http://hdl.handle.net/123456789/17261 2026-10-17T02:50:49Z http://hdl.handle.net/123456789/21830 Assessing Management Information System (MIS) User Satisfaction through the Delone and McLean Model in Higher Education Alina Shaukat, 01-212251-001 Complex Management Information Systems (MIS) are currently being applied by higher education (HE) institutions in their practices in the administrative and academic functions and strategies [1]. These systems can be Student Information Systems (SIS) and Learning Management Systems (LMS), which can be discussed as a significant institution investment to help students decide relying on data [2]. The technical complexity is not the difference between the final success of the systems but rather the efficiency in their usage and acceptance by the end-users [3]. User satisfaction is one of the most vital indicators in evaluating the effectiveness of MIS in HE as the high rate of the former is linked with increased system utilization and increased merits generated by an organization [4]. To determine this multi-faceted notion mentally, the Delone and McLean (D&M) Information Systems (IS) Success Model is common among researchers [5]. It is a multi-dimensional paradigm that fits the theoretical framework of investigation of effectiveness of MIS in the HE sectors best [5]. The current phase of digital transformation has never been witnessed before in higher education institutions around the world due to the accelerated technological change, globalization of education, high levels of student mobility, and higher standards of quality, transparency, and accountability [1][2]. Data-driven reporting and performance monitoring that is being demanded by the governments, accreditation organizations as well as stakeholders are contributing to the demand of digital infrastructures that have necessitated universities to invest heavily in digital infrastructures. Management Information Systems (MIS) have become the center of the integration of academic, administrative, and strategic processes. For this reason, these systems are used to gather, process, store, and share data within the institutions allowing them to operate more efficiently and responsively in a competitive knowledge economy [6][12]. The use of MIS in higher education is not only a process of change of technology but also a change of processes and culture of decision making. MIS has become the foundation of university management of admissions, enrollment, assessment, grading, faculty and budgeting tasks as well as compliance reports. The adoption of these systems has transformed the flow of information among the departments and has minimized the silos and increased holistic oversight of the institution. Yet, the sophistication of these systems also poses the problems tied with their usability, acceptability by users, as well as sustainability over long-term, which contributes to the fact that the systematic analysis of their competent functioning is a key issue in the field of research [3][4]. Collectedly around the world, universities and colleges are finding themselves in a phase of deep digital change, a process of change precipitated not merely by new technological possibilities, but of core shift in the perception of stakeholders, regulatory pressures and competitive dynamics of the knowledge economy. The predominant use of elaborate Management Information Systems (MIS) that have evolved into administrative aids into strategic resources is the hallmark of this change. The academic and administrative processes have become highly dependent on systems like Student Information System (SIS), Learning Management System (LMS) and Enterprise resource Planning (ERP), which undertake all forms of work like admissions and enrolment; curriculum management and financial planning among others. Supervised by Dr. Hafiz Ishfaq Ahmad 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21829 Impact of Cognitive Biases on Online Consumer and Purchase Behavior: a Generational Study Laiba Khalid, 01-322242-008 The speedy improvement of e-Commerce and digitization of trade has transformed the rational decision-making model to judgmental decision-making model based on cognitive biases in the process of consumer decision-making. From the view of traditional micro-economics, a consumer is seen as a rational and info, systemically driven decision maker. However, with all the information that surrounds consumers, the time that they have to make a decision, and the ease of digitally persuading them, it seems logical that heuristics will be used to determine their buying decision. The name of this research is Cognitive Biases and Consumer Psychology in Online Purchase Decision Making, which studies about the influence of three cognitive biases, namely Anchoring, Scarcity and Social Proof on consumer behaviour. The biases predict a single behavioural outcome (Purchase Decision) which is measured as a composite of a wallet-buy item and a seven-day behavioural likelihood item. This paradigm is not similar to the psychology literature, which is prevalent and in which bias literature reviews only one bias and/or pure self-reported purchase intent is analyzed. This study aims to rank the primacy of prediction, that is, which of the three biases (anchoring, scarcity or social proof) better predicts the purchase decision, as well as whether or not such effects are different across generations, and which of them are the Millennials and Generation Z. The environment used is a mock e-commerce system where participants are exposed to various bias-inducing cues (e.g., high versus low price anchors, scarcity (limited time offers, limited stock), and social proof (Reviews/Popularity)). Also for the sake of greater explanatory power the study takes into account the modulating factors of gender, shopping experience and device type. The study examines by behavioral economics, consumer psychology and digital real-time metrics, how some theoretically valid and practically usable indications for some ethically questionable aspects of generation digital marketing and heavy reliance on persuasion in the digital commerce environment can be obtained. The experiment was conducted with N = 258 Pakistani consumers (Generation Z and Millennials) randomly assigned to one of four conditions: Anchoring, Scarcity, Social Proof, or Control. A one-way ANOVA revealed a significant