National College of Business Administration and Economics

The importance of CSR is undeniable—it serves as a powerful driver that boosts both employee performance and overall organizational success. Extensive research is found in literature on CSR and its several dynamics related to the performance. Therefore, the objective of the study is to investigate how employees’ external CSR perception influences the task performance of the employees. Based on the social identity theoretical lens, this study drives the research framework of CSR and performance with potential mediating effect of organizational pride and effective commitment. The data was collected from a sample of 372 employees working in private organizations of service sector. For data analysis, PLS-SEM was utilized which validates the hypothesized relationships between variables. The results of this study lend support for hypothesized model. Additionally, it is exhibited that organizational pride and affective commitment sequentially mediate the relationship between employee’s external CSR perception and task performance. The findings of this study contributed to the existing literature by explaining the CSR and task performance in the different context that has not been explored yet. Moreover, this study also discussed the robust theoretical contributions and practical implications of the results.

Abstract The sustainability of public health systems relies heavily on the mental health and well-being of the healthcare workforce. In resource-constrained settings like South Punjab, Pakistan, excessive job demands pose a significant risk to both employee welfare and the quality of healthcare delivery. This study examines the impact of job demands on job performance, specifically investigating the mediating role of emotional exhaustion as a critical determinant of public health service effectiveness. Grounded in the Job Demands–Resources (JD-R) model and Effort–Reward Imbalance (ERI) theory, this research utilized a quantitative cross-sectional design. Data were collected through a structured questionnaire administered to a purposively selected sample of 249 healthcare professionals, including doctors, nurses, and paramedical staff, from public sector institutions. Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) technique was employed to test the hypothesized relationships. The findings indicate that high job demands exert a significant positive effect on emotional exhaustion (β = 0.835), which subsequently degrades job performance. Emotional exhaustion was found to significantly mediate the relationship between job demands and performance (β = 0.426), suggesting that workforce burnout is a primary pathway through which systemic pressures undermine healthcare service quality.

Within organizational psychology, leadership is recognized as a vital driver and a key organizational competency in promoting innovation and sustaining competitiveness in an increasingly dynamic industrial landscape. This research explores the effect of strategic leadership on innovation ability even as it explores the mediating factor of innovation networks in organizations. The study draws on the Diffusion of Innovation Theory to understand how leadership practices can promote the process of knowledge sharing and network cooperation which leads to improved innovation performance of firms. Cross-sectional research design has been used to gather quantitative data on the employees who work in the Pakistan telecom industry. They received 229 valid responses to evaluate perceptions on strategic leadership, innovative networks and innovations capability. Structural Equation Modeling (SEM) and SPSS were used to analyze the data collected and evaluated the proposed relationship and mediation strategies. The results show that the strategic leadership plays a significant role in building innovation capability. In addition to this, the innovative networks mediate by enhancing the relation between the strategic leadership and the organizational innovation outputs as a result of the enhanced knowledge sharing, collaboration, and diffusion of ideas. The findings indicate the value of the use of leadership-based networking processes in facilitating innovation in manufacturing sectors. The research is relevant to the literature on leadership and innovation because it incorporates strategic leadership and innovative networks into the context of the Pakistan telecom sector using the Diffusion of Innovation Theory. The results provide viable suggestions to managers and policy makers who want to maximize their innovation capacity by employing appropriate management techniques and teamwork-based organizational system.

ABSTRACT This paper presents the implications of integrating deep reinforcement learning (DRL) and the Internet of Things (IoT) in optimizing energy management, specifically in smart buildings for sustainable urban development. It further explores how DRL, along with real‐time IoT sensor‐based data, helps improve energy performance in responding to actual HVAC, lighting and renewable energy conditions. Key techniques like genetic algorithms, particle swarm optimization and hybrid techniques are critically examined in maintaining an equilibrium between energy consumption versus renewable sourcing in smart building models. Boundary‐preserving strategies and federated learning appear as techniques addressing expansibility and information protection difficulties, notably over IOT systems. Further research would include technology in local processing and situation‐responsive DRL to enhance more independent, user‐focused and ecologically responsive buildings. This review provides a roadmap for implementing robust, privacy‐conscious AI frameworks in smart buildings, underlining their potential to cut energy use and contribute to broader environmental goals.

