Journal of Business and Management Studies
The Journal of Business and Management Studies (ISSN: 2709-0876) is a double-blind peer-reviewed, open-access journal published by Al-Kindi Center for Research and Development. It covers the latest developments in the broad areas of business and management. The journal offers readers free access to all new research issues relevant to business and management. While the journal strives […] Read More.
Al-Kindi Center for Research and Development
Voice AI Accessibility in Customer Support: A Business Review
Voice artificial intelligence is becoming a strategic tool in customer support as firms seek faster, more scalable, and more personalized service delivery. However, its business value depends not only on automation efficiency but also on whether it expands or restricts access for diverse customer groups. This review examines Voice AI for accessibility in customer support from a business and industry perspective, focusing on its implications for customer experience, service quality, operational efficiency, inclusion, trust, and risk management. Using a semi-systematic review approach, the study synthesizes recent literature published between 2016 and 2026 on conversational AI, voice assistants, automated speech recognition, accessible service design, and AI-enabled customer support. The review finds that Voice AI can improve accessibility by enabling hands-free interaction, reducing dependence on screen-based interfaces, supporting multilingual or low-literacy users, and increasing the availability of customer support outside traditional service hours. From a business perspective, these capabilities may improve customer satisfaction, service consistency, brand reputation, and support-channel efficiency. Nevertheless, the review also identifies critical limitations. Speech recognition systems may perform unevenly across accents, dialects, speech impairments, age groups, and noisy environments, creating exclusionary experiences for customers who already face service barriers. Over-automation, weak escalation pathways, privacy concerns, and lack of accessibility testing may further reduce customer trust and increase reputational or compliance risk. The study argues that firms should evaluate Voice AI not only through cost reduction and call deflection metrics but also through accessibility, fairness, customer effort, and inclusive service outcomes. The review contributes a business-focused foundation for understanding accessible Voice AI as a strategic customer support capability rather than a purely technical innovation.
Voice AI; Accessibility; Customer Support; Conversational AI; Service Management; Inclusive Customer Experience
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by-nc/4.0
The Essence of Corporate Social Responsibility Among Manufacturing Enterprises in Beijing, China: A Phenomenological Inquiry
Corporate Social Responsibility (CSR) has become an essential strategic approach for manufacturing enterprises seeking to balance economic performance with environmental sustainability and social responsibility. In China, the increasing emphasis on sustainable development and responsible corporate governance has heightened the importance of understanding how CSR is implemented within manufacturing organizations. This study explored the lived experiences of Corporate Social Responsibility (CSR) practitioners among selected manufacturing enterprises in Beijing, China, with the aim of understanding the essence of CSR implementation in the context of organizational sustainability. A qualitative phenomenological research design was employed to capture the experiences of five CSR practitioners who were purposively selected based on their direct involvement in the planning, implementation, monitoring, and evaluation of CSR initiatives. Data were collected through in-depth semi-structured interviews and analyzed using thematic analysis. The findings revealed eight interrelated themes that characterize successful CSR implementation: effective CSR leadership, community engagement and shared value creation, implementation challenges, CSR as a source of competitive advantage, organizational constraints, adaptive coping strategies, strategic planning, monitoring and evaluation, and digital communication for stakeholder engagement. The results indicate that effective CSR implementation extends beyond regulatory compliance and philanthropy, requiring leadership commitment, stakeholder collaboration, employee participation, transparent governance, and alignment with organizational sustainability goals. The study contributes to the growing body of knowledge on CSR by providing empirical evidence from the Chinese manufacturing sector through the lived experiences of CSR practitioners. The findings offer practical insights for manufacturing enterprises, policymakers, and CSR professionals in strengthening CSR strategies that support sustainable business practices and long-term organizational performance.
Corporate Social Responsibility; Manufacturing Enterprises; Phenomenology; Sustainability; Beijing, China; Stakeholder Engagement
Maximizing human capability and capacity: Refreshing the triad of professional identity, responsibility, and accountability in service organizations
Organizations can only maximize human capability and capacity when they move past traditional approaches to professional identity, responsibility, and accountability, by mobilizing these three core pillars instead as a single, interconnected triad. This conceptual review delivers a responsive framework that treats this professional triad as the core engine of organizational performance, directly addressing the value-creation needs of transforming service-oriented sectors, including Saudi Arabia’s Vision 2030 initiatives. To unpack how this refreshed operational mindset is achieved, the purpose of the analytical review is synthesizing contemporary literature aimed at reinvigorating three workplace pillars of professionalism. The framework systematically maps the dynamic interrelationships among the three constructs, revealing that their collective capacity remains locked without adaptive institutional scaffolding. The execution integrates Rogers’ seminal diffusion of innovations theory, framing institutional empowerment as dynamic 'software' explicitly calibrated to diverse employee adopter profiles from innovators to laggards. By synchronizing strategic human resource protection with these diffusion-based approaches, the review provides an actionable diagnostic blueprint and revitalization process. Ultimately, this review demonstrates that the path to sustainable high performance requires a total system upgrade: refreshing the professional triad to successfully convert the latent energy of human capability and capacity into visible, strategic organizational empowerment.
