Economics, Finance and Management Review

An Application of HR Analytics Tools in Strategic Decision-Making and Workforce Optimization

Tue, 30 Jun 2026 00:00:00 +0300

In the digital business environment, organizations increasingly rely on workforce data to improve human resource management, strategic planning, and organizational performance. HR analytics has become an important managerial tool because it enables companies to move beyond intuition-based decision-making and use evidence-based insights for workforce planning, talent allocation, employee retention, performance monitoring, and productivity improvement. The objective of this article is to examine the application of HR analytics tools in strategic decision-making and workforce optimization and to evaluate how these tools contribute to data-driven human resource management in organizations. The study applies a quantitative research methodology based on primary and secondary data. Primary data were collected through a structured questionnaire using a five-point Likert scale. The sample consisted of 356 respondents selected from approximately 300,000 IT employees in Andhra Pradesh, India, using Cochran’s sample size formula at a 95% confidence level. Secondary data were obtained from research articles, case studies, journals, books, and credible online sources related to HR analytics, predictive analytics, workforce planning, and organizational performance. The data were analysed using descriptive statistics, frequency and percentage analysis, correlation analysis, and multiple linear regression. The findings show that HR analytics tools are actively used in organizations for descriptive analytics, predictive analytics, HR dashboards, compensation analytics, engagement analytics, and workforce planning. The results indicate that 73% of respondents either strongly agreed or agreed that HR analytics improves strategic decision-making. The study also shows that HR analytics supports workforce optimization by identifying skill gaps, improving employee retention, enhancing productivity, and enabling better resource allocation. The article concludes that HR analytics is becoming a strategic asset in modern human resource management. Organizations that use analytics tools can make more accurate, evidence-based decisions and improve workforce efficiency. Future studies should expand the sample size, include more sectors and regions, apply longitudinal research designs, and test standardized models for measuring the impact of HR analytics on strategic decision-making, retention, productivity, and organizational performance.

Digital Transformation’s Foundation: Structural and Managerial Issues and Obstacles of Hybrid Work

Erhan Kılınç, Recep Yücel — Tue, 30 Jun 2026 00:00:00 +0300

The COVID-19 pandemic accelerated the global transition from traditional office-based work to remote and hybrid work models. Although hybrid work offers flexibility, improved work-life balance, reduced commuting time, and broader access to talent, its sustainable implementation remains a complex organizational challenge. Hybrid work affects not only the location of work but also technological infrastructure, managerial practices, organizational culture, communication systems, and employee well-being. The objective of this study is to examine the structural, managerial, organizational, and individual barriers encountered in hybrid work systems and to develop strategic recommendations for their sustainable implementation in the context of digital transformation. The study applies a qualitative conceptual and analytical approach based on a structured literature review and thematic synthesis. The analysis is grounded in the Job Demands-Resources theory and Conservation of Resources theory, which explain the relationship between job demands, organizational resources, employee well-being, and performance in digitally mediated work environments. Selected statistical evidence is also integrated to support the relevance of hybrid and remote work. The study identifies four main groups of barriers. Structural barriers include technological infrastructure limitations, physical workspace transformation, and cybersecurity risks. Managerial barriers concern insufficient digital leadership competencies, outdated performance evaluation systems, weak feedback mechanisms, and the trust-control dilemma. Organizational barriers are related to culture erosion, communication breakdowns, knowledge management problems, information overload, and perceived inequality in career opportunities. Individual barriers include technostress, burnout, blurred work-life boundaries, social isolation, quiet quitting, and health-related risks. Sustainable hybrid work requires strategic alignment between technology, leadership, organizational culture, fairness, and employee well-being. Hybrid work should be understood as a comprehensive organizational transformation rather than a temporary or purely technical arrangement. Future studies should focus on longitudinal effects of hybrid work, intergenerational differences, sectoral comparisons, cross-cultural contexts, and the impact of artificial intelligence and immersive technologies on hybrid work dynamics.

