Common institutional investors and the quality of management earnings forecasts-Empirical and machine learning evidences.

Based on the data of the Chinese A-share listed firms in China Shanghai and Shenzhen Stock Exchange from 2014 to 2021, this article explores the relationship between common institutional investors and the quality of management earnings forecasts. The study used the multiple linear regression model and empirically found that common institutional investors positively impact the precision of earnings forecasts. This article also uses graph neural networks to predict the precision of earnings forecasts. Our findings have shown that common institutional investors form external supervision over restricting management to release a wide width of earnings forecasts, which helps to improve the risk warning function of earnings forecasts and promote the sustainable development of information disclosure from management in the Chinese capital market. One of the marginal contributions of this paper is that it enriches the literature related to the economic consequences of common institutional shareholding. Then, the neural network method used to predict the quality of management forecasts enhances the research method of institutional investors and the behavior of management earnings forecasts. Thirdly, this paper calls for strengthening information sharing and circulation among institutional investors to reduce information asymmetry between investors and management.

Carbon emission fluctuations of Chinese inter-regional interaction: a network multi-hub diffusion perspective.

The "double-carbon" policy is a new opportunity for the transformation of China's production sector. With steady economic growth, each province has proposed specific policies aimed at cleaner production. However, the interactions between regions and the complex linkages between industries have hindered the implementation of the "double-carbon" policy. In order to address this issue, we introduced a complex network framework with multiple industries at a national level. The framework aimed to clarify whether there is fluctuation diffusion in China's multi-province multi-industry carbon emission system, to identify key industries and regions, and to answer the question of "who" is the most effective in governance. The results showed that the fluctuations of industrial carbon emissions had a cross-regional diffusion effect in China indeed. The diffusion capacity of industry fluctuation depends on whether the industry is located at a "hub" position in the network. Hub industries with strong capacity can spread the carbon emission fluctuation of themselves and upstream or downstream industries to the whole country through regional interactions. This characteristic of the hub industry should be taken into account in governance to maximize the effectiveness of emission reduction. Shandong and Inner Mongolia, as important provinces for the production of intermediate products and energy chemicals in China, had a greater role to play in global carbon supply push from their hub industries than in the demand pull. The pulling capacity of Beijing-Tianjin-Hebei region to the national carbon demand side was greater than that of Yangtze River Delta and Pearl River Delta. These findings might have implications for environmental and economic policymaking, particularly with regard to cross-provincial coordinated systemic solutions and policy anchors for synergy with industries.

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm.

Learning about the regional business model is essential for the sustainable development of the regional economy. From the perspective of urban renewable energy, city A is the product of energy development. This paper analyzes the current situation and existing problems of the industrial model of city A through fuzzy k-means clustering algorithm. The results show that although the optimization of industrial structure in city A has achieved some results, the more intuitive problems mainly include low labor productivity of the primary industry, strong resource dependence, insufficient extension of industrial chain, and slow development of technology intensive industries. This paper uses fuzzy k-means clustering algorithm to select the leading industries from the perspective of the current situation of leading industries, urban development pattern, and regional policies in city A. The results show that, as a renewable resource-based city, the leading industries suitable for the current development of city A include manufacturing, power, alkali gas and water production and supply, transportation, warehousing and postal industry, leasing, and business services. The results of fuzzy k-means clustering algorithm are quite excellent, and the accuracy rate is 93.3%. This paper uses the grey dynamic linear programming model to predict the future development of the Urban A business model and combines the selection of key functions to obtain the best business model: deep and efficient technical equipment as a good goal, achieved through regional logistics, transportation, new services, etc., to enhance the output value of the tertiary industry in city A and optimize the internal structure of the secondary industry in city A.

Energy efficiency of the industrial sectors in Beijing-Tianjin-Hebei urban agglomeration: does technological gap matter?

As the political and technological innovation center of China, Beijing-Tianjin-Hebei urban agglomeration (BTHUA) is an important engine of national economic development. However, the BTHUA is faced with uneven industrial development and environmental pollution problems. Energy efficiency of the industrial sector, critical to energy conservation and environmental protection, is the key to achieving green economic transformation. For this reason, this study adopts the parametric meta-frontier approach to measure the industrial total-factor energy efficiency (TFEE) of the BTHUA, centering on the evaluation of regional technology gap ratio (TGR). Empirical results indicate that there are significant regional disparities of industrial TFEE in the BTHUA. In particular, industrial TFEE tends to be underestimated without considering technological heterogeneity in production technology. The TGRs of manufacturing cities, tourist cities, and the modernized metropolis (Beijing) are the highest among the region. On this basis, the influencing factors of industrial TFEE of the BTHUA are further accessed based on the fixed effects model and the Tobit model. This article verifies that the evaluation of TFEE in the BTHUA must take regional technological gap into account, and provides additional empirical evidence on how to promote coordinated regional industrial development and energy efficiency improvement.

