Center for Management Science Research, ISSN “3006-5291 & 3006-5283" is an interdisciplinary, open-access, and quarterly journal that publishes articles in the fields of business management and economics studies.
DOES THE DIVIDEND PUZZLE DEPEND ON HOW PAYOUT IS MEASURED? MULTI-PROXY EVIDENCE FROM NON-FINANCIAL FIRMS ON THE PAKISTAN STOCK EXCHANGE
This study was an attempt to determine the stability of Firm-specific determinants of dividends on the 30 non-financial listed companies at the Pakistan Stock Exchange (PSX) from 2016 to 2025 and in terms of three conceptually different measures of dividend i.e. Dividend Payout Ratio (DPO), Dividend per Share (DPS) and Dividend Yield (DY). The six firm-level explanatory variables, namely asset growth (AG), collateral assets (COLLAS), current ratio (CR), debt-to-equity ratio (DER), earnings per share (EPS) and operating cash flow (OCF) are analyzed in combination with firm size (FS) as a control. The sources of secondary data were audited annual reports, companies’ disclosures and PSX portal. Pooled Ordinary Least Squares (POLS) regression had been estimated in EViews 14, with descriptive and Pearson-correlation analysis performed. The results obtained showed that the dividend determinants with positive sign are COLLAS, CR, EPS, OCF and FS and these determinants were found to be significant in all the three measures of dividends. In all, DER was negative but irrelevant. AG represented the primary source of proxy sensitivity: It was positive for DPO and DPS, yet negative for DY, indicating that growth and higher absolute or higher earnings-relative distributions could went hand in hand while generating a lower market-price-scaled yield. The methodological and empirical contribution of the study was thus inferences regarding the “dividend puzzle” are therefore partial to the measurement and single-proxy modelling masked important economic heterogeneity. For emerging market managers and investors, liquidity, profitability, cash generation, tangible collateral and organizational scale were a more reliable measure of the capacity for dividends than leverage alone. The conclusions confirm a holistic view of signaling- and agency-, pecking-order- and life-cycle augmented and showed that the chosen payout proxy affects the interpretation given to growth.
Dividend Policy; Dividend Payout Ratio; Dividend Yield; Dividend Per Share; Pakistan Stock Exchange; Pooled OLS
DIGITALIZED BUSINESS STRATEGY AND EMPLOYEE BEHAVIORAL DYNAMICS: A CORPORATE PATHWAY TO SOCIAL DEVELOPMENT
This study examines the role of digitalized business strategy in shaping employee behavioral dynamics and its subsequent contribution to social development within the corporate sector. In an era of rapid digital transformation, organizations are increasingly embedding digital technologies into their strategic frameworks, fundamentally altering how employees perceive, respond to, and execute organizational goals. Drawing on strategic management and behavioral theory perspectives, this research conceptualizes digitalized business strategy as a multidimensional construct that influences employee cognition, motivation, collaboration, and adaptive behavior. The study further explores how these behavioral shifts act as a mediating mechanism through which corporate organizations generate broader social development outcomes, including community engagement, sustainability practices, and socio-economic value creation. Theoretical development suggests that digitally enabled strategies enhance transparency, decision-making efficiency, and employee empowerment, thereby fostering pro-social and innovation-oriented behaviors. Consequently, organizations become not only profit-driven entities but also active contributors to societal progress. This research contributes to the literature by integrating business strategy, digital transformation, and employee behavior into a unified framework that explains corporate social impact. The findings provide implications for managers seeking to align digital strategy with human behavior to achieve sustainable and socially responsible organizational outcomes in a competitive corporate environment.
Digital Business Strategy, Employee Behavior, Corporate Sector, Social Development, Digital Transformation, Organizational Behavior
MANAGEMENT OF THE JUVENILE JUSTICE SYSTEM IN PAKISTAN
The juvenile justice system in Pakistan is a legal and social framework for responding to young people involved in delinquent or criminal conduct. Unlike the adult criminal justice system, it is designed for minors, generally those under 18, and is intended to reflect their age, vulnerability, and capacity for rehabilitation. With the enactment of the Juvenile Justice System Act 2018 (JJSA), Pakistan’s statutory framework may be viewed as relatively progressive. Children in conflict with the law continue to suffer from inadequate and unreliable age determination procedures, extended pre-trial detentions, poor access to meaningful legal representation, and very limited access to rehabilitation, which is more formally in place than in practice. This article discusses the legal structure and management system of the juvenile justice system, tracing the constitutional basis of the system, the legislative development of the juvenile justice system from the Juvenile Justice System Ordinance 2000 to the Juvenile Justice System Act 2018, and Pakistan's obligations under the Convention on the Rights of the Child, the Beijing Rules and the Riyadh Guidelines. It examines the implementation of the juvenile justice system. It puts Pakistani practice in perspective and provides an international and comparative context for better implementation. The article emphasizes the need for institutional investment, functional diversion systems, well-trained staff, data systems, and continuous monitoring programs as components of a rights-based, rehabilitative juvenile justice system.
Juvenile Justice Act 2018, Juvenile Justice Committees, diversion, child rights, rehabilitation, institutional coordination, Pakistan.
RESISTING HEGEMONY: CHINA AND RUSSIA’S COUNTER-MULTILATERAL STRATEGIES IN THE ASIA-PACIFIC AMID THE TRUMP ‘BOARD OF PEACE’ INITIATIVE, 2025-2026”
This article will analyze the rapid institutionalization of Donald Trump’s “Board of Peace” (hereafter, Peace Board) as a still emergent but institutionalizing policy body for the management of the Gaza Peace “business” (initially associated with post-ceasefire governance and reconstruction of the Gaza Strip) and, the author seeks to answer the question of whether it serves as a parallel, competitive, or, eventually, co-opted extension of the existing UN-centered peace architecture. Using realism, institutionalism, and constructivism, the analysis attempts to capture the strategic reservations of China and Russia as the UN Security Council's permanently concerned West. It posits that their reservations are less aimed at peace as an end, and more at (i) peace as a process (who decides, mandates, and orders execution), (ii) process legitimacy (law-based multilateralism v. a club of leaders governance), and (iii) legitimacy of outcomes (a club of payers and a selective geoeconomic arrangement that cuts off smaller states from the line of equity). The author posits that the Peace Board cannot simply “replace” the UN, but rather it will lead to UN (121) fragmentation by accelerating a two-tiered peace system – one with formal UN legitimacy, the other with direct, high-leverage, transactional governance peace – and the negative outcomes of such for the South and the future of collective security will be massive.
Board of Peace, United Nations, Great-power rivalry, Institutional legitimacy, Global governance fragmentation.
