (relational data governance mechanisms)–are more influential than accountability and responsibility (structural data governance mechanisms) in reducing user resistance to SHMSs. Privacy concerns significantly influence functional barriers to SHMSs and ultimately positively affect users' resistance to SHMSs. Cultural and religious differences and trust mechanisms are significantly associated with privacy concerns among users with a high personal innovativeness level. Research limitations/implications – The study extends innovation resistance theory by integrating data governance, showing how theoretical models can be practically adapted for diverse health information technology (HIT) contexts. The findings offer societal implications, informing policies that promote SHMS development with robust privacy protections, inclusive design and trust-building governance. Originality/value – This is a pioneering study that extends innovation resistance theory by integrating data governance, demonstrating how theoretical models can be tailored to address diverse needs within the HIT domain.Description
Keywords
46 Information and Computing Sciences, 3503 Business Systems In Context, 8.1 Organisation and delivery of services, 16 Peace, Justice and Strong Institutions, 08 Information and Computing Sciences, Marketing, 46 Information and computing sciences, Innovation resistance theory, Data governance, Privacy concerns, Functional barriers, Smart health monitoring
Source
Internet Research, ISSN: 1066-2243 (Print); 2054-5657 (Online), Emerald, 36(7), 82-106. doi: 10.1108/INTR-12-2024-2032
Rights statement
© Jingjing Zhang, Farkhondeh Hassandoust and Allen C. Johnston. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at https://creativecommons.org/licenses/by/4.0/