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.
Potential structural efficiency of Chinese commercial banks
Given that structural efficiency serves as a significant instrument, this paper applies a novel approach to measure structural efficiency levels within Chinese banks from the perspective of potential improvement. To further investigate the patterns of structural efficiency, the overall structural efficiency is disaggregated into a series of variable-specific structural efficiencies. It reveals that fixed assets and non-interest incomes constitute the primary sources of structural inefficiency during the study period. Furthermore, the structural efficiencies of small-medium commercial banks surpass those of large state-owned commercial banks, although the efficiency gap between the two types of banks has narrowed. Based on the variable-specific structural efficiencies, this paper further explores the structural efficiency patterns within the Chinese banking sector.
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Dynamic convergence in equity markets: evidence from an open-developing economy
This paper examines the speed and stability of stock market convergence in an open developing economy, using Vietnam as the case. The study applies a β-convergence framework to weekly FTSE equity-indices from 2013 to 2025, estimating both full-sample and time-varying models, including sub-period regressions and rolling-window analyses. Structural change is addressed by separating pre-crisis, crisis, and post-crisis periods. The findings reveal three key insights. First, Vietnam’s equity market shows long-run convergence with regional benchmarks such as Korea, the Asia-Pacific, and emerging markets, but weaker linkages with advanced markets such as the United States (U.S.), the euro area (EMU), and Japan. Second, convergence speeds rose during the crisis period, indicating temporary synchronization with global markets, then fell sharply in the post-crisis phase. Third, regional linkages are more persistent, suggesting a reorientation toward intra-regional financial alignment. These results have important research implications for understanding dynamic financial integration and convergence asymmetries. From a policy perspective, they support strengthening regional financial cooperation to bolster resilience and market development in open developing economies.
University and business environment in the Creative Helix: the impact of clusters on collaboration and employability of graduates
This study examines the role of clusters in enhancing collaboration between universities and businesses, and their impact on graduate employability. Drawing on the Creative Helix model and cluster theory, the research investigates how regional innovation ecosystems facilitate knowledge transfer, innovation, and workforce integration. A quantitative methodology used a structured questionnaire for three stakeholder groups: academic staff, students, and business representatives. Exploratory factor analysis and reliability tests supported the instrument’s validity and revealed five key factors shaping the university-business interface within clusters. The findings highlight that clusters stimulate cooperation, improve curriculum relevance, and increase graduates’ readiness for the labour market. The research contributes to the theoretical understanding of cluster-based collaboration and offers practical guidance for universities and regional policy-makers aiming to strengthen employability through structured partnerships. The paper’s originality lies in its integrative framework connecting regional development, higher education, and labour market needs, offering empirical evidence from an emerging economy. The study underscores the value of clusters as strategic tools for economic and educational transformation. This evidence is bounded by the study’s regional focus, sectoral coverage and reliance on self-reported questionnaires. Future research should integrate policy-maker perspectives and longitudinal or administrative employment data across multiple regions.
The impact of firm-level innovativeness on socioeconomic indicators: an AI-driven approach
This study examined the impact of firm-level innovativeness on socioeconomic indicators at regional and sectoral levels, using Artificial Intelligence (AI) techniques to analyze unstructured data from the websites of 32,559 companies. Using this data, an Innovation Index was constructed. The results indicated a generally low-to-moderate level of innovativeness among Lithuanian firms, with an average Innovation Index of 35 out of 100. Notably, 38.6% of firms scored 0, showing no detectable signs of innovation. Innovativeness was found to be highest in Vilnius and Kaunas, and in sectors such as electricity, information and communication, and public administration. An econometric analysis revealed that a 1-point increase in the Innovation Index was associated with a 0.02% rise in gross average earnings, a 0.27% increase in gross value added, a 0.17% increase in FDI per capita, and a 0.05% increase in GDP per capita. Higher innovativeness levels were also linked to lower unemployment and migration rates. The findings underscore the importance of innovation for regional development and labor market outcomes, and that an AI-driven approach can offer a reliable and scalable alternative to traditional methods, providing more timely and objective assessments. The approach is adaptable across countries, thus offering valuable insights for policymakers and researchers.
Development of marketing tools for the express delivery industry to increase consumer loyalty
This research explores how to develop and enhance marketing tools to increase consumer loyalty in the express delivery industry. The study analyzes the influence of these tools on customer loyalty by reviewing scientific literature. The theoretical framework examines various marketing tools, including digital marketing, social media marketing, and integrated marketing communications. Based on this analysis, hypotheses were created and then tested using a survey. The study’s empirical section tests these hypotheses and develops a conceptual model that identifies four key tools for boosting loyalty. The findings offer new opportunities for both start-up and established Lithuanian express delivery companies to improve customer loyalty and gain a competitive edge in the market.
