ACADEMIA International Journal for Social Sciences

The integration of the Internet of Things (IoT) into agriculture is revolutionizing the way food is produced, managed, and distributed. By combining networks of smart sensors, advanced communication protocols, distributed computing, and artificial intelligence (AI), IoT-based smart farming systems allow for precision monitoring and management of agricultural resources. These systems enable farmers to optimize irrigation, monitor crop health, and make real-time, data-driven decisions, thereby addressing challenges such as water scarcity, climate variability, and the growing demand for food. This paper presents an expanded IoT-driven smart agriculture framework with modular architecture, incorporating a perception layer, network layer, compute layer, application layer, and end-user layer. The framework integrates AI-based predictive analytics, blockchain for supply chain transparency, and renewable energy-powered devices. A pilot implementation on a 5-hectare wheat farm demonstrated a 30% reduction in water usage, early disease detection accuracy of 92%, and improved scalability for multi-crop environments. Comparative analysis with conventional farming practices shows significant improvements in resource efficiency and operational sustainability. The paper provides a detailed literature review, system design, experimental methodology, and future research directions, with a focus on interoperability, cost-effectiveness, and sustainability.

Adaptive capacity is also emerging as a significant factor defining organizational resilience, especially among the bodies in the government sector working in unpredictable and scarcity-prone conditions.This paper forms a part of the doctoral dissertation and is aimed at investigating the conceptual and functional interconnectivity between the notion of adaptive capacity and organizational resilience with reference to the Punjab Agriculture & Meat Company (PAMCO), which is a prime state-owned Agri-livestock enterprise in Pakistan. Based on a comprehensive analysis of scholarly literature, governance (institutional) reports, and structures, the paper has shown that there are five other key dimensions, including governance structures, leadership adaptive capacity, mechanisms of innovation, learning of institutions, and coordination among stakeholders, which form the basis of resilience-building activities. As emphasized in the study, an adaptive capacity can be used to enable public organizations to predict, absorb and respond to internal and external shocks without jeopardizing their strategic goals through institutional anchoring. The argument combines theory with policy/practice guidelines, providing a flexible approach to the reform of organizations of the same structure in the developing countries. With a clear understanding of the constraints that exist with regard to narrative synthesis, the paper nevertheless offers new conceptual clarity and sector-specific recommendations, which add up to the debate on the topics of the approach to public administration and organizational theory and as well as development policy. It is envisaged that research in the future will be conducted to carry out an empirical or cross-sectoral study with each and integrate it with digital government models to enhance resilience-driven reforms within the governance of the public sector.

In order to bridge the gap between academics and industry, this study paper delves into the crucial function of experiential learning. It gives some background and then dives into how experiential learning helps students build skills and critical thinking in preparation for the job by focusing on practical applications and hands-on experiences. The study draws attention to the problems by revealing the disconnect between what is taught in schools and what employers really need, and it stresses the importance of cultivating a talent pool that is both flexible and prepared to work in the real world. The paper's stated goals and objectives support its need for more experiential learning in schools so that students can meet the demands of employers. In order to demonstrate the real-world effects of experiential learning in producing a workforce with theoretical understanding and practical skills, the technique employs a thorough examination of case studies. The article presents findings that demonstrate the beneficial effects of experiential learning, with the use of in-depth case studies to back it up. The results highlight the value of partnerships between businesses and schools, and they suggest ways to bridge the gap between the two sectors by working together proactively and building an adaptive learning environment. The research report concludes by stressing the importance of experiential learning in training workers to adapt to a dynamic and unpredictable job market. In order to close the gap between the classroom and the workplace, the study promotes a paradigm shift by calling for the aggressive incorporation of experiential learning into course requirements.

The balance between dividend distribution and Corporate Social Responsibility (CSR) signifies a critical strategic challenge for firms, particularly in emerging markets. While dividend policy stimulates the allocation of earnings, CSR activities reflect a firm's commitment to social and environmental responsibilities. Board governance mechanisms may play a vital role in mediating this relationship. This study investigates the impact of dividend policy on CSR engagement and examines how board governance effectiveness moderates this relationship in publicly listed firms on the Pakistan Stock Exchange. Employing a dynamic panel data approach with the System Generalized Method of Moments (System GMM) estimation, the research analyses a panel of 100 firms over ten years from 2014 to 2023. Key variables include dividend payout ratio, CSR scores, and board governance indicators, controlling for firm size, leverage, and industry effects. Findings reveal a significant negative association between dividend payout and CSR activities, indicating that higher dividend payments tend to reduce CSR investment. However, effective board governance positively moderates this relationship, enabling firms to balance shareholder returns with social responsibility. Larger firms tend to engage more in CSR, while leverage negatively impacts CSR initiatives. The study underscores the importance of strong board governance in harmonizing dividend policies with CSR objectives, particularly in emerging markets. These insights have implications for corporate managers, investors, and policymakers aiming to foster sustainable and responsible corporate growth.

