Search Results (1,355)

This research examines the influence of environmental, social, and governance (ESG) strategies on corporate financial performance (CFP) in China’s automotive industry, characterized by intense regulatory pressure and fast-paced technological transformation. Using an unbalanced panel dataset of A-share listed automotive firms from 2009 to 2024, this paper combines ESG scores from the Huazheng ESG index with firm-level financial data from CSMAR. CFP is measured through both accounting-based (ROA) and market-based (Tobin’s Q) indicators. Panel regression models are applied to evaluate the influence of overall ESG performance and the three individual pillars, and to assess heterogeneity across ownership types, firm type, and firm age. The results show that ESG performance is significantly and positively associated with ROA, but is insignificantly associated with Tobin’s Q. It is suggested that ESG engagement improves accounting profitability but is not fully reflected in the capital market. Among the three ESG pillars, governance shows the strongest positive link with ROA, while environmental and social performance are weakly associated with ROA. Furthermore, the heterogeneity study shows that the positive relationship between ESG and CFP is more pronounced for non-state-owned firms, vehicle manufacturers, or mature firms. Overall, this paper presents fresh evidence on whether and how ESG initiatives can facilitate sustainable value in China’s automotive sector, offering insights for policymakers and management that may help this industry achieve sustainable growth. Full article

Foreign direct investment (FDI) has often been cast as a straightforward engine of growth, yet its record across Central and Eastern Europe tells a more tangled story where outcomes hinge on the interplay of education, governance, and the timing of external shocks. This study embeds fixed effects panel econometrics within a systems framework, treating FDI as a subsystem of socio-economic dynamics. Using a long-run panel of eleven economies from 2000 to 2023, the analysis models path dependence and regime shifts through interaction terms and period-specific dummies set against a systems-thinking backdrop. The analysis shows that for the average CEE economy, FDI’s contribution has waxed and waned: it dragged on growth during the early transition years (2000–2007), settled into a neutral role after the global financial crisis, and proved unpredictable in the pandemic era. Romania stands out, however, with a marked “FDI premium” quantified as approximately 0.7 pp of growth per pp of FDI that seems to stem from reinforcing loops between rising tertiary enrolment and productivity spillovers. Mapping these feedbacks brings to light virtuous circles where human capital and resilience make or break the benefits of foreign capital. The policy message is plain: nurture the positive loops through investment in skills and firm linkages, keep institutions nimble enough to adapt, and watch for early warning signs of systemic strain. Full article

Against the backdrop of global energy transition and sustainable development, advancing the new energy industry has become a critical pathway for optimizing energy structures and achieving the dual carbon goals. However, while China’s new energy sector has experienced rapid growth, it has also exposed a series of challenges, including insufficient innovation momentum, irrational resource allocation, and low conversion rates of R&D outcomes. To delve into the root causes and propose improvement pathways, this study selected 76 listed new energy enterprises from 2021 to 2023 as samples. It comprehensively employed the DEA-BCC model, Malmquist productivity index, and Tobit regression model to conduct empirical analysis across three dimensions: static, dynamic, and influencing factors. The findings revealed: firstly, during the study period, overall static efficiency remained low, with only about 32.90% of enterprises operating efficiently. Efficiency decomposition indicated that low and unstable pure technical efficiency constrained overall efficiency gains. In contrast, while scale efficiency was relatively high, its growth was sluggish, and some enterprises exhibited significant scale irrelevance. Secondly, dynamic total factor productivity exhibited fluctuating growth primarily driven by technological progress. However, declining technical efficiency—particularly the deterioration of scale efficiency—indicated that while the new energy industry advanced technologically and expanded in scale, its management capabilities had not kept pace. This mismatch among the three factors trapped the industry in a “high investment, low efficiency” dilemma. Thirdly, regression analysis of influencing factors indicated that corporate governance and market competitiveness were pivotal to innovation efficiency: the proportion of independent directors and revenue growth rate exerted significant positive impacts, while equity concentration showed a significant negative effect. Firm size had a weaker influence, and government support did not demonstrate a significant positive impact. Accordingly, this paper proposes pathways to enhance innovation efficiency in new energy enterprises, including optimizing corporate governance structures, formulating differentiated subsidy policies, and improving the innovation ecosystem. The findings of this study not only provide empirical references for the innovative development of the new energy industry but also offer theoretical support for relevant policy formulation. Full article

