American Journal of Business Science Philosophy
ISSN Online: 3064-7568 American Journal of Business Science Philosophy (AJBSP) is a globally recognized platform that fosters interdisciplinary dialogue and advances knowledge at the nexus of business, science, and philosophy. Established in 2024 under the publisher American Open Science Philosophy, this journal provides a unique space for researchers, scholars, and practitioners worldwide to explore and contribute to the evolving interdisciplinary research landscape. With a commitment to intellectual rigor and open access, the journal publishes two issues annually, offering high-quality, peer-reviewed content to a diverse audience of academics and professionals.
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Market Dominance of GCash in the Philippine Digital Payment Ecosystem: A Secondary Data Analysis
The rapid expansion of digital payment systems has transformed financial transactions in the Philippines, with mobile wallet platforms becoming central to everyday economic activities. This study examines the market dominance of GCash within the Philippine digital payment ecosystem using a secondary data analysis approach. Data were synthesized from official statistics, industry reports, and fintech market analyses to examine trends in digital payment adoption, mobile wallet usage, merchant integration, and market growth. Findings indicate an increase in digital payment adoption, with the share of digital retail payments rising from approximately 1% in 2013 to 57.4% in 2024. Concurrently, GCash experienced user expansion, growing from 20 million registered users in 2019 to more than 81 million in 2023, alongside a merchant network exceeding 2.5 million partners nationwide. Comparative analysis also shows that GCash maintains the most comprehensive service ecosystem among Philippine e-wallet platforms, contributing to its widespread adoption among consumers and small businesses. The results suggest that platform accessibility, trust, convenience, and network effects contribute to the platform’s dominant position. This study provides empirical insight into the structural and behavioral factors shaping digital payment adoption in the Philippines and highlights the role of fintech platforms in supporting the country’s expanding digital economy.
Copyright (c) 2026 American Journal of Business Science Philosophy
Quality Management as a Strategic Shift in Challenging Times: Evidence from Ground-Handling Enterprises
This study aims to examine and comparatively evaluate the quality management practices of three Turkish companies holding A-class ground handling service licenses. In response to increasing air transport demand and sectoral liberalization, the research investigates how structured quality management systems contribute to operational reliability, continuous improvement, and sustainable competitive advantage within airport ground handling operations. In the study, adopting a qualitative research design, the data were analyzed using the Maxqda 24.11 program. The findings indicate that A-class ground handling firms uniformly emphasize total quality management (TQM) in their vision–mission frameworks, supported by strong top management commitment and cultural institutionalization of quality. Maintenance and safety dominate technical priorities. However, firms diverge in strategic positioning, operational control architecture, and leveraging quality as a financial and competitive instrument. Managers in high-reliability aviation services should integrate TQM with digital governance to strengthen safety, sustainability, and competitive positioning. The study proposes hybrid high-reliability TQM model integrating digital governance frameworks.
Why Environmental Governance Struggles to Transform: A Business Governance Perspective on Credibility-Scaling-Resilience across Firms
The scope and ambition of environmental governance has grown, but with a variable ability to deliver credible and enduring environmental improvement. This theory-building review analyses environmental governance through the Credibility-Scaling-Resilience framework, through the governance dilemmas that are enacted through firms and industries that translate regulatory expectations into practice. Drawing on fifteen empirical studies from Asia, Africa, Latin America, and emerging Europe, the review uses PRISMA-guided procedures combined with insights from institutional theory, stakeholder theory, legitimacy theory, and the resource-based view. The findings reveal that governance credibility is driven by firms' perceptions of enforcement consistency and stakeholder scrutiny, scaling by the extent to which practices are diffused across industries and value chains, and resilience by organizational capabilities that allow them to sustain environmental commitments when facing economic or institutional adversity. Firms are prone to respond symbolically and opportunistically when these governance dynamics are misaligned; but when they are reinforcing, more substantive forms of environmental practice are likely to emerge. The review extends the framework by grounding it in firm and industry-level governance dynamics, and offers insights for policymakers, regulators, industry associations, and corporate decision-makers who wish to improve their environmental governance performance.