The convergence of financial technology (Fin Tech) and sustainable supply chain management (SSCM) has revamped the operational and strategic frameworks for global trade. Fin Tech advancements are rapidly becoming a major factor in assisting companies in meeting environmental, social, and governance (ESG) requirements, which are essential for fostering sustainable growth. The ways that digital finance tools-like block chain, AI, big data analytics, and digital payment platforms-assist in supplier risk assessment, environmental performance tracking, and ESG-based procurement are examined in this article. Drawing on recent empirical and theoretical literature, this study uses a qualitative approach and secondary data to investigate Fin Tech's revolutionary role in SSCM. Key findings indicate that digital finance technologies improve environmental monitoring by enabling supply chain traceability and transparency, speed up procurement processes through real-time ESG compliance checks, and enhance supplier risk management through predictive analytics.The paper contributes to the growing body of research on sustainability and digital transformation by providing a methodical analysis of Fin Tech capabilities. Policy implications emphasize the need for regulatory support, cross-sector collaboration, and capacity building to fully fulfill Fin Tech's promise in sustainable supply chains. The results provide credence to a digital-first approach to sustainability that places an emphasis on accountability, performance, and resilience.

The study is conducted with aim to analyze and examine the behavior of Asian Pacific stock market by analyzing the volatilities of five chosen stock markets; Karachi Stock Exchange (KSE) 100, Jakarta Stock Exchange (JKSE), Nikkei 225 Stock (N225), Shanghai Stock Exchange (SSE) and Taiwan Stock Exchange (TWSE) indices. This study takes 25 years, 2000 till 2024 of data by taking daily prices of the markets. The prices were transformed to log returns. In the descriptive statistics N225 index had recorded the highest positive return and highest negative return. Similarly, TWSE index recorded the lowest positive and lowest negative returns. Furthermore, modeling the volatilities, the study first estimated the ARCH effect for heteroscedasticity, the results are significant for all the series. The outcomes of GARCH model for all the series are significant. The study finds that past volatilities are significantly affecting the current volatilities and empirically the future returns and volatilities can be predicted by using past volatilities. The EGARCH model found that all the indices are having asymmetric volatilities. Thus, it is concluded that Asian pacific stock markets behave in similar way.

Supply Chain Finance solutions which utilize Financial technology analyze their effectiveness in providing improved liquidity access as well as cash flow stabilization together with credit risk management in worldwide value systems. The researcher explores how three financial technologies including blockchain and artificial intelligence and real-time analytics transform standard Supply Chain Finance procedures. The researcher used both survey results from 120 financial professionals in diverse sectors and semi-structured interviews with 15 respondents.FinTech technology improves financial agility because it supports efficient payment processing together with better visibility of working capital and reduces cost expenses. The common obstacles to adoption primarily affect SMEs operating in developing markets because they face both insufficient digital connectivity alongside regulatory policy hurdles. The combination of qualitative research findings elevates the role of FinTech technology in ESG-financed funding as well as supplier risk measuring systems.The research suggests that digital supply chain finance solutions create a method for building stronger resilient worldwide supply relationships. SMEs will benefit from structured digital financing regulation which policymakers must establish and support with financing programs. Research on FinTech demand more evaluation of its value across various industries and needs to track performance beyond short-term metrics as well as integrate financial technology solutions with sustainable development initiatives.