As China has increased implementation of its opening-up strategy and the “Belt and Road” initiative, Chinese enterprises have encountered significant historical opportunities to expand their outward foreign direct investment (OFDI). However, international organizations and major nations are increasingly focusing on nonfinancial indicators for multinational corporations; as a result, enterprises frequently encounter social responsibility crises in cross-border investments. Consequently, Chinese firms must enhance their environmental, social, and governance (ESG) practices to bolster their comprehensive competitiveness, which is crucial for promoting successful international engagement and sustainability. This research explores the U-shaped relationship between ESG performance and OFDI, examining how different stages of the corporate lifecycle affect OFDI. The findings indicate that ESG investments compete with OFDI for internal resources during the introduction, growth, and decline phases, thereby inhibiting OFDI activities. In contrast, strong ESG performance in the maturity phase provides a competitive advantage in international markets, facilitating OFDI. The empirical analysis uses a fixed-effects model on a sample of Chinese A-share-listed companies from 2009 to 2022 and employs the PSM, 2SLS, and System GMM methods to test for endogeneity. The results reveal that (1) a positive U-shape relationship between ESG performance and corporate OFDI, and the inflection point occurs when the ESG score equals 69.04. Moreover, (2) the corporate lifecycle intensifies this nonlinear relationship, with growth-phase firms showing a significant inhibitory effect and mature-phase firms showing a pronounced promotional effect. Finally, (3) the U-shaped relationship between ESG performance and corporate OFDI is more pronounced in nonstate-owned enterprises. Based on these findings, this paper provides targeted policy recommendations for enterprises and governments. Full article

Background: Paediatric pelvic and acetabular fractures are rare and usually the consequence of high-energy trauma, often associated with life-threatening injuries. The majority are managed non-operatively; however, open reduction and internal fixation (ORIF) is indicated in selected, complex, or displaced, acetabular fractures. The modified Stoppa approach is well established in adults, but has been rarely reported in skeletally immature patients, and evidence guiding surgical approach and fixation in children remains limited. Methods: We report the case of an 11-year-old girl who sustained a transverse acetabular fracture following a high-energy trauma. The fracture was treated with ORIF through a modified Stoppa approach. We also performed a systematic review of the literature, focusing on ORIF of acetabular fractures in children. Results: In our patient, ORIF of the acetabular fracture was performed, achieving an anatomical reduction, 10 days after initial damage-control fixation of a concomitant open tibial plateau fracture. Postoperative management consisted of four weeks of non-weight bearing, followed by progressive weight bearing. At six months, she had returned to full daily activities and sports. The review of the literature identified 16 studies (retrospective series and case reports) describing paediatric acetabular fractures treated with ORIF using plates, screws, or flexible nails. In the literature, good to excellent clinical and radiographic outcomes were reported when anatomical reduction and stable fixation were achieved, although growth disturbance and avascular necrosis were described, particularly in cases with delayed reduction or severe triradiate cartilage injury. Conclusions: Our case illustrates the technical feasibility of the modified Stoppa approach in a skeletally immature patient with a complex acetabular fracture, with excellent mid-term outcome. Although it is not contraindicated in paediatric patients, it should be reserved for treating this type of complex fracture. The available literature supports that satisfactory results are reported after ORIF in children, but the heterogeneity and low level of evidence preclude firm recommendations on the optimal approach. Full article