The Impact of Influencer Marketing on Generation Z Purchase Decisions: Evidence from the Personal Care Products Market

Santosh Kumar Yadav, Harish Naidu, Mukesh Ramdas Malavde — Tue, 30 Jun 2026 00:00:00 +0300

The rapid growth of social media has transformed consumer communication and created new opportunities for influencer marketing, especially in the personal care products market. Generation Z, as a digitally native consumer group, actively uses platforms such as Instagram, YouTube, and TikTok to search for product information, follow influencers, and evaluate recommendations before making purchase decisions. In this context, personal care influencers have become important sources of reviews, product demonstrations, and brand-related information. The objective of this study is to examine the impact of influencer marketing on Generation Z purchase decisions in the personal care products market, with particular attention to influencer credibility, brand popularity, credibility of information, brand loyalty, and influencer expertise. The study applies a survey research design based on primary data collected from 252 Generation Z respondents, mainly from Pune, Maharashtra, India. A structured questionnaire was distributed through social media platforms, including LinkedIn, Facebook, and WhatsApp groups. The study used non-probability convenience sampling. The collected data were analysed using percentage statistics, hypothesis testing, ANOVA, and Spearman rank correlation analysis. The findings show that credibility of information and influencer expertise significantly affect Generation Z purchase decisions. The hypothesis testing results indicate that credibility of information has a significant effect on purchase decision, with p = 0.021, while influencer expertise also has a significant effect, with p = 0.005. In contrast, influencer credibility and brand popularity were rejected as direct significant predictors in the hypothesis testing. Correlation analysis revealed a moderate positive relationship between brand popularity and purchase decision, and between credibility of information and purchase decision. The study concludes that Generation Z consumers are influenced more by reliable information and influencer expertise than by brand popularity alone. Future studies should use larger and more diverse samples, compare different product categories, include platform-specific analysis, and examine mediating variables such as trust, engagement, authenticity, and visual content quality.

The Impact of Green Supply Chain Management on Sustainability Performance: Evidence from Vietnam

Tran Anh Son — Tue, 30 Jun 2026 00:00:00 +0300

Green supply chain management has become an important managerial approach for manufacturing firms seeking to improve sustainability performance under increasing environmental pressure, stakeholder expectations, regulatory requirements, and global market standards. In emerging economies such as Vietnam, manufacturing firms are encouraged to integrate environmental considerations into purchasing, production, distribution, product design, customer cooperation, and information systems while maintaining competitiveness in global value chains. The objective of this study is to examine the effect of green supply chain management practices on sustainability performance in Vietnamese manufacturing firms, with sustainability performance evaluated through environmental, economic, operational, and social dimensions. The study applies a quantitative research design based on data collected from 123 manufacturing firms operating in Vietnam. Green supply chain management is measured through ten practices: internal environmental management, green information systems, eco-design, environmental education, customer cooperation, green distribution, investment recovery, green purchasing, green manufacturing, and green marketing. The hypotheses are tested using regression-based analysis in Stata. Descriptive statistics are also used to assess the overall distribution of the variables. The empirical results show that eco-design, environmental education, customer cooperation, green distribution, and investment recovery have positive and significant effects on sustainability performance at the 5% level. Green information systems also have a positive effect at the 10% significance level. In contrast, internal environmental management, green purchasing, green manufacturing, and green marketing do not show statistically significant effects. Investment recovery has the strongest coefficient among the significant variables. The study concludes that sustainability performance in Vietnamese manufacturing firms is mostly enhanced by practical and externally oriented green activities rather than by formal internal policies, green procurement, green manufacturing, or green communication alone. Future studies should expand the sample size, include other industries and countries, and examine mediating variables such as green innovation, environmental capabilities, and supply chain resilience.

The Impact and Process of the ESG Peer Effect on Heavy-Polluting Companies' Green Innovation. Case of companies in the United Kingdom

Adel Necib, Mohamed Haddad Ben Mabrouk, Anis Jarboui — Tue, 30 Jun 2026 00:00:00 +0300

Environmental innovation has become increasingly important for heavy-polluting companies because environmental pollution, climate change, and carbon reduction targets require firms to strengthen ecological responsibility and improve green technology innovation. ESG disclosure provides non-financial information to the market and may influence corporate green innovation not only directly, but also through the behaviour of peer companies operating in the same industry. This study examines the impact of the ESG peer effect on green innovation in heavy-polluting companies in the United Kingdom and investigates the mechanisms through which peer ESG disclosure promotes ecological innovation. The study uses data from heavy-polluting companies observed during 2018-2024. The ESG peer effect is measured as the average ESG score of other firms in the same industry, excluding the target company. Green innovation is measured by the natural logarithm of green patent applications plus one. The empirical analysis applies fixed-effects regression models, robustness tests, mediation mechanism tests, and heterogeneity analysis. Financing constraints, information asymmetry, and green awareness are examined as mediating mechanisms. The findings show that the ESG peer effect has a positive and statistically significant influence on green innovation. The baseline regression results indicate that ESG peer disclosure promotes ecological innovation among target companies, and the results remain valid after robustness checks, including Tobit regression, shorter sample period, lagged explanatory variables, and propensity score matching. The mediation analysis shows that the ESG peer effect promotes green innovation by reducing financing constraints, lowering information asymmetry, and strengthening corporate green awareness. Heterogeneity analysis reveals stronger effects among state-owned enterprises, large firms, and firms located in central and eastern regions. ESG peer disclosure encourages heavy-polluting companies to improve green innovation through competitive pressure, learning effects, and information signalling. Future studies should expand the sample to other industries and countries and examine additional mechanisms linking ESG performance, innovation strategy, and environmental transformation.

