http://hdl.handle.net/123456789/180 2026-10-17T01:49:32Z http://hdl.handle.net/123456789/21842 Impact of Artificial Intelligence Adoption on Supply Chain Performance in Pakistan’s Textile Sector withthe Mediating Roles of Supply Chain Resilience and Supply Chain Innovation Uswa Saeed, 01-322242-033 This study examined the impact of the adoption of AI on the performance in the supply chain in the Pakistani textile industry, considering the mediating variables as supply chain resilience and supply chain innovation. The research itself was mainly based on the theory Organizational Information Processing Theory, which describes how companies can improve their performance by improving their ability to process information when they are in dysfunctionality. In addition, the Dynamic Capabilities View highlighted the importance of perception of change in order to realign resources to redesign the processes to achieve better performance in the operations. The quantitative research approach was used and the data set was obtained from 384 respondents related to textile organization of Pakistan. The relationships were tested using SmartPLS 4 software with the application of Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. Results indicate that there's a robust constructive relation between AI and supply chain resilience and supply chain innovation. AI is also directly impacting the supply chain's performance. The mediation analysis, however, indicates that Supply chain innovation plays a significant mediating role between AI adoption and supply chain performance; by contrast, Supply chain resilience doesn't play a significant mediating role between AI adoption and supply chain performance. Based on the findings, it can be concluded that adopting AI can positively impact supply chain performance, primarily by facilitating the adoption of new supply chain practices—particularly digital process improvement, supply chain coordination, and data-driven decision-making. Whilst AI increases resilience this alone may not be enough to enhance performance and require innovation and operational integration. The study makes a novel contribution to the literature by the designing and testing of an integrated model on AI adoption, resilience, innovation and performance in an emerging-economy context of textiles. In practical terms, the study's outcomes indicate that textile companies need to integrate AI investments with strategies that prioritize innovation to drive tangible improvements in supply chain performance. Supervised by Ms. Javeria Aftab 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21839 Strengthening Sustainable Supply Chains through E-Procurement Adoption: The Mediating role of Product Innovation in the Textile Industry Malik Asimullah Khan, 01-322242-025 Sustainability and digital change have grown in importance and enticed textile companies to consider electronic procurement to enhance supply chain effectiveness. But the empirical research on the contribution of various e-procurement practices to the sustainability of supply chains in the form of product innovation is little. This research has analyzed how E-Design, E-Sourcing, E-Negotiation, and E-E-Evaluation affect Supply Chain Sustainability and Product Innovation is the mediating variable. Dynamic Capability Theory is the theory that underpins the study and describes how organizations can build and restructure digital capabilities to attain sustainable competitive advantage. Positivist philosophy, deductive reasoning, descriptive cross-sectional research design, and a survey strategy were used as quantitative research approaches. The structured questionnaire was used to gather primary data with 310 employees of textile manufacturing companies based in Islamabad and Rawalpindi, Pakistan, by convenience sampling. The Smart-PLS were used to analyze data. Descriptive statistics, reliability and validity test, correlation test, regression test and mediation test were all analyzed. The results indicated that E-Design, E-Sourcing, E-Negotiation and E-Evaluation significantly positively influenced Supply Chain Sustainability. E-Sourcing appeared to have the most significant positive impact, then E-Design, E-Negotiation and E-Evaluation. Moreover, Product Innovation played a huge role in mediating the associations among all four e-procurement practices and Supply Chain Sustainability, which means that digital procurement practices create more sustainable effects in case they increase the ability of products to become innovative. It is concluded in the research that by incorporating innovative e-procurement systems with ongoing innovations in products, textile companies can enhance their environmental, economic, and operational sustainability. The study also adds to the body of literature by extending Dynamic Capability Theory to the digital procurement and sustainability context and offers practical advice to managers who aim to enhance sustainable performance of the supply chain by developing e-procurement strategies that are based on innovation. Supervised by Dr. Muhammad Waseem 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21841 Uses of Artificial Intelligence in Improving Environmentally Sustainable Supply Chain Performance: Mediating Role of Supply Chain Resilience and Moderating Role of Internal Green Supply Chain Management Practices Muhammad Hassan Raza Khan, 01-222242-005 The rapid growth of Artificial Intelligence (AI) has significantly changed modern supply chain operations by improving effectiveness, adaptability, and sustainability. As more businesses use AI-powered technologies, it is critical to analyze their effect on Environmentally Sustainable Supply Chain Performance (ESSCP). Furthermore, ability of supply chains be resilient during disturbances, as well as the application of internal green supply chain management practices, play a key role of obtaining environmental sustainability. The main objective of this research was to examine the effect of AI adoption on Environmentally Sustainable Supply Chain Performance. Furthermore, study intended to explore mediating impact of Supply Chain Resilience (SCR) between AI adoption and ESSCP. Furthermore, this study aimed to evaluate the moderating impact of Internal Green Supply Chain Management Practices (IGSCMP) in enhancing relationship between AI adoption and supply chain resilience. Primary research has been carried out in this research with the data collected by conducting a survey. The selected group consists of supply chain professionals in various sectors of supply chain management within Islamabad and Rawalpindi. The SPSS software package has been used to analyze the data obtained. The results suggest that integrating AI into supply chain operations improves environmental sustainability performance, not only on its own but also by strengthening supply chain resilience, which acts as a mediating mechanism. In addition, strong internal green supply chain management practices were found to reinforce the link between AI adoption and resilience outcomes, making that relationship more pronounced. Overall, the study extends existing academic understanding while also offering practical direction for managers and policymakers who aim to build more resilient and environmentally responsible supply chains through the use of AI-driven systems. Supervised by Dr. Muhammad Haroon Malik 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21843 The Influence of Managerial Attitudes and Perceptions on Artificial Intelligence Adoption in Pakistan's Banking Industry: The Moderating Role of Technological Infrastructure Fatima Saleem, 01-221251-002 Artificial Intelligence (AI) has emerged as a transformative technology in the banking industry, improving operational efficiency, decision-making, fraud detection, and customer service. adoption in Pakistan's banking industry while investigating the moderating effect of technological infrastructure. A quantitative research approach was adopted using a structured questionnaire administered to 199 managers working in commercial and Islamic banks in Islamabad, Lahore, and Karachi. Data were analyzed using SPSS Version 26, employing descriptive statistics, reliability analysis, correlation analysis, multiple regression, hierarchical regression, and an independent-samples t-test. The findings revealed that Managerial Attitudes and Perceptions positively and significantly influenced AI Adoption (β = 0.430, p < .001), while Technological Infrastructure also had a significant positive effect on AI Adoption (β = 0.297, p < .001). The regression model explained 47.4% of the variance in AI Adoption (R² = 0.474; Adjusted R² = 0.469; F = 88.31; p < .001). Furthermore, technological infrastructure significantly moderated the relationship between managerial attitudes and AI adoption, indicating that stronger technological capabilities enhance the effectiveness of managerial support in implementing AI. Comparative analysis also showed that commercial banks possessed stronger managerial support and technological infrastructure than Islamic banks. The study concludes that successful AI adoption in Pakistan's banking industry requires both positive managerial attitudes and robust technological infrastructure. The findings contribute to the Technology Acceptance Model (TAM) and the Technology–Organization–Environment (TOE) framework while providing practical recommendations and an implementation roadmap to support AI adoption in the banking sector. Supervised by Dr. Asif Khattak 2026-01-01T00:00:00Z