The clean energy claims of BP, Chevron, ExxonMobil and Shell: A mismatch between discourse, actions and investments.

The energy products of oil and gas majors have contributed significantly to global greenhouse gas emissions (GHG) and planetary warming over the past century. Decarbonizing the global economy by mid-century to avoid dangerous climate change thus cannot occur without a profound transformation of their fossil fuel-based business models. Recently, several majors are increasingly discussing clean energy and climate change, pledging decarbonization strategies, and investing in alternative energies. Some even claim to be transforming into clean energy companies. Given a history of obstructive climate actions and "greenwashing", there is a need to objectively evaluate current and historical decarbonization efforts and investment behavior. This study focuses on two American (Chevron, ExxonMobil) and two European majors (BP, Shell). Using data collected over 2009-2020, we comparatively examine the extent of decarbonization and clean energy transition activity from three perspectives: (1) keyword use in annual reports (discourse); (2) business strategies (pledges and actions); and (3) production, expenditures and earnings for fossil fuels along with investments in clean energy (investments). We found a strong increase in discourse related to "climate", "low-carbon" and "transition", especially by BP and Shell. Similarly, we observed increasing tendencies toward strategies related to decarbonization and clean energy. But these are dominated by pledges rather than concrete actions. Moreover, the financial analysis reveals a continuing business model dependence on fossil fuels along with insignificant and opaque spending on clean energy. We thus conclude that the transition to clean energy business models is not occurring, since the magnitude of investments and actions does not match discourse. Until actions and investment behavior are brought into alignment with discourse, accusations of greenwashing appear well-founded.

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents.

Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors' potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor's future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation.

Research on the spatial association network structure for innovation efficiency of China's new energy vehicle industry and its influencing factors.

It is of great significance to study the spatial network of the new energy vehicle (NEV) industry innovation efficiency and its factors to promote the rational allocation of innovative resources and the coordinated development of Chinese NEV industry. First, the Super Efficiency Data Envelope Analysis model is used to measure innovation efficiency in the NEV industry in Chinese provinces, and based on the results, the improved gravity model is applied to construct a spatial correlation network. Then, by applying social network analysis (SNA) to study NEV industry development node spatial correlations, we conclude that there is no overall hierarchical structure. The SNA are applied to examine spatial correlations with respect to NEV industry innovation efficiency in each province, and to analyze the role and position of each province in the spatial correlation network. Finally, the influencing factors of spatial correlation of the innovation efficiency of China's NEV industry has been discussed. The result shows that the difference in spatial distance and R&D investment has a significant impact on the spatial correlation of the NEV industry.

Understanding the Green Development Behavior and Performance of Industrial Enterprises (GDBP-IE): Scale Development and Validation.

Industrial enterprises have provided outstanding contributions to economic development in countries around the world. The green development of industrial enterprises has received widespread attention from researchers. However, existing research lacks the tools to scientifically measure the green development behavior and performance of industrial enterprises. According to the theory of green development behavior and performance of industrial enterprises (GDBP-IE), the aim of this paper is to provide a tool for scientifically measuring such behavior and performance. This paper determined the initial scale through literature analysis and expert discussions and obtained valid samples from 31 provincial administrative regions in China through field and online surveys (N = 853). The exploratory factor analysis method was used to test the reliability and validity of the scale. The main conclusions are as follows: (1) The reliability and validity of the GDBP-IE scale are good; (2) the GDBP-IE scale, with a total of 70 items, comprises four sub-scales: The internal factors sub-scale, the external factors sub-scale, the green development behavior of industrial enterprises sub-scale, and the green development performance of industrial enterprises sub-scale. Among them, the internal factors sub-scale, with a total of 13 items, consists of two dimensions: Corporate tangible resources and corporate intangible resources. The external factors sub-scale, with a total of 23 items, consists of three dimensions: Market environment; public supervision; policy and institutional environment. The green development behavior of industrial enterprises sub-scale, with a total of 18 items, consists of two dimensions: Clean production behavior and green supply chain management practice. The green development performance of industrial enterprises sub-scale, with a total of 16 items, comprises three dimensions: Corporate social performance, corporate financial performance, and corporate environmental performance. The findings enrich the research on corporate organizational behavior, green behavior, and green development system theory, and provide tools for further empirical testing. The development and verification of green development behavior and performance of industrial enterprises can help guide various types of industrial enterprises in transforming to green development and can provide a reference for the government to formulate targeted green development policies.

