Journal of Business Economics and Management
The Journal of Business Economics and Management publishes original research papers that provide insights into business and strategic management issues. More information ...
Copyright © 2021 The Author(s). Published by Vilnius Gediminas Technical University. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
East-West risk connectedness in the European banking sector
This study examines the risk spillover dynamics between banks in Central and Eastern Europe (CEE) and Western Europe (WE) across 30 banking groups from 2014 to 2023, segmented into three distinct periods: pre-COVID-19, during COVID-19, and the Russo-Ukrainian conflict. The key contribution of the paper lies in combining a cross-regional perspective with a longer time horizon, covering major shocks. Utilizing the Diebold-Yilmaz interconnectedness index model, we analyze volatilities derived from daily stock prices to identify key players in the transmission and absorption of financial shocks. Our findings, supported by existing literature, reveal a strong interconnectedness between the two parts of Europe. WE banks are more likely to be shock transmitters, while CEE banks play the role of shock receivers. However, during the Russo-Ukrainian war, CEE banks appeared more among the net transmitting banks. Although one of the main features of the CEE financial system is its dependence on WE, a bank nationalism has also emerged in some countries. This may nuance the dynamics of CEE financial stability: reducing the magnitude of WE shock, but in the case of CEE-specific shocks, the possibility of risk transfer (dispersion) is also weakened.
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Firm credit rating changes, capital structure, and the asymmetric moderating role of debt capacity and financial constraints
This study analyzes how debt capacity and financial constraints impact credit rating changes. Using a comprehensive sample of European companies, we analyze rating upgrades and downgrades separately to allow us to uncover whether the effects differ. Our results show that only one of the four commonly used proxies for debt capacity can explain credit rating changes. Specifically, we find that debt capacity can influence both rating upgrades and downgrades, but financial constraints or profitability can only impact rating downgrades. Our results are robust to various model specifications. The Monte Carlo simulation results reveal that uncertainty related to factors causing rating upgrades increases sharply when debt exceeds 30% of total assets. Similarly, when debt exceeds 50% of total assets, uncertainty related to rating downgrades surges.
Barriers to blockchain implementation in supply chain finance – based on perspectives of grey transaction behaviour
The purpose of this study is to identify grey transaction behaviours that function as barriers to blockchain implementation in supply chain finance, explore which obstructions arise from these grey transaction behaviours and subsequently hinder blockchain implementation, and further measure the influence levels of the corresponding implementation barriers. The Delphi method and DANP are the main analysis methods used in this study. According to the analysis, three grey transaction behaviours that function as implementation barriers are identified, namely, kickbacks, internal and external accounting, and informal transaction relationships with banks. In addition, seven obstructions arise from these three barriers, and these obstructions can be adopted to explain why the three barriers hinder blockchain implementation. Finally, although internal and external accounting represents the main barrier, informal transaction relationships with banks may function as a critical underlying barrier that enhances the other two barriers. This study contributes in that it fills the gap of existing studies related to the intersection of supply chain finance and blockchain and provides a new perspective enabling practitioners to rethink how blockchain can be successfully implemented in the context of supply chain finance.
What causes the return and volatility spillover in Chinese green finance markets? A time-frequency perspective
This paper analyzes both return and volatility spillovers between green bonds, green stocks, clean energy, and carbon markets from April 28, 2014, to May 31, 2024, using the time-frequency connectedness methodology. Further, determinants of these spillovers are examined from perspectives of economic fundamentals (macroeconomics, inflation, and rate), market contagion (market volatility and investor sentiment), and uncertainties (EPU, CPU, GPR, and the COVID-19 pandemic) with the linear regression and quantile regression methods. Our investigation demonstrates that return and volatility spillovers exhibit significant crisis jumps during periods of financial turmoil. During most periods, both return and volatility spillovers occur predominantly in the short run. Second, green bonds and carbon markets show safe-haven characteristics as net risk recipients. Furthermore, economic fundamentals, market contagion, and uncertainty factors exhibit obvious impacts on both green finance market spillovers, albeit in differing magnitudes and directions. Notably, both return and volatility spillovers in the short and long run are determined by economic fundamentals, market contagion, and uncertainty variables. What’s more, these factors exhibit stronger interpretations of extreme return spillovers. These findings pose significant ramifications for risk mitigation and portfolio diversification for investors and authorities throughout Chinese green finance markets.
