The scope of the Engineering Economics journal covers research that examines innovations-driven transformations in business, public, and financial domains, contributing to the qualitative evolution of economies. The journal seeks to explore the antecedents, processes, and outcomes of these transformations to inform managerial and policy efforts aimed at fostering sustainable economic and social development. The journal represents research from disciplines such as economics, finance, business and management, and public management, as long as creative destruction is evident through structural changes, market dynamics, institutional shifts, or innovation-driven economic adjustments. It particularly welcomes studies that analyze the role of organizational, regulatory, and strategic adaptations that reshape industries, financial markets, and public governance. The journal publishes research at macro, meso, and micro levels of analysis, embracing a wide range of empirical methods. However, it does not accept studies based solely on mathematical proofs of economic relationships. The Journal also does not publish papers that address issues primarily relevant to engineering sciences or related technical fields. Conceptual papers are not published unless they take the form of reviews employing quantitative bibliometric analysis methods.
Herding or Anti-Herding? Understanding Investor Behavior in the Baltic States
This paper investigates market-wide herding behavior in the stock markets of Estonia, Latvia, and Lithuania, employing measures that assess the proximity of market returns to market consensus. Using a survivor-bias-free dataset of daily stock returns, we document significant anti-herding behavior among investors in Latvia and Lithuania throughout the sample period. Results for the Estonian market vary based on the herding measure chosen. Herding dynamics fluctuate over time, with the COVID-19 pandemic increasing the intensity of the effect in Estonia and Lithuania. Moreover, the deterioration of investor sentiment and stronger funding restrictions are found to amplify herding in these two markets. Estonia's market displays asymmetric behavior, with herding being more pronounced during negative market performance. Collectively, these findings are relevant to management practice since they suggest that it is difficult to extract the desired benefits of international diversification in the Baltic region, especially during market downturns.
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Effects of Female Entrepreneurship on Sustainable Development Goals: The Moderating Role of Gender Gap
Female Entrepreneurship (FE) is discussed and examined for its potential to support Sustainable Development Goals (SDGs). Recent economic literature has recognized that the contribution of FE to the achievement of the 2030 Agenda is a domain still scarcely explored. The aim of this study is to analyze if FE has a positive impact on Social, Economic and Environmental Development Goals. Our premise is that these impacts are negatively moderated by Gender Gap. To achieve this objective, the research conducts an empirical cross-country analysis with the Structural Equations Model (SEM) for 76 countries worldwide using different databases such as the SDG Index, FE Index, and Global Gender Gap Index, all of which are open access. Our findings show positive and significant effects of FE on social, economic and environmental development. Moreover, the Gender Gap plays a negative and significant moderating role in Environmental Development Goals. Although other studies have proven the relationship between female entrepreneurship and economic, social or environmental sustainability, the integration of all of them into a single model gives rigor to our results. Moreover, it is the first to include the moderating role of the gender gap in this relationship. Policymakers, business leaders and communities should work together to create an environment encouraging and supporting FE, and reducing the gender gap, for the positive consequences that this can have in the form of greater impact of FE on environmental sustainable development.
The Effect of External Environment Factors and Founders’ Characteristics on Digital Platform Start-up Performance. Dynamic Competition Perspectiveive
Digital platform start-ups rely on technological innovations to compete with other start-ups and incumbents. Competition by innovation, so-called dynamic competition, radically changes how start-ups leverage the external environment and founders’ characteristics to create superior performance. Although scholars unveiled the significant role of dynamic competition in entrepreneurial ecosystems, it is little known about how external environment factors and founders' characteristics interact under dynamic competition. This study focuses on the healthcare industry, which is a highly innovative sector where digital platform start-ups face unique challenges and opportunities. Using a sample of 235 digital platform start-ups, this study quantifies the impact of external environment factors and analyses the role of founders’ characteristics through managerial effectiveness. The findings reveal that economic freedom and governance quality may negatively affect performance, while founder characteristics enhance managerial effectiveness and significantly support start-up success. This study contributes to the literature by linking digital entrepreneurship with dynamic competition and offers insights into how start-ups can strategically navigate competitive environments to achieve superior performance.