Digital Transformation of Corporate Governance and Its Impact on Enterprise Investment Attractiveness

Zinaida Zhyvko, Liliia Kukharska, Oksana Ostapenko — Tue, 30 Jun 2026 00:00:00 +0300

Digital transformation has become an important factor in the modernization of corporate governance and investment management. In the digital economy, enterprises increasingly use management information systems, artificial intelligence, blockchain, cloud services, big data analytics, ERP, CRM, and BPM platforms to improve transparency, corporate control, reporting quality, managerial decision-making, and stakeholder communication. These changes directly influence investment attractiveness because investors require timely, reliable, and structured information for assessing corporate performance, risks, and long-term value creation. The objective of this article is to identify the key features of the digital transformation of corporate governance and to assess its impact on enterprise investment attractiveness, investment activity, and managerial decision-making effectiveness. The study applies a conceptual and analytical methodology based on the systematization of literature on digital transformation, corporate governance, agency theory, investor protection, data-driven decision-making, and investment efficiency. The article uses SWOT analysis, conceptual modelling, and an author-developed Digital Corporate Governance Investment Attractiveness Index. For the demonstration of the proposed index, the study applies proxy-based scoring to selected Ukrainian enterprises using publicly available annual reports, sustainability disclosures, investor relations materials, corporate governance information, and governance transformation projects. The results show that digital transformation enhances corporate transparency, reduces information asymmetry, improves managerial decision-making, strengthens corporate monitoring, reduces agency costs, and increases investor confidence. The SWOT analysis demonstrates that the benefits of digital corporate governance include automation, real-time data analysis, improved investor communication, and better access to financial markets, while the main risks are cybersecurity threats, high implementation costs, dependence on IT infrastructure, and uneven digital maturity. The model calculation for Ukrainian enterprises shows that MHP, Kernel, Ukrgasbank, Naftogaz, and Ukrnafta differ in their levels of digital governance investment attractiveness due to differences in transparency, reporting, risk control, stakeholder communication, and digital risk exposure. The article concludes that digital transformation of corporate governance is a strategic factor in increasing enterprise investment attractiveness. Its positive effect depends not only on technology adoption but also on digital competencies, cybersecurity, regulatory compliance, data quality, and integration with corporate strategy. Future research should empirically test the proposed model using company-level data, compare industries and countries, assess the role of AI and blockchain in corporate governance, and evaluate the financial impact of digital governance maturity on investment flows, market value, and cost of capital.

Econometric Analysis of Geopolitical Risk Hedging Strategies in Supply Chains

Savanam Chandra Sekhar — Tue, 30 Jun 2026 00:00:00 +0300

Geopolitical uncertainty has emerged as a critical challenge for globally integrated supply chains due to trade wars, sanctions, regional conflicts, export restrictions, and political instability. These disruptions increasingly affect procurement efficiency, logistics continuity, operational flexibility, and organizational profitability across industries. This study examined the impact of geopolitical risk exposure on supply chain performance and evaluated the effectiveness of managerial hedging strategies in strengthening organizational resilience under volatile international conditions. The research adopted a quantitative and explanatory design grounded in managerial economics and econometric modeling. Data were collected from 328 supply chain executives and logistics professionals representing manufacturing, logistics, electronics, retail, pharmaceuticals, and energy sectors. The study employed correlation analysis, multiple regression, Structural Equation Modeling, mediation analysis, and moderation analysis using SPSS, STATA, and SmartPLS/AMOS. The findings revealed that geopolitical risk exposure exerted a significant negative effect on supply chain performance (β = −0.426, p < 0.001), while hedging strategies positively improved resilience and operational continuity (β = 0.351, p < 0.001). Supply chain resilience also demonstrated a strong positive influence on organizational performance (β = 0.417, p < 0.001), whereas digital risk monitoring significantly enhanced responsiveness and adaptability (β = 0.228, p < 0.001). The regression model explained 69.2% of the variance in supply chain performance (R² = 0.692). Furthermore, resilience partially mediated the relationship between hedging strategies and organizational performance through an indirect effect of 0.174. The results further indicated that technologically advanced and larger firms derived greater benefits from resilience investments and hedging mechanisms. Electronics and semiconductor industries reported the highest geopolitical risk exposure (Mean = 4.41), whereas pharmaceutical firms demonstrated the highest resilience capability (Mean = 4.12). As a result, the study highlights the practical importance of supplier diversification, regionalization, inventory buffering, reshoring, and digital monitoring systems in improving resilience, competitiveness, and long-term sustainability under increasing geopolitical fragmentation.