Are renewable energy stocks, investor sentiment, and the cryptocurrency market-related?
This paper applies wavelet quantile correlation to research on the relationship among renewable energy stocks, investor sentiment, and the cryptocurrency market. The empirical results indicated that under extremely negative conditions, in both the short and medium run, renewable energy stocks and cryptocurrencies are negatively correlated, implying that during such periods, renewable energy stocks can be used as a safe haven for cryptocurrencies. The opposite happens when the market is average or booming. This indicates that investors tend to invest simultaneously in these two promising asset classes when the market performs well. Under varied market conditions, FGI correlates positively with cryptocurrency, demonstrating sentiment influences price patterns. Moreover, the correlation between FGI and renewable energy stocks further validates the relationship between cryptocurrencies and renewable energy stocks. These findings can be used to improve the prediction of market trends by investors using sentiment indices and to devise more effective portfolio diversification strategies that minimize risk amid an evolving market.
Business ambience for implementing Just-in-sequence strategy – the automotive industry in Serbia: case study
Persistent issues in the automotive industry – such as delivery delays and frequent stock-outs – indicate that the vision of perfectly synchronized flows of raw materials, parts, and components within complex industrial production and logistics systems remains a significant challenge. To mitigate demand variability and uncertainty, companies often maintain high levels of safety stock, which significantly increases costs and erodes competitiveness. At the same time, such supply chains are characterized by limited responsiveness, resulting in unfulfilled targets related to reduced lead times and reliable customer deliveries. As a response, supply chains in the automotive sector are increasingly opting for the implementation of Just-in-Sequence (JIS) strategies to ensure adaptation to diverse product requirements and cost savings, as well as enhance both responsiveness and efficiency. Within this context, the objective of this research is to identify key elements necessary for the successful implementation of the JIS strategy in an automotive company. The research findings reveal notable differences in the perceptions of employees from Production, Logistics, and Sales sectors regarding the importance of the analysed variables and the potential for implementing a JIS strategy.
The impact of Search Volume Index on FDI outflow: the moderating role of uncertainty avoidance
This study examines the relationship between the Search Volume Index (SVI) and FDI outflow levels and tests whether the level of national culture, particularly whether the Uncertainty Avoidance Index (UAI), moderates such a relationship. The authors document that SVI is positively associated with FDI outflow in the sample of 69 countries. When we distinguish between low and high-uncertainty avoidance countries, we find that this positive association is significant at the current value of SVI for countries with low uncertainty avoidance. However, the relationship becomes stronger for countries with high uncertainty avoidance at the one-year time lag of SVI. Moreover, the results remain intact after various robustness checks. These results imply that the level of national culture may cause individuals to hesitate to invest through internet search queries. Our empirical findings should be particularly informative for investors from countries whose governments exhibit high levels of uncertainty avoidance, as they spend more time on investment planning than investors from countries whose governments exhibit low uncertainty avoidance.
Multi-criteria analysis of the Baltic banks from client attraction and profit generation perspectives
The economic and regulatory environment banks operate in poses challenges in regard to different facets of sustainability and requires proper managerial and technological innovations. Bank performance can be analysed from various viewpoints. Therefore, it is important to develop comprehensive frameworks for assessment of banking performance. The paper develops a twostage approach for measuring banking performance from the client attraction and profit generation perspectives. The multi-criteria framework involving three multi-criteria decision-making methods is developed to ensure robustness of the results. The empirical research deals with the 17 commercial banks operating in the three Baltic States. This case is interesting as it covers a low-interest-rate environment. While Lithuanian banks excelled in the client attraction perspective, the results for 2017–2021 suggest that they should focus on the improvement of performance in this regard and profit generation if compared to banks operating in Latvia and Estonia.