AI-ENABLED PREDICTIVE RISK INTELLIGENCE FOR SAUDI BANKING SYSTEMS: INTEGRATING SHARIAH COMPLIANCE, ADVANCED FINANCIAL ANALYTICS, AND REGULATORY DATA GOVERNANCE
The rapid digital transformation of Saudi Arabia’s banking sector has created significant opportunities for intelligent financial risk management while introducing increasingly complex challenges related to credit exposure, liquidity pressure, financial fraud, cybersecurity threats, operational disruption, regulatory compliance, and Shariah governance. This study develops an AI-driven risk assessment model for Saudi banking systems by integrating Shariah-compliant financial analytics with regulatory-aware data governance. The proposed framework addresses the distinctive requirements of banks operating within the Saudi financial ecosystem, where advanced risk assessment must support Shariah-compliant financial practices while ensuring transparency, cybersecurity resilience, data protection, and regulatory accountability. A multi-source dataset was constructed using published annual reports of Saudi banks, Saudi Central Bank (SAMA) banking statistics, Tadawul-listed bank disclosures, financial stability indicators, Shariah governance reports, macroeconomic variables, and structured banking-risk records. To enhance the realism and analytical depth of the framework, anonymized and simulated transaction-level data were incorporated, including customer financing behavior, delayed repayment patterns, digital payment activities, suspicious transaction indicators, abnormal login attempts, cybersecurity alerts, and Shariah-compliance risk signals. The collected data were processed through feature normalization, missing-value treatment, class balancing, contract-based feature engineering, risk-category labeling, and regulatory attribute mapping. Multiple machine-learning approaches were evaluated, including logistic regression, support vector machine, random forest, gradient boosting, and the proposed explainable ensemble risk assessment model. Experimental results demonstrate that the proposed model achieved superior predictive performance, attaining 96.4% accuracy, 95.8% precision, 96.1% recall, 96.0% F1-score, and a ROC-AUC of 0.982. Compared with conventional statistical and individual machine-learning models, the proposed framework reduced false risk classifications by 18.7% and enhanced the early identification of high-risk financing cases, suspicious digital transactions, cybersecurity vulnerabilities, and potential Shariah non-compliance events. Explainable AI analysis further identified repayment irregularity, financing concentration, contract type, customer risk history, liquidity stress, abnormal transaction frequency, and cybersecurity risk flags as the most influential risk predictors. The proposed framework provides a Saudi-specific, Shariah-aligned, and regulatory-aware approach for transparent risk scoring, secure data governance, continuous compliance monitoring, and responsible data-driven decision-making in digitally evolving banking environments.
Saudi banking systems; AI-driven risk assessment; Shariah-compliant financial analytics; regulatory-aware data governance; explainable machine learning; cybersecurity risk intelligence; financial fraud detection; SAMA regulatory compliance
ARTIFICIAL INTELLIGENCE–DRIVEN PREDICTIVE CYBER THREAT INTELLIGENCE IN SAUDI BANKING SYSTEMS: AN INTEGRATED FRAMEWORK FOR FINANCIAL FRAUD DETECTION, NETWORK SECURITY ANALYTICS AND TRANSACTION BEHAVIOUR MODELING
The rapid digitalization of banking services in Saudi Arabia has increased operational efficiency and financial accessibility while simultaneously expanding exposure to financial fraud, cyber intrusions, account compromise, and anomalous transaction activities. This study proposes an Artificial Intelligence–Driven Predictive Cyber Threat Intelligence framework for Saudi banking systems that integrates financial fraud detection, network security analytics, and transaction behaviour modeling within a unified predictive environment. A multi-source dataset was constructed using publicly available Saudi banking indicators, institutional financial and cybersecurity disclosures, regulatory statistics, and synthetically generated anonymized transaction and network-security records. The final experimental dataset comprised 85,000 transaction and security observations characterized by 42 predictive features, including transaction amount and frequency, login behaviour, device and location anomalies, failed authentication attempts, unusual fund transfers, IP reputation indicators, network traffic patterns, account activity, and historical fraud signals. Following missing-value treatment, feature normalization, categorical encoding, class balancing, and feature selection, four benchmark algorithms Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and XGBoost were developed and comparatively evaluated. Stratified 80:20 training–testing partitioning with five-fold cross-validation was employed to improve evaluation reliability. Experimental results demonstrated that XGBoost achieved the strongest overall predictive performance, with 96.8% accuracy, 96.2% precision, 95.7% recall, 95.9% F1-score, and 0.984 ROC-AUC, compared with accuracies of 84.6%, 89.3%, and 94.1% for LR, SVM, and RF, respectively. The proposed intelligence framework detected 97.1% of high-risk fraudulent transactions and 95.4% of network-security anomalies, while reducing the false-positive rate to 3.8%. Behavioural transaction analytics further improved early identification of abnormal account activities by 11.6% compared with conventional rule-based screening. Explainable AI analysis identified transaction velocity, authentication failures, device inconsistency, unusual transfer patterns, and network anomalies as the most influential risk indicators. These findings demonstrate that integrated AI-based cyber threat intelligence can substantially strengthen proactive risk detection, support real-time security decision-making, and enhance the cyber resilience of Saudi banking systems. The proposed framework provides a scalable foundation for intelligent fraud prevention, continuous network monitoring, and data-driven cybersecurity governance within rapidly evolving digital banking environments.
Artificial Intelligence; Cyber Threat Intelligence; Saudi Banking Systems; Financial Fraud Detection; Network Security Analytics; Transaction Behaviour Modeling; Predictive Cybersecurity; Explainable Artificial Intelligence.
FINTECH AND THE LIQUIDITY–RESILIENCE PARADOX IN STOCK MARKETS: A CRITICAL REVIEW
This study explores the impact of financial technology (FinTech) on the liquidity and resilience of global financial markets during 2014–2024. The analysis covers electronic trading, algorithmic and high-frequency trading, artificial intelligence, big data analytics, digital brokerage platforms, and distributed-ledger technologies, and their impact on transaction costs, price discovery, market liquidity provision, information efficiency, and market stability. Evidence from around the world has shown that FinTech has significantly reduced information and execution frictions and enhanced market liquidity during normal times by enabling faster order matching, providing liquidity to a larger number of investors, and increasing competition among liquidity providers. The level of technology integration in financial systems is evident in global investment in FinTech, which totaled US$239.3 billion in 2021 and US$95.6 billion in 2024, despite the drop. The facts do, however, show an important liquidity-resilience paradox. While algorithmic trading and market fragmentation may lead to lower average bid–ask spreads, some evidence from the large equity markets shows that spreads are becoming more skewed and kurtotic, meaning that abnormally poor liquidity conditions could still occur during a market stress. In fact, the market shock in March 2020 due to the outbreak of COVID-19 was another example of how digital infrastructure can ensure continuous market access while also accelerating synchronized trading, deleveraging, and shock transmission. When assessing the impact of FinTech, cross-country evidence shows that the impact varies with technological infrastructure, market depth, financial development, regulatory quality, and investor involvement. The study finds that FinTech can improve the efficiency of the markets and the liquidity of everyday transactions, but resilient outcomes is not a foregone conclusion. To sustain its contribution, the adoption of efficient regulation, cybersecurity, clear algorithms, fragmented technological platforms, and institutional resilience to handle systemic risks arising from the growing automation and interdependency of financial markets is needed.