Artificial Intelligence and Corporate Accountability in International Law: A Conceptual Exploration
This paper explores the intersection of artificial intelligence (AI) and corporate accountability within the framework of international law. As AI increasingly assumes decision-making roles in global business operations, traditional legal doctrines—designed around human agency and state-centric liability—struggle to address harms arising from autonomous, opaque, and transnational AI systems. Drawing upon scholarship in international corporate law, human rights law, and technology regulation, this study develops a conceptual framework to guide corporate accountability in the age of AI. The proposed framework integrates three interrelated dimensions: responsibility and liability, transparency and auditability, and governance and ethical oversight. Responsibility is distributed across corporate, managerial, and technical levels, ensuring accountability for algorithmic harms. Transparency emphasizes explainable AI, documentation, continuous monitoring, and stakeholder engagement, while governance embeds ethical standards into organizational structures, aligning practices with international norms. By synthesizing legal, ethical, and organizational approaches, the framework provides a roadmap for accountable AI deployment, risk mitigation, and compliance with global standards. The paper highlights implications for corporate practice, international law, and policy development, emphasizing the need for adaptive, multi-level mechanisms to ensure responsible technological innovation in transnational contexts.
Driving Governance Excellence in Non-Profit Organizations through Digital and Strategic Transformation
The research investigates which essential organizational abilities lead to better governance results in non-profit organizations. The research examines four essential elements which include digital governance capability and strategic agility and social capital and organizational learning capacity to determine their effects on non-profit governance performance. The research employed quantitative methods to obtain data from 354 non-profit organization staff members based in Saudi Arabia. Data analysis was performed using Structural Equation Modeling with SmartPLS. The research demonstrates that all four factors directly impact governance effectiveness because non-profit organizations need to unite technological readiness with strategic flexibility and collaborative networks and continuous learning processes. The research demonstrates that organizations can achieve optimal governance through the implementation of digital tools and agile strategies and trust-based relationships and ongoing learning processes. The research develops an extensive model which demonstrates how different organizational capabilities affect governance results in non-profit organizations. The research delivers useful guidance to leaders and policymakers who want to improve their governance systems and organizational achievements.
Influence of Government on the Performance of Public Sector Projects: A Case of Government-Funded School Projects in Morogoro Municipality, Tanzania
This study examines the influence of government on the performance of public sector projects, with a specific focus on government-funded school construction projects in Morogoro Municipality, Tanzania. The study employs a cross-sectional research design and utilizes multivariate regression analysis on data collected from 194 sampled participants within the municipality. The findings reveal that adequate budgeting, regulatory compliance, efficient procurement processes, and supportive government policies significantly influence the performance of public sector projects managed by the Morogoro Municipality Council. Based on these findings, the study recommends the promotion of collaborative partnerships and coordinated efforts to continuously enhance public sector project performance management. Furthermore, local government authorities should adopt a more inclusive and participatory approach to project planning, implementation, and monitoring. This includes actively engaging and empowering local communities, as well as ensuring that government commitment to funding public school infrastructure is both visible and sustainable.
Enhancing Business Accounting Student Performance through Gamified Learning
Accounting is widely regarded as a complex subject, and traditional teaching methods often fail to fully engage students or enhance learning outcomes. This study investigates the effectiveness of gamification and vocational programmes as pedagogical approaches to improve student engagement and academic performance in accounting education. A quantitative research design was employed, with primary data collected from 254 undergraduate and postgraduate students enrolled in accounting and vocational accounting programmes across India. Measurement scales were adapted from validated studies, and Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied using SmartPLS 4.0 to test the proposed hypotheses. The results indicate that gamification has a significant positive effect on student engagement (β = 0.683, p < 0.001) but does not directly influence academic performance (β = 0.017, p = 0.448). Conversely, vocational programmes positively affect both engagement (β = 0.264, p = 0.014) and academic performance (β = 0.903, p < 0.001). These findings suggest that while gamified interventions enhance motivation, participation, and collaboration, practical and skill-based vocational training is essential for improving measurable learning outcomes. This study contributes to the accounting education literature by demonstrating the complementary roles of gamification and vocational programmes, emphasizing the importance of integrating motivational and performance-oriented pedagogical strategies. For educators and curriculum designers, combining gamified learning with vocationally oriented activities offers a promising approach to increase engagement, reinforce conceptual understanding, and prepare students for real-world professional challenges. The study also provides implications for curriculum design, policy development, and future research on hybrid pedagogical models.
Understanding Environmental Governance in Emerging Markets: A Multi-Level Theory-Building Review of Institutions, Stakeholders, and Firm Capabilities
This theory-building review explores how environmental governance works in emerging markets. It synthesizes findings from twenty-three empirical studies in Asia, Africa, Latin America, and emerging Europe. Using PRISMA guidelines, structured search, the review integrates institutional, stakeholder, legitimacy, and resource-based insights to explain why firms react differently to environmental expectations. The findings highlight that credible regulatory enforcement emerged as the most consistently identified factor shaping substantive environmental practices; when enforcement is limited, firms are more likely to comply symbolically. Stakeholder pressure—exercised by NGOs, media, communities, and global buyers—serves an important complementary function, particularly where the state’s capacity is limited. Firm-level capabilities (e.g., board experience, financial slack, and environmental expertise) moderate how organizations interpret and implement governance pressures. Adoption is further strengthened by a cohesive mix of policy instruments. The review proposes an integrated conceptual framework and outlines implications for policymakers, regulators, firms, and global value-chain actors.