Unpacking Competitive Performance in 5* Hotels: The Joint Effect of Dynamic Managerial Capabilities and Digital Transformation
Digital transformation in the hospitality sector was accelerated by the COVID-19 pandemic. Strategy scholars discussed dynamic managerial capabilities as capabilities needed to adapt to rapid change and navigate digital transformation to gain a competitive advantage in the hospitality sector. It suggests that by leveraging digital technologies, fostering a culture of innovation, and building agile business ecosystems, hospitality organizations can enhance their competitive position and ensure long-term sustainability in an increasingly digitalized marketplace. The research question of our study is how dynamic managerial capabilities and the adoption of digital technologies affect the competitive advantage of the hospitality sector. We address the research question by deploying a multiple case study research design and collecting data from 5* Hotels in Lithuania. The study finds that the synergy between dynamic managerial capabilities such as data-driven decision-making, connectivity to internal and external networks, also digitally driven operational efficiency, and sustainability-oriented attitudes significantly enhances the competitive performance of 5-star hotels by fostering innovation, strategic alignment, and superior guest value. We also provide insights for 5* hotel owners and managers.
Leveraging Financial Inclusion to Drive Public-Private Partnership Investments in Energy: Role of Financial Institutions in ASEAN Nations
Amid rising concerns over energy security and the growing demand for sustainable infrastructure, mobilizing public-private partnership (PPP) investments in the energy sector has become a critical policy objective for ASEAN nations. This study contributes to the literature by uncovering the pivotal role of financial inclusion (FIC) in enhancing such investments. By improving access to financial services, FIC fosters a more conducive environment for energy-related PPPs, particularly in emerging economies where capital mobilization is constrained. Using panel data from 1999 to 2023 for ASEAN countries, the analysis confirms that FIC exerts a positive and statistically significant impact on PPP investments in energy (PPI), even after controlling for government spending, FDI, economic growth, and aid. These findings position financial inclusion not only as a tool for economic empowerment but also as a strategic lever for infrastructure development. The study further strengthens its conclusions through robust empirical techniques. Overall, this research offers novel insights into how inclusive financial systems can unlock private investment in critical energy infrastructure, supporting broader sustainable development goals in the region.
SME Bankruptcy Prediction Using Convolutional Neural Networks
Failure to repay obligations to creditors, whether credit institutions or business partners, causes serious economic problems not only for the debtor but also for its stakeholders. Preventing this problem requires identifying the potential threat. This paper explores the potential use of Convolutional Neural Networks (CNN) in identifying businesses at risk of bankruptcy. It is based on a graphical representation of differences in company performance and selected macroeconomic indicators. In our research, we used the GoogLeNet neural network architecture. The approach used allowed to display the financial situation of a company so that the generated CNN could identify active companies and companies at risk of bankruptcy with high accuracy. The procedure was applied to data of companies operating in the construction industry in the Czech Republic. The accuracy of the model was evaluated using receiver operating characteristic (ROC) curve and area under the curve (AUC). The use of CNN has yielded high forecast accuracy, demonstrating the ability to efficiently process graphical displays of financial data and capture differences between healthy and risky companies. The indicators identified in the constructed model can be used as input variables in an early warning system for financial distress.
Does Greenwashing Hinder the Contribution of Fintech to Environmental Sustainability? Evidence from BRICS Countries
The greenwashing problem arises when companies provide misleading information about environmental sensitivity or exaggerate the sensitivity in question. At this point, it is claimed that financial technologies are seen as a solution to greenwashing. However, it is not known how environmentally friendly fintech companies are, in other words, whether fintech activities are a greenwashing problem. In this regard, this study investigates the effects of fintech on the novel load capacity factor to examine whether fintech creates a greenwashing problem for BRICS countries. In doing this, the period of 1992-2021 is analyzed with the quantile-on-quantile technique. According to empirical findings, financial technology activities harm environmental quality. Therefore, it is concluded that companies carrying out fintech activities for BRICS countries cause the greenwashing so the problem of greenwashing hinders fintech's potential contributions to the environment. Based on the findings, policy recommendations are made to audit companies conducting R&D studies on fintech and to penalize companies that make fake reports.
