Energy Consumption Of Enterprise Research Articles

Multilayer asset association network, green technical cooperation innovation, and default risk: Evidence from China's high energy-consuming industries

High energy-consuming industries are expected to play a significant role in energy conservation and emissions reduction. This study collects data on China's high energy-consuming listed companies from 2009 to 2022. Using the complex network theory, we construct a multilayer asset association network for high energy-consuming enterprises and examine how different layers and totality affect default risk. The results revealed that node-weighted degree centrality in the asset association networks of high energy-consuming enterprises, particularly in the guarantee association network, significantly increased default risk. Further mechanistic analysis reveals that the level of green technical cooperation innovation mitigates the impact of increased weighted degree centrality on the default risk of high energy-consuming enterprises. For high energy-consuming enterprises located in the eastern region, central region or non-heavily polluting industries, the influence of weighted degree centrality in the asset association network on default risk is more significant. This study enriches complex network research and provides guidance for managing default risk in high energy-consuming enterprises. Additionally, these studies align with global trends toward enhanced asset transparency, sustainability, and financial resilience, and contribute emerging markets to the transition toward more sustainable energy practices.

Towards Green and Low-Carbon Transformation via Optimized Polygeneration System: A Case Study of the Iron and Steel Industry

Polygeneration systems have significant potential for energy conservation and emission reduction and can effectively promote green and low-carbon development in energy-intensive industries, such as the iron and steel industry. However, its application faces the difficulty in technology selection under multiple objectives simultaneously, which is to determine the technology portfolio to achieve the synergy of energy conservation goals and air pollutant emission reduction goals, as well as ensure the economic benefits of the enterprises. This study investigated a case polygeneration system where the iron and steel plant are the core with four polygeneration paths and twenty polygeneration technologies. A multi-objective optimization model is developed to select the optimal technology combination of each polygeneration path under energy conservation, emission reduction, and cost control objectives, which is solved by the non-dominated sorting genetic algorithm-II (NSGA-II). The optimal results can reach significant energy conservation and emission reduction effects while obtaining economic benefits. However, synergistic and conflicting relationships among the objectives exist in both scales of iron and steel plants. The final decision scheme can achieve the mitigations equivalent to 15.9–27.1% and 16.3–42.6% of the energy consumption and air pollutant emissions of the steel enterprises with annual production of 3 Mt/a and 9 Mt/a, respectively. There are thirteen and twelve technologies that are selected as the final decision scheme in the polygeneration system in these two case enterprises. These findings demonstrate the significant roles the polygeneration system plays and provide critical insights and methodology in the technical selection of the polygeneration system.

The impact of sustainable development policy for resource-based cities on green technology innovation: Firm-level evidence from China

The sustainable development policy targeting resource-based cities (RBC) is a critical measure initiated by China's government to transform these cities. Green technology innovation (GTI) has surfaced as a pivotal route in achieving sustainable development in RBCs. However, whether implementing this policy can induce GTI remains underexplored. To fill this gap, exploiting the National Plan for Sustainable Development of Resource-based Cities (2013–2020) (NPSDRC) as a quasi-natural experiment, we employ the difference-in-differences (DID) method to examine the influence of NPSDRC on corporate GTI and potential mechanisms. We observe that NPSDRC significantly reduces the GTI of RBC enterprises. Mechanism analysis reveals that NPSDRC escalates environmental governance costs and decreases R&D investment, impeding corporate GTI. Meanwhile, our findings suggest that providing more bank loans and tax incentives could weaken this adverse effect on corporate GTI. Heterogeneity results indicate that non-SOEs, enterprises with weak financing capabilities, enterprises with long-sighted vision, and high energy consumption enterprises are more susceptible to the influence of NPSDRC. This study offers empirical evidence for countries seeking to employ policies to drive the transformation of RBCs.

Does executive environmental protection experience reduce enterprise energy consumption intensity?