Examining Factors Influencing Governance Effectiveness in Non-Profit Organizations in Saudi Arabia
This study investigates the determinants of governance effectiveness in non-profit organizations in Saudi Arabia, with a focus on board competency, transparency, stakeholder engagement, compliance, and leadership quality. Adopting a quantitative research design, data were collected from 266 employees working in Saudi non-profits. Data were analyzed using Structural Equation Modeling (SEM) with SmartPLS. Structural model results revealed that all five predictors had a significant positive effect on governance effectiveness, with stakeholder engagement (β = 0.565) and leadership quality (β = 0.565) emerging as the most influential factors. The model explained 60.4% of the variance in governance effectiveness, indicating substantial explanatory power. The findings highlight that governance effectiveness is multi-dimensional, requiring the integration of stakeholder participation, transparent practices, compliance with regulations, competent boards, and ethical leadership. In the Saudi context, these results align closely with the objectives of Vision 2030, which emphasizes accountability, transparency, and capacity-building in the non-profit sector. It also offers practical recommendations for policymakers and practitioners to strengthen governance through leadership development, stakeholder inclusion, transparency mechanisms, compliance frameworks, and board training.
Copyright (c) 2025 American Journal of Business Science Philosophy (AJBSP)
An Empirical Analysis of the Impact of Supply Chain Strategy and Organizational Structure on Operational and Financial Performance
Indonesia has encountered significant economic challenges indicated by the mass closure of major factories in Indonesia, which are related to the current issue, such as global supply chains, logistics, declining sales, and due to the company's reliance on outdated supply chain methodologies. This research will examine and investigate the relationship between supply chain strategy, organizational structure and operational performance on financial performance based on 153 respondents sample data that has been collected through questionnaires. The data was analyzed using PLS-SEM through SmartPLS 4.0 software. The findings of this study indicate the nonexistence of a direct effect on supply chain strategy and organizational structure towards the financial performance and the relationship between supply chain strategy and operational performance is also not supported. However, organizational structure is found to influence operational performance and has a direct effect on financial performance. It is also revealed that the operational performance has a significant positive mediating effect on the relationship between organizational structure and financial performance. The results shows that external factors like competition, the US-China trade war, the pandemic’s long-term impact and the parent company’s decision play a major role for the decline in Indonesia companies operational and financial performance.
Leveraging Artificial Intelligence for Big Data Analysis: Enhancing Administrative Processes and Service Delivery in the Private Sector – A Case Study of SABIC
This study seeks to explore the effect of employing artificial intelligence (AI) techniques in the analysis of big data within managerial contexts, focusing on their role in enhancing administrative operations and service delivery in private sector organizations, with SABIC (www.sabic.com/en) serving as a case example. A descriptive survey design was adopted, and data were gathered through a questionnaire administered to a sample of 50 employees— comprising 30 males and 20 females—selected through a convenience sampling method. The outcomes of the research revealed that the implementation of AI techniques for analyzing big data within the managerial context at SABIC had a notably strong impact on enhancing administrative operations and the quality of services provided. From the viewpoint of the employees who participated in the study, the influence of AI integration was perceived as substantial and beneficial across multiple aspects of the organization’s internal processes. Moreover, the statistical analysis demonstrated that there were no significant differences at the 0.05 level in the participants' overall attitudes toward the use of AI for big data analysis and its effect on improving both administrative efficiency and service delivery—when responses were categorized by gender (male vs. female). This indicates a generally shared perception among employees, regardless of gender, regarding the positive value of AI in modernizing administrative functions. However, further examination of the data uncovered statistically significant gender-based differences in specific dimensions, particularly in how AI contributes to enhancing administrative processes. Based on these findings, the study recommends several strategic actions: First, promoting a stronger organizational culture around AI, especially in the field of administrative work. Second, leveraging AI tools and systems as part of talent acquisition and managerial decision-making processes at SABIC. Third, encouraging departments and employees to adopt AI applications by offering training workshops and awareness campaigns that emphasize the practical benefits of AI in improving work performance and service efficiency.