Research on the valuation of internet enterprise data assets based on value chain theory
As data assets grow strategically important yet remain difficult to value in internet enterprises, this study analyzes the factors influencing their valuation. Using value chain theory and a system dynamics model, it uncovers the mechanisms of value formation. Results show that data asset value is realized dynamically across stages – collection, analysis, mining, and application – shaped by internal attributes and external factors. The process follows a diminishing marginal return pattern and exhibits significant value lag. Therefore, data asset assessment should account for the full life-cycle, intrinsic properties, and technological conditions.
Unveiling leadership dynamics and tournament incentives: insights from the environmental misconduct of Chinese listed companies
This study investigates whether the tournament compensation motivate executives to adopt environmentally responsible practices and reduce environmental violations. Focusing on CEO characteristics, we also examine whether politically connected CEOs and CEO gender enhance the effectiveness of these incentives in mitigating corporate environmental violations. Using a fixed-effects model, two stage least square (2-SLS) and the Generalized Method of Moments (GMM) on data from Chinese companies, spanning from 2010 to 2023, this study finds that executive tournament incentives play a significant role in reducing environmental violations. Our results further reveal that political connections and female CEOs strengthen the negative relationship between tournament incentives and environmental violations, demonstrating the critical influence of leadership diversity and institutional ties in driving corporate sustainability. Additionally, our findings provide robust support for tournament theory, highlighting the pivotal role of CEOs in shaping corporate environmental behaviour. This study provides pertinent insights for regulators and policymakers, assisting them to develop tailored strategies, regulations and legislative frameworks to reduce environmental violations and improve sustainable development.
Analysis of the relationship between ESG and labor costs: the moderating effect of the legal tradition
This study examines the relationship between Environmental, Social, and Governance (ESG) scores and labor costs per employee (LCE) in firms operating under different legal traditions, specifically comparing civil law (France) and common law (United Kingdom) countries. Utilizing data from the Orbis database for the period 2020–2022, the study employs random-effects estimations with robust standard errors. Results indicate that while the relationship between ESG and LCE is not significant in common law, it is positively significant in civil law. Results are robust to alternative ESG measures, such as the social pillar score (SOCP) estimations methods and samples. The findings suggest that the legal tradition moderates the ESG-LCE relationship, with stronger positive effects observed in civil law countries. The study highlights the importance of legal frameworks in shaping the economic impacts of ESG initiatives on labor costs. While ESG concerns may result in higher LCE, and thus increased employee compensation, implementing appropriate regulations to protect workers’ rights can foster a more effective ESG-LCE relationship than relying solely on market-based regulatory systems driven by stakeholder influence.
From farm to fork: determinants of supplier-retailer relation in organic agri-food supply chain on EU Eastern – Western approach
The European Union’s Farm to Fork Strategy, embedded within the Green Deal, aims to create equitable and sustainable food systems, fostering environmentally responsible practices and addressing challenges comprehensively throughout the agri-food supply chain. Organic farming plays an important role in this transition, particularly in the context of the circular economy. This study explores the key determinants influencing supplier-retailer relationships in the organic agri-food supply chain, focusing on the interaction between Romanian suppliers and retailers from Germany, Austria, and Switzerland. Using a mixed-methods approach that combines quantitative and qualitative analysis, the research identifies price, quality, and trust as essential factors shaping demand. Given Romania’s growing organic agriculture sector and the increasing consumption of organic products in German-speaking markets, this study highlights both challenges and opportunities for enhancing trade relations. As one of the first investigations into the East-West dynamics of the EU organic agri-food supply chain, the findings provide valuable insights for strengthening sustainable agriculture and market integration in Romania. It is also relevant for other Eastern European countries emphasizing the importance of a strong green agri-food sector throughout the European Union, as well as coordinated efforts along the supply chain.