Do Financial Inclusion, Regulatory Quality and Government Effectiveness Matter for Green Development? Evidence from New EU Countries
Nowadays, the world is facing climate change and environmental problems due to the increasing use of energy resources and environmental emissions. In order to promote green development, financial inclusion is an important factor in the development process. Therefore, this paper examines the effects of financial inclusion, regulatory quality, government effectiveness and economic growth on green development in the new EU countries for the period from 2004 to 2021. In order to obtain empirical results, the pooled mean group and mean group estimator have been employed to check the short-run and long-run effects on green development. The results show a strong relationship between the variables and CO2 emissions in the long run. The findings support that enhancing the level of financial inclusion and regulatory quality by 1% increases carbon emissions by around 0.3% and 0.4% in the long run. However, government effectiveness and economic growth have a negative effect on CO2 emissions in the long run, while in the short run economic growth has a positive effect on CO2 emissions. Based on the empirical results, policymakers should improve financial inclusion and reinforce stringent regulations to enhance green development.
Does Enterprise Digitalization Promote the Green and Low-carbon Transformation and Upgrading? Evidence from A-share Listed Companies in China
As the world's top emitter of greenhouse gases, China's acceleration of emission mitigation is critical for global climate governance. Enterprises, as core economic actors, play a pivotal role in achieving sustainable development through green and low-carbon transformation (GLCT), a cornerstone of China's carbon peaking and neutrality objectives. This study examines whether enterprise digitalization—a key driver of digital-real economy integration—facilitates reductions in corporate greenhouse gas and pollutant emissions, thereby advancing GLCT. Utilizing 2008-2020 data from Chinese listed firms, we investigate the mechanisms underlying this relationship and heterogeneity across enterprises. Results reveal that digitalization significantly lowers emission intensity via pathways such as technological innovation, efficiency gains, operational environment optimization, and structural adjustments. Heterogeneity analysis highlights stronger effects in state-owned enterprises and competitive industries, with no regional regulatory disparities observed. This study demonstrates that digitalization significantly contributes to corporate green and low-carbon transition (GLCT) by reducing carbon and pollutant emission intensities. Empirical evidence reveals four critical mechanisms driving this transformation: technological innovation enhancement, operational efficiency optimization, managerial environment improvement, and production structure reorganization. Heterogeneity analysis highlights pronounced GLCT effects in state-owned enterprises and firms within hypercompetitive industries, while environmental regulation intensity shows negligible regional differentiation. The research systematically examines enterprise pathways for emission reduction in digital contexts, establishing a theoretical framework for achieving carbon neutrality goals. The findings inform policymakers in developing tailored digital strategies aligned with enterprise capabilities and sectoral attributes.
Specific Risk Modelling Approach Under Permacrisis Conditions: Some Empirical Evidence
The subject of the research is testing, analyzing, and considering the possibility of applying different risk modeling approaches to optimize the effects of investment activities. In order to have a realistic research basis, concrete data from certain markets were used to cover the studied phenomena as efficiently as possible. The aim is to obtain reliable, timely information about the accomplishment of the specific risk modeling approach under permacrisis conditions. Specific results and their significance for science and practice underscore the focus on distinct crisis periods. The findings confirm the practical relevance and advantages of applying EVT and CEVT-based Value-at-Risk models. This is achieved using different confidence levels (90% and 99%) and a 250-day moving window. The novelty of the research lies in the comparative assessment of investment risk in both developed and developing markets under permacrisis conditions, with the strengths and weaknesses of the tested models clearly identified. The study thereby contributes to creating an optimal market environment that supports informed investment decisions regarding expected returns. The limitations of the research reflect the distinct characteristics of developed and developing markets, with a particular challenge being the identification of systemic risk under the prevailing conditions.
