Economics, Finance and Management Review

Environmental Regulations, Financial Incentives, and Sustainable Supply Chain Performance: Evidence from SMEs in Vietnam’s Logistics Sector

Tran Anh Son — Tue, 31 Mar 2026 00:00:00 +0300

This study investigates the influence of environmental regulations and financial incentives on supply chain efficiency and green logistics implementation in small and medium-sized enterprises in Vietnam. Drawing on the Sustainable Supply Chain Management approach, the study proposes a conceptual model to test the relationships between environmental regulations, financial incentives, supply chain efficiency, and green logistics implementation in SMEs. The objective of the study is to examine how environmental regulations and financial incentives affect supply chain efficiency and the implementation of green logistics practices in Vietnamese SMEs, as well as to determine the relative strength of these factors in shaping sustainable supply chain performance. The study collected data from 87 managers and professionals in Vietnam working in logistics and supply chain activities in SMEs. The study applies Partial Least Squares Structural Equation Modeling to evaluate the proposed relationships in the conceptual model. The results show that both environmental regulations and financial incentives have positive effects on supply chain efficiency and green logistics implementation in SMEs. While environmental regulations are more dominant in influencing supply chain discipline, compliance, and efficiency, their effect on green logistics implementation in SMEs is relatively less significant. Conversely, financial incentives are more powerful in influencing supply chain efficiency in SMEs. Financial incentives also have a positive effect on green logistics implementation in SMEs, but only in combination with institutional encouragement and managerial commitment. The findings confirm that regulatory and financial mechanisms are both important drivers of sustainable supply chain development in SMEs; however, their effectiveness differs depending on the specific dimension of performance being assessed. Regulatory pressure strengthens efficiency and compliance, whereas financial support becomes especially important for practical implementation of green logistics measures. Further studies should expand the sample size, compare SMEs across different regions or industries, and explore additional mediating variables such as organizational culture, technological readiness, and leadership commitment in order to better explain green logistics adoption.

Digital Transformation of the Construction Industry: The Role of BIM, Digital Twins, Artificial Intelligence and Blockchain in Smart Real Estate Ecosystems

Tue, 31 Mar 2026 00:00:00 +0300

The digital transformation of the construction industry is becoming an important prerequisite for increasing the efficiency, transparency, and sustainability of real estate asset management. The objective of this study is to determine the role of Building Information Modeling, digital twins, artificial intelligence, blockchain, and related digital technologies in shaping smart real estate ecosystems. The methodology is based on a systematic review of scientific publications, comparative analysis, content analysis, and conceptual generalization of approaches to the digitalization of construction and real estate management. The main results show that the integration of BIM, Digital Twins, IoT, AI, and blockchain improves coordination among project participants, supports real-time monitoring, enhances asset valuation and lifecycle forecasting, automates contracts and payments, and creates the foundation for digital leasing and smart real estate management. At the same time, the study identifies major barriers, including high implementation costs, integration complexity, shortages of digital competencies, and cybersecurity risks. The conclusions emphasize that digitalization is a strategic factor in the modernization of construction and real estate ecosystems, provided that technologies are implemented comprehensively and supported by organizational change. Further research should focus on integrated digital platform models, economic feasibility for small enterprises, and cybersecurity standards.

A Study of the Relationship Between Expansionary Monetary Policy and Real Estate Prices: An Analysis of Capital Flows in the Gulf Countries for the Period 2010-2022