Strengthening Artificial Intelligence Governance through Ethical Handling of Sensitive Data: An Applied Study on Text Classification and Differential Privacy
This research develops a comprehensive hybrid framework to enhance Artificial Intelligence governance by ethically managing sensitive textual data through advanced classification techniques. Focusing on natural language processing (NLP) applications, the study integrates rule-based systems, logistic regression, and transformer-based models, notably BERT, to address the challenges of identifying and handling sensitive information within complex and ambiguous linguistic contexts. Experimental results demonstrate that the hybrid model attains an overall classification accuracy of 91%, with precision and recall scores of 89% and 94%, respectively, achieving an F1-score of 92%. These metrics reflect the model’s robustness in real-world scenarios where explicit textual indicators are often lacking. Individually, the rule-based approach excels in precision (98.6%) for clearly identifiable sensitive content, logistic regression ensures perfect recall (100%), capturing all sensitive instances albeit with increased false positives, and the BERT model achieves perfect precision, effectively minimizing false alarms. The hybrid approach synergizes these strengths, resulting in a balanced and reliable classification system. The study further explores the integration of differential privacy via a differentially private logistic regression model using the diffprivlib library, assessing privacy-utility trade-offs at varying privacy budgets (ε = 3, 5, 6). Results reveal that stronger privacy guarantees (lower ε) reduce classification accuracy (78% at ε=3), while looser privacy constraints (ε=6) approach non-private model performance (97% accuracy). These findings underscore the potential of combining hybrid NLP models with differential privacy to deliver scalable, trustworthy, and privacy-preserving AI systems. The proposed framework holds significant relevance for sensitive domains such as healthcare, public administration, and corporate governance, where balancing data privacy and AI performance is critical. Future research should extend these findings by exploring additional privacy configurations and validating the approach against diverse real-world datasets to optimize the equilibrium between privacy protection and analytical effectiveness.
Sustainable Aquaculture in India: Environmental and Economic Assessment in West Godavari, Andhra Pradesh
Aquaculture has become a cornerstone of rural livelihoods and food security in India, particularly in Andhra Pradesh where districts such as West Godavari have evolved into high- density shrimp and fish farming zones. Despite considerable economic gains in export revenues and rural employment, questions remain regarding the ecological costs and long- term economic resilience of small and medium-scale farmers. Building on prior studies, this paper addresses gaps in micro-regional sustainable-aquaculture research by (i) explicitly stating and testing hypotheses grounded in ecosystem and resilience theory, (ii) validating our survey instrument (content validity index = 0.89; Cronbach’s α = 0.87), (iii) applying advanced quantitative techniques (exploratory factor analysis, structural equation modeling) alongside rigorous thematic analysis, and (iv) offering an integrated framework for policy and practice. Data were collected January–March 2023 via a cross-sectional survey of 200 stakeholders (farmers, input suppliers, institutional actors) and 30 in-depth interviews across five mandals in West Godavari. Structural equation modeling confirms that intensive input use (chemicals, high stocking densities) significantly predicts environmental degradation (β = 0.52, p < 0.001), which in turn negatively affects farm profitability (β = –0.65, p < 0.001). Adoption of sustainable practices (water recycling, polyculture) mitigates these effects (indirect standardized effect = +0.22, p < 0.05). Qualitative analysis yielded three major themes—“Ecological Risk Awareness,” “Economic Vulnerability,” and “Adaptive Innovation”—each illustrated by farmers’ verbatim statements. We discuss theoretical contributions to triple-bottom-line sustainability models, outline practical extension and credit mechanisms, and propose policy reforms including aquaculture zoning, zero-discharge mandates, and sustainability-linked finance. This study provides a robust empirical foundation for steering India’s aquaculture toward long-term ecological integrity and economic resilience.
Activating Building Information Modeling Using Artificial Intelligence: An Applied Analytical Study
This study introduces the development of an intelligent, cost-effective, and replicable system for the classification and analysis of Building Information Modeling (BIM) data through supervised machine learning. The primary aim is to enhance the interpretability and functional value of BIM metadata by embedding artificial intelligence (AI) techniques into the design evaluation process. The research focuses on classifying BIM elements using structured attributes—such as dimensions, materials, fire ratings, and load-bearing status—and contextualizing these classifications within specific application domains, including residential, industrial, and healthcare environments. To identify the most effective classification strategy, four machine learning algorithms were evaluated: Logistic Regression, XGBoost, Neural Network (MLP), and Random Forest. Among these, the Random Forest model demonstrated superior performance with 99% accuracy, 0.99 precision, 0.98 recall, and a 0.99 F1-score, and was thus adopted as the core model for the proposed system. Unlike conventional BIM tools that depend on manual labeling, the proposed system autonomously predicts element categories using raw numerical and categorical data, showcasing a practical approach to semantic enrichment and intelligent automation in digital design workflows. The application, developed using Streamlit, features an interactive interface that accepts BIM data in CSV format, processes and classifies elements, assesses compliance with intended use contexts, and calculates associated design risk scores. It also generates simplified 3D-like visualizations to support user comprehension. In addition to classification, the system provides descriptive feedback and actionable suggestions, thereby facilitating informed decision-making during early design stages. By bridging the gap between static, IFC-based BIM data and AI-powered design intelligence, this research presents a novel tool for automated classification, risk evaluation, and context-aware assessment. The findings underscore the feasibility and utility of integrating AI into BIM environments to support more efficient, intelligent, and responsive architectural and structural planning.