Urban distances, individual resources, and migrant entrepreneurship: a configurational analysis in China
Given its significance for economic and social sustainability, migrant entrepreneurship (ME) has attracted increasing attention from scholars and policymakers. However, existing research provides limited insights into how various antecedents jointly affect ME. To address this gap, this study develops a theoretical model that integrates mixed embeddedness theory and entrepreneurial opportunity construction theory to explain the processes of opportunity construction and exploitation in ME. Using 130 cross-city migration cases in China – each comprising individuals from the same origin and destination cities – we examine how urban distances and individual resources jointly shape ME. The analysis identifies three pathways to high ME: the opportunity-resource endowed path, the resource bricolage path, and the opportunity-resource matching path. Although no single factor is necessary for high ME, greater geographic distance consistently promotes it. This study advances our understanding of the interplay between urban conditions, individual resources, and ME, and further enriches the mixed embeddedness theory by integrating the opportunity construction perspective.
Promotion path of digital transformation in China's manufacturing industry based on technology-organisation-environment framework
As the global economy becomes increasingly digitalised, the digital transformation of manufacturing has become an important way to enhance national competitiveness and corporate viability. This study focuses on the digital transformation of the manufacturing industry. First, the digital transformation of listed manufacturing companies is scientifically measured and their current state of transformation analysed. Then, the technology-organisation-environment framework is used to examine the driving factors of digital transformation. Based on this, fuzzy-set qualitative comparative analysis is employed to summarise different digital transformation configurations. The findings show that the digital transformation of China’s manufacturing industry is still in its early stages, with significant regional differences. Achieving a high level of digital transformation can be accomplished through four paths: environment- dependent, strategic leadership, internally capability support, and comprehensive-driven approaches. Finally, practical guidance is provided on accelerating the digital transformation process and promoting high-quality development in the manufacturing industry.
An integrated system for evaluating the impact of firm-based innovations on GDP
The study analyses the impact of innovation on the economy in the EU and related countries (Norway and Switzerland), highlighting the large differences between these countries. An integrated measurement framework is proposed to assess the long-term impact of firm-based innovations on GDP comprehensively. The literature analysis sheds light on the link between firm-based innovations and economic growth, and the study follows a three-step methodology: firstly, data on innovation and GDP are collected from Eurostat and OECD, followed by an econometric analysis to identify the links between firm-based innovation performance and economic growth, and finally, a cluster analysis is performed. This cluster analysis grouped countries according to their level of innovation and economic performance. The empirical results showed that Germany, Denmark, Finland, the Netherlands, Sweden, and Ireland have high innovation and GDP growth rates, and their innovation ecosystem contribute significantly to economic prosperity. The study confirms that innovation drives GDP growth, but its impact varies across countries depending on R&D investment, workforce skills, and policy environment. Therefore, policymakers should develop innovation strategies that consider each country’s specificities following the results of cluster analysis to maximise the economic impact.
Tailoring fund selection to diverse investors: integrating financial and sustainability performance
This study explores the integration of financial and Environmental, Social, and Governance (ESG) criteria in the evaluation of investment funds within the energy equity sector, considering both short and long-term investor perspectives. Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision model, this analysis includes scenarios tailored to investors prioritizing financial returns and those focused on sustainability. The findings reveal that investors’ subjective preferences influence fund rankings, highlighting the need for adaptive classification systems. Finally, a customizable investment tool aligned with diverse investor priorities is proposed.
How does digital transformation moderate the link between ESG ratings and financial constraints?
This research aims to examine the moderating role of digital transformation in the link between ESG ratings and financing constraints faced by firms. A sample is a dataset consisting of 4255 listed companies operating in China from 2012 to 2022. The results showed that higher ESG ratings contribute to reducing financing constraints and that digital transformation positively enhances this relationship. In addition, the results also reveal that long-term ESG ratings contribute more effectively to reducing financing constraints. This study provides guidance for managers to practice ESG practices in the long term and insights for firms to find solutions to financing dilemmas. This study’s originality lies in demonstrating that higher ESG ratings alleviate financing constraints, with digital transformation enhancing this effect, providing novel insights into the interplay between sustainability efforts and technological advancement in corporate finance. The findings offer valuable implications for firms integrating ESG practices and digital strategies to optimize financial performance.
Should we be wary of using artificial intelligence-based big data management in social research?