Human capability, human capacity, service organizations, professional identity, professional responsibility, professional accountability, triad alignment, Rogers' diffusion theory, organizational empowerment
Ethical ideology and its impact on organizational citizenship behavior: The moderating role of servant leadership
This study examines the relationships between the ethical leadership ideology (as stipulated by idealism and egoism), organizational citizenship behavior (OCB), especially on the helpful conduct, and the moderating role of servant leadership. The design adopted in this study to address existing theoretical and methodological gaps is a dyadic design, where 392 leader-subordinate pairs in the Iraqi industrial sector were used to collect data. The results showed a positive relationship between leadership idealism and OCB, with a negative relationship between leadership egoism and OCB using the Covariance-Based Structural Equation Modeling (CB-SEM) in AMOS. The main contribution of the study is the confirmation of the moderating role of servant leadership that was found to enhance the positive role of leadership idealism on OCB and reduce the negative impact of leadership egoism on OCB. The findings contribute greatly to the body of theoretical literature on leadership, OCB, and social exchange theory by highlighting the importance of ethical foundations in leadership and servant practices to a company, manager, worker, and policymaker.
Ethical Leadership, Idealism, Egoism, Servant Leadership, Organizational Citizenship Behavior, Dyadic Design, CB-SEM, AMOS
From Automation to Agentic Intelligence: A Framework for AI-Driven Digital Transformation, Innovation Capability, and Strategic Decision-Making in Contemporary Enterprises
From descriptive analytics to generative systems and, most recently, autonomous agentic architectures, artificial intelligence (AI) is transforming how enterprises achieve digital transformation and develop innovation capabilities and how they shape strategic decision-making. This study highlights an AI adoption-value paradox; despite significant investments, many organizations report a lack of business value from AI. The authors present a conceptual framework for the relationship between AI capability inputs (generative, predictive, and agentic) and organizational absorption processes (culture, skills, and governance) and downstream effects (digital transformation maturity, innovation performance, and decision quality), which are moderated by the regulatory environment and innovation industry context and mediated by innovation capability and employee AI literacy. Based on decision intelligence theory, the technology-organization-environment (TOE) framework, and dynamic capabilities theory, this study follows a mixed-methods approach with a structured survey of mid-to large-sized enterprises, followed by semi-structured interviews with C-suite and senior IT executives that will be analyzed through partial least squares structural equation modelling (PLSEM) and thematic analysis. This study extends the dynamic capabilities theory to the domain of agentic AI, provides managers with practical guidelines for governing AI decisions, and provides regulators with insights into responsible AI adoption. The implications, limitations, and directions for empirical validation are discussed.
Agentic AI, Generative AI, Digital Transformation, Innovation Capability, Decision Intelligence; AI Governance, Dynamic Capabilities
Copyright (c) 2026 Journal of Business and Management Studies https://creativecommons.org/licenses/by-nc/4.0
Impact of COVID-19 on Consumer Buying Behavior During COVID-19 Pandemic Using Data Analytics
This research focuses on the impact that Covid-19 had on consumer buying behaviors using data analytics. Covering the impact of fear, uncertainty and changes in lifestyle on shopping decisions and a shift in focus for consumers, it examines how these factors played a role in shifting their priorities. The study employs exploratory data analysis techniques of secondary survey data to identify patterns in spending habits, psychological impacts and digital adoption. The findings demonstrate that consumers were more cautious, more aware of safety needs, and that businesses had to evolve to respond to new demands via digital platforms. The analysis further shows that emotional and psychological factors had a significant influence on the buying behavior. In summary, the study offers significant insights into the use of data analytics to gain insights into consumer adaptation and inform business strategies in crisis situations.
Impact, Covid-19, Consumer Buying Behaviors, Data Analytics, Lifestyle, Exploratory Data Analysis, Demands, Digital, Psychological Impacts
Copyright (c) 2021 https://creativecommons.org/licenses/by-nc/4.0
Beyond Satisfaction: Commitment and Perceived Customer Lifetime Value in Iranian Banking
We investigate how Iranian banks transform brand experience and service quality into perceived customer lifetime value through customer satisfaction and commitment. We surveyed customers of major public and private banks in Iran and tested the proposed relationships using partial least squares structural equation modeling. We first examined a serial mediation model linking brand experience and service quality to customer satisfaction, customer commitment, and perceived customer lifetime value. We then evaluated an extended model that allowed brand experience and service quality to strengthen commitment directly. Our findings show that both brand experience and service quality improve customer satisfaction. This favorable evaluation then strengthens customer commitment, which emerges as the most important driver of perceived customer lifetime value. Brand experience also plays a stronger upstream role than service quality. The extended model provides a clearer explanation of how commitment develops by showing that customers can become committed not only because they feel satisfied, but also because they connect with the bank’s brand and trust the quality of its service. These results show that satisfaction alone cannot create durable customer value. Iranian banks build stronger relationships when they turn positive customer experiences into genuine commitment. The study highlights commitment as the central mechanism that converts brand experience and service quality into continued usage, first-choice preference, loyalty, and advocacy. It also offers bank managers a practical framework for managing customer experience, service delivery, satisfaction, and commitment as one integrated process for building long-term customer value.