FinTech; Stock Market Liquidity; Market Resilience; Financial Technology; Algorithmic Trading; Artificial Intelligence; High-Frequency Trading; Information Efficiency;
THE EVOLUTION OF FAIR TRIAL RIGHTS IN PAKISTAN: FROM COLONIAL LEGACY TO CONTEMPORARY CHALLENGES
Fair trial rights in Pakistan have undergone a complex development from a colonial criminal justice system to a constitutional rights-based system of due process and fair trial adjudication. This paper explores this evolution by tracing how colonial criminal procedure has been transmitted, how procedural rights have been progressively recognized in the Constitution, how courts have evolved their understanding of the principles of a fair trial, and the current disparity between legal protection and institutional practice. Special focus is also laid on Article 10A of the Constitution of Pakistan, which has been added through the Eighteenth Constitutional Amendment of 2010, providing express security of fair trial and due process in deciding civil rights and obligations and criminal charges. The analysis establishes that the concept of fair trial has been gradually broadening from a right within the courtroom to include the right to lawful investigation, the right to an effective defense, the right to impartial adjudication, the right to the fairness of the evidence, the right to a reasonable determination of the proceedings, and the right to procedural equality. While these constitutional and judicial developments have been achieved, significant gaps and issues still exist, including delays in court proceedings, extended pre-trial periods, deficiencies in investigation and prosecution, inadequate access to quality legal representation, procedural issues related to evidence, and new issues concerning digital evidence and technological decision-making. The paper suggests that the root issue confronting Pakistan today is not the acceptance of fairness as a constitutionally recognized value, but its proper incorporation into the system. The need for sustainable reform, therefore, is for improved case management, responsible investigation, improved legal aid, modernization of evidentiary protection, and judicial independence and digitalization. A fair trial should become a reality, not just a promise in a constitution.
Fair Trial; Article 10A; Due Process; Pakistan; Constitutional Rights; Criminal Justice; Judicial Evolution; Colonial Legal Legacy; Fundamental Rights; Access to Justice
UNDERSTANDING EMPLOYEE WELL-BEING THROUGH DARK TRIAD TRAITS, ORGANIZATIONAL JUSTICE, AND PSYCHOLOGICAL DISTANCE
This study examines the relationships between Dark Triad personality traits narcissism, Machiavellianism, and psychopathy organizational justice, psychological distance, and employee well-being in the private banking sector of Pakistan. Drawing on Social Exchange Theory, the study proposes that socially aversive personality traits are associated with lower employee well-being and reduced perceptions of organizational justice, while organizational justice and psychological distance play important roles in employees’ workplace experiences. Data were collected through online and paper-based questionnaires from 876 employees working in private banks across different districts of Punjab, Pakistan. The proposed relationships were analyzed using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4.0. The findings supported all eight hypotheses. Narcissism (β = −0.282), Machiavellianism (β = −0.314), and psychopathy (β = −0.286) were significantly and negatively associated with employee well-being. Similarly, narcissism (β = −0.333), Machiavellianism (β = −0.342), and psychopathy (β = −0.316) were negatively associated with organizational justice. Organizational justice showed a strong negative association with psychological distance (β = −0.781), while psychological distance was negatively associated with employee well-being (β = −0.192). The findings extend research on Dark Triad personalities by integrating organizational justice, psychological distance, and employee well-being within a collectivist and hierarchical work context. Practically, the study highlights the importance of fair organizational practices, ethical leadership, transparent human resource policies, and initiatives aimed at strengthening employee–organization relationships and reducing psychological distance to promote employee well-being.
Dark Triad, narcissism, Machiavellianism, psychopathy, organizational justice, psychological distance, employee well-being, private banking, Pakistan
THE LIVED EXPERIENCE OF BEING A UNIVERSITY HEAD OF DEPARTMENT: A COMPARATIVE MULTIPLE-CASE STUDY
Although academic middle managers have received considerable scholarly attention, little is known about the personal and identity-based dimensions of the university Head of Department (HOD) role. This position is characterised by extensive responsibility but constrained authority and situated at the intersection of institutional expectations and departmental realities. The study explores how Heads of Department experience and negotiate the tension between responsibility, authority, and leadership identity. This comparative multiple-case study involved semi-structured interviews with two Heads of Department and non-participant observations. Data analysis was conducted by using the six-phase framework of thematic analysis. Six themes emerged including the responsibility-authority paradox, collaborative leadership, identity construction, emotional labour, communication, and leadership as coordination and service. Results indicate that academic middle management is a liminal zone that is located between institutional authority and structural powerlessness, and between administrative demands and collegial expectations. While both were rejecting authoritarians, they faced a shared paradox, and their ways of relating and collaborating differed in ways that may reflect possible sociocultural influence; as this pattern is drawn from a single pair of cases, it is offered as a tentative observation rather than a generalizable gender difference. The male participant used tactics of influence and emotional detachment, and the female participant used tactics of relational coordination, emotional openness and transformational communication. The findings extend the literature on academic middle leadership by providing a comparative case-based account of how leadership identity, responsibility, and authority are experienced and negotiated in practice, highlighting the need for clearer role expectations and stronger institutional support for Heads of Department.
Academic Middle Management, Head of Department, Responsibility–authority paradox, Leadership identity, Emotional labour, Qualitative case study, Higher education, Gender and leadership.