Evaluating Green Investment Performance in Morocco: An Empirical Study on Policy, Environmental, and Economic Drivers
This study investigates the performance of green investments in Morocco, focusing on their financial returns, environmental impact, and social contributions within the framework of the country’s sustainability and economic development goals. Drawing on Sustainable Finance Theory and the Triple Bottom Line (TBL) framework, the research examines five key influencing factors: government policies and incentives, investment challenges, environmental impact, investor confidence, and job creation. Primary data were collected through a structured survey administered to 225 participants, including policymakers, investors, and industry experts involved in green investment projects. The survey utilized a Likert scale format to assess perceptions of investment effectiveness and barriers. Quantitative methods, including descriptive statistics, multiple regression, and correlation analysis, were employed to analyze the relationships between these variables and green investment performance. The results reveal that environmental impact (β = 0.181, p < 0.01), job creation and economic impact (β = 0.155, p < 0.01), and investment factors (β = 0.119, p < 0.01) significantly enhance investment performance. In contrast, investor confidence has a negative effect (β = −0.322, p < 0.01), and government policies do not show a statistically significant impact. The model explains 74.7% of the variation in green investment performance (R² = 0.747). These findings underscore the need for stronger and more consistent policy implementation, targeted investment incentives, and a greater focus on job-generating sustainable projects. The study offers practical insights for policymakers and stakeholders aiming to advance Morocco’s green transition and promote sustainable development through more effective green investment strategies.
Business Model Innovation in the Trading Card Grading Industry: Cross-National Insights from Pokémon Trading Card Game and Non-fungible Tokens
This study examines how firms in the Pokémon Trading Card Game (PTCG) grading industry adapt their business models in response to digital disruption. We employ a qualitative multiple-case design, investigating three leading grading companies – PSA (United States), CCIC (China), and SQC (Thailand) – through 30 in-depth interviews and supplemental document analysis. The findings reveal divergent strategies shaped by both dynamic capabilities and institutional contexts. PSA leverages scale and AI technology to enhance efficiency, CCIC focuses on legitimacy and incremental improvements under regulatory constraints, and SQC pursues exploratory digital initiatives (e.g., NFT-linked trials) to co- create value with its community. These patterns highlight the ambidexterity required for business model innovation in a digitizing niche service sector. The study contributes to business model innovation and digital transformation literature by demonstrating how national institutions and customer engagement influence innovation paths. Practical implications include lessons for balancing core business sustainability with transformative innovation in different regulatory environments.
Transforming Export Competitiveness: Technological Upgradation and Digitalization in the Indian Heating, Ventilation, and Air Conditioning Industry
This study investigates the impact of technological upgradation and digitalization on the export competitiveness of India’s Heating, Ventilation, and Air Conditioning (HVAC) industry. Drawing on a 23-year panel dataset from 51 low-and-lower-middle-income countries, the research employs econometric analysis using high-tech exports and broadband subscriptions as proxies. The findings reveal that technological upgradation—measured through medium and high-tech exports—has a statistically significant positive impact on export competitiveness. In contrast, digitalization, proxied by broadband subscriptions, shows no significant effect, suggesting that mere infrastructure is insufficient without deeper operational integration. The Indian HVAC sector, though poised for growth amid global demand and sustainability mandates, faces challenges such as limited R&D investment, inadequate digital adoption, and scale inefficiencies. The study proposes a theoretical framework linking technological advancement and digital readiness with competitive export performance, offering insights for policymakers and industry stakeholders. It underscores the need for strategic investments in innovation, sector-specific digital tools, and workforce development. By aligning macroeconomic data with sectoral realities, the research contributes to a nuanced understanding of how emerging economies like India can leverage technological transformation to boost global trade competitiveness.