The Relationship of Service Quality Process Improvements and Collection Rates of An Electric Cooperative in Bataan
Electric cooperatives play a vital role in ensuring reliable electricity distribution and maintaining financial sustainability through efficient revenue collection. However, collection inefficiencies, service delivery issues, and evolving customer expectations continue to challenge the operational performance of many electric cooperatives. This study determined the relationship between service quality process improvements and collection rates of an electric cooperative in Bataan. Specifically, it examined customers’ assessments of process improvements in terms of reliability, assurance, tangibles, empathy, and responsiveness, evaluated collection rates, identified current collection challenges, and proposed additional process improvements. A descriptive-correlational research design utilizing a mixed-methods approach was employed. Data were gathered from 252 electric cooperative customers through a researcher-made questionnaire based on the SERVQUAL framework. Descriptive statistics, including weighted mean and standard deviation, were used to analyze service quality and collection rates, while Pearson’s correlation coefficient was applied to determine the relationship between variables. Qualitative interviews with key personnel were analyzed through thematic coding to validate and enrich the quantitative findings. Findings revealed that respondents rated the cooperative’s service quality process improvements as “Very Good” across reliability (M = 3.25), assurance (M = 3.21), tangibles (M = 3.27), empathy (M = 2.80), and responsiveness (M = 3.22). Collection rates were also rated Very Good (M = 3.25). Inferential analysis showed a significant positive relationship between service quality process improvements and collection rates (r = 0.452, p < .05), with process improvements explaining 20.4% of the variance in collection performance (R² = 0.204). Interview findings identified operational delays, outdated systems, data management issues, regulatory constraints, and external economic conditions as persistent challenges affecting collection efficiency. Service quality process improvements significantly contribute to improved collection rates. Strengthening customer-centered services, digital technologies, and data-driven collection strategies can further enhance revenue recovery, operational efficiency, and long-term sustainability of electric cooperatives.
Service quality, process improvements, collection rates, electric cooperative, SERVQUAL, revenue collection, customer satisfaction
From Data to Decisions: The Impact of Big Data Analytics Capability on Supply Chain Resilience and Agility
This paper analyses how Big Data Analytics Capability (BDAC) can enhance supply chain resilience and agility in more challenging and uncertain business contexts. The study aims at the application of the data-driven decision-making to the operational responsiveness and to improve the supply chain performance. The research approach will be qualitative research design with thematic analysis of scholarly articles based on peer-reviewed journals, academic books, and conference papers on the topic of big data analytics and the supply chain management. The results show that BDAC enhances the visibility of supply chain, predictive decisions, and responsiveness of an organization. The analytics features allow companies to predict disruptions, minimize the response time, and enhance the supply chain operation flexibility. Practical Implications: The study outlines the significance of digital transformation strategies, data infrastructure advancement, and analytics-based capabilities with regard to supply chain managers aiming to increase agility and resilience. The research paper has value in the supply chain literature since it combines the lenses of dynamic capability and information processing theories. Future research can be done to examine industry-specific applications and empirical support on BDAC effects.
Evaluating Internal Control over Financial Reporting in State-Owned Enterprises A COSO-Based Case Study of Indonesia's Infrastructure Sector
The integrity of financial reporting constitutes a fundamental pillar of corporate governance, particularly for state-owned enterprises operating under heightened public scrutiny. PT Hutama Karya (Persero), a major Indonesian state-owned infrastructure enterprise, faces significant challenges in its financial consolidation process due to heavy reliance on manual procedures despite SAP implementation at the entity level. This dependency exposes the organization to human error, inconsistent accounting policies, and potential fraud risks. This study evaluates the design effectiveness of Internal Control over Financial Reporting within the Financial Statement Closing Process at PT Hutama Karya using a qualitative case study methodology grounded in the COSO 2013 framework. Data from semi-structured interviews with eight key stakeholders, questionnaire responses from financial and risk management personnel, and comprehensive document analysis were thematically assessed across the five COSO components. The findings reveal that the current ICFR design is not fully effective, with critical deficiencies identified in manual process dependency, system integration gaps, competency limitations, inadequate IT general controls, and restricted monitoring scope. Four interrelated root causes underpin these deficiencies: technology-process mismatch between entity-level SAP and group-level Excel consolidation; competency and awareness gaps across all three lines of defense; inadequate IT general controls including absence of digital approval workflows; and monitoring scope limitations driven by resource constraints. The study proposes an enhanced, technology-integrated ICFR framework anchored on automation, integration, standardization, real-time monitoring, and competency development. A phased implementation roadmap is developed to transform the consolidation process, aiming to significantly reduce consolidation cycle times, improve data timeliness, minimize control deficiencies, and strengthen external audit readiness. This study contributes to the internal control literature by extending the COSO framework to complex state-owned enterprise contexts, identifying "technology-process mismatch" as a distinct theoretical construct, developing a competency framework for ICFR implementation, and refining the Three Lines of Defense model through identification of the "testing gap." The enhanced framework provides reasonable assurance over financial reporting, ultimately strengthening corporate governance and stakeholder confidence in the organization's financial disclosures.
