درخت حوزه‌های تخصصی

Background: The rapid growth of computer technology in recent decades suggests that people today, in addition to print media, have many electronic information items that need to be managed appropriately and have increased the use of personal computers.Aims: This Researches descriptive and analytical based on the purpose of applied Research, and in terms of data collection and nature and comparison between the activities of personal information management and two measures of knowledge and skills has been presented.Methodology: The statistical population includes the students of Jundishapur University of Medical Sciences in Ahvaz in the academic year 2017-2018. To determine the statistical population, the sampling method was used by determining the total number of students 1300 and using the Karjesi-Morgan table, the approximate number of the sample was determined to be 297. The data collection was done using the questionnaire of 2012 and in order to analyze Pearson and Spearman correlation tests and AMOS and SPSS software were used.Results: The results of the survey show that knowledge and skill variables have a significant and positive effect on personal information management, and age, level of education, and school of study have a significant and positive effect on personal information management.Conclusions: The results of the research show that the status of personal information management of medical students in Jundishapur Ahvaz has a positive and meaningful effect based on the knowledge and skills of the students. According to the changes made in the management of personal information activities, it can be said that the difference in the amount and amount created in the variables of personal information management can be seen. The main reasons for this can include not having enough time, work pressures and lack of familiarity with the activities required for personal information management.

The advancement of artificial intelligence (AI) and its growing societal importance are reshaping decision-making processes and policy analysis roles. This study examines the readiness of manufacturing companies in Malaysia to embrace AI technology, considering its potential to enhance decision-making, productivity, quality control, job automation, and data analysis. Focusing on the Technology, Organization, and Environment (T-O-E) readiness framework, the research investigates the relationship between these dimensions and AI adoption readiness among manufacturing companies in Shah Alam, Selangor, Malaysia. AI adoption readiness serves as the dependent variable, while technological, organizational, and environmental readiness dimensions act as independent variables. The study applies the T-O-E framework to AI readiness and proposes a framework for assessing AI readiness at the manufacturing level. It identifies factors influencing readiness within the technological, organizational, and environmental dimensions, including relative advantage, compatibility, resources, competitive pressure, top management support, and government regulations. Through rigorous analysis, patterns, trends, and correlations are revealed, highlighting a significant link between the T-O-E readiness dimensions and AI adoption readiness. Notably, organizational readiness emerges as a key driver of AI adoption in Malaysian manufacturing companies. The results of this investigation have broad implications, offering suggestions to improve organizational preparedness and unlock AI’s potential benefits for businesses in the industrial sector. Additionally, the research lays the groundwork for further studies on AI readiness across various industries and international contexts. As AI becomes increasingly integrated into manufacturing processes, adaptive businesses gain competitive advantages on a global scale. These advantages include increased productivity, informed decision-making, streamlined quality control, improved customer satisfaction, and potential contributions to economic growth. The study concludes by recommending strategies to reinforce organizational readiness and emphasizes the need for future research to deepen understanding of AI adoption readiness in the manufacturing industry. The integration of AI technology offers benefits such as enhanced productivity, decision-making, quality control, and customer satisfaction, granting businesses a competitive edge in the digital landscape and increasing stakeholder interest.