This comprehensive review aims to find the causes of the decline in cotton production in Pakistan over the years. The study explains in detail the causes of the decline in production in Pakistan and the future of cotton production in Pakistan. Cotton, sometimes called 'white gold,' is traditionally the chief money spinner in Pakistani agriculture. This essential crop is the backbone of Pakistan's textile sector, contributing about sixty per cent of the country's overall exports. On the other hand, Cotton production sales in Pakistan have been worsening over the past decade, and the crop is facing several complications. This slumping cotton production is expected to drop to just 6.9 million bales by the 2024-25 season, down from 15 million bales just a decade ago. This is happening in the worst kind of season possible. There are several reasons for the decline in cotton production in Pakistan. The issues are climate change, obsolete agricultural techniques, a lack of investment in current technology, and government policies favoring alternative crops. In Pakistan, many pests carry a persistent risk to the cotton crop. These pests include the army-worm, white-fly, pink boll-worm, and jassid. These pests can inflict damage more significant than the economic harm threshold if allowed to continue uncontrolled. This may result in severe losses in both yield and quality. Mainly because the need for cotton revival is growing with time, the findings emphasized in this research constitute a vital addition to the current body of knowledge. These results will serve as a road map for decision-makers and institutions to revitalize the cotton crop in the core cotton zone. Before the completion of this research, there was a lack of sufficient scientific knowledge about cotton failure, particularly in the core cotton zone. A small number of the currently available research is descriptive, and their scope is restricted. For this investigation, a thorough list of constraints is retrieved and experimentally derived via principal component analysis. The reasons for cotton failure in the cotton zone are discussed. In this manner, the research fills in a methodological gap that was previously present and provides the foundation for the recommendations that will be used for the future course of action.

This study examines the role of machine learning in enhancing knowledge sharing practices among university faculty members. In the contemporary digital era, machine learning technologies are increasingly being integrated into higher education to improve academic collaboration and knowledge management processes. The study aims to explore how these technologies influence faculty members’ knowledge-sharing behavior in universities. The objectives of the study were to examine the level of machine learning utilization among university faculty members, to investigate knowledge sharing practices among faculty members, and to determine the relationship between machine learning and knowledge sharing. A quantitative research design based on a cross-sectional survey method was adopted for this study. The population consisted of approximately 22 universities in Islamabad with an estimated 4,000 faculty members. A sample of 300 faculty members was selected using stratified random sampling technique to ensure proportional representation of public and private sector universities. The research tool was a structured questionnaire based on a five-point Likert scale. Validity of the instrument was ensured through expert review, while reliability was confirmed through Cronbach’s Alpha test, yielding acceptable values above 0.70. Data were analyzed using SPSS software through descriptive statistics, correlation, and regression analysis. The first objective revealed that faculty members demonstrate a moderate level of machine learning utilization, and it is recommended that universities should provide training programs and technical support to enhance advanced machine learning adoption among faculty members. The significance of the study lies in its contribution to educational technology literature, as it provides empirical evidence on how machine learning can improve knowledge sharing, support academic collaboration, and assist policymakers in developing technology-driven strategies for higher education institutions.

The proliferation of the Internet of Things (IoT) has intensified the need for robust real-time anomaly detection to safeguard system reliability and operational efficiency. This study presents a comprehensive framework that integrates statistical methods with machine learning techniques for anomaly detection in IoT sensor data. Initial analyses employed descriptive statistics, correlation structures, Z-score, and Interquartile Range (IQR) to characterize data distributions, establish anomaly thresholds, and assess sensor stability. Results identified loudness as the most volatile feature, while light demonstrated high consistency. To enhance detection accuracy, multiple machine learning models were evaluated, including Logistic Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), and Neural Network (MLP). Comparative findings revealed that ensemble and deep learning methods significantly outperformed traditional approaches, with the Neural Network achieving superior accuracy and Random Forest providing strong efficiency. The results highlight the potential of hybrid statistical–machine learning frameworks for effective, scalable, and interpretable real-time anomaly detection in IoT environments.

The article is a biographical study of Faqeer Jameel Baig (more commonly referred to as Faqeer Baba) who was an obscure Sufi mystic, poet, scholar and the sole full brother of the renowned Pashtun warrior-poet Khushal Khan Khattak. He was born in Akora Khattak to the Khattak chieftain Shahbaz Khan, but his name became Jameel Baig because of his family’s connection with Mughals. The historical wrongs about the birth date of his life, commonly reported as 966 AH (1558 CE) - this paper will concentrate on the primary sources and the localized learning to determine the actual date when he was born 1024 AH (1615 CE). The work describes his life during his youth, the work as a son of a chieftain, his involvement at the Battle of Aka Khel (1050 AH) together with his father and brother, resulting in the martyrdom of his father. After this turning point, Jameel Baig abdicated his chieftainship, material possessions and legacy to lead a life of utter asceticism (Faqr) with the spiritual guidance of Hazrat Sheikh Rahamkar (Kaka Sahib). He took his family to Chashmai, setting up a sanctuary (Khalwat) where he performed vigorous self-mortification (Riyadat), in order to overcome his ego (Nafs). In spite of his renunciation, he was a kind benefactor, who financed marriages of the poor, distributed revenues of his estate at Nihalpura, and gave shelter to the family of Khushal Khan whenever life squeezed them. The paper also mentions his literary work in Pashto, Persian and Arabic including Tazkirat-ul-Awliya, alongside more oral narratives documenting his spiritual charisma (Karamat). Ultimately, this paper shines a lot on the life of Faqeer Jameel Baig as a writer, a Sufi saint, on the spiritual heritage he left and the bond he had with Khushal Khan Khattak.