The Relationship Between Big Five Personality Traits and Innovative Work Behavior: The Mediator Role of Psychological Safety
This paper will explore how the Big Five personality traits (Extraversion, Conscientiousness, Openness to Experience, Agreeableness, and Neuroticism) influence the innovative work behavior of employees working in healthcare sectors in Iraq. It also explores the mediating process of psychological safety in converting personality traits into innovative behavior. The study was based on the Trait Activation Theory and Psychological Safety Theory, and a quantitative, time-lagged survey design was used to minimize common-method bias. A mixed-mode methods approach (online and on-site) was used to collect data from 425 workers in Iraqi health care. Partial Least Squares Structural Equation Modeling (PLS-SEM) and SmartPLS 4 were used to test the hypothesized relationships. Extraversion, Conscientiousness, and Openness to experience have a significant positive influence on innovative work behavior, whereas Agreeableness and Neuroticism have a significant negative influence. Moreover, psychological safety was identified as mediating the associations between all five personality traits and innovative work behavior, serving as a crucial process that triggers trait-consistent behaviors within the working environment. The study fills a gap in the innovation literature by examining the psychological drivers of innovation at the micro level in the health sector of a developing economy. It provides empirical data that psychological safety is a crucial conditional variable in the activation of personality traits toward innovation, thereby expanding the use of Trait Activation Theory to non-Western, hierarchical organizational settings.
Innovative Work Behaviour, Big Five Personality Traits, Psychological Safety, Trait Activation Theory, Manufacturing Industry, Iraq
Next-Generation Task Trackers as Diagnostic Operating Systems: Structuring and Analyzing Team Performance
Task trackers are usually treated as passive record-keeping tools, yet the accumulation of unresolved commitments inside them shapes team performance long before a deadline is missed. This article examines a recent proposal to reframe trackers as diagnostic operating systems that expose commitment saturation, coordination cost, and execution instability as structural conditions rather than as failures of individual discipline.. The discussion identifies where this reframing extends existing productivity models such as SPACE and DevEx, where it converges with Kanban and flow-based management, and where the governance risks documented in algorithmic-control research reappear in a new instrumental form. The article closes by outlining the conditions under which diagnostic instrumentation improves execution coherence and the conditions under which it degrades into a surveillance layer.
Task trackers, commitment saturation, coordination overhead, work-in-progress admission control, execution instability, algorithmic workplace monitoring, developer productivity measurement, flow management
Job-Related Factors Influencing Employee Engagement: Towards an Improved Human Resource Policy in Selected Technology Enterprise, Hangzhou, China
This study identified the job-related factors influencing employee engagement, resignation intention, and retention at Xiaomi Enterprise in Hangzhou, China, and used the findings to propose an improved human resource retention policy. A descriptive-correlational quantitative design was used with 200 valid employee responses. Respondents were profiled by years of work experience, job level, and department. Job-related factors included salary and benefits competitiveness, career development opportunities, work environment and atmosphere, and corporate culture identity, while employee engagement was measured through communication and job autonomy. Weighted mean, standard deviation, reliability testing, and Pearson correlation were applied. Results showed that career development opportunities were the most influential retention factor, followed by salary competitiveness. Work environment, atmosphere, and corporate culture identity showed moderate but meaningful influence. Engagement was moderate overall, with communication stronger than job autonomy. All job-related factors were significantly and positively correlated with employee profiles and employee engagement at p < 0.001, leading to the rejection of H01 and H02. The findings support a retention policy focused on career paths, fair compensation, supportive leadership, workplace well-being, transparent communication, autonomy, and organizational culture.
Employee engagement; employee retention; job-related factors; resignation intention; human resource policy; career development; compensation and benefits; Xiaomi; Hangzhou; technology enterprise
Digital Alchemy: When Influencer Marketing, E-Business, and Project Management Converge
This study examines the organizational conditions that enable productive synergy between influencer marketing, e-business operations, and project management within a digital content optimization company. Using a qualitative single-case study informed by six months of non-participant observation in a creator-focused digital marketing firm, referred to as AlphaStream to preserve anonymity, the research documents how structured collaboration between content creators and the company generates measurable value through integrated KPI alignment, iterative A/B testing, and AI-assisted project governance. Five enabling principles emerge from the analysis: a shared market-oriented logic, creator–stakeholder engagement, technological leverage, role differentiation, and inter-KPI alignment. The study contributes an empirically grounded analytical framework to a body of literature that has largely examined this integration from a theoretical perspective and offers practical implications for digital businesses seeking to implement content-driven growth strategies.