Honeyberry (Lonicera caerulea L.) is a recently domesticated fruit crop, and there has been rather limited research on its phenological characteristics. In this study, we comprehensively evaluated the phenological and fruit quality traits of a honeyberry germplasm collection comprising 45 accessions. The annual growth period of the 45 accessions ranged from 153 (part of Russian accessions) to 173 days (part of Japanese accessions) in Harbin, China. The accessions of Japanese origin (‘Ri–5’, ‘Ri–68’, ‘RiM–3’, ‘Riwan’, ‘Riwandianlan’, and ‘Riwan–13’) consistently exhibited delayed flowering and ripening, as well as higher single fruit weights and fruit firmness. In contrast, the accessions of Russian and Chinese origins displayed relatively early to mid-season phenology, along with higher levels of vitamin C, anthocyanins, and soluble solids. Furthermore, there were great coefficients of variation (CVs) in total anthocyanins (CV = 35%), flavonoids (CV = 30%), phenolics (CV = 21%), and titratable acidity (CV = 19%) among the 45 accessions. Principal component analysis and hierarchical clustering revealed distinct clustering patterns among Japanese accessions. Among these accessions, ‘RiM–3’ exhibited both a relatively large fruit size and high firmness, implying its potential to overcome the inevitable trade-off between fruit size and firmness typically observed in Chinese and Russian honeyberry accessions. Our investigation and findings provide valuable information for honeyberry breeding aimed at optimizing the maturity period and enhancing fruit quality, as well as a reference for the current cultivation and management methods. Full article

Employing textual analysis of the “short-term vision” vocabulary in annual reports, we investigate the impact of managerial myopia on firm innovation and performance. Our results indicate that managerial myopia hampers innovation, and this result remains robust across a battery of robustness checks. Managerial myopia also weakens the positive impact of innovation on firm growth, and value in the long run. We find that state ownership and good corporate governance mitigate the negative impact of managerial myopia. The evidence supports the upper echelon theory and time orientation theoretical framework. This paper enriches the research on the influencing factors of corporate innovation, by providing evidence that people’s perception of time affects decision making and provides support for government ownership and strong corporate governance practices in alleviating the negative consequences of managerial myopia. Full article

Melatonin (MEL), also known as N-acetyl-5-methoxytryptamine, has been reported in plants as a secondary messenger involved in regulating abiotic stress responses. MEL treatment, either preharvest or postharvest, regulates several physiological and biochemical processes during fruit growth and ripening in horticultural products. These include reproductive development, tissue and quality maintenance, delayed senescence, and responses to abiotic stress. Due to its natural origin, low toxicity, and multifunctional regulatory capacity, MEL has recently attracted attention as a promising ‘green preservative’ for sustainable postharvest management. Additionally, MEL coordinates through cross-talk with other plant hormones, such as abscisic acid, ethylene, polyamines, jasmonic acid, γ-aminobutyric acid, salicylic acid, and nitric oxide, to regulate postharvest ripening and senescence. Furthermore, MEL enhances antioxidant systems and improves membrane integrity, thereby alleviating chilling injury and enhancing fruit firmness and colour. Notably, recent evidence highlights the innovative regulatory mechanisms of MEL involving redox homeostasis, hormone signalling reprogramming, and transcriptional modulation of stress-responsive pathways. MEL could therefore be considered an emerging, eco-friendly tool for prolonging the shelf-life of fruit and vegetables and maintaining their quality. This review summarises the mechanisms by which MEL contributes to plant stress resistance by regulating the biosynthesis and metabolism of stress tolerance and improving fruit quality. Full article

The global maritime and logistics sectors are undergoing rapid digital transformation driven by emerging technologies such as automation, the Internet of Things (IoT), and blockchain. Artificial Intelligence (AI), with its ability to analyze complex datasets, predict operational patterns, and optimize resource allocation, offers a transformative potential beyond the capabilities of conventional technologies. However, mixed results are shown in its implementation. This study examines the current state of AI applications to unlock higher levels of efficiency and competitiveness in logistics firms. A mixed-methods approach was employed, combining surveys from logistics companies with in-depth interviews from key stakeholders in ports and logistics firms to triangulate insights and enhance the validity of the findings. Our results reveal that while technologies such as automation and digital tracking are increasingly utilized to improve operational transparency and cargo management, AI applications remain limited and largely experimental. Where implemented, AI contributes to strategic decision-making, predictive maintenance, customer service enhancement, and cargo flow optimization. Nonetheless, financial conditions, data integration challenges, and a shortage of AI-skilled professionals continue to impede its wider adoption. To overcome these challenges, this study recommends targeted investments in AI infrastructure, the establishment of collaborative frameworks between public authorities, financial institutions, and technology-driven Higher Education Institutions (HEIs), and the development of human capital capable of sustaining AI-enabled transformation. By strategically leveraging AI, Oman can position its ports and logistics sector as a regional leader in efficiency, innovation, and sustainable growth. Full article