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder that affects women of reproductive age and is often difficult to diagnose due to variability in clinical symptoms. This study presents an interpretable machine learning approach for PCOS diagnosis using a Decision Tree classifier trained on clinical and hormonal data. The dataset was obtained from Kaggle and consists of anonymized records of 200 women, including both PCOS and non-PCOS cases. Key features such as age, body mass index (BMI), menstrual irregularity, testosterone levels, and antral follicle count were used for model development. The proposed model achieved an overall accuracy of 84% and a recall of 75% for PCOS cases, demonstrating its effectiveness in identifying individuals at risk. Feature importance analysis highlighted menstrual irregularity, testosterone levels, and BMI as the most influential predictors, consistent with established clinical findings. However, the study is limited by the use of a single publicly available dataset and the lack of external validation. The results indicate that interpretable machine learning models can support early PCOS screening and clinical decision-making.

Cyberloafing, which is the personal use of the internet during work hours, has become an increasingly common practice in the academic setting but few studies have examined the practice from a psychological and contextual viewpoint, particularly in the context of university teachers. This was a qualitative study that explored the perception and experience of cyberloafing by faculty members in higher education settings. In this study, 12 university teachers were interviewed using the semi-structured interview technique using the purposive method. Data were analyzed through thematic analysis and five major themes emerged: Coping with Stress and Emotional Relief, Autonomy and Flexibility in Teaching Roles, Social Connectivity and Emotional Support, Guilt-Justification Cycle and Institutional Culture and Digital Norms. Findings show that teachers do not see cyberloafing as counterproductive behavior but rather as a behavior adaptive to support emotional recovery, stress regulation, and social connectedness. Academic autonomy and absence of institutional policy further institutionalized cyberloafing, although the participants did admit minor feelings of guilt and emphasized self-regulation. The study adds to the growing understanding of cyberloafing as a coping strategy that is useful in flexible work contexts in academia. It emphasizes the importance of a balanced set of institutional guidelines that uphold academic autonomy while fostering responsible digital behavior. The cross-institutional comparisons and the effects of cyberloafing on teacher well-being and performance should be considered by future research employing mixed-method designs.

This mixed-methods study examines the influence of school leadership strategies on teacher motivation in public secondary schools in Lahore, Pakistan. Using survey data from 130 female teachers and interviews with 20 female principals, the study identifies key motivators, including recognition, structural incentives, and intrinsic purpose. While both teachers and principals concur on the importance of supportive leadership and professional development, differences arise regarding monitoring and accountability practices. The results highlight systemic challenges, including delayed salaries, favouritism, and limited autonomy, emphasizing the need for policy reforms focused on fair evaluations, decentralized decision-making, infrastructure improvements, and culturally relevant professional development. These recommendations are framed within Pakistan’s socio-cultural and gender dynamics, aiming to boost teacher motivation and improve educational quality in the public sector.

Social media platforms, particularly Twitter, have become integral to global communication, enabling users to share information instantly with large audiences. However, Twitter’s growing popularity has attracted malicious actors who spread misinformation, phishing attempts, and other spam content. This paper introduces a novel hybrid approach that combines Latent Semantic Analysis (LSA) with traditional machine learning classifiers to effectively distinguish between legitimate and spam tweets. We collected and processed over 5.5 million tweets using Twitter’s API, extracted key features using a statistically validated LSA technique, and implemented four supervised learning algorithms: Naïve Bayes, Support Vector Machine, Decision Tree, and Logistic Regression. The experiments were conducted using rigorous 10-fold cross-validation, and models were evaluated based on accuracy, precision, recall, and F1-score. Our LSA-enhanced approach demonstrated significant performance improvements over traditional methods, with the Naïve Bayes classifier achieving 96.82% accuracy, representing a 5.49% improvement over baseline techniques. Additional error analysis revealed that our approach is particularly effective at identifying evolving spam patterns involving promotional content and malicious URLs.

ABSTRACT This study examines the interplay between Organizational Socialisation Tactics (OSTs), Proactive Socialisation Behaviours (PSBs), and Social Capital Resources (SCRs) in influencing newcomers’ work engagement, framed by self-determination theory (SDT). Using a cross-sectional survey, data were collected from 619 newcomers in various sectors in Punjab, Pakistan, who joined their organisations within the past 3 years. The results reveal that SCRs, particularly prior relationships and horizontal ties, mediate the relationship between PSBs and work engagement. Information-seeking notably enhances these social ties, leading to greater work engagement, while feedback-seeking and networking also contribute positively. Networking, in particular, further strengthens social connections. Although OSTs support the development of horizontal ties and engagement, their impact is less pronounced compared to PSBs. The study notes the limitation of its cross-sectional design and suggests that future research adopt a longitudinal approach to track changes in work engagement over time. The findings highlight the importance of strong social ties in organisationalorganisationalorganisational socialisation, showing that encouraging PSBs can significantly enhance newcomers’ engagement, retention, and performance. Overall, this research underscores the critical role of social connections in improving employee well-being, offering valuable insights for organisations to enhance integration, retention, and work-life quality.