http://hdl.handle.net/123456789/17261 Fri, 01 May 2026 19:33:36 GMT 2026-05-01T19:33:36Z http://hdl.handle.net/123456789/21043 Integrating Artificial Intelligence into Management Information Systems to Enhance Public Sector Decision-Making Quality; Mediating role of Trust in AI and moderating Effect of Computer Self-Efficacy between AIMIS and Trust in AI Asim Farooq, 01-222241-019 The integration of Artificial Intelligence into Management Information Systems has become increasingly important for enhancing decision-making quality in the public sector, where efficiency, transparency, and accuracy are critical. The present study examined the role of AI Integration into Management Information Systems in enhancing public sector decision-making quality, with a specific focus on the mediating role of Trust in Artificial Intelligence and the moderating effect of Computer Self-Efficacy on the relationship between AI integration and trust in AI. Grounded in technology acceptance and socio-technical system perspectives, this study adopted a quantitative, cross-sectional research design. Data were collected from 200 public sector employees holding managerial, administrative, and IT-related positions across multiple departments. Standardized self-report instruments were used to measure AI integration into MIS, trust in AI, computer self-efficacy, and decision-making quality. Statistical analyses were conducted using SPSS, including descriptive statistics, independent sample t-tests, ANOVA, correlation analysis, and mediation and moderated-mediation testing using PROCESS macro. The results indicated that AI integration into Management Information Systems positively influences public sector decision-making quality, demonstrating that AI-enabled systems support more informed, timely, and effective decisions. Although trust in automated systems showed a significant association with decision-making quality, mediation analysis revealed that the indirect effect of trust was not statistically significant. This indicates that trust in automated systems does not function as a mediator in the relationship between AI integration into Management Information Systems (AIMIS) and decision-making quality. However, the moderation analysis revealed that Computer Self-Efficacy did not significantly moderate the relationship between AI integration into MIS and trust in AI, indicating that confidence in computer usage alone may not be sufficient to strengthen trust in AI-driven systems. Additionally, independent sample t-test results showed no significant gender differences in trust or decision-making outcomes, highlighting the consistency of AI-related perceptions across male and female employees. The findings contribute to the growing body of literature on AI adoption in the public sector by integrating technological and psychological factors into a single explanatory framework. The study offers valuable implications for policymakers, system developers, and public administrators aiming to leverage AI-enabled MIS for improved governance and decision-making. Supervised by Dr. Arif Khattak Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21043 2025-01-01T00:00:00Z http://hdl.handle.net/123456789/21044 Analyzing the impact of MIS Adoption on Organizational Culture Dimensions. A Quantitative Study of Small and Medium Enterprises Naseem Abbas, 01-321232-031 Small and Medium Enterprises (SMEs) have a great role to play in economic growth, creation of jobs and innovation but most SMEs find it difficult to perform sustainably because of their limited resources, technological capacity and resistance to change. With the rise of digitalization, the use of Management Information Systems (MIS) has become a necessary measure in enhancing decision-making, operational efficiency and competitiveness. The thesis explores how MIS adoption relates to organizational culture in SMEs, how MIS affects important dimensions of culture-involvement, consistency, adaptability and mission as well as how organizational culture, leadership and change management can support or inhibit MIS adoption. This relationship is significant since technological investments tend to collapse in cases where cultural alignment is overlooked especially in resource-limited SME settings. The research examines the literature on MIS development, digital transformation of organizations and organizational culture typologies, specifically Denison Organizational Culture Model and the Technology Acceptance Model (TAM). Previous literature indicates that MIS provides substantial gains in performance, however, its effective implementation depends greatly on the organizational culture, leadership style and employee willingness to change. Another gap in the literature is that there is no empirical research on the relationship of the relationship in SMEs operating in developing economies. It utilized a quantitative research methodology that was a cross-sectional survey. A total of 150 managers and decision-makers of SMEs in manufacturing, IT and service industries were sampled. The dimension of MIS adoption and organizational culture were measured through standardized questionnaires. Analysis of the data was carried out with the help of SPSS and AMOS with the help of descriptive statistics, correlation analysis, multiple regression, and Structural Equation Modeling (SEM). The results reveal that there is a strong positive correlation between MIS adoption and all the four dimensions of organizational culture. Adoption of MIS leads to employee participation, internal