Ability to Borrow Modeling Techniques for Small and Medium-Sized Enterprises
This study comprehensively evaluates the ability to borrow machine learning modeling techniques for SMEs, utilizing a sample of the Baltic States with many variables. The study aims to assess the applicability of access to credit modeling techniques for SMEs. This is the first study in which a large–scale assessment has been carried out in the Baltic States sample, covering five years of credit applications from SMEs to a depository institution. The results showed that Gradient Boosting produces the most accurate results. Gradient Boosting demonstrated better results than the benchmark Logistic Regression as well as other advanced machine learning models, including Random Forests and Multilayer Perceptron models. The method showed the highest accuracy of the overall receiver operating characteristic (ROC) curve and the associated area under the curve (AUC) (ROC–AUC) and Average Precision values, as well as other discriminatory threshold values, compared to alternative methods.
ESG Performance and Market Capitalization of Industries in the BRICS Region: The Mediating Role of Cost of Equity
The evaluation of environmental, social, and governance performance is a component of investment portfolio analysis that aids in the identification of potential risks and opportunities. The paper investigates the relationship between ESG performance and market capitalisation, with a keen interest in the mediating role of the cost of equity. The study focuses on industries in the BRICS region with a sample of 78 individual industries streamlined from 144 specific sectors across Brazil, Russia, India, China, and South Africa from 2019 to 2023. We use robust and flexible econometric methods that account for homoskedasticity, heteroskedasticity, multicollinearity, cross-sectional heterogeneity, and cross-sectional dependence. We find that the impact of ESG performance on market capitalization is positive and significant, irrespective of industry-specific and country-specific characteristics. Moreover, the relationship is linear but not non-linear, except for the mediating role of the cost of equity. We established an inverted U-shape curve relationship between the cost of equity and market capitalization.
Navigating Technological Change: The Role of Passive Social Policies in Central and Eastern European Labour Markets
Central and Eastern European (CEE) countries have limited research attention regarding the impact of technological change on the labour market. While existing studies offer many insights into developed countries, research on CEE countries, which have not yet achieved the level of prosperity seen in Western nations, does not take into consideration the following paradox – the existing labour force deficit and lack of technological innovation at the same time. This makes the region particularly valuable for the analysis in the context of technological change. Our study expands current theoretical understanding of the relationship between technological change and employment by examining the effects of passive labour market policies. The empirical analysis, using fixed-effects models, reveals that the overall effect of digitalization on employment is inconsistent, suggesting that the direct relationship between ICT capital and employment is not robust across specifications. This may result from the balancing of both positive and negative effects of technological change on the labour market. However, three models find a positive and statistically significant moderating effect of social protection benefits, while two showed insignificant estimates. This suggests that higher social protection can help mitigate digitalization’s negative employment effects by sustaining demand and supporting jobs in non-automated sectors.
Is There a Shift in the Intended Tax Compliance During the COVID-19 Outbreak? An Exploratory Study
This exploratory study investigates whether there was a shift in intended tax compliance during the COVID-19 pandemic in Romania, identifying factors influencing taxpayers' perceived moral obligation to pay taxes amid crises. Using data from an online survey with 404 respondents conducted at the end of 2021, a multinomial logistic regression (MLR) analysis, informed by the slippery slope framework, was employed to analyze the role of voluntary and enforced compliance, trust in government, power of tax authorities, and other socio-demographic factors in influencing taxpayer behavior. The results indicate that older taxpayers felt a heightened moral obligation to comply with tax regulations during the COVID-19 crisis compared to younger individuals. Gender did not significantly affect intended tax compliance in crisis periods. Voluntary compliance showed mixed outcomes; taxpayers who recognized taxes as beneficial to society demonstrated increased compliance during the pandemic, whereas those who usually paid willingly displayed decreased compliance. Crucially, higher perceptions of tax fairness and greater trust in governmental institutions substantially increased taxpayers' moral obligation to comply during the pandemic. Unexpectedly, reduced corruption perceptions did not correspond with improved tax compliance. This research contributes to existing literature by highlighting the complex interplay of demographic variables, voluntary compliance motivations, and institutional trust during economic crises. The findings emphasize the need for policymakers to foster transparent communication, equitable tax policies, and enhance institutional trust to maintain and potentially increase tax compliance during challenging economic conditions.
