The present study examined cloud computing adoption and organizational performance, with particular emphasis on the roles of security and scalability within organizational settings in Punjab and Sindh, Pakistan. The study was significant because the increasing reliance on cloud-based technologies has created opportunities for organizations to improve operational efficiency, flexibility, productivity, and resource management, while concerns related to data security and the ability of cloud systems to accommodate changing organizational requirements remain important challenges. A quantitative, cross-sectional survey research design was adopted, and data were collected from 433 respondents working in relevant public, private, and semi-government organizations and institutions. A structured and adopted questionnaire was used to measure cloud computing adoption, security, scalability, and organizational performance through a five-point Likert scale. Data were collected through an online Google Forms questionnaire, which was distributed electronically to eligible respondents in Punjab and Sindh. The collected responses were initially organized and screened in Microsoft Excel and were subsequently transferred to IBM SPSS for statistical analysis. Descriptive statistics, Cronbach’s alpha reliability analysis, Pearson correlation, multiple linear regression, independent-samples t-test, one-way ANOVA, and Tukey HSD post-hoc analysis were conducted. The findings demonstrated that cloud computing adoption was positively associated with organizational performance, while security and scalability also showed positive relationships with organizational performance. The regression findings further indicated that cloud computing adoption, security, and scalability made significant contributions to organizational performance, while the group-comparison analyses showed that organizational performance differed significantly across different levels of cloud computing adoption. Overall, the study concluded that effective cloud computing adoption, supported by strong security and scalable technological infrastructure, can contribute substantially to improved organizational performance. The study provides useful implications for organizational managers, IT professionals, policymakers, and decision-makers seeking to develop secure, flexible, and performance-oriented cloud-computing strategies.
Rimsha Arif, Ali Yousuf Khan, Engr A. S. Sadiq et al.· SOCIAL PRISM· 0 citations
Artificial Intelligence (AI)-supported education is increasingly transforming higher education by providing personalized learning, immediate academic assistance, and flexible access to educational resources; however, its psychological implications for students remain an important area of investigation. The present study examined the relationships among Artificial Intelligence-Supported Education, Student Anxiety, Academic Engagement, and Coping Self-Efficacy, with particular emphasis on the moderating role of coping self-efficacy in the relationship between anxiety and academic engagement. A quantitative, cross-sectional research design was employed, and data were collected from 268 university students from higher education institutions in Punjab and Sindh, Pakistan. Data were collected through an adopted structured questionnaire using online Google Forms, and the completed responses were organized in Microsoft Excel and analyzed using IBM SPSS. Descriptive statistics, Cronbach’s alpha reliability analysis, Pearson correlation, multiple linear regression, independent-samples t-test, one-way ANOVA, post-hoc analysis, and moderation analysis were employed. The findings indicated significant relationships among the major study variables, with AI-supported education being positively associated with academic engagement and negatively associated with student anxiety. Student anxiety was negatively associated with academic engagement, whereas coping self-efficacy demonstrated a positive association with academic engagement. The regression findings further indicated that AI-supported education, student anxiety, and coping self-efficacy were significant predictors of academic engagement. The moderation findings demonstrated that coping self-efficacy significantly weakened the negative relationship between student anxiety and academic engagement, highlighting its potential protective role in students’ academic experiences. The study contributes to the emerging literature on AI-supported higher education by demonstrating that the effectiveness of AI-based learning should be considered alongside students’ psychological well-being and coping resources. The findings have practical implications for universities, educators, and policymakers in developing AI-supported learning environments that promote academic engagement while addressing student anxiety and strengthening coping capabilities.
Agha Fakhar Imam, Rimsha Arif, Farzana Saeed et al.· Journal of Global Social Tra...· 1 citation
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