Ameen Fahad Jayed — Tue, 31 Mar 2026 00:00:00 +0300

The relationship between expansionary monetary policy and real estate market performance has become increasingly important in the Gulf Cooperation Council countries, especially in the context of intensified foreign capital movements and post-oil-shock structural shifts. The issue concerns not only changes in real estate prices, but also the broader economic conditions in which these changes occur. The study aims to assess how expansionary monetary policy affects real estate prices in GCC countries during 2010-2022, with particular emphasis on the role of foreign capital flows in shaping market dynamics. The research applies a vector error correction model based on quarterly data from six GCC countries. This methodological framework makes it possible to trace the transmission of monetary shocks and distinguish between immediate and subsequent effects on the real estate market. The findings reveal a significant inverse relationship between long-term interest rates and housing prices. In particular, a 10% decline in the interest rate was associated with an approximately 8.74% increase in housing costs, confirming a strong monetary transmission effect. Foreign direct investment, although smaller in scale than domestic credit, emerged as an important factor explaining real estate trends and market dynamics. Moreover, interest rate spreads, credit expansion, and foreign capital inflows that intensified after the 2015 oil price decline point to structural transformations in GCC economies. At the same time, the effects were less pronounced in the UAE and Saudi Arabia, where regulatory regimes and monetary policy frameworks differ more substantially. The study concludes that real estate price dynamics in the GCC require careful monitoring, while policy responses should support economic activity and ensure stable capital flows. Further studies may examine country-specific regulatory mechanisms, the long-term sustainability of capital-driven real estate growth, and the comparative resilience of GCC housing markets under changing external shocks.

An Application of Artificial Intelligence for Fundamental Analysis of Stock Selection During Inflationary Phases in the Indian Economy

Tue, 31 Mar 2026 00:00:00 +0300

Inflation is a major macroeconomic factor influencing investment strategies, particularly in the Indian market, where stock market volatility is strongly affected by broader economic conditions. In such periods, stock selection becomes more complex and requires analytical approaches capable of capturing both firm-level financial strength and changing market dynamics. This study aims to explore the integration of artificial intelligence with traditional fundamental analysis techniques in order to improve stock market decision-making during inflationary phases in the Indian economy. The study is based on the financial analysis of five NSE-listed companies, namely Reliance Industries Ltd, Tata Consultancy Services Ltd, Infosys Ltd, HDFC Bank Ltd, and ICICI Bank Ltd. Traditional tools of fundamental analysis, including ratio analysis, trend analysis, and SWOT analysis, are used to assess financial stability, while artificial intelligence is incorporated conceptually through predictive analytics to strengthen investment evaluation. The findings show that companies with stronger financial stability, lower debt exposure, and better profitability indicators perform more favorably during inflationary periods. The study also indicates that artificial intelligence improves the efficiency and accuracy of stock market decision-making by enhancing predictive interpretation and identifying patterns beyond traditional historical analysis. The integration of artificial intelligence and fundamental analysis provides a more effective framework for stock selection during inflation in the Indian market. Future studies should empirically test AI-based stock selection models, extend the sample to additional sectors and firms, and incorporate other macroeconomic variables alongside inflation.

Financial Support for the Development of Ukraine’s Construction Industry: Sources, Barriers, and Instruments for Post-War Recovery

Nazar Reshitko — Tue, 31 Mar 2026 00:00:00 +0300

The article is devoted to the study of financial support mechanisms for the construction industry of Ukraine under conditions of prolonged military aggression and the planning of post-war recovery strategies. The relevance of the topic is determined by the unprecedented scale of destruction of civilian and industrial infrastructure, which requires capital mobilisation exceeding the country’s annual GDP. The purpose of the study is to identify key sources of financing, determine the barriers to investment activity, and assess the effectiveness of modern financial instruments for reconstruction. The methodology is based on a systematic analysis of the World Bank reports (RDNA4), statistical data from the State Statistics Service of Ukraine, and expert assessments of international financial institutions. The study finds that, as of the end of 2024, the total recovery needs increased to USD 524 billion, with the housing sector remaining the most affected. The main channels of financial inflows are characterised, including the EU Ukraine Facility program amounting to EUR 50 billion and the state mortgage lending program «eOselya». It is identified that the main barriers to the development of the sector include a shortage of qualified personnel, an annual increase in the cost of construction materials by 25–30%, and high security risks. The results of the study have practical significance for public authorities in developing investment policies and for construction companies in planning their activities strategically. The findings confirm the need to transition to «Build Back Better» models and to implement green construction principles in accordance with the EU taxonomy. Based on an analysis of international experience, approaches to optimising public-private partnerships to attract private capital are proposed.