Push-Pull Dynamics in Medical Education Choice: Strategic Marketing Framework for Indian Students in Metro Manila
Anchored on the Push-Pull Theory of Migration, this study examined the push-pull dynamics influencing Indian medical students’ decisions to pursue medical education in selected medical schools in Metro Manila, Philippines. The study employed a quantitative descriptive-comparative research design and utilized a structured survey questionnaire with influence-based rating scales. Data were analyzed using descriptive statistics and inferential tests to determine differences in perceptions based on age, sex, year level, and family income. The findings revealed that major push factors in India included the limited availability of medical seats, the high cost of education, and stringent admission requirements. On the other hand, the decision to study in the Philippines was shaped by key pull factors such as affordability, ease of admission, English-medium instruction, and the perceived quality of medical education in the Philippines. The results further showed that age, year level, and family income significantly influenced respondents’ perceptions, while sex showed significant differences. Based on the findings, the ACCESS-CAREER Strategic Marketing Framework was developed to guide institutions in enhancing the attractiveness, global competitiveness, and sustainability of Philippine medical schools.
Push-pull theory, medical education, Indian medical students, international student mobility, strategic marketing framework, Metro Manila, Philippines
The Effect of Marketing Mix and Technological Integration on the Profitability of Commercial Banks in Bangladesh
The marketing mix plays a vital role in enhancing profitability of commercial banks in today's digitally-enabled banking industry. This study focuses on analyzing the effect of the four components of marketing mix namely Product, Price, Place, and Promotion on bank profitability among Bangladeshi commercial banks. Furthermore, the study evaluates how technological integration affects the relationship between marketing mix and profitability. The quantitative approach has been used for this research and primary data was collected from 355 respondents via convenience sampling using the questionnaire. The structural equation modelling (SEM) technique has been employed for data analysis using SmartPLS version 4 software. It was observed that all four elements of marketing mix have positive impacts on bank profitability. Additionally, technological integration has an extremely significant impact in strengthening such a relationship. The findings offer practical insights for bank managers, policymakers and marketing professionals seeking to improve financial performance through customer-oriented marketing strategies and digital transformation.
Marketing Mix, Profitability, Technological Integration, Banking, Bangladesh, Performance
Experiences of Registered Nutritionist-Dietitians in Selected Tertiary Government Hospitals in Metro Manila on the Implementation of the Nutrition Care Process (NCP): Basis for a Clinical Nutrition Framework
The Nutrition Care Process (NCP) was developed as a standardized and evidence-based approach to improve the quality and consistency of clinical nutrition care. Despite policy mandates in the Philippines, its implementation in tertiary government hospitals remained inconsistent. This study explored the lived experiences of Registered Nutritionist-Dietitians (RNDs) in implementing the NCP in selected tertiary government hospitals in Metro Manila and served as a basis for developing a Clinical Nutrition Framework. A phenomenological qualitative design was employed, involving purposively selected RNDs. Data were collected through in-depth interviews and analyzed using thematic analysis guided by the Consolidated Framework for Implementation Research (CFIR). The findings revealed that NCP enhanced clinical reasoning and professional accountability but was constrained by limited resources, manpower shortages, and inconsistent organizational support. Leadership engagement, professional commitment, and adaptive strategies were identified as key facilitators. The study concluded that successful NCP implementation depended on the interaction of organizational, individual, and external factors. A Clinical Nutrition Framework was proposed to strengthen implementation through policy support, organizational readiness, capacity building, patient-centered adaptation, and monitoring mechanisms.
Nutrition Care Process, Registered Nutritionist-Dietitians, Clinical Nutrition, CFIR, Government Hospitals, Philippines, Qualitative Study
Factors Affecting the Utilization of Mental Health Services in Selected Rehabilitation Centers in Lanao del Norte: A Basis for a Quality Improvement Project
The utilization of mental health services remains a critical concern in rehabilitation settings, particularly in resource-constrained areas. This study examined the factors affecting the utilization of mental health services in selected rehabilitation centers in Lanao del Norte. A mixed-methods approach was employed, combining quantitative survey data from 155 respondents with qualitative insights from interviews and focus group discussions. Descriptive statistics and inferential analyses were used to determine relationships between demographic variables, perceived barriers, and service utilization patterns. The findings revealed that most respondents were middle-aged, predominantly male, married, and had at least secondary education. Service utilization was generally moderate, with most respondents accessing services monthly or 3–4 times per month. However, significant barriers persisted, particularly service-related issues, financial constraints, and accessibility challenges. Educational attainment and socioeconomic status were found to have significant relationships with perceived barriers, while age and gender significantly influenced utilization frequency. The absence of younger respondents highlighted a critical gap in youth engagement. The study concluded that mental health service utilization was influenced by a combination of structural, socioeconomic, and psychosocial factors. A multi-component Quality Improvement Project was proposed to enhance accessibility, affordability, and service quality.