Geopolitical risks, market volatility, and tech firms involved in quantum computing
This study examines how global uncertainty influences the financial dynamics of technology firms involved in quantum computing, a strategically significant but structurally fragile segment of emerging deep-tech markets. Using daily data from January 2015 to May 2025, the analysis integrates principal component decomposition, panel regression, Granger causality testing and volatility diagnostics to assess the transmission of market volatility and geopolitical risk. The findings show that market volatility, proxied by the VIX index, exerts a persistent and adverse influence on stock returns, confirming its role as a systemic risk factor. Geopolitical risk, measured through the ACT and THREAT sub-indices of the Geopolitical Risk Index (GPR), also affects return behaviour, but through asymmetric and time-varying transmission mechanisms that emerge under heightened uncertainty and global strategic tension. The results further reveal heterogeneous vulnerability profiles across firms, indicating conditional risk spillovers rather than uniform market reactions. The study contributes new empirical evidence on the interplay between financial and geopolitical risk in advanced technology sectors and offers a replicable framework for uncertainty modelling in frontier markets.
The spatial relationship between innovation capacity and housing affordability in Chinese cities
With China’s rapid urbanization, innovation capacity and housing affordability have become important factors affecting sustainable development. This paper aims to address this research gap by examining the spatial characteristics and correlation between the housing market and urban innovation capacity. With statistical analyses of the housing market and innovation indicators in China’s major cities, there are following findings. Firstly, it is found that there are obvious spatial characteristics between urban innovation ability and housing affordability. Housing supply has a significantly positive effect on urban innovation, particularly in central regions. Similarly, housing demand also positively impacts urban innovation. The impact of the housing supply-demand ratio on urban innovation exhibits regional variation. Secondly, the impact of housing affordability on urban innovation levels exhibits a nuanced pattern, resembling an inverted “U” shape, particularly pronounced in the eastern region. When the housing price-to-income ratio remains below a critical threshold, its growth positively contributes to enhancing urban innovation levels. Thirdly, an increase in the housing supply-demand ratio adversely affects urban innovation levels through a mediated pathway. The housing supply-demand ratio serves as a vital metric indicating the housing market’s stability.
Investment implications of Industry 4.0: evidence from smart manufacturing ETFs
The rise of smart manufacturing, driven by digital transformation and Industry 4.0, has introduced new opportunities for investors seeking to diversify their portfolios. Smart manufacturing ETFs offer a unique risk-return profile tailored to the evolving landscape of industrial automation and data-driven processes. This paper explores the comparative risk-adjusted performance of a smart manufacturing ETF, a conventional industrial portfolio, and a broad-market SP500 tracking portfolio, utilizing daily data from October 2019 to October 2022. By deconstructing the excess returns of these portfolios through one-factor, three-factor, and five-factor asset pricing models, we provide insights into the risk exposure and performance drivers of smart manufacturing investments. Results indicate that investing in smart manufacturing, while less performant relative to the other investments, carries less exposure to market risk and can provide important diversification benefits to equity portfolios. Moreover, there is a positive loading for the size factor and a negative loading for the value and profitability factors for the smart manufacturing portfolio during a period of positive premium for all factors except for size. This implies that the consequent payoff in terms of profitability will eventually turn the loading of the profitability factor into positive territory, increasing returns on smart manufacturing investing.
Multi-criteria decision analysis of e-commerce software selection using AHP-NWA hybrid model
In the digital economy, selecting the right e-commerce platform is a strategic decision with significant implications for efficiency and competitiveness. This paper applies a hybrid decision-making framework that integrates the Analytic Hierarchy Process (AHP) and Net Worth Analysis (NWA) to evaluate five popular e-commerce platforms: Magento, WooCommerce, Shopify, PrestaShop, and OpenCart. AHP was used to derive weights for evaluation criteria, while NWA incorporated expert assessments of alternatives. Results indicate that security (32%) and functionality (25%) are the most critical factors, followed by maintenance costs (14%) and scalability (11%). The ranking shows Magento as the leading platform (0.575), excelling in security and functionality, while WooCommerce (0.567) is highly flexible and Shopify (0.563) stable though less customizable. PrestaShop (0.505) and OpenCart (0.496) scored lower, making them suitable for smaller businesses. The contribution of this study lies in the integration of AHP-derived weights into the NWA framework under a dual expert panel structure, ensuring methodological independence and reducing bias. This hybrid approach offers both practical implications for digital business strategy and theoretical insights into combining hierarchical and network-based MCDM methods, thereby addressing a research gap in e-commerce software evaluation.
