The purpose of this investigation was to establish the connection between ownership arrangement and valuation of the ability of a business to carry on. The investigation's goal is to clarify how various ownership forms affect how to assess a company's ability to remain in business. The listed firms at ASE throughout the year 2016–2022, according to this study of 65 covers the years 2016–2022, a dynamic panel system GMM estimation, had demonstrated a substantial degree of ownership structure in line with higher going concern awareness and implementation in Jordan. This study indicated that family ownership, foreign ownership, and block holder ownership were particularly important in affecting Jordan's going concern. This study explores the complex relationship between ownership forms and a company's ability to continue operating. In light of our findings, it is crucial for both practitioners and policymakers to adopt a thoughtful and nuanced approach when assessing the continued viability of businesses. This involves considering the unique ownership structures and governance mechanisms of each company.

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.