INSIDE THE EDUCATORS’ MINDS: A FIELD STUDY ON THE PHILOSOPHICAL ROOTS OF EDUCATION
This qualitative field study delves into the educational beliefs of teachers within the urban schools in Sindh, Pakistan, tracing their philosophical origins back to Idealism, Pragmatism, and Islamic Thought. The study was conducted based on the phenomenological and interpretive research paradigm by collecting rich and contextual data through semi-structured interviews with 15 experienced teachers and analysis of school documents related to the study. It has been found that there is a complex relationship between traditional, modern and faith-based pedagogical orientations. Though many teachers adopted more idealist principles, with attention to character development and moral instruction and the transmission of eternal truths, a strong pragmatic influence was found in their attention to problem-solving, experiential learning, and preparing students for real-world challenges. Islamic philosophical concepts were profoundly influential in shaping pedagogical strategies and classroom management, especially those focused on the comprehensive development of students and the aim of acquiring knowledge for the sake of Allah SWT. This study shows the syncretic nature of educational beliefs in this context, as well as the need for teacher training programmes that recognise and develop these different philosophical traditions to create more coherent and effective teaching practice.
Educational beliefs, Philosophical roots, Idealism, Pragmatism, Islamic Thought, Urban schools, Sindh, Qualitative research, Teacher education
FROM JOB DISPLACEMENT TO WORKFORCE TRANSFORMATION: WHAT PAKISTAN CAN LEARN FROM GLOBAL LEADERS IN MANAGING AI-DRIVEN EMPLOYMENT CHANGES
Ever since the Industrial Revolution, machines have been replacing human workers bit by bit; automation is nothing new. First, a gradual change in agriculture and skilled crafts like hand weaving, then a high-volume shift in manufacturing. From these advances in technology, the economy was recycled and generated new demand for human labor; generally, still plenty of jobs to go round. But now, this is a new era: rapid advances in artificial intelligence (AI) and robotics have the potential to replace many human jobs. There are some new jobs created in the market, but only for those who are good and have the potential to learn AI. Artificial intelligence is transforming industries, labor markets, and economies at an extraordinary pace. AI has the potential to improve productivity, business performance, and innovation; it can even help you with daily chores. AI is your new friend. Pakistan is at an early stage of AI and is increasingly adopting AI-powered technologies across manufacturing, banking, customer services, healthcare, education, and information technology. In Pakistan, AI is replacing many jobs, simultaneously creating new employment opportunities that require advanced technical, analytical, and digital skills. USA, UK, Germany, China, Singapore, and South Korea have responded to these rapid changes by investing in AI education, research & development, advanced technology, and strong collaboration with universities and government. These initiatives have enabled them to reduce the negative effects of automation and create new jobs for new talent, and people have new AI courses so they can get a job in the near future. This study can show how Pakistan can learn from and prepare its industry for the adoption of AI from global AI leaders, and prepare its workforce for the future of work. In Pakistan, there is a lack of AI education; no proper investment in AI research and development; weak industry-government collaboration; and weak collaboration with Universities. This study offers practical policy recommendations and actionable knowledge to help Pakistan improve AI readiness, strengthen its human capital, invest in research & development, collaborate with universities, and create sustainable employment opportunities. This research suggests that AI should not be seen as a threat or a replacement for jobs but as a new golden opportunity.
Artificial intelligence, employment, workforce, transformation, future of work, human resource management, Pakistan, digital skills, Global AI leaders
SMART CLOUD ACCOUNTING SYSTEM FOR SMES: ENHANCING FINANCIAL DECISION MAKING
Small and Medium Enterprises (SMEs) are adopting smart cloud accounting solutions to enhance financial management and decision-making due to the quick development of digital technology. This study looks at how financial analytics, automation efficiency, data security, and cloud accounting adoption affect SMEs' financial decision-making. A structured questionnaire was used to gather primary data from 100 SME respondents as part of a quantitative research methodology. Multiple regression analysis, Pearson correlation, reliability analysis, and descriptive statistics were used to examine the gathered data. With mean scores higher than 3.90, the results showed that respondents had favorable opinions of every research variable. With an overall Cronbach's Alpha better than 0.70, the reliability study verified the measuring tool's dependability. Additionally, multiple regression analysis showed that Cloud Accounting Adoption, Data Security, Automation Efficiency, and Financial Analytics significantly and favorably influence Financial Decision-Making, while correlation analysis revealed significant positive relationships among all variables. The two elements that had the most impacts on financial decision-making were cloud accounting adoption and financial analytics. According to the study's findings, SMEs' operational efficiency, timeliness and informed decision-making, and financial management are all improved by implementing smart cloud accounting systems. In order to achieve sustainable business growth, the findings offer SME owners, managers, and legislators useful implications for encouraging the adoption of cloud-based accounting solutions.
Smart Cloud Accounting Systems, Cloud Accounting Adoption, Data Security, Automation Efficiency, Financial Analytics, Financial Decision-Making, SMEs.
IMPACT OF ENTREPRENEURIAL ORIENTATION AND SOFT TOTAL QUALITY MANAGEMENT PRACTICES ON WORK PERFORMANCE: MEDIATED BY AFFECTIVE COMMITMENT IN SMEs
Small and Medium Enterprises (SMEs) are considered the backbone of economic growth, industrial development, innovation, and employment generation worldwide. However, increasing globalization, technological transformation, and market uncertainty have compelled SMEs to adopt strategic orientations and employee-centered management practices to remain competitive and sustainable. In this context, entrepreneurial orientation (EO) and soft Total Quality Management (TQM) practices have emerged as important determinants of organizational effectiveness and employee performance. Despite growing scholarly attention, limited empirical studies have simultaneously examined the combined effects of EO and soft TQM practices on work performance through affective commitment within SMEs. The present study investigates the impact of entrepreneurial orientation and soft TQM practices on work performance, with affective commitment acting as a mediating variable among SMEs in the textile sector. The study is grounded in Human Capital Theory, which suggests that organizational investments in employees through entrepreneurial orientation and soft quality management practices enhance employees' knowledge, skills, commitment, and ultimately their work performance. A quantitative research approach was adopted using a cross-sectional survey design. Data were collected from managerial employees working in textile SMEs through structured questionnaires. A total of 650 questionnaires were distributed, and 607 valid responses were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that entrepreneurial orientation significantly and positively influences work performance and affective commitment. Similarly, soft TQM practices demonstrate a strong positive effect on both affective commitment and employee work performance. The mediation analysis further confirms that affective commitment partially mediates the relationships between entrepreneurial orientation, soft TQM practices, and work performance. The results suggest that organizations emphasizing innovation, proactive strategic behavior, employee participation, supportive leadership, teamwork, and continuous improvement create emotionally committed employees who exhibit superior performance outcomes. The study contributes theoretically by integrating entrepreneurial orientation, soft TQM practices, affective commitment, and work performance into a unified framework within the SME context. Practically, the findings provide strategic insights for SME managers and policymakers regarding the importance of entrepreneurial culture and employee-centered quality management practices in improving employee productivity and organizational sustainability.