Sustainable Business and Global Supply Chains in ASEAN: Escaping the Middle- Income Trap
This study explores the influence of sustainable business strategies and facilitative policy frameworks on ASEAN companies' upgrading and integration into global supply chains (GSCs). The study employs a qualitative document analysis approach to critically examine 12 national and regional policy reports, 6 international institutional reports, and 12 firm-level sustainability and annual reports. Thematic coding and cross-case comparative analysis were conducted using ATLAS.ti software to determine main drivers of sustainable GSC involvement at firm and policy levels. There are suggested and argued conceptual frameworks: the Sustainable Value Chain Upgrading Framework and the Policy-Driven Sustainable Trade Framework. Evidence indicates that firms embracing environmental, social, and governance (ESG) values, circular economy approaches, and innovation investment possess higher market positioning and supply chain resilience. Meanwhile, green growth policies at the national level and international efforts promoting sustainable trade assist in guaranteeing main compliance reduction and corporate sustainability uptake incentives. Cross-country analysis reveals growing convergence towards ASEAN global ESG standards among ASEAN firms, with differences in social impact strategies localized. The article contributes to the existing literature by integrating firm- and policy-level perspectives and offers practical recommendations to policymakers and business managers interested in pursuing economic upgrading through sustainability in the region. The findings call for dynamic firm-policy interactions to attain resilient, inclusive, and sustainable engagement in global value chains.
Human Capital Perception in Hybrid Work Environments: A Qualitative Exploration of Artificial Intelligence Integration
Hybrid work environments that blend human labor with artificial intelligence (AI) systems reconceptualize assumptions about identity, agency, and value creation within the firm. Grounded in the philosophical postulate that organizational reality is a social construct, this study analyses how human capital interprets AI integration in companies located in the Sierra de Zongolica, Veracruz. A phenomenological design was employed; twenty-five semi structured interviews and two focus groups were conducted with service, production, and administrative workers who interact daily with human–AI systems. Thematic coding revealed four interrelated constructs: AI as an operational enabler, perceived occupational well-being, enhanced professional autonomy, and holistic job satisfaction. Participants reported that AI lightens repetitive tasks, shortens cycle times, and broadens decision-making scope, thereby reducing stress and improving work–life balance. Concurrently, concerns arose regarding the loss of human interaction and job stability, particularly among longer-tenured employees. The findings indicate that AI functions as a contingent complement to human expertise; its value depends on transparent algorithms, upskilling programmes differentiated by age cohorts, and change management sensitive to the cultural context. The study concludes that corporate strategies and public policies must align technological efficiency with ethical governance so that digital transformation simultaneously fosters productivity and human development.
The Mediating Role of Innovation Capability in the relationship between Supply Chain Management and Firm Performance
In today's dynamic and competitive business environment, organizations adopt supply chain management to boost innovation and improve performance. This study investigates the linkbetween supply chain management and firm performance and the mediating role of innovation capability. A cross-sectional survey research design was employed; 5 textile firms in Lagos State were conveniently selected for the study. 353 structured questionnaires were administered to top-, middle-, and lower-level managers of the selected firms, of which only 328 were returned. After data screening, only 312 responses were valid for analysis. The study employed SPSS statistical software to perform both descriptive and inferential statistical analysis. The mediation aspect of the analysis was done using Model 4 of the SPSS PROCESS macro. The study found that supply chain management has a significant positive effect on firm performance and innovation capability. Also, innovation capability significantly influences firm performance and plays a mediating role in improving the relationship between supply chain management and firm performance. The study recommends that leaders from industry should prioritize investments in SCM practices that can bring supply chain partners together to build a strong IC for performance improvement.
Strengthening ASEAN-Guangxi Trade Relations: Enhancing Regional Integration and Industrial Collaboration
A complex array of global disruptions—including the COVID-19 pandemic, the US-China trade war, the Russia-Ukraine conflict, retaliatory tariffs, economic stagflation, supply chain breakdowns, and the rise of artificial intelligence technologies—has significantly challenged the foundational structure of regional economic development. This study investigates the key barriers hindering ASEAN–Guangxi trade from achieving sustainable and accelerated economic growth. Trade data from 2019 to 2024 were analyzed, and empirical data were collected through structured questionnaires administered to 200 business practitioners and policymakers across ASEAN member states and Guangxi. The data were processed and validated using the Statistical Package for the Social Sciences (SPSS). The results indicate that enhanced regional integration and the presence of positive spillover effects are pivotal in promoting sustainable trade relations between ASEAN and Guangxi. These findings offer actionable insights for companies operating in the region and serve as a valuable reference for policymakers and future researchers seeking to strengthen regional economic cooperation. This study contributes to the literature by identifying integration and spillovers as critical drivers of resilient regional trade amid contemporary global uncertainties.