Generational Disparities and Their Impact on Sectoral Labour Demand
This study estimates the economic impacts of demographic changes driven by generational changes on the labour market and business environment in the Slovak Republic and selected European countries (Hungary, Poland, Czech Republic, Germany, France, Italy). It examines how demographic changes influence sectoral labour demand and the number of business entities. The main research questions are: RQ1: How do generational disparities affect sectoral demand? RQ2: How do generational disparities affect the number of entrepreneurs in the labour market? A comparative analysis of statistical data from 2013 to 2023 shows that sectors such as wholesale, retail, industry, and information and communication technology (ICT) face a shortage of skilled labour. To address RQ2, a regression analysis covering the long-term period from 1995 to 2020 is applied. The evaluation of RQ2 is supported by two hypotheses (H). H1: Changes in population development affect the number of enterprises at a statistically significant level. H2: Changes in population development affect the size of companies in a statistically significant variable. The results indicate that demographic trends associated with generational changes are reshaping the labour market structure, with the most significant impact observed in industries with high skill requirements and the segment of small and medium-sized enterprises. These businesses are flexible yet particularly vulnerable to shortages of skilled labour.
A Systematic Literature Review of Supply Chain Management Strategies and SME Performance: A Retrospective Analysis, Current Trends and Future Opportunities
This study conducts a systematic literature review on supply chain management (SCM) strategies and their influence on Small- and Medium-sized Enterprise (SME) performance in emerging economies. Covering 241 Scopus-indexed articles from 2001 to 2024, the analysis utilizes bibliometric and content analysis with tools such as RStudio, VOSviewer, and Microsoft Excel. Three main themes emerged from the analysis: (1) SCM strategies’ impact on SME performance, (2) integration and collaboration for enhanced performance, and (3) technology adoption for competitive advantage. Findings reveal notable trends, such as the growing interest in green SCM and supply chain resilience, with the UK and India leading in contributions. This research offers SMEs actionable insights for integrating supply chain strategies, enhancing collaborative planning, and refining supply chain management capabilities. Additionally, the study provides a roadmap for future research into sustainable practices, regulatory compliance, and technology driven SCM strategies to support SMEs in addressing complex market challenges.
An Integrating Framework through the Extension of the UTAUT2 Model for Online Banking: A Context from a Two-Staged Approach with PLS-SEM and Fuzzy Z-AHP
This study aims to develop a conceptual model for online banking by identifying key factors influencing its acceptance and use. In light of the complexities of online banking and the challenges posed by the COVID-19 pandemic, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was extended with three additional constructs: customer service, perceived security, and fear of COVID-19. The proposed framework combines the UTAUT2 model with a hybrid methodology that integrates PLS-SEM and Fuzzy Z-AHP. The study first tested the model’s hypotheses using PLS-SEM, and the results were used to construct a decision matrix for Fuzzy Z-AHP analysis. Data were collected from 346 online banking customers in Albania, revealing that habit is the most influential factor in online banking adoption. This research makes significant contributions across theoretical, managerial, and methodological domains. Theoretically, it enriches the UTAUT2 model by incorporating new constructs, enhancing its applicability. From a managerial perspective, the findings highlight critical factors shaping customer decisions, offering actionable insights for practitioners. Methodologically, the study introduces a sequential multi-method research approach by integrating PLS-SEM and Fuzzy Z-AHP.
Environmental Regulation and Corporate Social Responsibility: The Impact of Executive Authority and Equity Concentration Ratio on Technological Innovation
During the 75th session of the United Nations General Assembly, the Chinese government presented a proposal indicating its commitment to enhance its independent national contribution by implementing robust policies and measures, with the objective of achieving carbon neutrality by 2060. As the main energy consumption and pollutant emission enterprises, manufacturing enterprises should also take the initiative to grasp the opportunity of carbon neutral development and respond to the national call. In addition, technological progress as a potential solution to environmental pollution, how should enterprises promote technological innovation? These problems need further study. In view of this, this study selects 2011-2020 China a-share manufacturing listed enterprises, using fixed effects model, analyse the impact of environmental regulation, corporate social responsibility, CEO Power and equity concentration on corporate technological innovation. Research shows that environmental regulation, corporate social responsibility, CEO Power and equity concentration all have a significant positive impact on technological innovation, CEO Power and equity concentration play a positive moderating role in the impact of environmental regulation and corporate social responsibility on technological innovation.
