Technopreneurship in Healthcare: Evaluating User Satisfaction and Trust in AI-Driven Safe Entry Stations

Abstract

The development of technology in the health sector has encouraged the adoption of technopreneurship, especially in the application of artificial intelligence (AI) to support the safety and efficiency of health services. One of the innovations that has emerged is the AI-driven Safe Entry Station, which is designed to improve the safety and comfort of patients and medical personnel. However, the success of implementing this technology is highly dependent on the level of user satisfaction and trust. This study aims to evaluate the level of user satisfaction and trust in Safe Entry Stations in the health care environment and also explore the variables that influence the acceptance of this technology among users. This research method uses a quantitative approach with a survey involving 673 respondents from various health institutions that have used Safe Entry Stations. Data were analyzed using Structural Equation Modeling (SEM) with SmartPLS 4.0 software to identify the relationship between User Satisfaction (US), trust (TR), behaviour intention (BI), usage behaviour (SB) and technopreneurial impac (TI). The results showed that US and TR significantly influences BI and UB. Additionally, BI strongly impacts TI, suggesting that stronger intentions lead to a greater perceived impact on technopreneurship. This study found that AI-driven Safe Entry Stations has great potential for widespread adoption in the healthcare sector. These findings provide important insights for further development of this technology as well as technopreneurship strategies in the healthcare sector.