Entrepreneurial Orientation, Soft TQM Practices, Affective Commitment, Work Performance, SMEs, Organizational Performance, PLS-SEM
NONLINEAR EFFECTS OF PORTFOLIO INVESTMENT ON GREEN GROWTH IN PAKISTAN: A THRESHOLD REGRESSION ANALYSIS
Green growth has become a central objective of sustainable development, requiring efficient financial mechanisms to support environmentally responsible economic transformation. Although foreign portfolio investment (FPI) represents an increasingly important source of external finance for developing economies, its contribution to green growth remains inconclusive due to its volatile nature and the potential for nonlinear effects. This study investigates whether the impact of portfolio investment on green growth in Pakistan varies across investment regimes by identifying a critical threshold level. The analysis employs annual time-series data for Pakistan covering the period 1995–2021 and applies Hansen's (1999) Threshold Regression Model (TRM) to examine the nonlinear relationship between portfolio investment and green growth. Renewable energy consumption, real GDP per capita, trade openness, and inflation are included as control variables. The findings identify an estimated portfolio investment threshold of −0.103% of GDP; however, the bootstrap threshold test indicates that the estimated threshold is statistically insignificant, suggesting no robust evidence of a nonlinear regime shift. Both the baseline and threshold models reveal that portfolio investment exerts a positive but statistically insignificant effect on green growth. The findings suggest that increasing portfolio investment alone is insufficient to promote green growth unless capital inflows are effectively channeled towards environmentally sustainable and productive sectors. Strengthening sustainable finance frameworks, capital market governance, and green investment policies is therefore essential for enhancing the environmental contribution of foreign capital. The study contributes to the sustainable finance literature by providing one of the first threshold-based empirical assessments of the portfolio investment–green growth nexus in Pakistan and offers valuable policy insights for advancing sustainable economic development.
CONSTRUCTION PROJECT PORTFOLIO MANAGEMENT FOR THE CIRCULAR ECONOMY: ADVANCING RESOURCE PRODUCTIVITY, INDUSTRIAL RESILIENCE, AND SUSTAINABLE ECONOMIC DEVELOPMENT
The construction industry remains one of the most resource-intensive sectors globally, contributing substantially to material depletion, waste generation, and supply chain vulnerability. This study examined the integration of circular economy (CE) principles into construction project portfolio management to advance resource productivity, industrial resilience, and sustainable economic development. Grounded in the Resource-Based View, Circular Economy Theory, and Dynamic Capabilities Theory, the study adopted a quantitative, cross-sectional design. Data were collected via a structured, close-ended questionnaire from a population of 3,500 construction professionals across PEC-registered Grade 1–3 contracting firms in Lahore, Faisalabad, and Rawalpindi. Using stratified random sampling, 380 questionnaires were distributed, yielding 331 valid responses for analysis. Data were analyzed using SPSS and Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings revealed moderate and inconsistent CE adoption (M = 3.14) within portfolios, while CE adoption significantly predicted resource productivity (β = 0.512) and industrial resilience (β = 0.478). Resource productivity and industrial resilience jointly explained 48.7% of variance in sustainable economic development, confirming partial mediation. The study concludes that circular economy integration drives sustainable development primarily through enhanced resource efficiency and resilient supply chains.
Circular Economy, Project Portfolio Management, Resource Productivity, Industrial Resilience, Sustainable Economic Development, Construction Industry, Resource-Based View, Dynamic Capabilities, PLS-SEM, Material Recovery
THE ROLE OF CORPORATE GOVERNANCE, CAPITAL ADEQUACY AND FINANCIAL DERIVATIVES IN CREDIT RISK MANAGEMENT: EVIDENCE FROM COMMERCIAL BANKS IN PAKISTAN
Purpose This study examines the impact of risk management strategies on the credit risk faced by commercial banks of Pakistan. Specifically, it investigates the role of Derivatives, risk management, capital adequacy ratio and corporate governance practices in minimizing credit risk in the banking sector. Design/methodology/approach Primary data were collected through a structured questionnaire administered to 250 employees of commercial banks in Pakistan. Descriptive statistics, reliability tests and multiple regression analysis were conducted using SPSS to assess the relationship between risk management strategies and credit risk. Findings The results indicate that all four risk management strategies have a significant association with credit risk. Derivatives demonstrates the strongest influence, followed by corporate governance, then risk management and capital adequacy ratio. Banks that adopt transparent governance practices, diversify their portfolios for risk management effectiveness and maintain adequate capital levels are more effective in managing credit risk. Practical implications The findings suggest that bank managers and regulators should prioritize strengthening corporate governance frameworks, developing effective risk management policies and enforcing capital adequacy requirements. These strategies can collectively reduce default risk and enhance the operational stability and performance of commercial banks. Originality/value This study provides empirical evidence from Pakistan, an under-researched region, on how multiple risk management strategies jointly shape credit risk in commercial banks. It offers practical insights for policymakers and practitioners aiming to improve risk management practices in emerging banking markets.
Credit risk; Risk management Effectiveness; Derivatives; Risk management; Capital adequacy ratio; Corporate governance and Commercial banks
MINORITY SHAREHOLDER PROTECTION IN PAKISTAN: A CRITICAL, CONTEXTUAL ANALYSIS
This essay critically examines minority shareholder protection in Pakistan's corporate law against the backdrop of the global neo-liberal free-market paradigm. It surveys the doctrinal foundations of separate corporate personality before analysing the principal remedies available to minority shareholders in Pakistan and the United Kingdom — just and equitable winding up, the unfairly prejudicial conduct remedy, and the derivative claim — alongside the supervisory role of the Securities and Exchange Commission of Pakistan. Adopting a socio-legal and comparative lens, the essay argues that Pakistan's post-colonial corporate structures, dominated by ‘Seth’ culture and blurred lines between ownership and shareholding, demand a contextual rather than a transplanted approach to reform. It concludes that codifying derivative action and director's duties, and revisiting the 10% locus standi threshold, are necessary steps toward a shareholder protection regime suited to Pakistan's own realities.
