Search Results (3,401)

Accurate and non-destructive assessment of fruit firmness is critical for evaluating quality and ripeness, particularly in postharvest handling and supply chain management. This study presents the development of an image-based vibration analysis system for evaluating the firmness of kiwifruit using computer vision and machine learning. In the proposed setup, 120 kiwifruits were subjected to controlled excitation in the frequency range of 200–300 Hz using a vibration motor. A digital camera captured surface displacement over time (for 20 s), enabling the extraction of key dynamic features, namely, the damping coefficient (damping is a measure of a material’s ability to dissipate energy) and natural frequency (the first peak in the frequency spectrum), through image processing techniques. Results showed that firmer fruits exhibited higher natural frequencies and lower damping, while softer, more ripened fruits showed the opposite trend. These vibration-based features were then used as inputs to a feed-forward backpropagation neural network to predict fruit firmness. The neural network consisted of an input layer with two neurons (damping coefficient and natural frequency), a hidden layer with ten neurons, and an output layer representing firmness. The model demonstrated strong predictive performance, with a correlation coefficient (R²) of 0.9951 and a root mean square error (RMSE) of 0.0185, confirming its high accuracy. This study confirms the feasibility of using vibration-induced image data combined with machine learning for non-destructive firmness evaluation. The proposed method provides a reliable and efficient alternative to traditional firmness testing techniques and offers potential for real-time implementation in automated grading and quality control systems for kiwi and other fruit types. Full article

Industry 4.0 (I4.0) is reshaping manufacturing by integrating advanced digital technologies and is increasingly seen as an enabler of the circular economy (CE). However, most research treats digitalisation and circularity separately, with limited empirical insight regarding their combined implementation. This study investigates I4.0 adoption to support sustainability and CE across industries, focusing on how enterprise size influences adoption patterns. Based on survey data from 69 enterprises, the research examines which technologies are applied, at what stages of the product life cycle, and what barriers and drivers influence uptake. Findings reveal a modest but growing adoption led by the Internet of Things (IoT), big data, and integrated systems. While larger firms implement more advanced tools (e.g., robotics and simulation), smaller enterprises favour accessible solutions (e.g., IoT and cloud computing). A positive link is observed between digital adoption and CE practices, though barriers remain significant. Five main categories of perceived obstacles are identified: political/institutional, financial, social/market-related, technological/infrastructural, and legal/regulatory. Attitudinal resistance, particularly in micro and small enterprises, emerges as an additional challenge. Based on these insights, and to support the twin transition, the paper proposes targeted policies, including expanded funding, streamlined procedures, enhanced training, and tools for circular performance monitoring. Full article

This study assesses energy management practices in the automotive sector of Poland’s Silesian Voivodeship, a highly industrialized region. Using structured interviews with 40 manufacturing firms, it examines the adoption of energy monitoring, submetering, Energy Performance Indicators (EnPIs), audits, and energy efficiency investments. The research addresses the problem of persistent energy waste and the difficulties many firms face in integrating ISO 50001-aligned energy management into daily operations, where declared policies often outpace actual practices. Results show that 92.5% of firms monitor total energy consumption, but only 40% implement submetering, and 45% use EnPIs. Half have conducted energy audits, and 85% report taking energy-saving actions such as lighting upgrades, equipment modernization, and thermal improvements. However, no companies reported measurable energy or cost savings, and few track investment outcomes quantitatively. While energy awareness is widespread, many practices appear to be implemented in a tactical manner, potentially lacking strategic integration or consistent performance tracking. Larger firms are more likely to use audits and EnPIs, while smaller firms face barriers such as limited resources or technical expertise. The findings highlight a need for formalized EMS adoption, standardized energy governance, and greater use of performance-based tools such as EnPIs. By exploring EMS-aligned behavior without referencing management systems directly, the study provides a unique lens on the operational maturity of industrial firms. Full article

In the era of digital–real integration, open-source collaboration has become a strategic pathway for accelerating the innovation catch-up of China’s industrial software. This study employs an exploratory multi-case design, focusing on the China Automotive Operating System open-source project and the FastCAE open-source domestic CAE software integrated development platform to examine how open-source strategies shape collaborative mechanisms and innovation outcomes. The analysis reveals that firms adopt both formal (behavioral and outcome coordination) and informal (relationship and empowerment coordination) strategies, fostering high-level complementary collaboration in data, technology, institution, and human resources. These mechanisms significantly enhance R&D efficiency and quality, drive technological innovation, and create new market innovation, thereby improving collaborative performance. The study contributes to theory by linking open-source-driven digital–real integration with industrial software innovation catch-up and offers practical governance recommendations for strengthening China’s industrial software autonomy and ecosystem sustainability. Full article