Nonlinear effects of ageing population and AI on China’s GDP growth: a threshold analysis
This research empirically explores the influences of ageing on China’s GDP growth, incorporating Artificial Intelligence (AI) as a moderating factor. Specifically, industrial robot penetration was used as a proxy for AI adoption. This research selects panel data in 31 provinces of China (2000–2022). The nonlinear association between ageing population and GDP growth is examined using panel threshold regression models, while threshold variables are ageing and AI adoption, respectively. To verify the robustnes, the old-age dependency ratio is utilized as a proxy of ageing population. According to the findings, GDP growth is initially negatively affected by ageing population. However, when AI adoption surpasses a critical threshold, this negative effect is significantly mitigated. This finding highlights the importance of AI adoption in managing the economic challenges brought by ageing. Therefore, some valuable recommendations have been put forward to support inclusive and sustainable economic development. These include greater investment in research and expansion concerning AI, promoting AI-driven robotics in key sectors, and offering targeted skilling programs for elderly employees. Further suggestions are to invest in digital infrastructures and the industry of ageing, as well as to leverage and develop elderly human capital.
Dividend policy in a crisis: a pre and post-COVID-19 comparison of DJIA and DAX companies
This study examines the shifts in dividend policy drivers for companies listed on the Dow Jones Industrial Average (DJIA) and Deutscher Aktienindex (DAX) by comparing the pre-COVID-19 (2015–2019) and post-COVID-19 (2020– 2024) periods. Employing a two-stage methodology, we first use factor analysis to distill traditional and cash flow-based profitability indicators into key factors, followed by panel regression models to assess their impact on dividend payouts. Findings indicate that the 2020 crisis significantly altered dividend strategies. For DJIA firms, dividend policy shifted from asset-based profitability (pre-2020) to a strong reliance on equity-based profitability (ROE, CFROE) post-2020, reflecting investor preference for immediate returns during uncertainty. For DAX firms, cash flow-based profitability emerged as the primary driver post-2020, unlike the pre-crisis period where no profitability factor was significant, highlighting distinct market responses to economic shocks in the U.S. and Germany.
Promoting a green luxury product to belong or to stand out: a concept comparison test approach
Literature on luxury products reveals that product promotion involves two status-signaling goals as psychological mechanisms of social adaptation: the value-expressive function (to stand out: status enhancement) and the social-adjustive function (to be accepted: status affirmation). Traditionally, the value-expressive mechanism has been the most effective in promoting luxury goods. However, how these mechanisms operate for sustainable products, given the common assumption that luxury customers tend to disregard sustainability attributes, remains underexplored. This study challenges the aforementioned assumption by assessing how status-signaling goals influence willingness to pay for luxury products with sustainability attributes. Findings indicate that brand promotion that uses the social-adjustive function can be effective. This study recruits 464 participants and adopts an experimental approach involving concept comparison testing to explore the differences in consumers’ willingness to pay for a green luxury car. The car is presented with two distinct claims related to the above-mentioned luxury mechanisms and the absence or presence of a sustainable feature. Across all combinations of stimuli, participants perceive the sustainable luxury car as more appealing. This study shows that introducing a sustainability attribute in luxury brand communications can enhance consumers’ willingness to pay under either of the two status-signaling mechanisms.
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.
Green bond vs green stock: which one can resist climate policy uncertainty in China?
This paper applies the time-varying parameter-stochastic volatility-vector auto-regression (TVP-SV-VAR) method to explore the correlations among China’s climate policy uncertainty (CPU), green stock (GS), and green bond (GB). The findings evidence dynamic impacts from CPU to the green assets, indicating that the hedging ability of green assets varies over time. In the short and medium term, the GS may hedge the rising CPU risks effectively while the GB is not. However, in the long term, both the GS and GB may resist the CPU risks, although the GS is found to perform better. Furthermore, the results also suggest that the GS is more reliable when the unexpected shocks happen. Thus, compared to the GB, the GS may possess higher uncertainty risks hedging ability. Nevertheless, the results also suggest that the hedging ability of the GS decreases in recent years. The findings may help investors construct portfolios to hedge CPU risks. Moreover, the results suggest that the government should further promote the standardisation of green investment and reduce the information asymmetry of climate policy, which is critical to improve the performance of green assets.
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.