Regional Disparities and the Degree of Income Convergence of the EU Regions
This study investigates income convergence across NUTS 2 regions in the EU, focusing on disparities between EU 14 and EU 13 Member States from 2004 to 2023. Employing econometric tools such as absolute and conditional β-convergence, σ-convergence, and disparity indices (Gini, DRC, ADRC), the study analyzes temporal and spatial income inequality. Structural controls such as education, investment, and migration were considered in conditional models. Visualizations include Gini trends, convergence maps, and GDP distributions. EU 13 regions exhibit robust convergence (2.7% annually), while EU 14 show divergence. Results reveal a paradox between convergence and disparity metrics, suggesting structural and geographic factors shape outcomes. Effective cohesion policy must be regionally tailored. The study provides policy recommendations, segmented by macro-regions, and highlights gaps in institutional capacity, innovation ecosystems, and policy resilience.
The Triple Interaction: Environmental Corporate Social Responsibility, Environmental Regulation, and Environmental Commitment in Shaping Environmental Performance in China
Growing demands for environmental corporate social responsibility (ECSR) from firms have been brought about by the rise of environmental sustainability and green business management. An increasing number of academics have focused on the impact of ECSR on firm environmental performance (FEP). However, scant attention has been given to environmental commitment (EC) as a mediator and environmental regulation (ER) as a moderator. To bridge this gap, this study checks the impact of ECSR on FEP through EC. Moreover, the relationship between ECSR and FEP was investigated in the presence of ER. The data has been collected from manufacturing companies that operate in China using convenience sampling to disburse questionnaires among respondents. We received 354 valid responses to 560 questionnaires, and 106 responses were incomplete, making an impressive response rate of 76.95 %. The findings of this study reveal that ECSR significantly enhances FEP, indicating that companies engaging in responsible environmental practices can improve their environmental outcomes. It also confirms that EC serves as a mediator in the relationship between ECSR and FEP, suggesting that a firm's dedication to environmental sustainability strengthens the positive impact of ECSR on FEP. Additionally, the study finds that ER negatively moderates the link between ECSR and FEP. This means that stricter environmental regulations might dampen the positive effects of ECSR on a FEP. This study also has limitations and future directions, persuading the researcher to develop new avenues.
Environmental Corporate Social Responsibility
“Stylized facts” in Price Dynamics: Do They Matter for ESG Financial Markets?
We investigate the presence of “stylized facts” within the ESG segment of the developed financial markets. The effects resulting from their presence are relevant given their impact on asset pricing, portfolio management, and even the efficiency of policy decisions. Moreover, during turbulent periods, the effects and presence of such elements can enable integration to act as a net transmitter of volatility. To explore this concept, we employed a broad and diversified toolset to detect their presence and influence. We tested five developed ESG indices, covering a time window from January 2014 to March 2023, by employing high-frequency data. The selection of indices captures and accounts for different geographical settings. The results suggest that “stylized facts” are present in the ESG segment of developed markets and volatility can spill over from market to market and fuel the contagion effect on a global scale, via the integration process and its effects.
Spillover Effects of Cryptocurrency Volatility on Green Finance
This study investigates the risk spillover between clean and dirty cryptocurrencies and their impact on green finance indexes (solar, wind, and nuclear energy) and regional economic indexes (Baltic Dry Index and CRB Index), with data processed using the diagonal BEKK model. The results identify several dirty cryptocurrencies such as: Ethereum Cash (ETC), Litecoin (LTC), and Bitcoin (BIT) as potential diversifiers and hedges with specific green energy and economic indexes. Our findings show that news from the cryptocurrency markets predominantly have a positive, significant effect on the covariance with green finance indices. The study also presents the covolatility spillover effect, showcasing the impact of a return shock in one market, such as the cryptocurrency market or the green finance market, on the co-volatility between markets, including regional economic indices like the Baltic Dry Index and CRB Index. The analysis reveals differential spillover patterns between clean and dirty cryptocurrencies and various green finance indices, highlighting the complexity of their interactions and the varying degrees of influence on regional economic indicators.