Mental Health Services; Service Utilization; Rehabilitation Centers; Barriers to Access; Quality Improvement; Philippines
The Mediating Role of AI Adoption in Talent Management in the Relationship Between TOE Factors and Perceived Talent Management Effectiveness in Metro Manila Organizations
This study explored how Artificial Intelligence (AI) adoption mediates the relationship between Technology–Organization–Environment (TOE) factors and perceived talent management effectiveness among HR professionals in Metro Manila organizations. Anchored on the TOE framework and supplemented by the Ability–Motivation–Opportunity (AMO) framework, the study explains both the adoption of AI and the capability stage through which AI may enhance talent management outcomes. A quantitative, cross-sectional research design was employed, with data collected from 137 HR professionals in Metro Manila using purposive and snowball sampling. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the relationships among constructs. The results indicated that technological and organizational contexts serve as the primary engines of AI adoption, whereas external environmental pressures did not drive any influence in AI adoption. The findings on mediation analysis suggested that while AI enhanced talent management effectiveness, it was not a prerequisite for achieving strong HR outcomes. Instead, AI functioned as an enabling capability that amplified organizational readiness through improved decision support, process efficiency, and more consistent talent management practices. Ultimately, this study contributes to the literature by clarifying the role of AI as a performance-enhancing mechanism and highlighting the importance of internal readiness over external pressure in driving adoption and providing insights to researchers, HR professionals, industry leaders, into leveraging AI for organizational success.
Financial Management Practices and Risk Attitude of Public High School Teaching Personnel in Parañaque City: A Proposed Personal Finance Management Strategies
This study examined the financial management practices and risk attitudes of public high school teaching personnel in Parañaque City from Parañaque National High School – Main, San Antonio National High School, and Moonwalk National High School. The research gap lies in the limited localized studies focusing on how financial management practices relate to risk attitude among public high school teachers in Parañaque City. Using a quantitative-descriptive design, data were collected through surveys assessing budgeting, saving, investing, debt management, financial planning, and risk attitude. Findings showed moderate financial management practices and a moderately conservative risk attitude among teachers. Based on the results, the study proposed financial literacy, budgeting, investment, and retirement planning strategies to improve teachers’ financial well-being.
Financial management practices; Risk attitude; Personal finance management; Public high school teachers; Financial literacy; Budgeting; Saving; Investing; Debt management; Financial planning.
The Role of Educational Leadership in Influencing Student Retention in Higher Education Institutions
This research proposal will explore the role of educational leadership in influencing student retention within higher education institutions. In every institution across the globe, student retention has been a subject of discussion. Student retention indeed has remained a central challenge across universities and colleges in the United States and globally, with declining persistence rates particularly affecting first-generation, minority, and economically disadvantaged students. Schools have been on the way, and even though significant resources will continue to be devoted to advising, academic support, and institutional reforms, the connection between leadership practices and student persistence will remain underexplored. Within the entire course, this study will employ a mixed-methods design, combining quantitative analyses of institutional retention data with survey-based measures of leadership practices, to determine the extent to which leadership approaches such as transformational, servant, and distributed leadership will influence persistence outcomes. In general, this research proposal will bridge leadership theory with retention research to provide actionable insights for higher education leaders, policymakers, and stakeholders committed to improving both student success and institutional sustainability.
| KEYWORDS Keywords: Public performance - Higher education - Indicators – University
Reducing Absenteeism in Employees: A Qualitative Study on Clear Bereavement Leave Policies
This study aims to investigate the impact of well-defined bereavement leave policies on employee absenteeism. A qualitative research design is employed to explore employee experiences and managerial perspectives regarding bereavement leave policies. Data is analyzed through an interpretive phenomenological lens to understand the lived experiences of employees. The study contributes to workplace policy development by identifying best practices for reducing absenteeism through structured bereavement leave policies. The findings are expected to provide insights for human resource professionals and policymakers in establishing clear and effective bereavement leave policies that balance organizational efficiency with employee well-being.
Venture Capital Research: An In-Depth-Cluster Analysis
This exploratory bibliometric study reviews and classifies the existing state of venture capital research. By conducting a co-citation analysis with a sample of 1,410 papers, we complement existing qualitative and quantitative studies while visually uncovering the intellectual structure of venture capital research. We identify three broad research areas (venture capital life cycle, interfirm relationships and knowledge exchange as well as economic and policy perspectives) that also reveal the evolution of the research field. These research areas are composed of 13 thematic clusters. In addition, we introduce the idea of connecting and methodology papers: we explore thematic linkages between the respective clusters as these connecting papers bring together research topics from at least two different fields of research. We highlight the most important articles, show how clusters interact with each other and finally identify potential future research directions.