Optimal Strategies of Product Price, Quality, and Corporate Environmental Responsibility.

With the awakening of environmental consciousness, more and more firms desire to go "green" by shifting their focus of corporate social responsibility (CSR) from charitable contributions to environmental actions called corporate environmental responsibility (CER). We develop a monopoly differential game to depict optimal corporate strategies of product price, quality, and CER. Using the Hamilton-Jacobi-Bellman (HJB) equation, we analyze optimal feedback equilibrium strategies for pricing and investing in both quality and CER with/without government subsidies. Numerical simulations show that government subsidy can improve CER and profit.

An Evolutionary Game Model for Industrial Pollution Management under Two Punishment Mechanisms.

In recent years, with the rapid development of the economy, industrial pollution problems have become more and more serious. This paper constructs an evolutionary game model for industrial pollution between the local governments and enterprises to study the dynamic evolution path of a game system and the evolutionary stable strategy under two punishment mechanisms. The results show that, in a static punishment mechanism (SPM), the strategy between governments and enterprises is uncertain. Moreover, the evolutionary trajectory between governments and enterprises is uncertain. However, under the dynamic punishment mechanism (DPM), the evolution path between governments and enterprises tends to converge to a stable value. Thus, the DPM is more conducive than the SPM for industrial pollution control.

Occupational Health Risk Assessment in the Electronics Industry in China Based on the Occupational Classification Method and EPA Model.

The awareness of occupational health risk management in the electronics industry is weak in China, and many Chinese occupational health management regulations have not been effectively implemented. China's current occupational hazards classification method and the Environmental Protection Agency (EPA) inhalation risk assessment model recognized internationally were used to perform health risk assessments for a chip manufacturing company in the electronics industry in order to determine the existing problems and put forward the optimization proposals of the occupational hazards classification method in China. The results showed that the detected concentrations of toxic and harmful chemicals in all testing points did not exceed the occupational health exposure limits in China. According to the EPA inhalation risk assessment model, the highest values of non-carcinogenic risks of ammonia, chlorine, fluoride, sulfuric acid, hydrogen chloride, ethylene glycol, phosphine, boron trifluoride, isopropanol, benzene, and xylene were 5.10, 67.12, 1.71, 45.98, 1.83, 1.43, 160.35, 46.56, 2.52, 5.55, and 5.37, respectively, which means workers in electronic chip manufacturing companies exposed to these chemicals have higher occupational health risks. However, on the basis of the occupational hazards classification method, the occupational health risks of exposure to the toxic and hazardous chemicals are relatively harmless operations. The evaluation results of the EPA inhalation risk assessment model are generally higher than those of the occupational hazards classification method. It's recommended to refine the value of occupational exposure limit B, taking more characteristics of the hazard factors into account and fuzzifying the parameters to optimize the occupational hazards classification method. At the same time, it is suggested that the electronic chip manufacturing company should conduct anti-virus risk management covering in three aspects: increasing the awareness of occupational hazards, enhancing system ventilation, and improving personal health management measures.

Proceedings of the 2017 Viral Clearance Symposium Session 5: Facility Risk Mitigation.

The discussion on facility risk mitigation was included for the first time at the 2017 Viral Clearance Symposium. A few topics were discussed in this session, including sanitization/cleaning against viruses, viral segregation, as well as the definition of a "functionally closed" system.Virus inactivation by disinfectants is critical for the biotechnology industry. The efficacy can differ, depending on whether applied to surfaces, in solutions, or in gas phases, as well as the respective disinfectants (i.e., peracetic acid/hydrogen peroxide-based, hypochlorite-based, or glutaraldehyde-based).Most equipment used in the biotech industry can be cleaned or sanitized by alkaline solutions. Many of these methods were studied regarding their virus reduction potential and were defined considering alkaline concentration, time, and temperature.Virus clearance may be compromised if cross contamination or carryover happens from an early step with potentially a higher level of virus to a later step in the purification process (i.e., after virus removal or inactivation). Critical potential carryover (Vcpc) is defined as the volume of carryover that will significantly affect the overall virus clearance of a purification process. Based on the evaluation of critical potential carryover, mitigation actions can be introduced to avoid such carryover.Appropriate segregation within manufacturing facilities is required by regulators and utilized by manufacturers to ensure that the final product has appropriate safety margins. However, consensus around basic definitions and approaches related to facility segregation is lacking. To address this gap, the member companies of the Consortium on Adventitious Agent Contamination in Biomanufacturing have begun a project with the goal of developing a definition for a "functionally closed" manufacturing system.LAY ABSTRACT: The discussion on facility risk mitigation was included for the first time at the 2017 Viral Clearance Symposium. The topics discussed in this session included sanitization/cleaning against viruses, viral segregation, as well as the definition of a "functionally closed" system.Virus inactivation by disinfectants is critical for the biotechnology industry. The efficacy can differ, depending on whether applied to surfaces, in solutions, or in gas phases, as well as the respective disinfectants.Most equipment used in the biotech industry can be cleaned or sanitized by alkaline solutions. Many of these methods were studied regarding their virus reduction potential and were defined considering alkaline concentration, time, and temperature.Virus clearance may be compromised if cross contamination or carryover happens from an early step with potentially a higher level of virus to a later step in the purification process (i.e., after virus removal or inactivation).Regarding segregation within manufacturing facilities, the member companies of the Consortium on Adventitious Agent Contamination in Biomanufacturing have begun a project with the goal of developing a definition for a "functionally closed" manufacturing system. During this session, the current definition was discussed.