This study examines the future role of artificial intelligence (AI) in transforming research processes within the social sciences, focusing on how AI may redefine researchers' responsibilities and potentially replace human participants in certain types of studies. Employing the Delphi method, the study collects expert opinions to evaluate both facilitating factors and barriers to the integration of AI into scientific research. Key findings indicate that while technological advancements – such as open-access data and the integration of AI with existing research tools – support the growing role of AI, significant challenges remain. These include the difficulty of verifying AI-generated information and concerns regarding authenticity in AI-driven research. Social factors, particularly the risk of excessive reliance on AI leading to diminished originality, emerged as critical barriers. In contrast, economic considerations, such as declining development costs, were viewed as less influential. The study’s practical implications include the need for robust ethical guidelines and enhanced AI training for researchers. By offering original insights into the evolving intersection of AI and social science research, this study highlights both the transformative potential of AI and the urgent need for its responsible integration to preserve research integrity and reliability.
Effectiveness of the ESG approach in portfolio selection – an empirical evidence from the US stock market
The purpose of this study is to explore whether ESG (Environmental, Social, and Governance) criteria can serve as a valuable tool for investors when making rational decisions about financial security selection and portfolio construction. By applying Modern and Post-Modern portfolio theories (MPT and PMPT) under the conditions of ESG and Return Max criterion, our primary objective was determined: “Is ESG a criterion for investors in the rational selection of financial securities and portfolio construction?” A five-year analysis (2018–2023) was carried out on 484 financial securities (companies) from the S&P 500 Stock Index to answer this question. Data collected included the daily close price of the S&P 500 Stock Index, its constituents (484 stocks), ESG scores, risk-free rate, and the equity risk premium of the U.S. market. The results showed that financial securities chosen based on the Return Max criterion were generally undervalued on the market; however, this was not consistently observed by ESG Max where examples of overvalued securities were also identified. Nevertheless, using the Sharpe and Sortino Ratio performance indicators, it was concluded that the return per unit of assumed risk is more appealing to investors (with risk aversion) when considering the portfolios built on the ESG Max criterion.
Multi-criteria decision analysis of Circular Economy performance in the Baltic States: a comparative evaluation
This study embarks on a comparative evaluation of Circular Economy (CE) performance in the Baltic States (Latvia, Lithuania, and Estonia) using a robust multi-criteria decision-making (MCDM) framework. Drawing on 22 key indicators, the research applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to systematically rank the country-level CE implementation across five thematic dimensions: production and consumption, waste management, secondary raw materials, competitiveness and innovation, and global sustainability. The results reveal that Latvia ranks highest, followed by Lithuania and Estonia, underscoring significant differences in waste management efficiency, investment in CE sectors, and material self-sufficiency. The main contribution of this paper lies in the development of a comprehensive, quantitative benchmarking framework that integrates multiple CE indicators and MCDM methods to assess national performance in a data-driven manner. The methodology developed here can serve as a replicable model for CE assessment in other regional or national contexts.
Drivers of price volatility in Romania’s electricity markets
The paper examines the price volatility, key determinants, and autoregressive distributed lag (ARDL) framework of Romania’s Intraday Continuous Market (IDC) during the summer months. The stability of the ARDL-ECM coefficients is assessed using the cumulative sum (CUSUM) test. We explore the interaction between IDC and Day-Ahead Market (DAM) prices, alongside the influence of economic and environmental variables, including traded volumes, consumption, export/import and the generation mix. Using hourly data and econometric techniques, we identify significant short- and long-run relationships between IDC prices and their drivers. DAM prices exhibit a strong positive impact on IDC prices, reflecting tight market integration. Higher shares of Renewable Energy Sources (RES) such as wind and solar are associated with increased IDC prices, highlighting challenges in integrating intermittent resources. Conventional sources, particularly coal and oil/gas, also elevate prices due to higher marginal costs. Conversely, electricity consumption is negatively related to IDC prices, suggesting that anticipated demand patterns may contribute to system stability. The findings carry implications for policymakers, indicating a need for enhanced forecasting, flexible resources and improved inter-market coordination to ensure price stability and efficient integration of RES.