Venture capital, co-citation-analysis, entrepreneurial finance, scientific visualization, start-up financing, bibliometric analysis
Predictive Analytics in Supply Chain Management: Enhancing Demand Forecasting and Operational Resilience under Uncertainty
Supply chains have been pressured, in recent years, by a sequence of disruptive events whose timing and magnitude were difficult to anticipate. From the prolonged shockwaves of the COVID-19 pandemic through the Suez Canal obstruction, the Russia–Ukraine conflict, and the persistent volatility in commodity markets, firms have repeatedly discovered that classical forecasting techniques, calibrated on stationary or near-stationary demand patterns, fail precisely when reliable guidance is most needed. This paper examines how predictive analytics, broadly understood to include statistical learning, machine learning, and deep learning approaches, can be deployed to strengthen demand forecasting and operational resilience under uncertainty. Drawing on a mixed-methods design that combines a structured review of 142 peer-reviewed studies published between 2015 and 2025 with an empirical comparison conducted on a multi-echelon retail dataset, we evaluate seven forecasting models: ARIMA, exponential smoothing state space (ETS), Prophet, XGBoost, Long Short-Term Memory (LSTM) networks, Temporal Fusion Transformers (TFT), and a hybrid ensemble. The empirical results indicate that the TFT and the hybrid ensemble outperform classical benchmarks by 18.6% and 22.4%, respectively, in mean absolute percentage error during volatile demand windows, while also yielding tangible improvements in fill rate, inventory turnover, and bullwhip dampening. Beyond model accuracy, we argue that predictive analytics contribute to resilience only when embedded within an organizational architecture that links forecasts to flexible sourcing, dynamic safety stock policies, and human judgment. We propose an integrative framework, the Predict–Sense–Adapt (PSA) loop, and discuss its managerial, theoretical, and policy implications. The study contributes to the literature on data-driven operations management by clarifying when, why, and under what conditions advanced forecasting techniques translate into resilience gains, and where their limitations remain consequential.
Predictive Analytics; Demand Forecasting; Supply Chain Resilience; Machine Learning; Deep Learning; Uncertainty; Operational Risk; Temporal Fusion Transformer
Factors Contributing to Work-Related Stress: A Qualitative Content Analysis
This article provides a theoretical basis for the causes of work-related stress. Research objective: to identify the factors determining stress experienced at work based on qualitative content analysis. Data were collected by presenting open-ended questions to the study participants (n=303), and the obtained data were processed and interpreted using the content analysis method. The results of the study showed that a heavy workload and unrealistic deadlines, as well as a lack of clearly defined employee responsibilities and functions and a lack of precise instructions for performing tasks, were identified as factors contributing to workplace stress. The study also found that the risk of workplace stress is heightened by limited opportunities for professional development and career advancement, as well as a lack of training on stress management within the organization, as well as a failure to recognize employees’ efforts, a lack of incentives for good performance, and predominantly tense relationships with colleagues and supervisors. The study’s results provided valuable insights into the causes of workplace stress, which, in the context of future research, opens up opportunities to reasonably identify directions for the prevention and management of workplace stress at the organizational level.
Work-related stress, causes of work-related stress, employees
Strategic orientations and innovation performance in Bangladeshi SMEs: Dual role of big data analytics and innovation capabilities
This study investigates how innovation performance (IP) in Bangladeshi manufacturing SMEs is affected by three strategic orientations: entrepreneurial (EO), digital (DO), and environmental (E2O). In addition to examining the moderating influence of big data analytics (BDA) and the mediating function of innovation capabilities (IC) , it further uniquely integrates these perspectives. Through the application of structural equation modeling, data from 369 managers in textile SMEs (weaving, spinning, and dyeing) were evaluated. The data reveal that whilst E2O has no direct influence on IP, whereas EO and DO have a beneficial impact . All three orientation-IP interactions are favorably mediated by IC. BDA has no discernible impact on the E2O-IP relationship, but it does strengthen the EO-IP and DO-IP relationships. Even though EO, DO, IC, and BDA have been shown to improve invention, little is known about how they work together. As the survey suggests on fostering innovation, SMEs are expected to focus on BDA, digital, entrepreneurial, and even environmental strategies. This paper outlines actionable recommendations aimed at policymakers, practitioners, and the managers.
Entrepreneurial Orientation, Digital Orientation, Environmental Orientation, Innovation Capabilities, Big Data Analytics, Innovation Performance
Leadership and Organizational Resilience in Multinational FMCG Companies Operating in Geopolitically Volatile Environments
In this original empirical research, the impact of transformational and adaptive leadership on organizational resilience and firm performance is analyzed for multinational fast-moving consumer goods (FMCG) corporations operating within geographically volatile markets. The data for this research were collected through surveys conducted on 328 middle and senior managers employed by Unilever, Nestlé, and Procter & Gamble in Lagos, Nigeria, an emerging economy known for its geographically volatile environment associated with political tensions, monetary crisis, and disruptions in supply chains. It is established through the analysis conducted using partial least squares structural equation modeling (PLS-SEM) that transformational leadership (β = 0.44, p < .001) and adaptive leadership (β = 0.39, p < .001) positively affect organizational resilience, mediating the effects of each type of leadership on profitability (β = 0.53), operational effectiveness (β = 0.49), and sustainability (β = 0.46).