Enhancing Market Reach and Profitability in the Indian Aquaculture Industry
The Indian aquaculture industry, a global leader, faces persistent challenges in marketing, pricing, and supply chain management that limit profitability and market expansion. This study investigates how marketing channels, pricing strategies, and supply chain practices influence commercial success, focusing on West Godavari (Andhra Pradesh), Hooghly (West Bengal), and Kollam (Kerala). Semi-structured interviews with 45 stakeholders, including farmers, marketers, and supply chain managers—reveal that using online platforms and targeting export markets significantly enhances reach and profitability. Value-based pricing improves margins by aligning prices with product quality and customer perception. Efficient supply chain management, particularly through blockchain and automation, is vital for maintaining product integrity and meeting market demands. However, high implementation costs, lack of technical expertise, and resistance to change hinder adoption, especially among smaller operators. The study concludes that sustainable growth requires integrating diversified marketing strategies, value-driven pricing, and tech-enabled logistics. Key recommendations include investing in digital tools, embracing innovation, and fostering stakeholder collaboration to address operational barriers and strengthen the industry’s economic impact.
International NGOs’ Educational Budgets on Human Development Index in Conflicting Low-and-Lower-Middle-Income Countries
This study critically examines the impact of International Non-Government Organizations’ (INGOs) educational funding on human development outcomes in conflict-affected and developing regions, focusing on Syria, Bangladesh, DRC, Sudan, and Ukraine. Employing a mixed-methods approach, the research analyses the relationship between INGO budget allocations for education and the Human Development Index (HDI), utilizing panel data regression models and qualitative thematic analysis. Quantitative findings indicate a positive association between INGO educational expenditures and HDI; however, econometric issues such as autocorrelation, heteroskedasticity, and cross-sectional dependence limit the robustness of results. Qualitative insights reveal that most INGOs operate with limited budgets, prioritize needs assessments, and consider macroeconomic factors like GDP and HDI in planning. Despite resource constraints, a majority intend to increase educational investments, often through partnerships with local governments. The study underscores the importance of context-sensitive strategies and comprehensive analysis for effective development interventions. While findings support the hypothesis that increased INGO funding correlates with improved human development, methodological limitations necessitate cautious interpretation. The research contributes to understanding operational dynamics, strategic planning, and the nuanced role of INGOs in fostering sustainable development in fragile contexts, offering valuable insights for policy and future research directions.
Consumer Behavior Evaluation Model for Marketing Tourist Destinations
The objective focused on designing a consumer behavior evaluation model to enhance the segmentation, positioning, and marketing of tourist destinations. The research employed both quantitative and qualitative methods, which facilitated the development of a model structured in three stages, using tools such as data analysis and specialized software. The sample consisted of 366 tourists, selected through random convenience sampling. Surveys conducted with tourists revealed a majority profile of young and middle-aged men with a high level of education and middle-class background, primarily seeking relaxation, recreation, and cultural experiences. Most expenses were directed toward food and accommodation. The conclusions suggest that, to close the gap between actual and desired behavior, it is necessary to improve the tourism offerings and align services and infrastructure with visitors' expectations to increase satisfaction and destination competitiveness. The proposed model aims to evaluate consumer behavior and design actions that improve the economic and commercial performance of tourist destinations.
Factors Influencing Consumer Purchase Behavior of Saudi Dates
This study examines the factors influencing consumer behavior toward Saudi dates, focusing on the roles of hedonic values, utilitarian values, purchase intention, and actual purchase behavior. A cross-sectional study design was employed, with data collected through an online survey from 271 consumers who include dates as part of their dietary plan. The questionnaire, translated into Arabic, was pilot-tested with 35 participants to ensure the validity and reliability of the measurement scales. Data analysis was conducted using structural equation modeling to explore the relationships between the constructs. The findings reveal that both hedonic values and utilitarian values significantly influence purchase intention, which in turn strongly predicts actual purchase behavior. The study demonstrates that consumers who derive pleasure and practical benefits from Saudi dates are more likely to intend to purchase them, and these intentions strongly translate into actual purchasing behavior. Additionally, the mediating role of purchase intention highlights its importance in linking hedonic and utilitarian values to actual behavior. By addressing both emotional and practical aspects of consumer behavior, businesses can create compelling marketing strategies that enhance purchase intentions and drive actual sales.
The Mediating Role of Green Innovation in the Relationship Between Strategic Green Marketing Orientation and Marketing Performance
This study investigates the relationships between strategic green marketing orientation (SGMO), green innovation, and marketing performance within the manufacturing sector in Saudi Arabia. Employing a cross-sectional research design, data was collected from mid-level employees in the marketing departments of manufacturing firms. A total of 357 responses were gathered using a structured questionnaire, which measured the three key constructs using validated scales adapted from prior studies. Structural equation modeling (SEM) was utilized to analyze the data, enabling the examination of both direct and indirect relationships among the variables. Results revealed that SGMO has a strong positive effect on green innovation, which in turn significantly enhances marketing performance. Additionally, green innovation was found to mediate the relationship between SGMO and marketing performance, highlighting its pivotal role in translating green marketing strategies into improved market outcomes. The study underscores the importance of integrating environmental concerns into marketing strategies and fostering green innovation to achieve sustainable business success. These findings offer valuable insights for managers and policymakers in the manufacturing sector, emphasizing the need to align green marketing practices with innovation to drive both environmental and economic benefits.