Corporate failure prediction remains a major topic in the literature. Numerous methodologies have been established for its assessment, while data envelopment analysis (DEA) has received particular attention. This study contributes to the literature, establishing a new approach in the construction process of prediction models based on the combination of logistic LASSO and an advanced version of data envelopment analysis (DEA). We adopt the modified slacks-based super-efficiency measure (modified super-SBM-DEA), following the “Worst practice frontier” approach, and focus on the selection process of predictive variables, implementing the logistic LASSO regression. A balanced sample with one-to-one matching between forty-five firms that filed for reorganization under U.S. bankruptcy law during the period 2014–2020 and forty-five non-failed firms of a similar size from the U.S. energy economic sector has been used for the empirical analysis. The proposed methodology offers superior results in terms of corporate failure prediction accuracy. For the dynamic assessment of failure, Malmquist DEA has been implemented during the five fiscal years prior to the event of failure, offering insights into financial distress before the event of a default. The model outperforms alternatives by achieving higher overall prediction accuracy (85.6%), the better identification of failed firms (91.1%), and the improved classification of non-failed firms (80%). Compared to prior DEA-based models, it demonstrates superior predictive performance with lower Type I and Type II errors and higher sensitivity as well as specificity. These results highlight the model’s effectiveness as a reliable early warning tool for bankruptcy prediction. Full article

Corporate carbon emissions reporting is central to climate accountability, yet significant gaps remain in transparency, completeness, and methodological rigor. This study introduces the Carbon Integrity Index (CIX), a structured framework for assessing disclosure quality through ten indicators covering Scopes 1, 2, and 3. Unlike existing standards focused on reporting requirements, the CIX evaluates how well emissions are reported, addressing methodological transparency, scope coverage, and treatment of uncertainty. Applied to 2022 sustainability reports from companies listed in Spain’s IBEX 35 index, the framework reveals an average score of 5.7/10, with 69% of firms achieving passing results. While Scope 2 reporting was generally robust (mean: 0.82), Scope 3 disclosures—often representing the majority of emissions—and uncertainty assessments were systematically weak (mean: 0.08). Findings provide empirical support for legitimacy and institutional theory, showing how formal compliance can mask performative compliance that limits meaningful accountability. Sectoral differences suggest that institutional pressures and operational complexity shape divergent transparency pathways, raising concerns that universal standards may entrench reporting disparities. The CIX offers regulators, investors, and companies a practical tool for distinguishing symbolic from substantive disclosure, enabling more informed decision-making and strengthening the role of reporting in driving the transition to net-zero business models. Full article

Environmental innovation represents a pivotal pathway toward achieving energy efficiency improvements, carbon footprint reduction, and ecological sustainability enhancement. The research investigates Chinese manufacturing enterprises listed on domestic stock exchanges throughout 2011–2023. The analytical framework utilizes count-based regression methodologies to explore how R&D investment intensity influences eco-innovation capabilities. Results demonstrate curvilinear associations linking R&D expenditure levels with both substantive and strategic environmental innovation achievements across industrial firms. This outcome successfully passed the turning-point test. Environmental oversight and financial incentives produce divergent moderating influences on innovation trajectories. Regulatory frameworks generate restrictive impacts through narrowing optimal investment ranges and dampening peak innovation outputs, whereas fiscal support mechanisms foster expansive effects via broadening resource availability and amplifying achievement levels. Cross-sectional examination uncovers substantial variations among ownership categories and geographical locations. State-owned enterprises demonstrate significantly lower optimal R&D intensity thresholds. Private firms require substantially elevated thresholds for optimal performance. Inland territories manifest unbalanced innovation dynamics. Coastal areas exhibit symmetric innovation patterns. The research enriches empirical knowledge in eco-innovation studies while offering context-specific strategic insights. The findings establish theoretical foundations and practical guidance for policy architects designing integrated environmental management systems that enhance innovation capabilities. Full article

The registration system reform (RSR) represents a landmark innovation in China’s IPO system, aiming to promote a more transparent, competitive, and sustainable market. Exploiting the staggered implementation of RSR as a quasi-natural experiment, we employ a difference-in-differences (DID) model using a sample of Chinese A-share IPO firms from 2016 to 2022 to investigate its impact on corporate sustainability, as proxied by environmental, social, and governance (ESG) performance. Our findings indicate that RSR significantly enhances corporate ESG performance, especially the governance (G) performance. Mechanism analysis suggests that market competition, investor rationality, and sponsor reputation are potential channels through which the reform facilitates corporate sustainability. Furthermore, the above relationship is more pronounced in regions with a higher degree of marketization, among non-state-owned enterprises, and those with weaker profitability. Moreover, the reform not only exhibits long-term effects but also demonstrates positive spillover effects on peer firms originally listed under the approval-based system. Overall, our study extends the understanding of how capital market institutional reforms promote corporate sustainability in the era of the digital economy and provides valuable insights for regulators to standardize and enhance RSR, thereby establishing a resilient and sustainable financial ecosystem. Full article