Transformational leadership, adaptive leadership, organizational resilience, multinational FMCG, geopolitical volatility, Nigeria, PLS-SEM
Strategic Financial Architecture of International Stadium-Level Touring: Revenue Diversification, Risk Mitigation, And Scalability in Live Music Events
Stadium-level international touring has emerged as the central profit generator for the global music live entertainment industry. However, the underlying financial architecture of stadium-level international touring is largely understudied. This paper proposes and tests a new theoretical framework for a strategic financial architecture for stadium-level international touring consisting of four interdependent pillars: revenue diversification, cost and logistics discipline, risk management, and leverage scalability. Using an explanatory sequential mixed-method multiple case-study design, this study examines empirical evidence obtained through 28 semi-structured interviews with high-ranking industry executives, financial documents, and a fan expenditure survey (N=1,247). The empirical findings show that the proposed architecture results in a consistent profit margin of 28–35%, net artist take-home earnings of 47% of total gross, and ancillary revenue of 22–34%. Furthermore, residency-hybrid tour strategies have resulted in 39% savings in logistics expenses, while a layered hedging strategy has kept currency fluctuation below 1.8%. Moreover, leveraging digital and metaverse platforms has produced marginal scalability of nearly 100%. This research contributes to the body of knowledge in cultural economics and event management literature by offering a comprehensive financial architecture framework for stadium-level international touring rather than focusing solely on fragmented studies.
Strategic financial architecture, stadium touring economics, revenue diversification, risk mitigation, live music scalability, ancillary revenue, mixed-methods case study, metaverse extensions
AI-Driven Predictive Analytics for Supply Chain Resilience, Financial Risk Management, and Digital Marketing Strategy: A Unified Business Intelligence Framework
The arrival of artificial intelligence and big-data analytics at scale has begun to redraw the strategic map of the modern enterprise. Three areas sit close to the center of that change: how firms manage their supply chains, how they assess financial risk, and how they think about digital marketing. Each has its own substantial literature, yet the three are seldom examined together inside a single, properly governed analytical architecture. This paper sets out to close that gap. We develop and empirically validate a Unified Business Intelligence (UBI) framework that brings machine-learning engines, predictive analytics pipelines, and explainable AI modules into one coherent three-layer design that spans all three domains. The framework is grounded in a structured synthesis of forty-three peer-reviewed studies published between 2023 and 2026 and is supplemented by multi-domain benchmark experiments. The results are consistent and, in places, striking. In supply chain management, the framework reaches 94.1% disruption-prediction accuracy, a 22.9 percentage-point lift over domain-specific baselines and pulls demand-forecast MAPE down from 12.4% to 7.8%. In financial risk, ensemble-transformer hybrids deliver an AUC-ROC of 0.93 on portfolio stress testing and an F1 of 91.4% on credit-risk classification. In marketing, AI-orchestrated cross-domain targeting raises campaign ROI from 14.2% to 45.3%, and churn-prediction recall climbs from 68.0% to 84.7%. Across the seven capability dimensions assessed among them cross-domain integration, real-time processing, and embedded explainability the UBI framework outperforms traditional BI, siloed AI, and integrated MIS benchmarks; no existing paradigm achieves all of these at once. Twelve concrete research gaps are mapped, spanning federated learning, regulatory-grade explainability, privacy-preserving marketing analytics, and questions of geographic generalizability, with a structured agenda proposed for each. The findings are directly relevant to practitioners moving enterprise AI into production, and to policymakers crafting governance for cross-domain algorithmic decision-making.
Artificial Intelligence; Predictive Analytics; Supply Chain Resilience; Financial Risk Management; Digital Marketing; Business Intelligence; Machine Learning; Explainable AI; Big Data; Data Governance.
Paying the Price: Management Implications of Public Market Vendors’ Debts and Its Effect on the Market Price of Goods in San Juan City Agora Market
Microenterprises are significant contributors to economic development and poverty reduction. However, they often struggle with financial capability issues. Market vendors usually resort to informal sources of loans, such as the "5-6" system. The borrowed money comes with extremely high interest rates, which traps market vendors in a cycle of debt dependency and financial strain. Guided primarily by the Cost-Push Inflation Theory, the research focuses on the debt management practices of market vendors and their influence on the pricing of goods at the San Juan City Agora Market. The study utilizes a mixed-methods research design that combines a case study focused on the San Juan City Agora Market with surveys. Structured interviews, observation checklists, and document reviews are used to obtain data, while thematic analysis is employed to interpret it. Results showed a significant relationship between the monthly debt repayment of market vendors for informal loans and their pricing strategies. The active loans that market vendors have, and their willingness to pay high interest rates in order to get money quicker, have a significant influence on the prices they set for the goods they sell, which are often higher than the suggested retail price (SRP). These findings indicate that debt practices, including reliance on informal lenders, such as “5-6,” and agreeing to the usurious interest rates charged by these informal lenders, have a direct impact on how market vendors set prices for the goods they sell, distributing or shifting the burden of paying the usurious interest rates of debts to consumers.