Examining Determinants of Real Estate Appraisal Accuracy in Property Business
This study investigates the factors influencing real estate appraisal accuracy, focusing on market dynamics, technological integration, appraiser expertise, and the regulatory framework. The research aims to explore how these factors impact the accuracy of property valuations performed by real estate appraisers in Saudi Arabia. A cross-sectional survey was conducted with 161 licensed real estate appraisers, using a convenience sampling method. Data was collected through a structured questionnaire, and the responses were analyzed using structural equation modeling (SEM). The study found that market dynamics, technological integration, appraiser expertise, and regulatory frameworks significantly influence real estate appraisal accuracy. The findings highlight the importance of these factors in improving the reliability of property valuations, providing valuable insights for real estate professionals, regulators, and policymakers. The findings suggest that real estate appraisers should stay informed about market trends, enhance their technological skills, and continuously develop their expertise to improve appraisal accuracy. Regulatory bodies should strengthen guidelines and standards to ensure consistency in the appraisal process. Policymakers can use these insights to develop strategies that promote trust and stability in the real estate market.
The Moderating Role of Emotional Intelligence in the Relationship Between Employee Resilience, Perceived Organizational Support, and Work Engagement: A Multi-Sector Study in Saudi Arabia
Employee engagement plays a crucial role in organizational success, influencing productivity, retention, and overall workplace performance. This study examines the impact of employee resilience and perceived organizational support (POS) on work engagement, with emotional intelligence (EI) as a moderating factor, across multiple sectors in Saudi Arabia. Grounded in the Job Demands-Resources (JD-R) model, the study hypothesizes that resilience and POS positively influence engagement, while EI moderates these relationships by enhancing employees’ ability to leverage resilience and support effectively. A quantitative research approach was employed, using a structured survey distributed to 450 full-time employees across industries such as healthcare, education, finance, manufacturing, and IT. Data were analyzed through structural equation modeling (SEM) to assess the relationships among the variables. The findings confirm that employee resilience and POS significantly enhance work engagement, supporting the direct effects. Additionally, EI moderates these relationships, indicating that employees with higher emotional intelligence are better equipped to utilize resilience and organizational support to sustain engagement. These findings contribute to Saudi Vision 2030, emphasizing workforce development and employee well-being. The study provides practical insights for HR professionals on fostering engagement through resilience training, supportive workplace policies, and emotional intelligence development programs.
Singapore Role in Advancing Global Low-Carbon Economy: A Joint Effort for Sustainability and Climate Commitments
This study examines Singapore’s proactive role in advancing a low-carbon economy by analyzing its policies, innovations, and global partnerships in addressing climate change and promoting sustainability. Despite being a small, densely populated island nation with limited natural resources, Singapore has emerged as a global leader in sustainable development. Its approach integrates forward-thinking policies, cutting-edge technologies, and strategic collaborations. This study employs a structured literature review with a qualitative approach, systematically analyzing key policy documents and case studies of successful initiatives. Initiatives such as the Singapore Green Plan 2030 and the Carbon Pricing Mechanism drive energy efficiency, promote renewable energy adoption, and reduce carbon emissions. Additionally, Singapore actively participates in global climate action, contributing to regional and international platforms. This study highlights Singapore’s efforts in fostering a low carbon economy, encouraging collaboration among policymakers, research institutions, and stakeholders to build a sustainable and resilient global future.
The Role of Artificial Intelligence and Blockchain Technology in Crisis Management, Startup Growth, and Sustainable Future
This study examines the impact of artificial intelligence (AI) and blockchain technology on crisis management, startup growth, and sustainability in the Indian business landscape. Using a quantitative, cross-sectional research design, data was collected from 123 research and development (R&D) employees across various enterprises. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze relationships between key constructs. The results indicate that AI plays a crucial role in enhancing crisis management and business resilience (β = 0.553, p = 0.000), while effective crisis management positively influences long-term sustainability (β = 0.272, p = 0.000). Additionally, blockchain technology is a key driver of startup growth (β = 0.684, p = 0.000), and growing startups significantly contribute to a sustainable future (β = 0.689, p = 0.000). The findings highlight the transformative potential of AI and blockchain in navigating business uncertainties, fostering innovation, and driving sustainable development. The study offers practical implications for business leaders, policymakers, and entrepreneurs in leveraging emerging technologies for long-term resilience and success.