This study examines the problem of enterprise energy consumption intensity from the perspective of executive environmental protection experience using data for China's A-share listed enterprises from 2007 to 2021. It is revealed that executive environmental protection experience has negatively impact on the enterprise energy consumption intensity. Moreover, the negative effect of executive environmental protection experience on enterprise energy consumption intensity is particularly pronounced in non-state-owned and low-energy consuming enterprises. According to mechanism study, the three primary approaches are low-carbon technology innovation, enterprise environmental protection investment, and recruiting green investors. In addition, media attention positively moderates the relationship between executive environmental protection experience and enterprise energy consumption intensity. The conclusions help to understand the influence mechanism of executive environmental protection experience on the enterprise energy consumption intensity at the micro level and have implications for pushing enterprise to save energy.

Factor mismatch measurement of resource-based cities: Evidence from all-round optimization total factor productivity decomposition framework

In-depth analysis of the factors affecting the transformation of resource-based cities can provide effective support for the transformation and development of resource-dependent regions. How to comprehensively identify the factors affecting the transformation of resource-based cities is a complex problem. This study starts from the total factor productivity model and focuses on the two core basic factors that affect the transformation process of cities reliant on resources. Economic benefits and energy efficiency, respectively, from the economic benefit analysis framework and energy efficiency analysis framework for reconstruction, the two frameworks are combined with the use of distorted prices of resource elements to solve the problem that the synergistic effect of economic benefits and energy efficiency can not be measured. In order to quantitatively analyze the factors that affect the development efficiency of cities reliant on resources under the single or synergistic effect of the comprehensive framework, this study optimizes the directional distance function from three perspectives: exogenous weight, direction vector endogeneity, and absolute distance transformation relative distance, thus achieving an accurate assessment transformation efficiency of cities reliant on resources. Considering the impact of the new coronavirus epidemic, this study only selected the data of resource-based cities from 2003 to 2018, and found through model calculation that the impact on the transformation of cities reliant on resources: (1) Labor mismatch is mainly achieved by affecting the structure about the production of resource-based enterprises and industrial human resources; (2) Capital mismatch is mainly realized by affecting the production of resource-based enterprises; (3) Energy mismatch is mainly achieved by affecting high energy consumption enterprises and low production technology level enterprises. Further research shows that the main objects of these factors are the four parts of production technology level, energy consumption, total factor productivity and industrial structure. Through these contents, they affect environmental efficiency and deeply affect the transformation process of resource-based cities.

Energy Saving Analysis of Coal Gas Resource Utilization in Iron and Steel Enterprises

The article discusses the preparation of a gas balance sheet, as well as the recovery, storage, transportation, and use of gas. An analysis was conducted on the occurrence and consumption quotas of various gas media, and specific energy-saving measures were elaborated for each process. This provides a theoretical reference for saving gas and reducing energy consumption in steel enterprises.

Impact of Enterprise Digital Transformation on the Efficiency of Total Factor Energy Utilization

With the advent of the information age and the rapid progress of technology, it has become inevitable for enterprises to move towards digital transformation. Energy is one of the most vital material bases for national economic and social development, which plays a vital role in national economic growth. How to use energy efficiently has been the core factor to measure the sustainable development potential of an enterprise. Based on the data of listed companies in China, this paper empirically analyzes the impact of enterprise informatization on energy efficiency from different perspectives. Studies have shown that the degree of enterprise informatization has a direct relationship with its energy efficiency. At present, the overall informatization of enterprises in various regions of China is low. However, with the continuous popularization of digital technology and applications, it has a certain inhibitory effect on enterprise energy consumption, with the effect becoming more and more apparent. Especially during the digital transformation, the role of state-owned enterprises in promoting total factor energy consumption has been more significant. Therefore, from the perspective of digital transformation, it is of great significance to study the energy efficiency of state-owned enterprises. This research explores the significant differences in energy efficiency among various industries, and the adoption of digital transformation strategies will help narrow these differences and further promote energy efficiency improvement across the industry. In addition, through the analysis of typical cases, this topic reveals the main problems faced by enterprises in the process of digital transformation and their causes, which puts forward corresponding countermeasures and suggestions. This study can provide a solid theoretical basis for the positive role played by Chinese enterprises and related departments during the digital transformation.