Despite substantial growth in eco-innovation (EI) research, most studies rely on cross-sectional data, limiting understanding of the temporal dynamics of EI and its determinants under varying macroeconomic conditions. This study addresses this gap by analysing panel data from Spanish manufacturing firms across three phases of the business cycle: pre-crisis expansion (2004–2007), the global financial crisis (2008–2013), and recovery (2014–2016). We investigate the drivers of two distinct types of eco-innovation: efficiency EI (energy and material savings) and environmental EI (reducing environmental harm), focusing on the role of regulation, institutional interventions, and firm-level innovation capacities. Using a random-effects panel probit model that accounts for unobserved firm heterogeneity, we examine how these drivers operate across different macroeconomic contexts. Our findings reveal that regulation consistently fosters EI, while the influence of subsidies, R&D capacity, and collaborative networks is more context-dependent, particularly during economic downturns. The results highlight the cumulative, path-dependent, and cyclical nature of EI, providing novel insights into the conditions that enable firms to sustain green innovation over time. Drivers of eco-innovation differ systematically between efficiency- and environment-oriented strategies, and these differences remain stable over the business cycle, implying distinct underlying mechanisms and policy implications. Accordingly, policy design—particularly during economic downturns—should distinguish between reinforcing incentives for internal efficiency improvements and sustaining regulatory and financial support for environmental EI. Full article

This study proposes a hybrid machine learning framework that integrates structured financial indicators and unstructured textual strategy disclosures to improve firm-level management performance prediction. Using corporate business reports from South Korean listed firms, strategic text was extracted and categorized under the Balanced Scorecard (BSC) framework into financial, customer, internal process, and learning and growth dimensions. Various machine learning and deep learning models—including k-nearest neighbors (KNNs), support vector machine (SVM), light gradient boosting machine (LightGBM), convolutional neural network (CNN), long short-term memory (LSTM), autoencoder, and transformer—were evaluated, with results showing that the inclusion of strategic textual data significantly enhanced prediction accuracy, precision, recall, area under the curve (AUC), and F1-score. Among individual models, the transformer architecture demonstrated superior performance in extracting context-rich semantic features. A soft-voting ensemble model combining autoencoder, LSTM, and transformer achieved the best overall performance, leading in accuracy and AUC, while the best single deep learning model (transformer) obtained a marginally higher F1 score, confirming the value of hybrid learning. Furthermore, analysis revealed that customer-oriented strategy disclosures were the most predictive among BSC dimensions. These findings highlight the value of integrating financial and narrative data using advanced NLP and artificial intelligence (AI) techniques to develop interpretable and robust corporate performance forecasting models. In addition, we operationalize information security narratives using a reproducible cybersecurity lexicon and derive security disclosure intensity and weight share features that are jointly evaluated with BSC-based strategic vectors. Full article

This article examines how European funding enhances the financial performance of Romanian SMEs, a sector facing growing regulatory pressure, market volatility, and resource constraints. The study combines a thematic analysis of InvestEU indicators and national SME financing data (2021–2023) with a firm-level difference-in-differences model comparing InvestEU-funded SMEs to a matched control group over 2023–2024. The qualitative evidence shows that InvestEU operates at the EU level as a multidimensional policy instrument fostering competitiveness, social inclusion, and long-term economic and environmental development, while Romanian SMEs continue to rely predominantly on their own funds and national co-financing, a conservative pattern that ensures stability but limits access to external capital and transformative investments. Econometric results indicate that funded SMEs record, on average, higher turnover and net profit growth than comparable non-funded firms and confirm a strong positive association between firm size and financial performance; however, the interaction term capturing the specific InvestEU effect is positive but not statistically significant at the 95% confidence level. The findings suggest that InvestEU has the potential to act as a catalyst for structural change but also highlight the need for longer observation periods, larger samples, and more comprehensive development indicators to assess its medium-and long-term impact on SME competitiveness. Full article

