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.

Cloud computing systems have been identified as an important technology that could increase the competitiveness and effectiveness of small and medium-sized enterprises (SMEs), but there has been less research focusing on examining their use from the perspective of their antecedents. The proposed study aims to explain the antecedent factors that influence the continued use of cloud computing systems in Jordanian SMEs by employing an integrated approach that combines the Technology-Organization-Environment (TOE) framework, the Fit-Viability Model (FVM), and the Expectation-Confirmation Theory (ECT). A structured questionnaire survey was conducted to examine opinions from 276 Jordanian SMEs, which showed that relative advantage, perceived benefit, simplicity, adaptability, and perceived security are major antecedent factors in defining perceived appropriateness. Characteristics related to organizations, involving the importance of reading and the role of senior management members in organizations, are major antecedent factors in defining viability. Mimetic forces exerted in organizations are major antecedent factors that have a positive association in defining viability in organizations. On the other hand, coercive forces are major antecedent factors that have negatively affected viability in organizations. The appropriateness and viability of technologies are major antecedent factors in defining an individual’s desire to adopt cloud computing systems for an extended period of time in organizations. The proposed study suggests that the fitness of technologies is the most effective predictor of cloud computing system adoption in organizations. The proposed research study uses an integrated research theory that reflects on increasing the awareness needed to detail cloud computing systems. Cloud computing studies have never encountered such increased awareness before.

This study investigates the benefits of Generative Artificial Intelligence (GAI) in human resources operations. It focuses on several key outcomes that include reliability, validity, digitalization, relative advantage, online response, computability, and the time and money costs. Basically, the study seeks an understanding of the less-consistent benefits of using GAI in HR. Data from 290 information technology professionals in Amman Town were collected during a well-planned public examination. The analysis uses a new approach to the method with IBM SPSS version 21 integrated with smart PLS. The findings reveal that determinants such as reliability, validity, digitalization, and relative advantage are strong in terms of efficiency, while computability and online response collaboration are weak determinants. The importance of the research is that it identifies the glitches when GAI skills are used in human resource management; hence, focusing on some vital areas of reliability, validity, digitalization, relative advantage, online responsiveness, and computability, one will have a detailed analysis of the potential issues while using GAI within HR, along with the possible solutions.

The research investigates the link between technology, organization, and environment, and the uptake of artificial intelligence among SMEs in Jordan. The objective is to get a deeper understanding of the factors that promote or hinder enterprises' use of artificial intelligence during the recruitment of leaders. A total of 295 participants, who were owners or managers in several SME sectors, manufacturing, including services, construction, and agriculture, were selected via judgmental sampling. Data collection was conducted utilizing a survey instrument, and the collected data was processed employing Smart PLS. The findings demonstrated a substantial correlation between attitude toward artificial intelligence uptake and factors such as relative advantage, complexity, top management commitment, and organizational preparedness. Nevertheless, factors like competitive pressure, external assistance, a favorable regulatory environment, compatibility, and staff flexibility do not significantly influence the attitude toward the uptake of artificial intelligence. In summary, these findings provide valuable insights for decision-making and resource distribution. They underscore the significance of factors such as relative advantage, complexity, top management commitment, and organizational readiness in achieving goals in the field of artificial intelligence. Additionally, they identify areas where efforts may not result in significant effects. The practical ramifications and future study paths are emphasized according to current technological needs.