The impact of public debt on economic growth: determining of factors and their interactions
This article suggests that the expenditure multiplier and the interactions among its key components can help explain whether increasing public debt encourages or inhibits economic growth. As per the theoretical underpinnings of the effect of debt on growth, its influence is observable in regard to private consumption, import and investment. The size of the expenditure multiplier depends on factors like the tax rate and the marginal propensities to consume, import, and invest – each influencing the multiplier differently. Specifically, the effect is positive in relation to marginal propensities to consume and invest and negative in relation to the tax rate and marginal propensity to import. Our findings show that in countries with relatively lower government effectiveness, debt has a greater impact on growth, mainly due to higher tax rates rather than high import levels. Conversely, in countries with higher government effectiveness, the influence of debt on growth remains similar regardless of tax rates, if the propensity to import is low. In cases where the public sector dominates the economy, the impact of debt on economic growth is determined by factors other than the multiplier effect.
Multi-criteria hybrid model of region assessment in the context of sustainable tourism
The main goal of the research was to develop a multi-criteria hybrid model for evaluating the region in the context of sustainable tourism, based on the example of the countries of the Visegrad Group. The research uses the mathematical apparatus of expert evaluation, theory of fuzzy sets, fuzzy logic, and multi-criteria evaluation of alternatives. For the first time, an expert method for assessing the level of sustainability of tourism in the region was developed, which was tested on the data of four groups of environmental criteria and sociocultural aspects. For the first time, a multi-criteria model for evaluating the region in the context of sustainable tourism was developed, based on the matrix multiplication method, which derives normalised estimates of regions by groups of sustainable tourism criteria. For the first time, a hybrid model of regional assessment in the context of sustainable tourism has been developed, aggregating the expert level of sustainable tourism development and the normalised estimates of regions by groups of sustainable tourism criteria. As a result, a ranking of regions in the context of sustainable tourism is being built for further decision-making by stakeholders of the new data-driven era. The multi-criteria hybrid model was verified and tested on real data from 2343 respondents of participants of the tourist movement in the V4 countries. The study outcomes will be very useful for policymakers, strategies and action plans, for agencies, national and international organisations, and other entities in the tourism system. They will support the development of a national and international comparative platform and strategic planning processes in the tourism sector aimed at the sector sustainability and the country’s economy.
How does environmental tax reform drive corporate innovation to green technologies? Quasi-natural experimental evidence from China
How to motivate enterprises to formulate green technology (GT) innovation is crucial for promoting green development and minimizing pollution control costs. This research employs a quasi-experimental approach to analyze the impact of environmental tax reform (ETR) on corporate innovation decisions. First, we construct a two-sector model within a single enterprise, where the enterprise produces goods using GT and non-green technology (NGT) respectively. ETR influences a company’s innovation choices by the relative market value, R&D intensity, and productivity of products manufactured using GT and NGT under profit maximization. Second, we test our model using 20122023 manufacturing firms’ data, and the empirical results confirm our theoretical predictions. Third, we perform robustness tests to exclude the impact of subsidies, command and control environmental supervision and the COVID-19 epidemic. Fourth, we conduct heterogeneity analysis in polluting level and market competition. Finally, this study uses two instrumental variables (IVs) to validate our main regression results: the interaction between regional water area and industrial chemical oxygen demand, and the proportion of days affected by temperature inversion. This study contributes to the literature related to innovation choices under environmental policy and has implications for directing firms’ innovation to GT.
On transforming a traditional organisational culture to meet the needs of a global business
This study highlights the challenges that a traditional organizational culture faces in terms of its adaptation in the context of contemporary business models and globalisation trends. In our attempt to answer the question – Can a traditional organizational culture and global business coexist? – the constructs as research and innovation, teamwork, decision-making, risk taking, market orientation, and adaptation of organisational culture, are included in the methodological framework. A case study of Montenegro as a developing country in Southeastern Europe was used as a research method. Firstly, a desk review of relevant secondary literature sources related to organisational culture, in general and in the context of globalisation, was carried out. Secondly, the impact of globalisation and international business on the traditional organisational culture in the developing environment, was investigated using a survey as a data collection method.