Transformational Leadership and Innovative Work Behavior: The Role of LMX Theory and Employee Voice Behavior
The aim of the study is to advance the understanding of direct and moderated effect between implemented transformational leadership style and employee innovative work behavior. The mediating role of Leader-member exchange theory and employee voice behavior is tested within the relationship of transformational leadership style and innovative work behavior. Respondents to a survey were 544 employees working in organizations in Serbia. Structural equation modeling was run by using Smart partial least square 3. to test the proposed model. Results suggest that transformational leadership style has significantly influenced employee innovative work behavior directly and through moderators as Leader-member exchange theory and employee voice behavior. This study was the first study in the Serbian business context that reveals a highly effective mediating mechanism like: leader-member exchange theory and voice behavior, which exists with transformational leadership style to increase innovative work behavior of employees. Furthermore, this study reveals additional results, like: transformational leadership style was significantly related to leader-member exchange theory and employees voice behavior, then leader-member exchange theory as well as employee voice behavior were significantly related to employees innovative working behavior.
Event Sentiment and Cross-Country Herding Spillover Effects Using Machine Learning
This research study investigates herding behaviour and its cross-country spillover effects in the UK, US, China, and Pakistan stock markets in the presence of event sentiment. We used three machine learning models for the empirical investigation: support vector regression, single-layer neural networks, and multi-layer neural networks. The daily data set of the listed stocks has been used. The results suggest a significant predictability of the Twitter sentiment of Brexit 2016 and COVID-19. Cross-country herding spillover is also evident from the UK to Pakistan and the US in the case of Brexit 2016. Similarly, there is a herding spillover effect from China to Pakistan and UK stock markets. The overall results of machine learning models are more significant than linear regression models. Furthermore, the event sentiment improves the performance of the machine learning models. The study provides a deep insight for individual and institutional investors to take care of unpredicted events while constructing their international portfolios in these stock markets.
Examining the Influence of Green HR Practices on Green Organizational Performance: Evidence from Pharmaceutical Sector of Asian Economies
The study investigates the relationship of green HR practices with green organizational performance. This paper further analyzes the impact of different dimensions: green performance management, green HR data and analytics, green recruitment and selection, green compensation and evaluation, green succession planning, green training and development, and green HR information systems on green HR practices. This paper examines the mediation of green HR purchasing and environment and eco-design and internal management between green HR practices and organizational performance. The researchers used structured and modified questionnaires and collected 465 responses from the pharmaceutical sector of Asian economies such as China, India, Pakistan, South Korea, and Japan. The researchers employed PLS-SEM modeling using Smart-PLS 4.0 software to analyze the data. The findings of this research demonstrate that green HR practices have a significant and affirmative relationship with green organizational performance. Results further indicate that green performance management, green HR data and analytics, green recruitment and selection, green compensation and evaluation, green succession planning, green training and development, and green HR information systems positively and significantly impact green HR practices. Finally, the findings show that green HR purchasing, environment, eco-design, and internal management significantly mediate between green HR practices and organizational performance. The study's findings have demonstrated a significant theoretical and managerial implication for researchers, academicians, industry practitioners, and policymakers. Moreover, the findings of this study also provide the roadmap to attain one of the most important goals of the sustainable development goals (SDGs) of the United Nations (UN): eco-friendly sustainability.
Endogenous Growth Factors and Economic Development: An In-depth Analysis of the Impact of Investments in R&D and Human Capital on Total Factor Productivity and Export Dynamics
Investments in research and development (R&D) and human capital affect economic growth by influencing total factor productivity (TFP) and competitiveness (exports). The determinants of this influence were analysed on a cointegrated panel of seven large countries and separately on five medium-sized or small countries. The results show that TFP and exports per unit of R&D or per unit of human capital mainly depend on the interconnection of these two factors, but also on capital per employee, the control of inflation, the foreign trade share in GDP, oil prices, digitalisation, electrification, the concentration of development activity related to the share of military expenditures in GDP, energy efficiency and ecological protection in the national economy. In medium-sized or small countries, the influence of regulation is greater, while the effect of development activities related to military expenditures is much smaller than in the large countries.
