Impact of Digital Twinning on Health Service Quality and Sustainable Competitive Advantage: A Study with Private Hospital Professionals

The paper assesses the impact of digital twinning (DT) on health service quality (HSQ) and sustainable competitive advantage (SCA) at private hospitals in Egypt. Data were collected from 300 of 69,650 employees at private hospitals in Egypt. A questionnaire was posted on private hospitals’ intranet and could be accessed by clicking on a link in the e-mails. Participants consisted of hospital employees who completed a questionnaire that assessed the relationship of DT with HSQ and SCA. The results showed DT has a strong relationship with HSQ and SCA. Specifically, there is a positive link between HSQ and DT dimensions (DT goals, policies and legislation for DT, digital infrastructure, trained human resources, electronic communities, and obstacles to applying). Also, there is a positive relationship between the dimensions of DT and SCA. The research provides an explicit relationship for DT with other variables in the organization. The findings contribute to a better understanding of DT’s influence on HSQ and SCA. DT acts as an important tool for enhancing HSQ and SCA. The paper promotes understanding the dimensions of DT, HSQ, and SCA. The study uses DT dimensions as independent variables, with HSQ and SCA as dependent variables, which is new. In this study, a model has been built to analyze the relationship between DT, HSQ, and SCA. DT is a groundbreaking technology that creates virtual replicas of physical objects, systems, and even processes. The DT’s benefits are far-reaching. By simulating real-world scenarios in a virtual environment, managers can test, analyze, and optimize their operations without risks and costs associated with physical prototyping. Digital twins can also be used to monitor and predict the performance of complex systems, such as industrial equipment or entire cities. Additionally, digital twinning can facilitate collaboration and knowledge-sharing among stakeholders to make data-driven decisions and drive innovation. The DT implications are significant, with potential applications across various industries: healthcare, manufacturing, energy, and transportation. For instance, digital twins can be used to create personalized models of patient anatomy for more accurate diagnoses and treatments. In manufacturing, digital twins can optimize production processes, reduce waste, and improve product quality. However, the widespread adoption of DT also raises important questions about data ownership, security, and ethics. As digital twins become increasingly sophisticated, there is a growing need for standards and regulations to ensure that they are developed and used responsibly. Moreover, the integration of DT with other emerging technologies, such as artificial intelligence and the Internet of Things (IoT), will require careful consideration of the potential risks and benefits, as well as the development of new business models and partnerships.