This study investigates the determinants of Long-Term Care Insurance (LTCI) adoption intention using the Unified Theory of Acceptance and Use of Technology (UTAUT), with Technology Readiness (TR) as a moderating variable. A quantitative approach was applied, utilizing self-administered questionnaires from 180 participants across health service institutions in Guangxi Province, China. Data were measured on a seven-point Likert scale and analyzed using Structural Equation Modeling (SEM) via SmartPLS. Results confirm that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence LTCI adoption intention. Additionally, TR moderates these relationships, strengthening their effects. The findings underscore TR's critical role in enhancing LTCI adoption and offer practical insights for policymakers and practitioners seeking to promote LTCI uptake.

This study examines the adoption intention of the Long-Term Care (LTC) regulatory system in Guangxi, China, emphasizing the influence of innovation attributes and perceived risk. It analyzes how relative advantage, compatibility, complexity, trialability, and observability positively affect healthcare providers' and elderly care institutions' willingness to adopt the system. The study further explores the moderating role of perceived risk in strengthening the relationship between these innovation attributes and adoption intention. Data were collected through a survey of 370 professionals from hospitals, rural health centers, and elderly care institutions and analyzed using SPSS and structural equation modeling (SEM). Results indicate that all five innovation attributes significantly enhance adoption intention, with perceived risk amplifying these effects. The findings underscore the need for supportive policies, technological advancement, and coordinated stakeholder engagement to ensure successful LTC system implementation. This research provides actionable insights for policymakers and industry leaders to support the expansion of LTC insurance systems amid China’s aging population.

This study aimed to measure the impact of attitude, social influence, and perceived usefulness on e-money adoption intention. Data were collected using an online instrument involving 264 participants in Indonesia, and 287 participants in Turkey. Data were analyzed using exploratory and confirmatory factor analysis, and structural equation modeling and there were five hypotheses to be tested. The results of the study indicated a significant impact of attitude on adoption indention. Also, a significant influence of perceived usefulness on attitude and adoption intention was also detected. Moreover, a significant effect of social influence on perceived usefulness and adoption intention was observed. However, there were different results when the calculation focused on participants in each country. This study discussed recommendations for practitioners and future studies.