Minority Shareholder Protection, Corporate Governance, Companies Act 2017 (Pakistan), Companies Act 2006 (UK), Derivative Claims, Unfairly Prejudicial Conduct, Separate Legal Personality
اسلامی تعلیمات میں عمر رسیدہ افراد کی کفالت: ایک تجزیاتی و تحقیقی مطالعہ
وَقَضَىٰ رَبُّكَ أَلَّا تَعْبُدُوا إِلَّا إِيَّاهُ وَبِالْوَالِدَيْنِ إِحْسَانًا "And your Lord has decreed that you not worship except Him, and to parents, good treatment" [i]. Human life inevitably descends into a phase of physical frailty. The Islamic ethical and legal paradigm transforms this vulnerability into a stage of profound spiritual reverence. Modern capitalistic societies increasingly measure human worth through economic productivity. Aging bodies are thus marginalized. They are often relegated to the institutional isolation of Old Age Homes. The Prophetic mission established a radically different worldview. Caring for the elderly is framed not as a societal burden but as a direct gateway to divine mercy and societal sustenance. We analytically examine classical Islamic jurisprudence regarding the financial and physical maintenance (Nafaqah) owed to parents and aging relatives. A comparative lens is applied to contrast the traditional extended family structure with contemporary commercialized care facilities. Institutional care strips away emotional intimacy. It breeds psychological alienation and a profound sense of abandonment. The Islamic framework enforces the protection of human dignity within the sanctuary of the home. The Qur’an’an’s directive specifically places the elderly "with you" (indaka), fundamentally rejecting the concept of distant confinement. Exceptional circumstances, such as severe medical deterioration or complete destitution, do invite state intervention and specialized medical shelter under the principle of public interest (Maslaha). Yet, the core societal default remains the family unit. Reviving localized community support networks and proposing hybrid daycare models offers a pragmatic solution to contemporary economic pressures. True societal welfare depends entirely on preserving kinship ties and recognizing the elderly as the spiritual anchors of the Muslim household. [i] Al-Isra 17:23
Islamic Jurisprudence, Elderly Care, Old Age Homes, Social Solidarity, Nafaqah, Kinship Ties, Utilitarianism.
گلوبل وارمنگ کے سدباب میں اسلامی اخلاقیات کا کردار: ایک تنقیدی و تجزیاتی مطالعہ
وَلَا تُفْسِدُوا فِي الْأَرْضِ بَعْدَ إِصْلَاحِهَا وَادْعُوهُ خَوْفًا وَطَمَعًا ۚ إِنَّ رَحْمَتَ اللَّهِ قَرِيبٌ مِّنَ الْمُحْسِنِينَ "And cause not corruption upon the earth after its reformation. And invoke Him in fear and aspiration. Indeed, the mercy of Allah is near to the doers of good" [i]. The escalating crisis of global warming presents an existential threat to the delicate ecological balance of our planet. Modern anthropocentric philosophies have commodified nature, viewing the environment solely as a resource for unchecked economic exploitation. This relentless industrial capitalization has precipitated severe climatic disruptions. The Islamic ethical paradigm offers a profoundly distinct eco-theology, rooted in the metaphysical concepts of Khilafah, Amanah, and Mizan. Nature is not a subjugated entity but a sacred sanctuary where every element exists in a state of continuous divine glorification. We critically analyze the integration of Islamic environmental ethics in mitigating climate change, moving beyond secular environmentalism to a spiritual framework of ecological responsibility. The prohibition of Israf and Tabdheer serves as a direct legislative counter to modern consumerism and carbon-intensive lifestyles. The Prophetic traditions strictly mandate the preservation of flora and fauna, the conservation of water, and the establishment of protected ecological zones. Western utilitarian approaches attempt to solve environmental degradation through mere technological fixes, ignoring the underlying spiritual void. The Islamic jurisprudential principles, specifically the maxim of "La Darar wa La Dirar”, provide a robust legal foundation for enacting state-level environmental policies and curbing industrial emissions. True ecological restoration is inextricably linked to spiritual reformation, demanding a paradigm shift from human supremacy over nature to harmonious stewardship under divine guidance. [i] Al-A'raf 7:56
Global Warming, Islamic Eco-Theology, Environmental Ethics, Khilafah, Amanah, Israf, Climate Change, Maqasid al-Shariah.
UNIFYING ECOSYSTEM PERSPECTIVES: A SYSTEMATIC LITERATURE REVIEW OF ENTREPRENEURIAL AND DIGITAL ECOSYSTEMS TO CONCEPTUALIZE THE DIGITAL ENTREPRENEURIAL ECOSYSTEM
This study advances the conceptualization of the Digital Entrepreneurial Ecosystem (DEE) by systematically unifying insights from entrepreneurial and digital ecosystem literatures. Through a rigorous review and bibliometric analysis, it identifies the fragmented nature of existing scholarship and synthesizes key attributes, governance, actors, resources, and digital infrastructures that define DEEs as dynamic socio‑technical systems. Unlike traditional entrepreneurial ecosystems, DEEs dissolve locational barriers, enabling ventures to scale globally from inception while fostering distributed collaboration and sustainable innovation. The framework highlights how digital enablers such as platforms, boundary resources, and orchestration mechanisms reshape opportunity recognition, resource mobilization, and venture performance. It also underscores the broader socio‑economic significance of DEEs, linking them to Sustainable Development Goals including decent work, reduced inequalities, and sustainable cities. Theoretically, the study clarifies definitional ambiguities and extends ecosystem theory by embedding digital governance and sustainability into its core. Practically, it provides policymakers, entrepreneurs, and institutions with a blueprint for designing inclusive, resilient, and innovation‑driven ecosystems. Overall, the research positions DEEs not as peripheral extensions but as a central paradigm in contemporary entrepreneurship, offering both conceptual clarity and actionable guidance for shaping entrepreneurial futures in the digital age.
Digital Entrepreneurial Ecosystem; Entrepreneurial Ecosystem; Digital Ecosystem; Systematic Literature Review; Bibliometric Analysis
WHEN ARTIFICIAL INTELLIGENCE THREATENS CAREERS: A MODERATED MEDIATION MODEL OF JOB INSECURITY, EMOTIONAL EXHAUSTION, AND TURNOVER INTENTION
The rapid integration of artificial intelligence into organizational operations has intensified employee concerns about job continuity, yet the psychological pathway linking such concerns to workforce withdrawal remains incompletely specified. Drawing on Conservation of Resources theory, this study examines how AI-induced job insecurity influences turnover intention, tests emotional exhaustion as a mediating mechanism, and evaluates perceived organizational support as a boundary condition attenuating the insecurity–exhaustion relationship. Using a quantitative, explanatory design, cross-sectional survey data were collected from 312 manufacturing employees selected through purposive sampling, and the moderated-mediation model was analyzed via partial least squares structural equation modeling (PLS-SEM) in SmartPLS. The measurement model satisfied reliability, convergent, and discriminant validity criteria. Results indicate that AI-induced job insecurity significantly increases turnover intention both directly and indirectly through emotional exhaustion, which functions as a partial mediator, confirming that perceived technological threat operates as a resource-depleting stressor driving defensive withdrawal. Perceived organizational support significantly weakens the insecurity–exhaustion relationship, substantiating a resource-substitution mechanism and helping reconcile prior inconsistent findings on the buffering role of support. The study extends Conservation of Resources theory by integrating its loss and gain dynamics within a single mechanism in the AI workplace and by treating AI-induced insecurity as a distinct construct.
