User Resistance and Acceptance in Information Technology Systems
Summary
User resistance and acceptance in information technology systems concern the behavioural and cognitive responses of individuals and organisations when new digital tools are introduced. Researchers have long employed theoretical frameworks such as the Technology Acceptance Model and Innovation Resistance Theory to identify factors that encourage or impede uptake. Core determinants include perceived usefulness and ease of use, social influence, self-efficacy and cognitive biases such as status quo bias. Organisational dimensions—such as leadership support, training provision, trialability of the system and the clarity of communication—shape collective responses. Empirical work frequently combines qualitative interviews with quantitative surveys and structural equation modelling to unpack how performance expectancy and perceived value relate to adoption intention. A growing body of evidence highlights that multi-stakeholder engagement, iterative prototyping and targeted interventions (for example enactive mastery experiences) can mitigate resistance and foster sustained usage. These insights carry global significance, informing implementation strategies in sectors such as healthcare, manufacturing, extended reality and the Internet of Things, and underscore the importance of tailoring change management to both micro-level user concerns and macro-level institutional pressures.
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User Resistance and Acceptance in Information Technology Systems publication trend
The graph below shows the total number of articles in user resistance and acceptance in information technology systems across all publications each year (not limited to Nature Index journals).
Technical terms
Resistance to Change: A tendency to oppose or avoid alterations in workplace processes or technologies.
Technology Acceptance Model: A framework positing that perceived usefulness and perceived ease of use govern behavioural intention to use a system.
Perceived Usefulness: The degree to which an individual believes that using a particular system will enhance their job performance.
Trialability: The extent to which an innovation can be experimented with on a limited basis before full adoption.
Status Quo Bias: A cognitive preference for maintaining existing conditions over change, often leading to inertia in technology adoption.
References
- Effect of user resistance on the organizational adoption of extended reality technologies: A mixed methods study. International Journal of Information Management (2024).
- Resistance of multiple stakeholders to e-health innovations: Integration of fundamental insights and guiding research paths. Journal of Business Research (2023).
- Unfolding IoT Adoption: A Status Quo Bias Perspective. Business & Information Systems Engineering (2024).
- Enactive mastery experience improves attitudes towards digital technology via self-efficacy – a pre-registered quasi-experiment. Behaviour and Information Technology (2023).
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