overall effect of bias condition on purchase decision (F(3,254) = 7.96, p < 0.001, η2 = 0.086). Scarcity emerged as the strongest predictor (Cohen’s d = +0.49, medium positive effect vs. Control), followed by Anchoring (d = +0.27, small positive), while Social Proof produced a negative effect relative to Control (d = −0.39). A two-way ANOVA showed no significant condition-by-generation interaction (p = 0.944), indicating that the bias rankings were consistent across both generational cohorts. These findings provide an empirical hierarchy of cognitive bias effectiveness in the Pakistani e-commerce context and offer evidence-based guidance for ethical digital marketing strategy Supervised by Dr. Asif 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21831 Determinants of Artificial Intelligence (AI) Adoption for Literacy Enhancement in Secondary & Higher Secondary Schools: Evidence from District Swabi, Pakistan Muhammad Ali, 01-322242-027 Artificial Intelligence holds substantial transformative potential for educational systems worldwide; however, its integration within developing nations continues to encounter considerable obstacles. This investigation examined determinants influencing AI adoption for literacy enhancement within secondary and higher secondary educational institutions of District Swabi, Pakistan, employing the Technology Acceptance Model (TAM) as the theoretical underpinning. This research employed a quantitative methodology utilizing a cross-sectional survey design. Data were collected from 369 teachers across public and private secondary institutions through a structured questionnaire designed to measure perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention (BI), and literacy enhancement (LE). Statistical analyses including correlation and regression techniques were executed using Python programming language. The findings established that both perceived usefulness (β=0.396, p<0.001) and perceived ease of use (β=0.238, p<0.001) emerged as statistically significant predictors of teachers' behavioral intention to adopt AI technologies, collectively accounting for 34.5% of variance (R²=0.345). Furthermore, behavioral intention demonstrated significant influence on literacy enhancement (β=0.478, p<0.001), explaining 23.9% of variance (R²=0.239). Educators reported that AI contributed positively to reading comprehension, writing proficiency, vocabulary expansion, and student engagement. Nevertheless, notable challenges were identified: 36.6% of educational institutions lacked computer laboratory facilities, 21.1% experienced unreliable internet connectivity, and teachers cited insufficient training opportunities and technical support. This investigation concludes that successful AI adoption within Pakistani secondary schools depends substantially on teacher perceptions of usefulness and ease of use, alongside institutional support mechanisms and infrastructure development. Recommendations encompass strategic investment in digital infrastructure, implementation of comprehensive teacher training programs, and formulation of supportive educational policies. This research contributes localized empirical evidence regarding AI adoption determinants while offering practical guidance for policymakers, school administrators, and educational authorities seeking to integrate AI for literacy enhancement within Pakistan's educational framework. Supervised by Dr. Asad Ullah 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21826 Bridging Consumer Engagement and Product Innovation: A Descriptive Investigation of Big Data Analytics in Digital Marketing Strategies in Pakistan Zainab Shahid, 01-321242-034 This study examines how Big Data Analytics influences Product Innovation, mediated by Digital Marketing Strategies and moderated by Consumer Engagement, within the service sector of Pakistan, a developing economy context. As Pakistani firms increasingly invest in digital infrastructure yet struggle to convert these investments into innovation outcomes, this research addresses the critical gap between analytics capability and tangible product innovation. Using a quantitative and cross-sectional research design, data were collected from a sample of 115 mid-to-senior-level professionals working across IT, telecommunications, banking, healthcare, FMCG, media, financial services, e-commerce, and education. The proposed methodology employs simple and multiple linear regression via SPSS, utilizing the Baron and Kenny approach for mediation testing and hierarchical multiple regression for moderation analysis to rigorously examine the hypothesized relationships. Data were analysed using simple and multiple linear regression via SPSS, employing the Baron and Kenny approach for mediation and hierarchical multiple regression for moderation. The expected outcomes include confirmation of a significant positive direct effect of Big Data Analytics on Product Innovation, full mediation of this relationship through Digital Marketing Strategies, and a significant moderating role of Consumer Engagement that may reveal a compensatory mechanism wherein digital marketing drives innovation more strongly in low-engagement settings. The findings indicate that Big Data Analytics has a significant positive direct effect on Product Innovation. Digital Marketing Strategies fully mediate this relationship, demonstrating that analytics capability enhances innovation primarily by enabling more effective digital marketing practices. Consumer Engagement significantly moderates the relationship between Digital Marketing Strategies and Product Innovation; however, the moderation is negative, suggesting that digital marketing strategies exert a stronger impact on innovation when consumer engagement is low. The mediation and moderation results together reveal a compensatory mechanism through which digital marketing drives innovation in the absence of rich organic consumer engagement. In conclusion, this study extends the Resource-Based View and Dynamic Capabilities Theory to Pakistan’s service sector, providing managers with an evidence-based roadmap for investing in analytics and digital marketing capabilities, and offering policymakers empirical justification for promoting digital infrastructure and analytics skills development to foster innovation in developing economies. Supervised by Ms. Nadia Kalsoom 2026-01-01T00:00:00Z