This study develops a four-dimensional value-assessment framework encompassing economic, innovation, social, and cultural dimensions to evaluate the multidimensional performance of family firms in China. Drawing on the entropy weighting method, we construct a composite value index for 251 A-share listed family firms from 2014 to 2023 and apply spatial statistical techniques—including Dagum Gini coefficients, Theil indices, and coefficients of variation—to examine temporal evolution and regional disparities. We further estimate explanatory panel models with firm and year fixed effects (Hausman test favoring FE) to identify the firm-level determinants of composite value. Leverage exhibits a significantly negative association with value, while firm size and innovation capacity are positively related; no significant moderating effect of technology-intensive industry is found. A robustness check using equal weights (0.25 for each dimension) yields an almost perfect correlation (0.9999) with the entropy-weighted index, confirming that the dominance of the innovation dimension in the weighting scheme does not materially affect the overall conclusions. The results highlight the importance of integrating multidimensional value perspectives into both academic research and policy design to promote balanced, inclusive, and sustainable development trajectories for family enterprises. Full article

There has been considerable scientific interest in third-order nonlinear optical materials for photonic applications. In particular, materials exhibiting a strong electronic optical Kerr effect serve as essential components in the ultrafast nonlinear photonic devices and are instrumental in the development of all-optical signal processing technologies. Therefore, the accurate prediction of material-relevant properties, such as second hyperpolarizabilities, remains a key topic in the search for efficient photonic materials. However, the field standards in quantum chemical computation are still inconsistent, as studies often lack a firm statistical foundation. This work presents a comprehensive in silico investigation based on multiple full-factorial experiments, aiming to clarify the strengths and limitations of various computational approaches. Our results indicate that the coupled-cluster approach at the CCSD level in its current response-equation implementations is not yet able to outperform the range-separated hybrid density functionals, such as LC-BLYP(0.33). The exceptional performance of the specifically tailored basis set Sadlej-pVTZ is also described. Not only was the presence of diffuse functions found to be mandatory, but also adding ample polarization functions is shown to be inefficient resource-wise. HF/Sadlej-pVTZ is proven to be reliable enough to use in molecular screening. Meta functionals are confirmed to produce poorly consistent results, and specific guidelines for constructing range-separated functionals for polarizability calculations are drawn out. Additionally, it was shown that many of the contemporary solvation models exhibit significant limitations in accurately capturing nonlinear optical properties. Therefore, further refinement in the current methods is pending. This extends to the statistical description as well: the mean absolute deviation descriptor is found to be deficient in rating various computational methods and should rather be replaced with the parameters of the linear correlation (the slope, the intercept, and the R²). Full article

We investigate whether and how the policy of establishing green finance pilot zones affects corporate environmental performance in China, by employing the DID model and taking 2324 Chinese A-share listed companies as the empirical sample. The main findings show that the green finance policy can significantly improve corporate environmental performance in the green finance pilot zones. The policy effect varies according to enterprise ownership, sector, and degree of environmental supervision. In particular, compared with private enterprises and enterprises subject to key pollution monitoring, the environmental performance of state-owned firms and non-key pollution-monitored firms is more positively affected by the green finance policy. Through a mechanism analysis, we find that corporate innovation and financial constraints can play partially mediating roles in the linkage of green finance policy and corporate environmental performance. Among them, the mediating effects of green innovation and financial constraints are more prominent in private enterprises and key pollution-monitored enterprises. However, although the green finance policy can positively influence bank loans obtained by enterprises, there is no evidence to suggest that bank credit plays a significant mediating role between the green finance policy and corporate environmental performance. Our findings are helpful for understanding the effect of green finance policy on environmental sustainability and could provide some references for policymakers. In particular, we suggest that private and key pollution-monitored enterprises should actively respond to the green finance policy, broaden financing channels, and enhance capability of green innovation, thereby improving their environmental performance. Full article