Qualitative and quantitative differences between common occupational health risk assessment models in typical industries.

OBJECTIVE: The differences in the methodologies of various occupational health risk assessment (OHRA) models have not been extensively reported. We aimed to understand the qualitative and quantitative differences between common OHRA models in typical industries. METHODS: The Environmental Protection Agency (EPA), Australian, Romanian, Singaporean, International Council on Mining and Metals (ICMM), and the Control of Substances Hazardous to Health (COSHH) models were evaluated, and a theoretical framework was established for a comparative study. RESULTS: Qualitative comparisons showed that each OHRA model had its own strengths and limitations, and exhibited a diverse distribution at different levels for each evaluation indicator. The Singaporean, COSHH, and EPA models had a much higher comprehensive advantage than the other models for all indicators. Quantitative comparisons demonstrated that these three models also had a stronger ability to distinguish the difference in risk ratios between different industries. The Singaporean model had the strongest correlation with the other models. CONCLUSION: Each model possessed its own strengths and limitations depending on its unique methodological principles. Combining the EPA, Singaporean, and COSHH models might be advantageous for developing an OHRA strategy. More studies comparing multiple models in key industries are required.

Spatial econometric analysis of factors influencing regional energy efficiency in China.

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Is ownership the decisive factor in collaborations between occupational health services and client companies?

BACKGROUND: Swedish employers are required to use external resources such as Occupational Health Services (OHS providers) if their own knowledge of occupational health and safety is insufficient. Some large employers have their own in-house OHS units but it is more common to engage the services of an external provider. However, no studies have been carried out from a critical perspective regarding how ownership of the OHS provider is related to a successful collaboration with client companies. OBJECTIVES: This study explores the extent to which the six key factors for a successful collaboration are related to ownership and seeks to identify the challenges that the different models of ownership pose. METHODS: Interviews with 15 client companies and their OHS providers were conducted in order to identify key factors in achieving a successful collaboration with an OHS provider. This study utilizes existing data to identify challenges related to ownership. RESULTS: Two key factors were identified with challenges related to ownership of the OHS provider: The importance of having a long-term perspective when building a relationship; and ensuring that collaboration extends beyond the client's HR Department to the various organisational levels of the company. CONCLUSIONS: Whatever form the ownership of an OHS provider may take, each comes with its own specific set of challenges that must be managed in order to achieve a successful collaboration with the client company.

[OCCUPATIONAL RISK ASSESSMENT IN MODERN CONDITIONS OF EXPLOITATION OF POLYURETHANEFOAM INDUSTRIES].

In the article there are presented data on the evaluation of occupational risk on two types of modern production of polyurethane foam (PUF), one of which is a large-tonnage fast-growth production, the 2nd type is semidomestic industry being different in small volume of output products. An analysis and evaluation of occupational exposure to large-scale production was performed patient-specifically with the use of elaborated individual cards, where there was introduced information about occupational route, the level of harmful factors of the working environment in all the years of work, the duration of exposure. The research results allowed to establish that the occupational risk in representatives of the main professions in the large-scale production (operators and handlers) is referred to a class of working conditions 3.2, which corresponds to the risk categories--moderate (Important), and demonstrates the need for further improvement of the system of preventive measures. At the small production working conditions were characterized by the presence of a large number of manual operations and comply with Class 3.3--category of professional risk-high (Unbearable). To reduce the risk to the health of workers of this type of production it is necessary to develop documents, that will increase the responsibility of employers to ensure safe working conditions.