Democracy in Pakistan has always developed within a difficult political environment shaped by civil-military tensions, institutional competition, political polarization, weak governance, and repeated constitutional disruptions. Although the country has maintained electoral institutions and experienced periods of civilian rule, democratic consolidation remains incomplete. In recent years, concerns about democratic backsliding have become more visible as political competition has increasingly been accompanied by restrictions on political participation, pressure on media, controversies surrounding elections, institutional confrontation, and a growing imbalance among state institutions. The 2024 general elections further demonstrated the complexity of Pakistan's democratic order: electoral competition remained significant, yet questions concerning political freedoms, the electoral process, representation, and the relationship between elected institutions and unelected centers of power continued to shape political debate.This article examines democratic backsliding and institutional resilience in contemporary Pakistan through a qualitative analysis of secondary sources, including academic literature, constitutional developments, democracy indices, institutional reports, and contemporary political analysis. The study argues that Pakistan should not simply be described as moving from democracy toward authoritarianism. Rather, it represents a more complicated form of democratic erosion in which formal democratic institutions continue to exist while their autonomy, accountability, and effectiveness are repeatedly challenged. The article focuses on five major areas: civil-military relations, electoral institutions, the judiciary, parliament and political parties, and media and civil society. It further argues that Pakistan's democratic institutions possess considerable resilience, particularly through constitutional continuity, electoral participation, judicial contestation, political mobilization, civil society activism, and public demand for representative government. However, institutional resilience alone cannot guarantee democratic consolidation. Long-term democratic stability requires stronger civilian supremacy, credible elections, judicial independence, parliamentary effectiveness, media freedom, political tolerance, and a political culture based on constitutional rules rather than short-term institutional advantage.

This study examined differences in the quality of work relationships among researchers working in an agricultural research institution in Punjab, Pakistan. Drawing on a sociological perspective of workplace relationships as socially and organizationally embedded experiences, the study investigated whether researchers’ perceptions of their relationships with immediate supervisors and coworkers varied according to marital status and job designation. Data were collected from 329 researchers using a stratified sampling technique. Quality of work relationships was measured through three items assessing satisfaction with relationships with immediate supervisors and coworkers and feelings of being valued in interactions with supervisors. The measure demonstrated satisfactory psychometric properties, including strong factor loadings, reliability, and acceptable variance inflation factors. Descriptive statistics, Welch’s ANOVA, and Games–Howell post hoc tests were used for analysis. Results showed significant differences in quality of work relationships across marital-status categories. Single researchers reported significantly higher scores than both married and divorced researchers. Significant differences were also found across job-designation categories. Scientific officers reported significantly higher quality of work relationships than senior scientists and principal scientists. The findings demonstrate that workplace relational experiences are differentiated by researchers’ social and organizational positions.

Paediatric neurological disorder is defined as delays in the nervous system development in children can result from genetic disorders, injuries, infections, low oxygen levels, and neurotoxins. These disorders in children affect their physical, cognitive, memory, motor, and speech functions. The dysfunction can lead to complicated ongoing problems. Therefore, physicians, parents, and caregivers must understand these issues to manage them effectively. The purpose of this research was to assess the quality of life (QoL) of caregivers for children with neurological disorder. Across-sectional study will be conducted to evaluate the QoL of caregivers of children aged 1 to 10 years old who have this neurological disorder, using a Qol questionnaire’s. This study to explore the quality of life experienced by caregivers of individuals with paediatric neurological disorders and to examine how this affects their lives. The Cross-sectional study carried out 377 children with neurological disorders and their caregivers to assess the quality of life of those responsible for the children’s daily care. Data was collected from caregivers of children with down syndrome, delayed milestone, epilepsy, and cerebral palsy in various tertiary hospitals and rehabilitation centres in Karachi, using a standardized Quality of Life (QoL) questionnaire, to assess caregivers' quality of life and the impact of paediatric neurological disorders on their lives. The data was evaluated and analysed using the most recent SPSS version 26. Most caregivers had poor to moderate HRQoL (56% poor, 39.8% moderate). Cerebral palsy and epilepsy were the most common conditions. SF-30 results showed mild–moderate physical limitations and moderate emotional and social difficulties (Cronbach’s α = 0.751). Child age, caregiver marital status, and caregiver–child relationship significantly affected HRQoL, while other demographic and clinical factors showed no significant association. The study found that caregivers of children with neurological disorders in Karachi experience significant physical, emotional, and social burden, leading to poor quality of life—especially among mothers. Marital status and the caregiver–child relationship significantly affect caregiver well-being. The findings emphasize the need for better family support systems, improved rehabilitation and education services, and further research to develop effective family-centered interventions.

