Piercing the corporate veil system and creditors protection: Based on the investigation of debt paying ability--Empirical evidence from the 2005 Company Law amendment.

This paper uses the difference-in-differences model to research how the "piercing the corporate veil" system marked by the 2005 Company Law amendment affects the level of corporate creditor protection. The research results show that private enterprises and local state-owned enterprises are sensitive and significant to this legal amendment. In contrast, local state-owned enterprises are more sensitive and have a stronger motivation to protect the interests of creditors. The motivation of companies with weaker profitability for creditor protection lasts not only for the year of law revision but also extends to the year of implementation. With the law's implementation, the growth effect of creditor protection for local state-owned enterprises has become more significant. Further analysis shows that the main findings of this article are more significant in companies with larger debt scales, companies with a higher year-on-year growth rate of operating income, companies with controlling shareholders, and companies with higher stock market capitalization. From an empirical research view, this paper explains the economic effect and mechanism of the whole corporate personality under the complete system and adds economic evidence for how the law acts on the capital market.

Determination of threshold values and heavy metal pollution assessment of soils in an industrial area in Ghana.

Industrial activities have the potential to pollute soils with a wide variety of heavy metals (HMs). In Ghana, however, assessment of HM pollution of soils in industrial areas remains limited. Accordingly, HM soil pollution in one of the industrial areas in Accra, Ghana was assessed. Soil samples were taken and analysed for HMs, including Fe, Zr, Zn, Ti, Sr, Rb, Mn, Pb, Cu, and Co, using X-Ray Fluorescence (XRF). HM geochemical threshold values (GTVs) were determined to establish soil HM pollution levels and identify areas needing remediation. Furthermore, risk assessments were conducted to evaluate the potential ecological and human health risks associated with these metals. The mean concentrations of Fe, Zn, Rb, Sr, Zr, Ti, Mn, Co, Cu, and Pb in the soils were: 27133.83, 147.72, 16.30, 95.95, 307.11, 4663.66, 289.85, 418.54, 44.97, and 112.88 mg/kg, respectively. Generally, the concentrations of HMs decreased with depth, although some lower layers exhibited elevated HM levels. Soil pollution levels were categorized as low for Fe, Rb, Zr, Ti, Mn, Co, and Cu; moderate for Sr and Zn; and considerable for Pb. Notably, the northwestern part of the study area displayed a considerable to very high degree of HM contamination. While HMs in the soils posed low ecological risk, the human health risk assessment indicated potential health effects from Co, particularly in children. The presence of HMs in the soils was noted to originate from both natural geological phenomena and human activities, including industrial operations, agricultural practices, landfill activities, and vehicular emissions.

Critical learning from industrial catalysis for nanocatalytic medicine.

Systematical and critical learning from industrial catalysis will bring inspiration for emerging nanocatalytic medicine, but the relevant knowledge is quite limited so far. In this review, we briefly summarize representative catalytic reactions and corresponding catalysts in industry, and then distinguish the similarities and differences in catalytic reactions between industrial and medical applications in support of critical learning, deep understanding, and rational designing of appropriate catalysts and catalytic reactions for various medical applications. Finally, we summarize/outlook the present and potential translation from industrial catalysis to nanocatalytic medicine. This review is expected to display a clear picture of nanocatalytic medicine evolution.

Systematic evaluation of integration between China's digital economy and sports industry: Two-stage grey relational analysis and vector autoregressive model.

OBJECTIVES: The development of the digital economy constitutes a key component of China's endeavors to advance towards "Digital China." The sports industry functions as a new catalyst for high-quality economic growth. This study systematically evaluated the integration between these two sectors. METHODS: First, we conducted two levels of grey relational analysis to assess their integration between 2016 and 2021. Second, we conducted a VAR analysis to determine whether their integration between 2009 and 2021 represents a causal relationship. RESULTS: At the macro level, the grey relational analysis reveals that the sports industry (grade = 0.770) ranked second among China's eight key economic sectors in terms of digital economy integration. At the meso level, a wide variation (ranging from 0.606 to 0.789) existed in the grade of integration between the digital economy and the sub-sectors of the sports industry. According to the VAR model, the digital economy does not Granger cause (p = 0.344) the growth of the sports industry. CONCLUSIONS: This study yielded two added values to the existing literature: First, there exists a sectoral imbalance in the digitization process; second, the explosive growth of the sports industry was not primarily caused by the digital economy. Accordingly, the "sports + digital" complex is still in the first wave of technological integration. We propose three policy recommendations, namely, sectoral synergistic development, overtaking via esports IP, and new economy and new regulation. Collectively, these findings provide updated insights for the digital transformation towards "building a leading sports nation" and "Digital China."