Against the backdrop of increasingly severe global carbon emissions and China’s commitment to achieving carbon peaking by 2030, accelerating the transition to a low-carbon economy has become an urgent priority. As fundamental microeconomic entities, enterprises play a crucial role in the national governance of carbon emissions. This study uses panel data on Chinese A share listed companies from 2019 to 2023 and employs fixed effects models that control for firm, year, and industry effect to analyze how ESG performance influences carbon emissions and through which mechanism. The findings indicate that improvements in ESG ratings significantly reduce firms’ carbon emissions. This effect operates primarily through the following two channels: (1) promoting green technological innovation, thereby enhancing environmental performance, and (2) increasing the attention of financial analysts, which strengthens external monitoring. The heterogeneity analysis further reveals that the mitigating effect of ESG improvement on carbon emissions is more pronounced in firms with a lower proportion of institutional ownership, while this effect is relatively weaker in firms with higher institutional ownership. This suggests that in contexts where institutional investors hold a smaller share, firms may place greater emphasis on the policy pressure and social responsibility expectations associated with ESG performance, thereby exhibiting stronger commitment to emission reduction actions. In contrast, in firms dominated by institutional investors, the implementation of ESG policy objectives may be partially compromised due to the investors’ short-term profit orientation. This study provides empirical evidence for firms to fulfill their environmental and social responsibilities and offers actionable insights for investors aiming to promote sustainable development. From a policy perspective, the findings also offer theoretical support for developing differentiated regulatory strategies based on variations in ownership and shareholding structures. Full article

Post-surgical complications are common complications following saphenectomy surgery, and strategies to facilitate its resolution are essential for postoperative recovery. This study evaluated the effects of adhesive elastic taping on edema control in patients undergoing saphenectomy. A randomized controlled clinical trial was conducted with 40 patients of both sexes, divided into two groups: intervention (IG), which received taping immediately after surgery combined with standard compression, and a control group, which received standard treatment with compression stockings (CG). Assessments were performed preoperatively and seven days after surgery, including limb volume (indirect calculation), edema (dielectric constant analysis), Skin Elasticity Assessment (durometer), pain (Visual Analog Scale—VAS), limb functionality (Lower Extremity Functional Scale—LEFS), and ecchymosis area (Image J, version 1.51). Both groups showed a significant increase in edema postoperatively (IG: p = 0.003; CG: p = 0.001). The intervention group exhibited a trend toward volume reduction (p = 0.069), better functionality (p = 0.006)—skin elasticity was assessed using a durometer—and fewer ecchymoses (p = 0.002). Only the control group showed a significant increase in tissue firmness (p = 0.012). No significant difference in pain was observed between groups (p = 0.203). The application of taping demonstrated beneficial effects on postoperative functional recovery and ecchymosis control following saphenectomy. Full article

This study examines the impact of environmental, social, and governance (ESG) practices on green innovation and financial performance among 174 publicly listed firms across ASEAN countries over the period from 2019 to 2023. Utilizing an unbalanced panel dataset of firms from key ASEAN economies, the analysis employs panel regression techniques. Green innovation performance is measured through innovation disclosures related to environmental technologies, while financial success is assessed via return on assets (ROA) and Tobin’s Q. The findings reveal that environmental and governance disclosure scores positively influence green innovation, whereas social scores exert a more immediate impact on financial performance. Moreover, green innovation is found to partially mediate the relationship between overall ESG practices and long-term market valuation. These results highlight the strategic role of ESG transparency in enhancing innovation-driven competitiveness, responsible business conduct, and sustainable employment across Southeast Asian markets. Implications are discussed for corporate managers, policymakers, and socially responsible investors. The study reinforces the case for ESG-aligned strategy as a pathway to both innovation, inclusive economic growth, and long-term competitiveness in ASEAN markets. Full article

This study examines the impact of overall Environmental, Social, and Governance (ESG) performance and its pillars on the default probability of Australian-listed firms. Using a panel dataset spanning 2014 to 2022 and applying the Generalized Method of Moments (GMM) regression, we find that firms with higher ESG scores exhibit a significantly lower likelihood of default. Disaggregating the ESG components reveals that the Environmental and Social pillars have a negative association with default risk, suggesting a risk-mitigating effect. In contrast, the Governance pillar demonstrates a positive relationship with default probability, which may reflect potential greenwashing behavior or an excessive focus on formal governance mechanisms at the expense of operational and financial performance. Furthermore, the analysis identifies trade credit financing (TCF) as a partial mediator in the ESG–default risk nexus, indicating that firms with stronger ESG profiles rely less on external short-term financing, thereby reducing their default risk. These findings provide valuable insights for corporate management, investors, regulators, and policymakers seeking to enhance financial resilience through sustainable practices. Full article