The Impact of Digital Banking on Customer Satisfaction and Financial Performance of Banks

Tue, 31 Mar 2026 00:00:00 +0300

The rapid migration from traditional branch-based banking to digital-first ecosystems has fundamentally transformed the banking experience and reshaped customer expectations. Digital banking now encompasses mobile applications, internet banking platforms, and AI-driven personalized services that influence both service delivery and institutional performance. This study aims to examine how digital banking affects customer satisfaction and how these changes are associated with the financial health of banks. The study is based on the analysis of recent market trends, customer-related evidence, and financial performance considerations related to digital banking adoption. It evaluates the interaction between digital service attributes, customer experience, and banking outcomes within a contemporary digital economy context. The findings show that convenience, 24/7 accessibility, and transaction speed are major drivers of customer satisfaction. At the same time, these benefits generate higher expectations regarding cybersecurity, technical reliability, and seamless digital performance. From the financial perspective, the study identifies a “profitability paradox”: although digital channels reduce long-term operational costs and create new revenue opportunities through data-driven cross-selling, significant technology investments and cyber-risk mitigation costs may weaken short-term margins. Banks with higher customer satisfaction tend to demonstrate stronger customer retention and improved return on assets. To remain financially robust in a digital economy, banks must move beyond automation and build digital trust through secure, reliable, and human-centered digital services. Future studies should examine the long-term financial effects of digital trust, compare traditional and digital-only banks, and explore customer behavior in increasingly AI-driven banking environments.

Internal Control Under Economic Uncertainty: A Forensic-Oriented Approach to Fraud Risk Management

Vira Shepeliuk — Tue, 31 Mar 2026 00:00:00 +0300

In the current context of growing economic uncertainty, digitalization of business processes, and increasing complexity of corporate relations, the role of internal control is becoming more significant as a tool for ensuring the transparency of enterprise activities and preventing financial and economic violations. Of particular relevance is the problem of the insufficient effectiveness of traditional internal control models, which are mainly focused on ex post identification of deviations and do not provide an adequate level of fraud prevention or mitigation of managerial vulnerabilities. The purpose of the study is to provide a theoretical substantiation for integrating a forensic approach into the enterprise internal control system in order to enhance its preventive and analytical capacity. The object of the study is the enterprise internal control system, while the subject is the theoretical and methodological foundations of its transformation under conditions of risk-oriented management. The methodological basis of the study includes the provisions of accounting theory, internal control, corporate governance, and forensic audit, as well as general scientific methods of analysis, generalization, systematization, and modeling. As a result of the study, the expediency of expanding the functional content of internal control through the inclusion of diagnostic and analytical components aimed at identifying corporate conflicts, information asymmetry, and fraud risks has been substantiated. It is proposed to integrate forensic tools into the internal control system, in particular the analysis of deviations and anomalies, the study of cause-and-effect relationships, IT-based analysis of digital data, and the formation of an evidence base. The practical value of the obtained results lies in the possibility of their use for improving internal control systems, enhancing the effectiveness of corporate governance, reducing fraud risks, and ensuring well-grounded managerial decision-making.

An Assessment of the Impact of Artificial Intelligence on the Recruitment Process