Evaluation method for the impact of digital finance on the environmental performance of manufacturing industry

ABSTRACT A new evaluation method for the impact of digital finance on the environmental performance of the manufacturing industry is proposed to improve the accuracy of evaluation results and provide reliable data for enterprise development. Establish a scientific and comprehensive evaluation index system that includes environment, cost-effectiveness, life cycle, and sustainable development. Collect sample data through indirect measurement and direct measurement methods through questionnaire surveys and standardize each data through the measurement of digital economy development level to eliminate differences between different indicators. Based on the constructed evaluation indicator system and sample data collection results, the weights of each evaluation indicator are determined by establishing a projection pursuit model. The fuzzy comprehensive evaluation method and the analytic hierarchy process are used to obtain the fuzzy comprehensive evaluation results of environmental performance based on the projection pursuit model to evaluate the impact of digital finance on the environmental performance of the manufacturing industry. The experimental results show that compared with traditional business models, digital business models can effectively reduce energy consumption, operating costs, and logistics transportation costs of enterprises, improve resource utilization efficiency, and outperform traditional methods in evaluation accuracy, recall rate, and efficiency, verifying the effectiveness of this method.

Optimization method for multi-process energy consumption in iron and steel enterprises under the coordinated use of comprehensive energy

Sustainable development goals, such as energy conservation, emission reduction, cost reduction, and efficiency enhancement, present pressing challenges for the iron and steel industry. Process optimization technology for efficient production, energy conservation, and consumption reduction in the steel manufacturing process is based on the coordination of material and energy flow. Therefore, this article takes the production process of a converter steelmaking plant as the object, considers the regulatory requirements of multi-process and multi constraint operation optimization under the cooperation of production organization and energy conservation and consumption reduction, and it explores a production scheduling optimization method for steelmaking plants oriented towards material flow and energy flow synergy. Based on the characteristics of the problem space, this study suggests a hybrid genetic algorithm with local search (MOHGALS) that employs both standard and advanced evolution techniques. Tests on concrete problems demonstrate that the MOHGALS approach yields a superior set of multi-objective Pareto schemes. Additionally, random-generated test cases were used to evaluate the algorithm’s performance. The outcomes show that MOHGALS performs better than competing algorithms on multi-objective evaluation indicators, and that the suggested improved evolution approach may effectively boost the algorithm’s performance.

Local Government Competition, Environmental Regulation and the Investment Efficiency of High Energy-Consuming Enterprises

Local Government Competition, Environmental Regulation and the Investment Efficiency of High Energy-Consuming Enterprises

RETRACTED ARTICLE: Digital transformation, green innovation, and carbon emission reduction performance of energy-intensive enterprises

Digital transformation and green innovation are powerful initiatives to achieve carbon peaking, carbon neutrality targets and high-quality economic development. Using a sample of high energy-consuming listed enterprises from 2012 to 2021, a double fixed-effect model is constructed to verify the effect of green innovation on the carbon emission reduction performance of high energy-consuming enterprises, and digital transformation is used as a moderating variable to analyze the inner mechanism of green innovation affecting the carbon emission reduction performance of high energy-consuming enterprises under the effect of digital transformation. The empirical results show that green innovation can significantly improve the carbon emission reduction performance of energy-consuming enterprises, while digital transformation positively moderates the effect of green innovation on the carbon emission reduction performance of energy-consuming enterprises. When considering the industry heterogeneity, the moderation effect of digital transformation is significant in the chemical raw materials and chemical products manufacturing industry and the electricity and heat production and supply industry, but the petroleum processing and coking and nuclear fuel processing industry, the non-metallic mineral products industry, the ferrous metal smelting and rolling processing industry and the non-ferrous metal smelting and rolling processing industry are not yet significantly affected by green innovation and digital transformation. The findings of the study provide empirical evidence to promote the improvement of carbon emission reduction performance of energy-intensive enterprises in China and to achieve the "double carbon" target.