Can Internet Development Inhibit Carbon Emission Efficiency of Industrial Sector? A New Perspective from Multiple Environmental Regulations
To achieve industrial low-carbon transformation, the industrial sector is progressively adopting "smart manufacturing" and "digital transformation" strategies. This study examines whether these strategies enhance carbon emission efficiency of industrial sector (CEEI) and explores how the effects of Internet development on CEEI change under various environmental regulations. Using provincial data from China between 2011 and 2020, we investigate the influence of Internet development on CEEI under different types and intensities of environmental regulations. Our findings suggest that Internet development promotes CEEI but is influenced by various environmental regulations, including command-controlled environmental regulation (CER), market-incentive environmental regulation (MER), and voluntary public participation environmental regulation (VER). The impact of Internet development varies depending on the regulatory context, and regional differences also influence this relationship. Therefore, we recommend the implementation of diverse environmental policies that leverage Internet development to maximize CEEI improvements based on regional characteristics.
Command-controlled environmental regulation
Market-incentive environmental regulation
Voluntary public participation environmental regulation
Carbon emission efficiency of industrial sector
Deep Learning Model for Estimation Market Risk in Insurance Sector
The paper developed a model for market risk assessment based on deep learning in combination with non-parametric, parametric and semi-parametric VaR and ES models. We presented the ANN-GRU model more precisely. It is intended for insurance companies operating in emerging markets because the model was developed to cover all the characteristics of emerging markets. The research was conducted on the example of 8 optimal investment portfolios for insurance companies operating in the Balkan countries. The portfolios were calibrated at the daily level and calculated for the period from 1 January 2020 to 31 December 2023. The first 500 data were used to estimate the calibration of the VaR model, the other 250 to estimate the validity of the VaR model, and the last 250 to test the validity of the VaR/ES-GRU-DL market risk estimates in accordance with Directive II. Conditional and unconditional coverage tests were used to test the validity of VaR estimates, while Berkowitz's ES test was used to test the validity of ES estimates. Due to the limitations of these tests, the validity of the backtesting VaR estimate was performed using Dufour Monte Carlo simulations, while the validity of the backtesting ES estimate used the Bootstrap procedure. The backtesting results, as well as the results of the validity of the backtesting results, show that the model generates reliable estimates of VaR and ES in accordance with the Solvency II directive as well as produces better estimates compared to the popular and widely used VaR and ES models.
Moving Toward Sustainable Finance: Leveraging Environment, Social and Governance (ESG) Performance and Risk Management to Drive Corporate Financing Efficiency
The growing demand for companies to adopt environmentally sustainable and ethical practices has led to a greater focus on the organization's environmental, social, and governance accomsplishments. This study aims to investigate the relationship between environmental social and governance (ESG) and corporate financial risk (CFR) on corporate finance efficiency (CFE) in China, using a dataset of 400 Chinese firms registered on the Shanghai and Shenzhen A-share exchanges between 2013 and 2022, the analysis uses a data envelopment analysis (DEA) model with entity-fixed effects regression and a robustness test. The findings show a positive relationship between ESG and corporate finance efficiency, implying that promoting ESG practices can boost corporate financing efficiency. However, the study also found the negative effect of high financial risk on corporate financing efficiency. These findings have significant implications for businesses, investors, and policymakers. Businesses can enhance their long-term financial performance by giving ESG practices top priority and controlling financial risks. Policymakers can utilize these findings to encourage businesses to enhance their ESG practices and risk management to increase overall financing efficiency.
Beyond Reality: The Role of Innovation in Virtual Sport Events
With the arrival of Pandemic COVID, most sporting events were suspended, including popular foot races, known for their massification and occupation of public space. This global situation forced sporting events to innovate to become safer and to continue offering their activities despite the restrictions. From this evolution, virtual editions of many events emerged and promoted a new format that is still in force. The present study addresses the role of innovation from three perspectives: service newness in the market, incremental service innovation and technology-focused innovation, to subsequently explain the perceived quality, perceived value and satisfaction with the event. The sample was 560 participants of the Medellin Virtual Marathon. Results show that incremental service innovation and technology-focused innovativeness are important to explain perceived quality, while newness in the market is not. Subsequently, quality influences value and value influences satisfaction. Therefore, innovation must be considered in the management of virtual sporting events.