AI-induced job insecurity, emotional exhaustion, turnover intention, perceived organizational support, Conservation of Resources theory
LEGAL RISKS AND REGULATORY CHALLENGES IN CROSS-BORDER REAL ESTATE INVESTMENTS: A COMPARATIVE STUDY OF PAKISTAN AND THE UNITED STATES
Cross-border real estate investment has become a substantial part of global capital flows and, at the same time, faces many legal challenges and legal uncertainty across jurisdictions. This paper will discuss the risks and regulatory challenges of cross-border real estate investment, particularly with the US and Pakistan. The main intention is to identify the impact of changes in property law, investment protection systems, compliance conditions, and the enforcement system on investors' exposure to risk and investor decision-making. It is existing research material, as it is a qualitative and comparative legal study drawing on academic writing, research papers, legal sources, and reports from international bodies. This approach helps me, in this practice, determine significant contrasts between the new and evolving real estate markets.Findings indicate that the property sector in Pakistan is suffering from inconsistent rules, weak enforcement of property rights, and vague procedures. All these complications drive up transaction costs and investment uncertainty for overseas buyers. In comparison, the United States has a more well-structured and stable legal system and robust investor protection. But it has challenges of its own, including tax, zoning, and compliance requirements. As to the risk and security of investment, both jurisdictions would have to comply with global financial and anti-money laundering regulations, but, chiefly with regard to the strength and maturity of their institutional frameworks, they would be most dependent.The study concludes that to mitigate the risks of cross-border real estate investment, further harmonization of regulatory frameworks, greater transparency, and stronger enforcement mechanisms are needed in emerging markets. The results can contribute to the development of knowledge on international real estate regulation and be useful for investors, policymakers, and professionals interested in real estate law involved in international real estate transactions.
Cross-border real estate investment; legal risk; regulatory challenges; property law; foreign direct investment (FDI); Pakistan; United States
IMPACT OF AI-POWERED FINANCIAL ADVISORY SERVICES ON RETAIL INVESTOR RETURNS
The proliferation of artificial intelligence (AI) in financial services has fundamentally transformed how retail investors access advisory services and make investment decisions. This study investigates the impact of AI-powered financial advisory services on retail investor returns, addressing a critical gap in the empirical literature on fintech adoption and investment performance. Using a quantitative research design, data were collected from 250 retail investors in Pakistan who actively use AI-based financial advisory platforms. A structured questionnaire with validated Likert-scale items was administered, and data were analyzed using IBM SPSS Statistics 26.0, employing Pearson correlation and simple linear regression analyses. Results demonstrate a statistically significant positive relationship between AI-powered financial advisory service usage and retail investor returns (r = .682, p < .001). The regression model explained 46.5% of the variance in investor returns (R² = .465), with AI advisory services emerging as a significant positive predictor (β = .682, t = 14.67, p < .001). Reliability analysis confirmed strong internal consistency for both constructs (Cronbach’s α > .84). These findings underscore the transformative potential of AI-driven tools—including robo-advisors, algorithmic portfolio optimization, and machine learning-based recommendation engines—in enhancing retail investment outcomes. The study contributes to the growing body of fintech literature and provides practical implications for financial institutions, regulators, and individual investors seeking to leverage AI for superior portfolio performance.
artificial intelligence, financial advisory services, retail investor returns, robo-advisors, portfolio optimization, fintech, algorithmic investment, machine learning
ETHICAL ISSUES OF ARTIFICIAL INTELLIGENCE IN DIGITAL MARKETING: CHALLENGES, RISKS, AND GOVERNANCE FRAMEWORKS
Artificial Intelligence (AI) is increasingly integrated into digital marketing, enabling personalized advertising, predictive analytics, and automated customer engagement. However, its rapid adoption raises significant ethical concerns. The purpose of this study is to examine the ethical issues associated with AI in digital marketing, focusing on challenges, risks, and governance frameworks. The introduction highlights how AI systems collect and process large volumes of user data to optimize marketing performance, while also creating concerns related to privacy, transparency, and algorithmic bias. A qualitative research approach is employed, using secondary data from academic literature, industry reports, and case studies to analyze ethical risks such as data misuse, manipulation of consumer behavior, and lack of accountability in automated decision-making. The study concludes that while AI enhances marketing efficiency, it also poses serious ethical challenges that must be addressed. Recommendations include implementing strong regulatory policies, improving algorithm transparency, ensuring data protection compliance, and promoting responsible AI governance in digital marketing practices.
Artificial Intelligence, Digital Marketing, Ethics, Data Privacy, Algorithmic Bias.
ARTIFICIAL INTELLIGENCE AND BUSINESS PERFORMANCE: THE MEDIATING ROLE OF DIGITAL INNOVATION
AI is seen as a strategic asset of business value; however, the impact of AI in improving the performance of the organization hinges on how it is translated into innovation. This study explores the relationship between the capability of Artificial Intelligence and Business Performance, while Digital Innovation is suggested as an important mediator. A three waves time-lagged survey of 400 managerial employees from Jazz, Daraz Pakistan and Habib Bank Limited (HBL) was conducted in a quantitative and explanatory approach. Partial Least Squares Structural Equation Modeling with 10,000 bootstrappes was used to analyse the data in SPSS 29 and SmartPLS 4. The results show how Artificial Intelligence capability enhances organizations' capability to develop digitally enabled products, services, processes and customer solutions. The overall model accounted for 46.1% of the variance in organizational performance, with Digital Innovation identified as a key pathway through which AI has an impact on Business Performance. The mediation analysis also revealed a large share of AI's impact is through innovation, not just operational efficiencies. This research contributes to the literature by bringing clarity to the process of converting AI capability to organizational value, in the context of an emerging economy. It highlights that the implementation of AI is most effective when complemented by innovation-driven processes, competent workforce, robust data capabilities, and managerial dedication and commitment. The study thus has significant implications for organizations looking to transform technological investment into sustainable performance and competitive advantage.