The business environment in Pakistan, especially for listed companies on the Pakistan Stock Exchange (PSX), is competitive and uncertain, and requires a well-done financial performance for business survival and development. Even though the policy makers and business community makes different efforts to create a conducive environment for business, still the difference in financial performance of companies is noticeable where some companies are performing better whereas some have decreasing their profitalike. This has motivated further research on firm-specific issues, for example, financial leverage, but the work has not set a clear path for the managers and practitioners to set optimal financing strategies. The main objective of this research work is to examine the effect of leverage on Financial Performance of Listed Companies of Pakistan Stock Exchange especially in the context of financial and non-financial firms. The type of research used is a panel study and the data used is secondary data that comes from the financial statements of 20 companies for the period 2021-2025. ROA, ROE and the debt ratio represent financial performance and leverage respectively. Panel data regression techniques such as Fixed Effects (FE) and Random Effects (RE) were used to analyse the data, and the choice of the model was determined using the Hausman test. Descriptive statistics, correlation analysis, Fixed Effects and Random Effects panel regression models were used to analyze the data. Hausman test was used to decide on the model of estimation. Results show that leverage varies in impact by industry. Leverage has a significant negative impact on ROA and significant positive impact on ROE for financial firms. In non-financial entities, there is a positive and significant relationship between leverage and ROA as well as the ROE measure. From hausman test, the results show that the Random Effects model is the best estimator.

The Iran‑Israel war (2024) and the Red Sea crisis (2023–2025) have simultaneously disrupted two critical maritime chokepoints: the Strait of Hormuz and Bab el‑Mandeb. Using quarterly data for the United Arab Emirates (UAE, 2017‑2026) and comparable data for Pakistan, this study employs Generalised Method of Moments (GMM), quantile regression, and Vector Autoregression (VAR) with impulse response functions. The UAE’s GMM coefficient of the supply shock is +0.0235 (p>0.9) and its VAR impulse response never exceeds +0.0033 percentage points – the shock is effectively neutralised. Pakistan’s GMM coefficient is –1.6356 (p<0.001) and the first‑quarter impulse response is –6.0 percentage points. The divergence is explained by the three pillars of cross‑continental development: infrastructure (Logistics Performance Index, 4.0 vs. 2.6), institutional quality (Rule of Law Index, 0.68 vs. 0.38) and manageable political friction. A composite institutional‑strength z‑score places the UAE in the top‑right quadrant (high strength, negligible impact) and Pakistan in the bottom‑left quadrant (low strength, large negative impact). These results confirm that economic effects are borderless, but resilience is not. Policy implications include global chokepoint governance and targeted institutional reforms in vulnerable economies.

The rapid introduction of AI into the education sector has resulted in a major change which has influenced English Language Teaching and Learning significantly. This study compares the effectiveness of AI-driven learning systems to impart English language skills to students with more conventional classroom methods. The article examines how AI-based applications (generative AI applications, adaptive learning platforms, intelligent tutoring systems, speech recognition technologies, and other AI-based tools) can improve language learning, student autonomy, teacher efficacy, and speech recognition technologies and other AI-based applications. In more traditional learning settings, students and teachers sit next to each other and follow the instructions of pre-established course maps. The scholarly publications, books, and reports of various institutions provide secondary data on the study. Studies indicate that learning systems powered by AI prove to be beneficial to students in that they offer a more immediate feedback, simplify the process of accessing educational content, and increase their level of engagement with the subject matter. Such skills as emotional intelligence, ability to pursue systematic academic processes, and the capability to effectively communicate with other people are well ingrained in the minds of the students due to the traditional teaching methods. The research finds that digital inequality, less personal touch, and an over-reliance on technology solutions are the three main problems. To teach English in the new digital age, the authors of the study suggest a mixed learning paradigm that combines AI technology with traditional teaching methods. Since it creates an inclusive classroom whereby all individuals have equal access to learning, the hybrid model helps students develop in their social, technical, and cognitive abilities.