High Resolution Emission Inventory of Greenhouse Gas and Its Characteristics in Guangdong，China

Based on the typical city survey data and statistics of Guangdong Province， a 2018-based 3 km×3 km gridded greenhouse gas emissions inventory was developed for Guangdong Province using the combination of top-down and bottom-up emission factor methods. The inventory covered the CO2， CH4， and N2O emissions from energy， industrial processes， agriculture， land use change and forest， waste management， and indirect sources. The results showed that estimates for CO2， CH4， and N2O in Guangdong Province for the year 2018 were 8.5×108， 1.9×106， and 1.1×105 t， respectively， and 8.5×108， 4.0×107， and 3.4×107 t by equivalent carbon dioxide， totaling 9.2×108 t. CO2 was the main greenhouse gas in Guangdong Province， accounting for 92.0% of the total emissions. Energy and indirect sources were the main emission sources， accounting for 77.9% and 7.6%， respectively， totaling 85.5%. Spatial distributions illustrated that most grids were greenhouse gas emissions， whereas some others were greenhouse gas sinks； the greenhouse gas emissions were distributed mainly in the Pearl River Delta region and had certain characteristics of distribution along the road network and channels. The greenhouse gas grids of high emission were mainly the locations of high energy-consuming enterprises such as large power plants， steel mills， and cement plants.

How does the opening of high-speed rail drive energy restructuring? New micro evidence from China

Against the dual backdrop of China vigorously promoting high-speed railways (HSR) construction and establishing an ecological civilization system, HSR as urban transportation infrastructure, is currently gaining growing attention from the academic community due to its environmental benefits as well as its effects in energy conservation and emission reduction. In this context, this research treats the initiation of HSR as a quasi-natural experiment, meanwhile empirically examining the effect of HSR on energy structure restructuring and exploring the micro-level channels through which it operates. The empirical results validate the reduction effect of HSR opening on fuel energy consumption of industrial enterprises, especially the usage of fuel coal. This highlight remains valid across a series of robustness tests. Moreover, it is evident that the “driving effect” of enterprise technological innovation capability and the “industrial upgrading effect” of enterprise relocation are effective transmission pathways in the process of HSR opening influencing the adjustment of energy consumption structure. Moreover, the unique characteristics of enterprise, industry, and region introduce a certain degree of heterogeneity. The low-energy-consumption effect of HSR is more pronounced in high-carbon industry enterprises, technology-intensive enterprises, firms engaged in innovation pilot cities, small to the medium-sized city and resource-based city. This paper provides a new perspective on energy structure adjustment, contributing to offering solid experiences and references for environmental governance in China and other emerging economies.

Economic assessment of investment projects of energy-saving technologies

The article examines the influence of the conditions for the implementation of investment projects on the level of energy consumption of industrial enterprises, as well as the amount of economic benefits received in production, and proposes an economic assessment of the efficiency of iron ore products. As an economic criterion for assessing the effectiveness of energy-saving measures, indicators were calculated that reflect the price of energy saving in relation to investment and operating costs. The practice of assessing the effectiveness of the implementation of investment projects to reduce the energy intensity of production shows that in the process of their control and operational management, priority should be given to natural indicators, and at the current stage of long-term planning – to cost indicators. An improved methodology for assessing the implementation of energy-saving technical solutions based on natural indicators is proposed. To do this, it is necessary to express the volume of production of natural units directly as a function f of the total amount of energy consumed in production (direct and embodied) and calculate the additional volume of production that can be obtained from saved energy resources during the implementation of the project, as well as the additional volume of production obtained in the basic version due to additional investments. The «given» volumes of industrial production are compared with each other. The criterion for evaluating energy saving measures using natural indicators is the minimum value of total energy costs according to the option, per unit of the given production volume. The economic assessment of energy-saving technologies is based on the calculation of changes (savings) in the following indicators: direct costs, integral costs and integral effect, calculated on the basis of indicators characterizing the amount of total energy resource savings in relation to investment and operating costs. In turn, this makes it possible to calculate the minimum volumes of energy resource savings required to ensure the effectiveness of an investment project at a given energy tariff.