Amid the normalization of flexible employment, labor dispatch, as a form of non-standard employment, has become an important component of China’s precarious labor market (PLM). Based on registration data of labor dispatch firms from 2002 to 2022, this paper analyzes the spatial distribution and evolutionary patterns of China’s PLM, using spatial autocorrelation, kernel density estimation, and Gini coefficient methods. Furthermore, it explores its driving mechanisms through a panel negative binomial regression model. The results show that (i) over the past two decades, China’s PLM has undergone four stages: initiation, acceleration, expansion, and adjustment. (ii) Spatially, it has evolved along the trend of “reinforced clustering with concurrent diffusion,” expanding from first-tier cities in eastern China to second- and third-tier cities in central and western China. (iii) Industrial upgrading, market competition, and the overall level of urban development have significantly promoted the growth of the PLM, while improvements in accessibility, proportion of migrant population, and public service provision have somewhat restrained its expansion. Overall, China’s PLM demonstrates both growth potential and structural vulnerability under institutional constraints and external shocks, offering valuable spatial insights for forging sustainable, high-quality employment and coordinated regional development. Full article

This study investigates the determinants of turnover intention among real estate sales professionals in Lebanon and the United Arab Emirates (UAE), two markets that represent contrasting economic realities within the MENA region. Drawing on Herzberg’s Two-Factor Theory, Vroom’s Expectancy Theory, and March and Simon’s Push-Pull Model, this study adopts a multidimensional framework to assess the effects of compensation, job stress, career growth opportunities, and work–life balance on employee retention. A quantitative method was employed using a structured questionnaire administered to 832 respondents (425 in the UAE and 407 in Lebanon), and data were analyzed using Structural Equation Modeling. The results reveal that job stress is the most influential predictor of turnover intention, particularly in Lebanon, followed by work–life balance, compensation, and career growth opportunities. These findings underscore the importance of psychological well-being and structural incentives in talent retention. By offering empirical evidence from an underexplored regional labor market, the study contributes to the global turnover discourse and provides comparative insights into the labor dynamics of both a crisis-prone and a high-growth economy. The results carry significant practical implications for HR managers, firm owners, and policymakers, highlighting the necessity of adopting holistic and context-sensitive retention strategies that extend beyond financial rewards to include flexible work arrangements, career development frameworks, and supportive workplace cultures. Full article

This study investigates the valuation dynamics of 30 publicly listed fintech firms across six Asian economies from January 2021 to December 2025. It examines how intrinsic firm-level scale (market capitalization) and extrinsic macroeconomic conditions (GDP growth) jointly influence fintech valuation ratios, as reflected in price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S) measures. It also identifies significant structural heterogeneity and distributional asymmetries in valuation outcomes by implementing a multi-method empirical strategy that includes a Panel Autoregressive Distributed Lag (ARDL) framework, two-way fixed-effects models with interaction terms, and quantile regression. The findings reveal a robust, positive long-run relationship between market capitalization and valuation multiples across all ratios, confirming that firm-level scale as reflected in market capitalization is the primary driver of market value. Critically, the analysis identifies a dual-regime landscape in the Asian fintech sector: developed markets (South Korea, Japan, and Singapore) are fundamentally firm-scale driven, where intrinsic scale is the superior predictor of valuation. In contrast, developing markets (China, India, and Indonesia) are primarily macro-growth driven, exhibiting high sensitivity to GDP growth as a macroeconomic indicator of market expansion. The quantile regression results demonstrate a winner-takes-all effect, where the impact of scale on valuation is significantly more pronounced for highly valued firms in the 75th percentile. These results challenge the efficacy of universal valuation models and provide a context-dependent navigational framework for investors, analysts, and policymakers to distinguish between structural scale and cyclical growth in the rapidly evolving Asian fintech ecosystem. Full article