Assessing the relationship between the biochemical and the morphological factors (leaf surface area and leaf surface texture) of industrial and roadside plants.

The study of biochemical parameters provides an idea of the resistance of plants against air pollutants. Biochemical and Physiological parameters are studied with the help of Air pollution tolerance index (APTI). Fifteen plant species were evaluated to assess biochemical and APTI from two polluted sites (Phagwara Industrial area and Phagwara Bus stand area). The values of APTI were found to be highest for Mangifera indica (19.6), Ficus religiosa (19.3), and Ficus benghalensis (15.8) in the industrial area. On the roadside, Mangifera indica (16.8), Ficus benghalensis (16.5), and Ficus religiosa (16.4). Mangifera indica, Ficus religiosa, and Ficus benghalensis were found to be excellent performers in reducing pollution at both the sampling sites as per the APTI values. The order of tolerance was Mangifera indica > Ficus religiosa > Ficus benghalensis > Polyalthia longifolia > Mentha piperita in both the polluted sites. Morphological changes were observed in the plants, suggesting the possibility of pollution stress, which is probably responsible for the changes in biochemical parameters. As a result, the relationship between morphological and biochemical parameters of selected plant species growing in roadside and industrial areas was explored. The findings revealed that relative water content showed a significant positive and negative correlation with leaf surface texture and leaf surface area. On the other hand, ascorbic acid showed a significant positive correlation with them. In conclusion, it has been studied that morphological parameters including biochemical parameters can be proved to be important in investigating the ability of plants to cope with air pollution and in calculating tolerance index.

Measurement of efficiency and its drivers in the Chilean banking industry.

This paper estimates efficiency measures for the banking system in Chile for the period 2000-2019. In contrast to previous studies, we use input-distance functions, introduce the nonparametric slack-based model, and choose the intermediate inputs approach in determining inputs and outputs. Our results suggest that the Chilean system has achieved relatively high levels of efficiency, although with no significant variation over the sample period. Ownership (government, foreign and public) and size had a positive impact on efficiency. On average, mergers and acquisitions seem to have targeted highly efficient banks in order to improve the overall efficiency of the controlling institution in the short run. Other sources of efficiency gains could be an increase in bond funding or a reduction in expenses and capital holdings. The latter could be induced by deepening the local derivatives market.

Open innovation and confidentiality agreements as key factors of innovative performance in the manufacturing and service industries.

The innovative performance of manufacturing and service companies can be impacted by the existing relationship between open innovation (OI) and the generation of confidentiality agreements (NDAs) as a tool for the protection of intellectual property. Based on the analysis of a cross-sectional sample of 6,798 industrial companies (2019-2020) and 9,304 companies in the service sector (2017-2019) that are part of the directory of the National Administrative Department of Statistics (DANE) in its Technological Innovation and Development Survey (EDIT and EDITS), it can be suggested that the interaction of these two variables (OI and NDAs) generate positive effects for the manufacturing industry but negative ones for the service sector. It could be deduced that the positive effect is due to the greater tradition of OI in the manufacturing industry and the negative effect to the caution that the service sector presents when collaborating with external actors.

Environmental regulation, industrial structure and energy efficiency: Evidence from 30 provinces in China.