Spatial linkages between digital economy and carbon reduction under dual carbon goals
Since announcing its “dual carbon” goals, China has made reducing carbon emissions a top priority. This study utilizes panel data from 285 cities in China, from 2011–2021, to systematically examine the relationship between the digital economy and urban carbon output. It aims to identify their relationship by introducing SDM and DID model. The findings are as follows: (1) Improving the digital economy is essential to significantly lowering carbon output. These benchmark regression results have passed robustness tests. (2) The SDM model results show that the development of the digital economy significantly reduces both total and direct carbon emissions in local cities, and there is a significant spatial spillover effect. (3) The digital economy’s impact on carbon reduction varies greatly by regional distribution and city size, exhibiting significant heterogeneity.
Linking collaborative supplier social sustainability practices and supplier performance in asymmetric power relationships with buyers
This article objective is to identify factors related to collaborative supplier social sustainability practices and supplier international performance, and to propose a set of propositions regarding their relationships within a conceptual model. The research context includes manufacturing companies of various sizes located in Poland, which are predominantly Polish-owned and act as suppliers to large foreign buyers in relationships characterized by power asymmetry. The study determines which operationalizations of the main factors should be retained through factor extraction, evaluates their internal consistency using exploratory factor analysis, and validates the control variables. The conceptual model distinguishes between two areas of supplier collaboration on social sustainability practices: supply chain collaboration and horizontal collaboration. Future research may focus on examining the direct impact of these forms of collaboration on suppliers’ financial and non-financial performance in the context of their international operations.
collaborative social sustainability practices
Does digital payments reduce the risk of money laundering? The role of financial sector development
This study examines how financial sector development mediates the relationship between digital payments and money laundering. The current study relies on a sample of 120 countries, including both developed and developing economies, for the years 2014, 2017, and 2021. The findings reveal that digital payments, the rule of law, and political stability reduce the risk of money laundering, indicating that the increased use of digital payments helps reduce the risk of money laundering. This suggests that digital transactions, being more traceable and transparent than cash transactions, can help authorities monitor and prevent illicit financial activities more effectively. Regarding the mediation effect of financial sector development, the results show that financial sector development and the rule of law positively affect the density of digital payment transactions. In addition, it revealed that money-laundering risk is lower when the financial system develops and compliance with laws and political stability. These findings provide actionable insights for policymakers, regulators, and financial institutions committed to strengthening anti-money laundering efforts.
Exploring business students' perceptions of artificial intelligence's impact on the labor market: a pilot study
Artificial intelligence (AI) and its impact on a large array of economic and social facets has recently become one of the most debated topics both in academic and civic environment. Existing literature varies from topics touching on the AI ethics to the future of the labor market. Current research highlights significant divergences and a lack of consensus on the future implications of AI, leading to a heterogeneous perception among the general public. In this context, our research explores the intersection between AI and its profound impact on the labor market, focusing on business students’ perceptions of AI impact on skills, productivity and employment dynamics. The study examines how personal AI competencies, risk perception, and anticipated economic effects of AI technologies shape labor market expectations using structural equations modelling. Seven hypotheses were tested which summarize the correlations between six reflective constructs. Findings reveal that students generally perceive AI positively, recognizing its potential to increase organizational efficiency and work productivity. Our research highlights the dual impact of AI, exploring students’ perceptions of the effects of AI on society, organizations and the labor market and revealing the key links between these views and efficiency.
Firm performance in times of crisis: does an innovative business strategy matter?
This study examines whether a firm’s business strategy – innovative vs. conservative – determines the extent to which a crisis impacts its performance. To explore this, the study calculates business strategy scores as a composite measure of six variables, where a high (low) score indicates an innovative/prospective (conservative/defensive) strategy. The COVID-19 pandemic (2020–2021) serves as the crisis context for the analysis. Using a sample of 7,143 firm-year observations in the U.S., the study finds that while the sample firms experienced a decline in their performance during the COVID-19 crisis period compared to the pre-crisis level (2018–2019), the decline was less pronounced for firms following innovative strategies. This finding suggests that a firm’s business strategy is a crucial determinant of its performance during a crisis. The study enhances theoretical understanding that business strategy is particularly important when operating conditions are abnormal.