Navigating the Adoption Maze: Evolutionary Dynamics of Stakeholder Behavior in AI-Driven Elderly Care Solutions - Jinxin Yang; Xiangqian Wang (Inquiry: The Journal of Health Care Organization, Provision, and Financing)
In the face of a rapidly aging population and the increasing demand for elderly care, the adoption of artificial intelligence (AI) in healthcare products has emerged as a promising solution to enhance service delivery. This paper investigates the behavioral evolution of multiple stakeholders—namely, government entities, AI healthcare enterprises, and medical professionals—in the adoption process of AI-enabled elderly care products. By employing an evolutionary game theory model, we analyze the stability strategies of these stakeholders under varying initial conditions. Our findings reveal that government subsidies and regulatory measures play a crucial role in promoting the adoption of these technologies, while the attitudes of enterprises and medical professionals are significantly influenced by perceived costs and benefits. Simulation analyses were conducted using MATLAB 2019a to validate the model, providing insights into optimizing stakeholder engagement and enhancing the adoption of AI in elderly care. We propose actionable recommendations for policymakers and industry leaders to foster the integration of AI into elderly care services, addressing critical challenges and leveraging opportunities in this evolving landscape.