Tue, 31 Mar 2026 00:00:00 +0300

Artificial intelligence has become a major force transforming recruitment and talent acquisition by reshaping traditional human resource practices through automation, predictive analytics, and data-driven decision-making. This study aims to assess the impact of artificial intelligence on the recruitment process, with particular attention to task automation, candidate sourcing and matching, candidate experience, operational efficiency, fairness, legal compliance, and ethical accountability. The article is based on a qualitative-analytical synthesis of academic literature, industry reports, and practical organizational examples, supported by tables and figures that illustrate key trends and applications of AI in recruitment. The study shows that AI significantly improves recruitment efficiency by reducing time-to-hire, increasing scalability, and supporting more structured candidate evaluation. At the same time, the analysis identifies substantial risks related to algorithmic bias, opacity of decision-making, privacy concerns, and the weakening of meaningful human oversight. The findings also indicate that AI performs best when integrated into a balanced human-AI collaboration model rather than used as a substitute for recruiter judgment. The successful use of AI in recruitment depends on transparent governance, continuous auditing, legal compliance, and responsible implementation aligned with organizational goals. The paper that the successful application of AI in recruitment depends on transparent governance, continuous auditing, legal compliance, and a balanced model of human-AI collaboration. Future studies should examine sector-specific applications of AI recruitment, comparative organizational practices, and long-term effects on hiring quality, inclusion, and institutional trust.

Personnel Audit as a Risk-Based Corporate Governance Instrument: A Conceptual Framework for Human Capital Risk Integration

Oksana Motuzenko — Tue, 31 Mar 2026 00:00:00 +0300

This study addresses a significant gap in contemporary corporate governance research, specifically the insufficient integration of human capital risks into enterprise risk management (ERM) frameworks. Although Solvency II, ISO 31000:2018, and COSO ERM 2017 establish comprehensive architectures for risk governance, they do not adequately position personnel audit as a structured mechanism for identifying, assessing, and communicating human capital risks. The study aims to reconceptualize personnel audit as a risk-based corporate governance instrument and to develop a framework that integrates human capital risks into ERM systems. The paper adopts a conceptual research design grounded in agency theory, stakeholder theory, and systems thinking. Through conceptual synthesis, systems analysis, and comparative regulatory review, it develops the Personnel Audit Risk Integration (PARI) framework as a three-tier model operating at operational, tactical, and strategic levels of governance. The study proposes a structured taxonomy of human capital vulnerabilities across five interrelated domains: competency risk, behavioral integrity risk, succession risk, compliance risk, and organizational culture risk. It further establishes theoretical and regulatory linkages between personnel audit outputs, board-level risk oversight, and Solvency Capital Requirement calculations in regulated industries. The PARI framework demonstrates both conceptual originality and practical relevance for boards of directors, chief risk officers, and HR governance practitioners seeking to strengthen resilience and governance quality. Future studies should empirically validate the framework and explore methodologies for quantifying human capital risks across different industries and regulatory contexts.

Invisible Threat: Reverse Mobbing in the Workplace and Manager Victimization

Erhan Kılınç, Recep Yücel — Tue, 31 Mar 2026 00:00:00 +0300

Workplace bullying, characterized by repeated negative interactions and a significant power imbalance, seriously threatens employees' career development and mental health. While traditional mobbing is generally associated with superiors targeting subordinates, "reverse mobbing" or upward bullying represents a critical, yet insufficiently researched, phenomenon where subordinates systematically target their managers. This study aims to examine the nature, causes, consequences, and coping strategies of reverse mobbing within an organizational context from a holistic perspective. Reverse mobbing differs from traditional mobbing in terms of hierarchical direction, power sources, and methods of application. While traditional mobbing relies on formal authority, reverse mobbing utilizes indirect power tactics such as collective action, information concealment, social exclusion, and cyberbullying. This phenomenon has largely remained invisible in academic literature due to the traditional positioning of the manager figure as possessing power. Various factors contribute to the emergence of reverse mobbing, including high task dependency, organizational silence, ineffective leadership styles, and digitalization. Its consequences are devastating at both individual and organizational levels. Victimized managers experience decreased emotional well-being, increased burnout, and a stronger inclination to leave their jobs. At the organizational level, corporate mission is compromised, productivity declines, and labor peace is being disrupted. Effective intervention requires multi-dimensional approaches, including clear anti-mobbing policies, transparent complaint procedures, anonymous evaluation mechanisms such as 360-degree feedback systems, and personal identity strengthening strategies for targeted managers. Future research is recommended to delve deeper into the cultural differences of reverse mobbing and its manifestations in the digital environment.