National Economic Challenges under International Conflicts, Digitalization, and Climate Shifts: A Triangular Resilience Balance-Sheet Model

Henriett Karolyi, Liudmyla Akimova, Oleksand Akimov — Tue, 30 Jun 2026 00:00:00 +0300

National economies increasingly face complex and overlapping economic challenges caused by international conflicts, accelerated digitalization, and climate shifts. International conflicts disrupt trade, energy security, investment flows, fiscal priorities, migration processes, and financial stability. Digitalization creates opportunities for productivity growth, innovation, public-sector modernization, and economic competitiveness, but also deepens structural inequalities between digitally advanced and digitally excluded states. Climate shifts intensify economic vulnerability through extreme weather events, infrastructure damage, food and water insecurity, displacement, productivity losses, and rising adaptation costs.The objective of this article is to analyse the economic challenges faced by individual states under the simultaneous influence of international conflicts, digitalization, and climate change and to propose a model for assessing national economic stress and resilience. The study applies a conceptual and analytical methodology based on academic literature and verified statistical evidence from the International Monetary Fund, World Bank, International Telecommunication Union, World Meteorological Organization, INFORM Risk Index, ND-GAIN, and Germanwatch Climate Risk Index. The article develops the Triangular National Economic Resilience Balance-Sheet Model, which compares three structural liabilities of a state: conflict liability, digital transition gap, and climate exposure, with its resilience buffer. The results show that national economic vulnerability is determined not only by the strength of individual shocks but also by their combination. The model calculations demonstrate that Germany has a resilience surplus, Ukraine faces high vulnerability due to conflict liability, India experiences elevated pressure because of the interaction between digital gap and climate exposure, Egypt faces elevated combined pressure, and Brazil remains manageable but close to elevated pressure. The article concludes that national economic security increasingly depends on integrated resilience planning. States should not treat conflicts, digitalization, and climate change as separate policy fields.Future research should test the proposed model using full country-level datasets, expand the sample of countries, introduce sectoral indicators, and conduct sensitivity analysis of resilience-buffer components.

AI-Driven Equity Valuation of Selected NIFTY 50 Companies Using Fundamental, Technical, and Machine Learning Techniques

Tue, 30 Jun 2026 00:00:00 +0300

Equity valuation remains a central task in financial markets because it allows investors to determine whether a stock is fairly priced and to identify attractive investment opportunities. Traditional valuation approaches, including financial statement analysis, accounting ratios, discounted cash flow valuation, and technical indicators, remain important, but they are increasingly insufficient in data-intensive and volatile market environments. Artificial intelligence and machine learning provide new opportunities for improving forecasting accuracy, identifying nonlinear market patterns, and supporting investment decision-making. The objective of this article is to develop and apply an AI-driven equity valuation framework for selected NIFTY 50 companies by integrating fundamental analysis, technical analysis, valuation models, risk indicators, and machine learning techniques. The study applies a multidimensional analytical and comparative methodology. It covers ten companies listed in the NIFTY 50 index, including TCS, Infosys, HDFC Bank, SBI, Reliance, ITC, HUL, Tata Motors, Maruti Suzuki, and Sun Pharma, over the period 2020-2025. The analysis includes fundamental indicators such as revenue growth, earnings per share, return on equity, return on assets, debt-equity ratio, and profit margin. It also uses technical indicators, discounted cash flow valuation, relative valuation ratios, risk and volatility indicators, and machine learning models, including linear regression, random forest, neural networks, and time-series forecasting. The results show that TCS, Infosys, ITC, and HUL demonstrate strong financial efficiency, while ITC, Tata Motors, HDFC Bank, and SBI show meaningful valuation upside based on intrinsic value estimates. Risk analysis identifies Tata Motors and SBI as higher-volatility stocks, while ITC, HUL, TCS, and Infosys demonstrate comparatively more stable profiles. Among the machine learning models, the neural network delivers the strongest predictive performance, with the highest accuracy and the lowest error values. The study concludes that artificial intelligence strengthens equity valuation when combined with traditional financial analysis rather than used as a standalone tool. The integrated framework improves the quality of stock assessment and supports better investment decisions in the Indian stock market.