The government's environmental protection policy can significantly contribute to alleviating resource shortages and curbing environmental pollution, but the impact of various policy instruments implemented by the government on energy efficiency is unclear. Based on the panel data of 30 provinces in China from 2005 to 2021, this paper analyses the impact of environmental regulation and the industrial structure on energy efficiency from the perspective of resource taxes. The U-shaped relationship between environmental regulation and energy efficiency and between the optimization of industrial structure can significantly improve energy efficiency, and the optimization of industrial structure is conducive to weakening the initial inhibitory effect of environmental regulation. In addition, the analysis of regional heterogeneity showed that the impact of environmental regulation was stronger in the central and western regions, while the impact of industrial structure was stronger in the eastern and western regions. The conclusions of this study can help to expand the understanding of the relationship between environmental regulation and industrial structure on energy efficiency, provide policy enlightenment for the realization of green development and high-quality development, and provide Chinese examples and experiences for developing countries to improve energy efficiency.

The role of regulatory policies in organizational culture: Insights from the education industry.

On February 26, 2018 and July 24, 2021, the Chinese government respectively issued two significant regulatory policies to address the problems caused by off-campus training institutions in terms of students' extra-curricular and family financial burdens. These policies have had a tremendous and far-reaching impact on the off-campus training industry in China. With the help of these two events, we explored the role of industry-level regulatory policies in shaping and forming organizational culture. This paper adopts a text analysis method, combined with the dimensions of the Denison Organizational Culture Survey (DOCS) and MAXQDA 18 software, to obtain data on corporate culture. Then, the approaches of regression discontinuity in time (RDiT) and regression discontinuity (RD) designs with multiple cutoffs are used to estimate the policy treatment effect. This empirical research suggests that regulatory policies have a significant impact on corporate culture. Moreover, regulatory policies of varying degrees of strictness have differential effects on different dimensions of corporate culture. The research findings contribute to the theories of corporate culture and can guide enterprises to evaluate the impact of policies on corporate culture more clearly, thereby enabling them to make wiser operation decisions.

Collaborative servitization in service-oriented company: The case study of telco company.

There is a growing interest in the subject of product-service system (PSS) and collaborative servitization in academia and practice. However, the focus is on exploring the growth of manufacturing companies without specifically analyzing the growth of service companies in applying PSS. There are companies, especially in the telco industry, that expand their service business to complex bundles of products and services. The paper investigates PSS in the service company and the role of collaboration in different PSS development phases: idea generation, development and go to market phase. The study adopted case-based research conducted in international Telco organization. The research demonstrates how a company creates and commercializes integrated packets of products and services, it identifies partners company works with and the benefits and challenges of their cooperation. The study addresses collaboration with customers and identifies five different customer profiles according to their openness to participate in the development of PSS. The study highlights the importance of (1) collaboration models, (2) customer involvement, and (3) strategic focus in successful application of collaborative servitization. The findings complement the literature for collaborative servitization and offer concrete input for companies in terms of how to better organize business, profit from collaboration models and gain market advantage.

Exploration and future trends on spatial correlation of green innovation efficiency in strategic emerging industries under the digital economy: A social network analysis.

With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with ω-order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011-2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE.

Concentrations of Volatile Methyl Siloxanes in New York City Reflect Emissions from Personal Care and Industrial Use.

Volatile methyl siloxanes (VMS) are a group of organosilicon compounds of interest because of their potential health effects, their ability to form secondary organic aerosols, and their use as tracer compounds. VMS are emitted in the gas-phase from using consumer and personal care products, including deodorants, lotions, and hair conditioners. Because of this emission route, airborne concentrations are expected to increase with population density, although there are few studies in large urban centers. Here, we report summertime concentrations and daily variations of VMS congeners measured in New York City. Median concentrations of the 6 studied congeners, D3 (20 ng m-3), D4 (57 ng m-3), D5 (230 ng m-3), D6 (11 ng m-3), L5 (2.5 ng m-3), and L7 (1.3 ng m-3) are among the highest reported outdoor concentrations in the literature to date. Average congener ratios of D5:D4 and D5:D6 were consistent with previously reported emissions ratios, suggesting that concentrations were dominated by local emissions. Measured concentrations agree with previously published results from a Community Multiscale Air Quality model and support commonly accepted emissions rates for D4, D5, and D6 of 32.8, 135, and 6.1 mg per capita per day. Concentrations of D4, D5, D6, L5, and L7 and total VMS were significantly lower during the day than during the night, consistent with daytime oxidation reactivity. Concentrations of D3 did not show the same diurnal trend but exhibited a strong directional dependence, suggesting that it may be emitted by industrial point sources in the area rather than personal care product use. Concentrations of all congeners had large temporal variations but showed relatively weak relationships with wind speed, temperature, and mixing height.