Can energy internet improve corporate ESG performance? -- Evidence from Chinese high energy-consuming companies

Under the challenges of global crises such as climate warming, ESG performance, which represents sustainable development, has received widespread attention at home and abroad. Using the panel data from 2011 to 2020, comprising 726 high energy-consuming companies listed on the Shanghai and Shenzhen A-shares, this paper takes Energy Internet demonstration project in 2016 as a quasi-natural experiment and builds a difference-in-difference model to study its microscopic policy effects. The study found that, firstly, Energy Internet can markedly enhance ESG performance of high energy-consuming companies. Secondly, the mechanism test finds that Energy Internet can facilitate high energy-consuming enterprises to enhance their ESG performance through three mechanisms: increasing government subsidies for enterprises in energy conservation and environmental protection, absorbing talent employment and improving information environment within the enterprises. Finally, the heterogeneity analysis proves that Energy Internet's policy effects are more pronounced in regions with higher financial expenditures on local science undertakings and among state-owned enterprises. China ought to persist in advancing the development of Energy Internet and provide companies with adequate support on finance, talent and technology. Meanwhile, during the construction of Energy Internet, attention should be paid to adapting to local conditions and enterprises.

How do energy-saving policies improve environmental quality: Evidence from China’s Top 10,000 energy-consuming enterprises program

Treating China’s Top 10,000 Energy-Consuming Enterprises Program (T10000P) as a quasi-natural experiment, this is the first study to investigate the synergistic effects of the representative energy-saving policy on environmental quality at the micro-level. We create a panel data set by matching China’s Environmental Statistics Database, Industrial Enterprise Database, and State Intellectual Property Office Database, and employ the difference-in-differences model to identify the policy’s environmental effects and their mechanisms. The results show that the T10000P can effectively lower chemical oxygen demand (COD) and sulfur dioxide (SO2) emissions, which still hold after a series of robustness checks, indicating that the policy has a significant synergistic effect on environmental quality improvement. Furthermore, compared with small polluters, the T10000P has a higher pollutant emission inhibition effect on large polluters. Such a positive environmental impact is confirmed for energy-intensive, large, rather than non-energy-intensive and small enterprises, showing heterogeneous effects across different enterprises. We also find that promoting green technology innovation and environmental compliance are the important channels through which the policy improves environmental quality. Therefore, the energy-saving policy can improve environmental quality by setting constrained targets on energy consumption, especially in developing countries.

Research on the evaluation of green suppliers of high energy-consuming enterprises--based on rough number-grey correlation TOPSIS method

With the Goal-Establishment of “carbon compliance” and “carbon neutrality”, enterprises should upgrade “green development” to a strategic position and implement it through all aspects of business operations. Green supplier selection is the initial phase of supply chain management, therefore a green supplier evaluation system is needed to achieve green development. Based on a literature analysis, We selected 45 metrics as candidates for evaluating suppliers. Then through expert interviews, some indicators were revised and supplemented, and finally a green supplier evaluation index system for high energy-consuming enterprises was constructed. A unique aspect of this paper is the introduction of rough number theory into the supplier evaluation process to improve the indicator assignment and the grey correlation TOPSIS method, which optimizes the processing of uncertain semantic information in the evaluation process. The rough number-grey correlation TOPSIS supplier evaluation model developed in this paper has been verified to be applicable and stable in case studies and successfully implemented.