Artificial Intelligence capability, Digital Innovation, Business Performance
INVESTIGATING THE MEDIATING EﬀECT OF PROJECT MANAGEMENT TOOLS AND TECHNIQUES BETWEEN THE RELATIONSHIP OF LEADERSHIP BEHAVIORAL PRACTICES AND PROJECT SUCCESS: AN EMPIRICAL STUDY IN IT SECTOR OF PAKISTAN
This study investigates the mediating effect of Project Management Tools and Techniques (PMTT) on the relationship between Leadership Behavioral Practices (LBP) and Project Success (PS) in the IT sector of Pakistan. The research aims to bridge the gap in understanding how leadership behaviors influence project outcomes and how project management tools can enhance this relationship. A quantitative research approach is employed, collecting data from 210 IT professionals in Pakistan using self-administered questionnaires. The study explores key leadership behaviors such as communication, relationship management, and conflict management, and evaluates their impact on project success, mediated by PMTT. The study finds that effective leadership behaviors positively influence project success. The integration of PMTT further enhances this relationship, providing a structured framework for project execution. The use of PMTT mediates the leadership behaviors, converting them into tangible outcomes such as improved coordination, time management, and stakeholder satisfaction. This research contributes new insights to the literature by exploring the unique role of leadership behaviors and project management tools in driving project success, particularly in the context of Pakistan’s IT sector. The study highlights the importance of leadership development and PMTT implementation for improving project success in developing economies. The findings suggest that IT companies in Pakistan can enhance their project outcomes by fostering strong leadership practices and adopting standardized project management tools.
Leadership Behavioral Practices, Project Management Tools and Techniques, Project Success, IT Sector, Pakistan.
FIRM-LEVEL DETERMINANTS OF DIVIDEND PAYOUT POLICY: A CROSS –COUNTRY ANALYSIS OF EUROPEAN LISTED FIRMS
This study examines the impact of firm-level determinants, i.e., firm size, cash flow, profitability, liquidity, lagged dividends, leverage, investment and growth opportunities, and business risk, on dividend payout policy of non-financial European firms. The study sample comprises 2,131 European listed manufacturing firms over the period 2009–2023. Moreover, to determine how the dividend payout policy is affected by various firm-specific characteristics, a high-dimensional fixed effects (HDFE) regression model is employed, alongside a binary logit model to identify which factors affect a firm’s dividend-paying decisions. Consequently, the results show positive effects of historical dividends, profitability, operating cash flow, and liquidity on payout policy, as well as on the likelihood of paying dividends. The negative coefficients on size and leverage, on the other hand, indicate their negative association with dividend payouts. Furthermore, the findings reveal that the likelihood of dividends initiation is positively associated with investment and growth opportunities. However, they were not strong enough to pass the robustness test in the dividend-to-assets ratio analysis with firm fixed effects. In addition, this paper presents new empirical evidence on the impact of firm-specific attributes on dividend payout policy across European countries. Likewise, it contributes new insights into the dividend policy of non-financial publicly traded firms, thus providing practical application for policy makers, corporate managers, investors, and minority shareholders. However, numerous prior research has concentrated at the country level within the EU member states to investigate the diverse determinants of the dividend policy. In contrast, this study exclusively examines the role of firm-level factors, separately from macro-level determinants, in dividend payout strategy by using a large firm-level panel dataset spanning the recent years and a high-dimensional fixed effects (HDFE) estimator.
Dividend payout policy, Firm-specific characteristics, European Market Type of paper: Research paper
PUSHED TO START, PULLED TO GROW? A QUALITATIVE STUDY OF NECESSITY- AND OPPORTUNITY-BASED ENTREPRENEURSHIP IN PAKISTAN
The distinction between necessity- and opportunity-based entrepreneurship is one of the most widely used typologies in entrepreneurship research. However, most of the knowledge derives from survey data collected in formal, Western labor markets. This paper explores the functioning of the distinction in the lives of micro- and small-enterprise owners in the Islamabad Capital Territory, Pakistan, based on 27 semi-structured interviews with entrepreneurs in the city's urban sectors and rural union councils. Six themes emerged from thematic analysis: braided motivations at founding; transition triggers that convert survival ventures into growth ventures; the household as financier, workforce, and gatekeeper; informality as both shelter and ceiling; improvised human capital that was developed through apprenticeship rather than formal education; and digital payment and social-commerce rails that narrow, but do not close, the rural–urban opportunity gap. The findings suggest that necessity and opportunity are rarely alternatives in this context. Most participants started from a need but held an opportunity in view, and whether they ever moved toward it depended less on their initial motivation than on household permission structures, the costs of formalization, and access to markets beyond the neighborhood. The paper contributes a contextualized, process-oriented account of the necessity–opportunity distinction in a South Asian informal economy and offers implications for SME policy in Pakistan.
necessity entrepreneurship, opportunity entrepreneurship, entrepreneurial motivation, and informal economy
BUSINESS INTELLIGENCE AND PREDICTIVE ANALYTICS FOR IMPROVING PUBLIC HEALTHCARE OPERATIONS: A SYSTEMATIC LITERATURE REVIEW
Public healthcare systems worldwide face mounting pressure to deliver safe, timely, and cost-efficient services under conditions of constrained budgets, workforce shortages, and rising patient demand. Business intelligence (BI) and predictive analytics have emerged as central enablers of data-driven decision-making in this environment, transforming fragmented operational, clinical, and financial data into actionable insight. This paper presents a systematic narrative review of the peer-reviewed literature published between 2015 and 2025 on the application of BI and predictive analytics to public healthcare operations. Following a structured search of Google Scholar and allied academic databases, forty studies were selected and synthesized around four themes: (1) the conceptual architecture of healthcare BI systems, including data warehousing, extract-transform-load pipelines, and visualization layers; (2) predictive analytics techniques, ranging from classical statistical forecasting to ensemble machine learning and deep learning; (3) operational application domains, namely patient flow and bed management, workforce and staffing optimization, supply chain and inventory management, disease surveillance, financial and fraud analytics, and clinical performance dashboards; and (4) the organizational, technical, and ethical barriers that constrain adoption, particularly in resource-limited and public-sector settings. The review finds consistent evidence that BI-enabled predictive analytics improves forecasting accuracy for admissions and resource demand, reduces preventable readmissions, shortens waiting times, and strengthens managerial decision-making, while also revealing persistent challenges around data quality, interoperability, governance, workforce analytics literacy, and equitable access to these technologies in low- and middle-income health systems. The paper concludes with an integrated conceptual framework linking data infrastructure, analytic capability, and organizational readiness, and proposes an agenda for future research emphasizing explainable artificial intelligence, real-time analytics, and governance frameworks tailored to public healthcare operations.
business intelligence; predictive analytics; public healthcare operations; big data analytics; hospital management; machine learning; healthcare decision support