The role of information industry convergence in energy transition.

To cope with global climate risks, promoting energy transformation has become a global consensus. China issued a reform policy in 2010 to promote the convergence of the three major information industries, namely broadcasting and television networks, telecommunications networks and the Internet (TPR policy). However, is the convergence of information industries able to promote energy transition? This study constructs a quasi-natural experimental framework using China's TPR policy as a representative case of industrial convergence. Using city-level panel data between 2003 and 2016 in China and a multi-period difference-in-differences model, this study examines the impact of TPR policy on energy transition. The results show that TPR policy positively contributes to energy transition at a 1% significance level. Extensive robustness tests support this finding. This positive effect is particularly evident in regions with less developed communications infrastructure and stricter environmental regulations. Mechanism analysis suggests that TPR policy promotes energy transition by improving the level of information networks, promoting technological innovation, and optimizing industrial structure. The findings of this paper emphasize the importance of information industry convergence in facilitating energy transformation.

Prediction analysis of carbon emission in China's electricity industry based on the dual carbon background.

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry.

Moss as a passive biomonitoring tool for the atmospheric deposition and spatial distribution pattern of toxic metals in an industrial city.

Anthropogenic pollution impacts human and environmental health, climate change, and air quality. Karabük, an industrial area from the Black Sea Region in northern Türkiye, is vulnerable to environmental pollution, particularly soil and air. In this research on methodological aspects, we analyzed the concentrations of six potential toxic metals in the atmospheric deposition of the city using the passive method of moss biomonitoring. The ground-growing terrestrial moss, Hypnum cupressiforme Hedw., was collected during the dry season of August 2023 at 20 urban points. The concentrations of Cr, Cu, Cd, Ni, Pb, and Co were determined in mosses by the ICP-MS method. Descriptive statistical analysis was employed to evaluate the status and variance in the spatial distribution of the studied metals, and multivariate analysis, Pearson correlation, and cluster analysis were used to investigate the associations of elements and discuss the most probable sources of these elements in the study area. Cd and Co showed positive and significant inter-element correlations (r > 0.938), representing an anthropogenic association mostly present in the air particles emitted from several metal plants. The results showed substantial impacts from local industry, manufactured activity, and soil dust emissions. Steel and iron smelter plants and cement factories are the biggest emitters of trace metals in the Karabük area and the primary sources of Cr, Cd, Ni, and Co deposition.

Geographic information system-based determination of priority monitoring areas for hazardous air pollutants in an industrial city.

Industrial cities are hotspots for many hazardous air pollutants (HAPs), which are detrimental to human health. We devised an identification method to determine priority HAP monitoring areas using a comprehensive approach involving monitoring, modeling, and demographics. The methodology to identify the priority HAP monitoring area consists of two parts: (1) mapping the spatial distribution of selected categories relevant to the target pollutant and (2) integrating the distribution maps of various categories and subsequent scoring. The identification method was applied in Ulsan, the largest industrial city in South Korea, to identify priority HAP monitoring areas. Four categories related to HAPs were used in the method: (1) concentrations of HAPs, (2) amount of HAP emissions, (3) the contribution of industrial activities, and (4) population density in the city. This method can be used to select priority HAP monitoring areas for intensive monitoring campaigns, cohort studies, and epidemiological studies.

Can energy saving and emission reduction policies promote green transformation of industrial enterprises--The Case of China.

