Artificial intelligence-driven transformation in healthcare: the mediating role of technostress in the impact of openness to organizational change and attitude toward AI on innovative behavior.
Aug 2026· Journal of health organization and management· pp.
1-15
· 0 citations· 45 references
Medicine
TL;DR
It has been demonstrated that employees' perceptions of technology and their openness to change shape innovative behavior through technostress in AI-driven transformation processes.
Abstract
Purpose
The rapid proliferation of artificial intelligence (AI) applications in healthcare is transforming the ways in which employees interact with technology, making it crucial to understand the effects of this process on employee behavior. The purpose of this study is to examine the effects of openness to organizational change and attitudes toward AI on employees' innovative behavior, and to test the mediating role of technostress in these effects.
DESIGN/METHODOLOGY/APPROACH
The research was conducted using a quantitative research design. Data were collected via face-to-face surveys from 305 healthcare workers employed at a university hospital in Istanbul, Türkiye, between January and February 2026 and analyzed using structural equation modeling. SPSS and AMOS software were used to analyze the collected data.
Findings
The findings revealed that employees with high levels of openness to organizational change and a positive attitude toward AI experienced lower levels of technostress, and that this, in turn, increased their innovative work behavior. Additionally, it was determined that technostress plays a partial mediating role in the effects of openness to organizational change and a positive attitude toward AI on innovative behavior.
RESEARCH LIMITATIONS/IMPLICATIONS
In conclusion, it has been demonstrated that employees' perceptions of technology and their openness to change shape innovative behavior through technostress in AI-driven transformation processes.
ORIGINALITY/VALUE
This study contributes to the literature by integrating digital transformation, organizational behavior, and health management; it also provides practical implications highlighting the importance of employee-centered digital transformation strategies for healthcare organizations and policymakers.
The study revealed the beneficial effects of AI on employee welfare in terms of productivity, reduction of unnecessary work, enhancement of flexibility in the workplace and employee satisfaction, but problems related to employment insecurity, surveillance, loss of privacy, loss of autonomy and continuous adaption to new technologies cannot be underestimated.
S. Rashed· Journal of human resource &...· 0 citations
Assessment of patients’ perceptions of the integration of Artificial Intelligence in healthcare and its impact on the doctor–patient relationship and participants’ trust, comfort, and concerns toward AI use found comfort and trust in AI are significantly affected by factors such as gender and digital literacy.
Faten M. Rabie, Youmna Mamdouh, Rama Ah. Alabadd et al.· PAIN, JOINTS, SPINE· 0 citations
This article shows how the Technology Acceptance Model and Technology Trust are combined in the Unified Theory of Acceptance and Use of Technology (UTAUT) and how the Perceived Empathy Model (PEM) and Perceived Clarity of Accountability Model (PCA) are extensions of these models.
This study aims to explore the impact of Human–AI Collaboration on the Innovation Behavior of employees in the banking sector, focusing on the mediation effect of Job Satisfaction and the moderation effect of AI Self-Efficacy. The study draws its concept of Human–AI Collaboration from the Job Demands–Resources (JD–R) Theory, which considers HACC as a strategic organizational resource that can boost employees' motivation and innovative performance. Quantitative, Cross Sectional. A quantitative, cross-sectional research design was used. Structured questionnaires were used to gather data on 384 employees of commercial banks who have experienced the use of AI in their work. To ensure the respondents had the relevant work experience with AI, purposive sampling was used and explore the direct, mediating, and moderating relationships, the proposed conceptual model was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique by SmartPLS 4. The results show that Human–AI Collaboration has a significant positive impact on Job Satisfaction and Innovation Behavior. Job Satisfaction positively impacts Innovation Behavior and partially mediates the link between Human–AI Collaboration and Innovation Behavior, suggesting that a collaborative environment with AI can foster innovation by enhancing employee work satisfaction. The findings of this study could help bank executives, human resource managers, and policymakers understand the importance of human-focused implementation of AI, ongoing AI skill-building, and favorable organizational practices that boost employee satisfaction and innovation. To truly unlock the strategic benefits of Human–AI Collaboration, organizations must include investment in employee capability development within their AI investments. This study adds to the growing increasingly relevant literature on Human–AI Collaboration by combining technological and psychological aspects in one framework. It expands on the JD–R Theory by clarifying the strategic role of Human–AI Collaboration as a job resource that fosters innovation by Job Satisfaction, and shows the contingent role of AI Self-Efficacy in AI-enabled workplaces.
This study demonstrates that extending the Technology Acceptance Model by incorporating nurses' knowledge and attitudes provides a meaningful framework for predicting AI adoption in resource-limited healthcare settings.
S. Sohrabi, Hossein Bonakchi, Rahman Kazemi· BMC Nursing· 0 citations
The rapid advancement of Artificial Intelligence (AI) is transforming organizational workflows and requiring employees to adapt to emerging technologies. This study aims to analyse the impact of AI literacy and trust in AI on work productivity, while examining whether AI anxiety serves as a mediating variable. A quantitative approach was employed using a cross-sectional survey design. Data were collected from 245 respondents working in the food and beverage sector in Jabodetabek, Indonesia, who have experience using AI-based systems. The instrument utilized a five-point Likert scale, and data were analysed through multiple regression within a mediation analysis framework. Results indicate that AI literacy has a strong positive and significant effect on work productivity $(\beta=0.637; \mathrm{p}<0.001)$, emerging as the strongest predictor in the model). However, AI anxiety does not mediate the relationship be-tween AI literacy or trust and productivity, as its effect on productivity is not significant $(\beta=-0.095; \mathrm{p}=0.291)$. These findings highlight the critical role of strengthening AI literacy to enhance employee productivity in the digital era. Organizations are encouraged to design training programs that go beyond technical skills, focusing on strategic AI utilization to optimize performance. The findings contribute to workforce development by highlighting the importance of AI capability building and psychological readiness in AI-driven operational environments associated with smart mobility ecosystems. Limitations include the small sample size and single-industry context, which limits the generalizability of findings across industries and smart mobility contexts. Future research should adopt longitudinal designs, explore additional variables such as perceived usefulness and organizational support, and extend to diverse sectors to deepen understanding of human–AI interaction dynamics.
Chintamy Rulliana Dewi, K. Krisna, Nur Damayanti· 2026 11th International Conf...· 0 citations