This study investigated the relationship between school heads’ transformational leadership practices and teachers’ job performance in public secondary schools of District Jhang, Pakistan. A quantitative correlational research design was employed. The population comprised heads of institutions and secondary school teachers from public secondary schools in the district. Using a simple random sampling technique, a sample of 222 respondents, including 62 school heads and 160 teachers, was selected. Data were collected through two researcher-developed structured close-ended questionnaires. The validity and reliability of the instruments were ensured prior to data collection, with a Cronbach’s alpha reliability coefficient of (α=.78). The collected data were analyzed using SPSS through Pearson Product-Moment Correlation and t-test statistics. The findings revealed that principals predominantly practiced a transformational leadership style and that a statistically significant positive relationship existed between transformational leadership and teachers’ job performance. The study concludes that transformational leadership serves as an important institutional mechanism for improving teacher effectiveness in public secondary schools. It is therefore recommended that educational authorities design and implement leadership development programs to help school principals cultivate environments characterized by mutual respect, collaboration, trust, and professional commitment.

Sports motivation is an important psychological factor influencing the behaviour and performance of athletes. According to Self-Determination Theory (SDT), athletes' motivation is broadly categorised into intrinsic and extrinsic motivation. Despite numerous studies from international contexts, the relationship between participation levels and motivation among university athletes in Pakistan has received limited empirical attention. The study aimed to examine the impact of participation levels on intrinsic and extrinsic motivation among university athletes in Lahore, Pakistan. A cross-sectional research design was used. Data were collected from 234 university athletes of Punjab University (Public) and the University of Lahore (Private) using convenience sampling. Participants were categorised into three groups: Beginner (n = 53), intermediate (n = 119), and elite (n = 62). The Kruskal-Wallis H test was used to test group differences, followed by Mann-Whitney U post-hoc comparisons with Bonferroni correction. Results showed significant differences in intrinsic motivation across participation levels, H (2) =15.074, P = .001, η² = .057. Post-hoc analyses indicated that beginner athletes showed significantly less intrinsic motivation than both intermediate and professional/elite athletes. However, extrinsic motivation revealed a significant difference overall, H (2) = 6.983, p = .030, η² = .022; however, none of the pairwise comparisons was significant after Bonferroni correction. The Spearman correlation analysis demonstrated a significant positive relationship between participation level and intrinsic motivation (rs = .240, p < .001), while the relationship with extrinsic motivation was relatively weak (rs = .156, p = .017). Higher participation levels are associated with stronger intrinsic motivation among university athletes, while extrinsic motivation appears to be relatively stable across participation levels. The results align with Self-Determination Theory (SDT) that increasing sports participation can enhance competence and autonomy, thereby strengthening intrinsic motivation. These findings contribute to the limited literature on sports motivation in Pakistan and provide practical suggestions for promoting an intrinsically motivating sports environment in universities.

This study examines the impact of Human Resource Management (HRM) policies on teachers’ professional stability in private primary schools of Islamabad. It explores how recruitment and selection, compensation systems, training and development, and performance appraisal practices influence teachers’ job satisfaction, retention, and long-term career stability. The objectives of the study were to examine the impact of HRM policies on teachers’ professional stability, to investigate the relationship between compensation systems and teacher retention, and to analyze the effect of training and development on job satisfaction and stability. The study employed a quantitative research design based on a descriptive and correlational approach. The population consisted of approximately 18,000 to 22,000 teachers working in private primary schools of Islamabad. A sample of 350 teachers was selected through stratified random sampling technique to ensure representation across different categories of private schools. The research tool used was a structured questionnaire based on a five-point Likert scale adapted from validated HRM and education research instruments. Validity was ensured through expert review, while reliability was tested using Cronbach’s Alpha through a pilot study of 30 respondents, achieving acceptable internal consistency above 0.70. Data were analyzed using SPSS through descriptive statistics, correlation analysis, and regression analysis. The findings of the first objective revealed that HRM policies have a significant positive impact on teachers’ professional stability, indicating that effective recruitment, compensation, and training practices enhance teacher retention; therefore, it is recommended that private schools strengthen HRM systems by implementing fair compensation structures and continuous professional development programs. The study is significant as it provides empirical evidence on the importance of HRM practices in improving teacher stability and offers practical implications for school administrators and policymakers to enhance workforce stability in private education institutions.