Fiscal Mechanisms for Adapting Veteran Business to Environmental and Energy Challenges

Serhii Petrukha, Dmytro Konovalenko, Nina Petrukha — Tue, 30 Jun 2026 00:00:00 +0300

Under the conditions of the full-scale armed aggression of the Russian Federation against Ukraine, the growth in the number of security and defence forces and the increase in the number of war veterans have made the issue of their support, in particular through reintegration institutions in the form of veteran business, especially acute. At the same time, the destruction of critical infrastructure, primarily energy infrastructure, as well as the climate commitments of our state, form a qualitatively new context for the entrepreneurial activity of veterans. The article examines the problem of forming and implementing fiscal mechanisms aimed at supporting the adaptation of veteran business to new environmental and energy challenges. The purpose of the article is to substantiate the authors’ concept of a fiscal incentive system that integrates support for veteran entrepreneurship with the instruments of the green economy. Based on a comparative analysis of international experience from the United States, Germany, Poland, Israel, and Lithuania, effective models of fiscal incentives are identified and the possibility of adapting them to the conditions of Ukraine is substantiated. The essence of the concept of “entrepreneurial resilience of veterans” in the environmental and energy dimension is revealed. It is established that Ukraine currently lacks systemic integration of fiscal instruments supporting veteran business and instruments of green transformation. The authors develop a conceptual model of a fiscal mechanism for adapting veteran business to environmental and energy challenges and propose a set of specific instruments, namely the “Veteran Energy Credit” (VEC, 30% of investments in renewable energy sources), accelerated depreciation of green equipment (three years), a unified social contribution bonus for veteran green producers, preferential VAT (7%) on renewable energy products, a local Green Veteran Fund, and a carbon credit. The results of the study have practical significance for public authorities, forming a scientifically substantiated basis for updating fiscal and energy policy in Ukraine’s post-war reconstruction.

Impact of Basel III Capital Adequacy Norms on the Profitability of the Indian Banking System

Tue, 30 Jun 2026 00:00:00 +0300

The Basel III framework was introduced after the global financial crisis of 2007-2009 to strengthen banking regulation, improve capital adequacy, enhance liquidity management, and reduce systemic financial risk. In India, the Reserve Bank of India implemented Basel III norms gradually from 2013, requiring banks to maintain stronger capital buffers. However, higher capital requirements may influence profitability because banks must balance financial stability with lending capacity and earnings performance. The objective of this study is to analyse the impact of Basel III Capital Adequacy Norms on the profitability of the Indian banking system during the period 2015-2024, with particular attention to the relationship between Capital Adequacy Ratio, Return on Assets, Return on Equity, and Non-Performing Assets. The study applies a quantitative descriptive-analytical research design based on secondary panel data. The sample includes five high-capital scheduled commercial banks: State Bank of India, Punjab National Bank, HDFC Bank, ICICI Bank, and Axis Bank. Data were collected from bank annual reports, the Reserve Bank of India Database on Indian Economy, RBI reports, and stock exchange disclosures. The study uses Pearson correlation analysis, simple and multiple linear regression analysis, independent samples t-test, and one-way ANOVA. The findings show that the average Capital Adequacy Ratio of the selected banks was above the RBI minimum requirement, indicating strong regulatory compliance. Private sector banks maintained higher CAR, ROA, and ROE, while public sector banks showed higher NPA levels. NPA emerged as a major negative factor affecting profitability. Basel III norms strengthened the capital position of Indian banks, but their profitability impact was asymmetric, favouring banks with stronger governance, lower credit risk, and better operational efficiency. Future studies should include more banks, longer time periods, macroeconomic variables, and advanced panel econometric models to assess the long-term effects of Basel III implementation on financial stability and profitability.