Determinants of land use conflicts with the method of cross-wavelet analysis: Role of natural resources and human activities in spatial-temporal evolution

The imbalance and mismatch between land use structures and resource elements lead to the intensified competition for land use cover, and the resulting land use conflicts (LUCs) have attracted much attention. However, there are few studies on multi-spatial scale determinants of LUCs, due to relatively discrete scales or single determinant used in previous studies. It is a great challenge to explore the method of prioritizing research multi-scales in view of the determinants of LUCs. This study took the Shenyang Economic Zone, a developed urban agglomeration at high latitudes in China, and used cross-wavelet analysis to clarify the determinants of LUCs between natural resources and human activities in typical years (1980, 1993, 2006, and 2019). The cross-wavelet coefficients were used to extract the determinants of LUCs, and the cross-wavelet phase angles were applied to reveal the acting direction and spatial multi-scale correlation of LUCs with the determinants in the Shenyang Economic Zone. The results showed that: (1) the determinants of LUCs in the study area were distance to industrial and mining storage, intensity, soil types, digital elevation model (DEM), and landforms in 1980, were DEM and distance to industrial and mining storage in 1993, were distance to industrial and mining storage, intensity, and diversity in 2006, and were energy consumption of industrial enterprises, gross domestic product (GDP), and intensity in 2019. From 1980 to 2019, the dominant determinants influencing LUCs in the SEZ shifted from a joint influence of natural resources and human activities to dominance of human activities. (2) The action direction of LUCs with determinants had both positive and negative effects in different spatial positions. (3) The multi-scale correlations between LUCs and their determinants were obvious, and the spatial scale correlations varied significantly. The spatial scale between 94,629 and 118950 m was the most suitable spatial scale to explain the association between LUCs and determinants. The results indicated that the competition between natural resources would aggravate LUCs, however, human activities were the main cause of LUCs. Therefore, we believed that territorial spatial planning should not only consider the land distribution pattern, but also took the determinants as control variables to participate in territorial spatial planning. Our findings could provide a scientific basis for alleviating regional land contradictions and effectively allocating resource elements.

Exploring the Transformation Path of High Energy-consuming Industries in A Low-carbon Economy

In recent years, under the background of "double carbon", reducing carbon emission and realizing green transformation and green development have become the necessary way for high energy-consuming enterprises to achieve sustainable development. However, the green transformation of high energy-consuming enterprises faces the problems of high investment cost and slow transformation, which makes it difficult for many high energy-consuming enterprises to take the step of green transformation. Based on the above background, this paper analyzes the concepts and theories related to low carbon economy and proposes the transformation path of high energy-consuming industries under low carbon economy environment.

A dual-core system dynamics approach for carbon emission spillover effects analysis and cross-regional policy simulation

As carbon emission continue to rise and climate issues grow increasingly severe, countries worldwide have taken measures to reduce carbon emission. However, carbon dioxide is continuously flowing in the atmosphere and is easily influenced by neighboring cities' policies. Therefore, how to solve the problem of carbon emission spillover effect has become the key to improve policy efficiency. Cross-regional carbon governance provides a perspective on solving the carbon emission problem by regulating and guiding the cooperative behavior of cross-regional governance actors. Taking Chengdu-Chongqing area as an example, this study used the SDM to analyze the influencing factors and spatial spillover effects of emission. Then we used the system dynamics method to construct a dual-core carbon emission system, and simulated the spillover effect and emission reduction potential of Chengdu and Chongqing emission reduction policies under different policy schemes. The results reveal that the mobility of population and enterprises have a significant impact on carbon emission prediction. Carbon reduction policies exhibit the phenomena of "carbon transfer" and "free-riding." When Chengdu lowers its economic growth rate, it leads to the transfer of high energy-consuming enterprises to Chongqing, increasing carbon emission in Chongqing. The implementation of comprehensive carbon reduction policies in Chongqing has a positive effect on Chengdu. Emission reduction policies exhibit issues related to their temporal efficacy, as the effects of industrial structural policies in Chengdu yield opposite outcomes in the short and long term. Each city's unique circumstances necessitate tailored carbon reduction policies. In order to reduce carbon emissions, Chengdu and Chongqing require opposite population policies.