consistency, adaptability to environmental changes and mission clarity. The mediating factor found to be effective in aligning MIS to organizational culture is leadership and effective change management. The study concludes that by embracing MIS and supportive leadership, training, and culture based change strategies SMEs will be able to perform and be more sustainable. It advises that management and policymakers of SMEs should strive to incorporate technological projects with the cultural development to achieve an effective digital transformation Supervised by Dr. Sana Aroos Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21044 2025-01-01T00:00:00Z http://hdl.handle.net/123456789/21046 Implementing Smart Compliance by Experimenting with Predictive Documentation and Intelligent ISO 27001 Checklist in AI-Driven Governance Ali Afzal, 01-321242-004 Information security has become a critical concern for organizations worldwide, and ISO/IEC 27001:2022 provides a recognized framework for managing information security risks, improving governance, and enhancing stakeholder trust. Despite these benefits, many organizations delay or avoid implementing the standard due to high costs, complex documentation, limited internal expertise, and time constraints. This study investigates the challenges in ISO/IEC 27001 implementation and evaluates the role of a smart, AI-driven predictive ToolKit, which consists of semi-automated documentation and an intelligent ISO 27001 checklist, in supporting effective, efficient, and sustainable compliance. A quantitative research approach was adopted using a cross-sectional survey design. Data were collected from information security professionals and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4. The study examined the relationships between perceived benefits of ISO/IEC 27001, implementation difficulty, organizational avoidance behavior, and the effectiveness of the AI-enabled predictive ToolKit. The findings reveal that while organizations recognize the strategic and operational benefits of ISO/IEC 27001, perceived implementation difficulty remains a major barrier, leading to avoidance behavior. The results further show that the AI-driven predictive ToolKit reduces this difficulty by simplifying documentation, providing clear guidance, and offering a dynamic, intelligent ISO 27001 checklist to monitor compliance. Implementation difficulty and ToolKit effectiveness were found to mediate the relationship between perceived benefits and actual adoption of ISO/IEC 27001. Overall, this research demonstrates that AI-enabled predictive ToolKits, integrating documentation and intelligent checklists, can transform ISO/IEC 27001 implementation from a complex, manual process into a guided, manageable, and sustainable practice. The study provides practical recommendations for organizations, practitioners, and ToolKit developers, contributing to both academic knowledge and real-world governance, risk, and compliance practices. Supervised by Ms. Zahra Saleem Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21046 2025-01-01T00:00:00Z http://hdl.handle.net/123456789/21045 Influence of On-the-Job Training Effectiveness on Job Performance: The Mediating Role of Job Involvement and the Moderating Role of Perceived Organizational Support in IFMIS based Organizations Mujahid Sohail, 01-222241-008 Employee training programs have become the focus in order to improve performance in modern organizations, especially in more formalized public sector setting. This research investigates the effects of on-the-job training on employee performance using the mediating effects of job involvement and moderating effects of perceived organizational support (POS). Based on the human capital theory and social exchange theory, the research hypothesizes that, training enhances performance both directly and indirectly by increasing psychological involvement with work roles. Data were gathered using a quantitative research design where employees who work in an organization of the public sector were involved. On-the-job training and job involvement perceived organizational support and employee performance were measured using standardized and validated measurement scales. The hypotheses put forward were tested by the mediation and moderation analysis relying on the Hayes PROCESS macro of SPSS. The results indicate that on-the-job training contributes to employee performance in a significant positive manner. Moreover, job involvement was also determined to partly mediate the relations between training and performance and so showed that training improves performance through the enhanced psychological attachment and involvement of the employees with their jobs. The perceived organizational support in mediating between job involvement and employee performance was however not supported. This implies that in an organized organizational structure; performance results can be more affected by formal position and task needs than the perceived overall support of discretion. On the whole, the research can add to the current literature by shedding light on the psychological process of training performance impact and by elucidating the contextual role of organizational support. Human resource managers and policy implications are presented based on the need to create training programs that promote employee engagement as a way of attaining long-term performance gains. Supervised by Dr. Arif Khattak Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21045 2025-01-01T00:00:00Z