In the context of the continued advancement of the green economy transition, the proactive pursuit of carbon emissions reduction and the early attainment of carbon neutrality goals have emerged as essential components in promoting high-quality economic development. Not only does it contribute to the creation of a community of human destiny, but it is also vital to the realization of sustainable development for human civilization. A dynamic evolutionary game model, which encompasses the interactions among government, enterprises, and the public, was constructed to examine the inherent impact mechanisms of the behavior of three players on the development of a green economy under the context of energy saving and emission reduction subsidies. The results showed that the incentive and punishment mechanisms served as effective tools for harmonizing the interests of system members. Within the mechanisms, the public demonstrated a higher sensitivity to rewards, while enterprises exhibited greater responsiveness to fines. Consequently, the government could influence the behavior of enterprises by incentivizing the public to serve as a third-party inquiry and oversight body. Simultaneously, the government could encourage enterprises to expedite green technology innovation by employing a combination of incentive and punishment mechanisms.

How can industrial intelligence change the employment structure of the floating population?

As the wave of industrial intelligence (AI) swept, the demographic dividend era in the Chinese labor market continued to decrease. This study aimed to explore how AI reshaped the labor employment structure of the floating population. Additionally, it clarified the internal mechanism of AI on the employment structure of the floating population based on the existing AI model and the theoretical model of AI technology. At the same time, the workforce was divided into high-, medium-, and low-skilled groups according to education level. Empirical analysis was conducted using relevant data from 31 Chinese provinces spanning from 2012 to 2018. The aim was to test the impact of AI technology on the employment of different types of floating populations. The results indicated that: (1) industrial robots impacted heterogeneous skilled floating population labor by bipolar promotion and central substitution. (2) The application of industrial robots had a promotion effect on unfinished school and primary school groups, a substitution effect on middle school, high school/technical secondary school, and college specialties, and a promotion effect on college undergraduate and graduate students. (3) Distinguish employment status, industrial robot application had a significant negative impact on low-skilled employees and significant positive effects on high-skilled employers. Hence, it was recommended to put forward corresponding policy suggestions to address this issue.

Hazard estimation in urban home garden soils in an industrial area using microarthropods, soil properties and GIS modelling: an integrated approach.

The use of soil microarthropods as indicators of soil pollution in home gardens of an industrial area has been covered in this study. Soil samples were collected from 25 home gardens in three zones in Eloor during summer and North East monsoon from 2014 to 2018, for the study of soil microarthropods, soil properties, soil nutrients, and trace elements. The relationships among QBS-ar, microarthropod abundance, soil properties, and soil nutrients, were used to estimate the pollution hazard of the industrial area. The microarthropods present in the study area were Coleoptera, Hymenoptera, Diplopoda, and Araneae. A prominent study area feature was the absence of Collembola and Acari. The QBS-ar index score in these regions showed that the home gardens located adjacent to the industrial area showed low soil quality, with soil quality class values ranging from 1 to 2 throughout the study period. Discriminant analysis of soil nutrients with soil properties and microarthropod abundance showed that in Zone 1 and Zone 2, the data in 2018 was very well discriminated compared to other years. The hazard assessment in the Eloor region showed various levels of hazard zonation: Zone 1 with high-hazard and medium-hazard areas, Zone 2 with medium-hazard areas, and Zone 3 with low- and medium-hazard areas. The study is one of the first kinds that have used QBS-ar scores and soil properties along with soil nutrients and trace elements for estimating the level of hazard in home garden agroecosystems and thus points to an easy, simple, and practical approach in the monitoring and management of soil ecosystems.

Do political connections facilitate or inhibit firms' digital transformation? Evidence from China's A-share private listed companies.

Given the advent of the digital era, digital transformation has become necessary for enterprise development. Political connections are the most important resources for enterprise development in most countries. However, the impact of political connections on corporate digital transformation has yet to be verified. This study uses ERNIE, a large language model, to construct a measurement of corporate digital transformation from the perspective of digital technology application through a textual analysis of the annual reports of A-share privately listed companies from 2008 to 2020 and analyzes the impact of political connections on corporate digital transformation and its mechanism of action. The findings demonstrate that political connections have a significant inhibitory effect on corporate digital transformation. This conclusion still holds after a series of robustness and endogeneity tests. The mechanism analyses demonstrate that political connections primarily affect corporate digital transformation through three mechanisms: weakening risk, inhibiting innovation, and enhancing resource crowding. We theoretically expand the understanding of the economic impact of political connections and provide new ideas for accelerating enterprise digital transformation from the perspective of policy makers.