Effects of technical and allocative inefficiencies on energy and nonenergy elasticities:an analysis of energy-intensive industries in China

Elasticity of substitution is traditionally estimated while ignoring technical and allocative inefficiencies,which could bias the estimates.We estimate elasticity of substitution for Chinese energy-intensive sectors by incorporating these inefficiencies.The results show most of the sectors are low substitutes between input factors and stress important differences among energy-intensive sectors.Concerning the cross-price elasticity for energy,with respect to capital(labor),the sectors are mainly characterized by weak substitutability or complementary.These imply the production structure is quite rigid and capital cannot be so readily used as a substitute for energy.

The impact of energy-intensive industries on air quality in China’s industrial agglomerations

Understanding the driving forces of regional air pollution and its mechanism has gained much attention in academic research,which can provide scientific policy-making basis for economy-environment sustainability in China.Being an important energy and industrial base,the North China Plain region has been experiencing severe air pollution.Therefore,understanding the relationship between industrialization and air quality in this region is of great importance for air quality improvement.In this study,the average annual concentrations of SO2,NO2 and PM10 in 47 sample cities at and above the prefecture level in the North China Plain region from 2007 to 2016 were used to illustrate the spatiotemporal characteristics of air pollution within this region.Furthermore,panel data model,panel vector autoregression model,and impulse response function were used to explore the correlation and driving mechanism between energy-intensive industries and regional air quality.The results show that:first,overall air quality improved in the study area between 2007 and 2016,with a significant greater fall in concentration of SO2 than that of NO2 and PM10;second,provincial border areas suffered from severe air pollution and showed an apparent spatial agglomeration trend of pollution;and third,the test results from different models all proved that energy-intensive industries such as the chemical,non-metallic mineral production,electric and thermal power production and supply industries,had a significant positive correlation with concentrations of air pollutants,and indicated an obvious short-term impulse response effect.It concludes that upgradation of industrial structure,especially that of energy-intensive industries,plays a very important role in the improvement of regional air quality,which is recommended to be put in top priority for authorities.Therefore,policies as increasing investments in technological innovation in energy-intensive industries,deepening cooperation in environmental governance between different provinces and cities,and strengthening supervision and entry restrictions are suggested.

Research on the Industrial Transfer and Restructuring Path of the Energy-Intensive Manufacturing Industry in Western China

The orderly transfer of the manufacturing industry is a major action in China’s industrial restructuring.From the perspective of industrial transfer,we used the concentration ratio to depict the trend of the industrial transfer of energy-intensive manufacturing in the eastern,central,and western regions since the policy of large-scale development of western China was implemented.We measured the total factor productivity(TFP)of western China using the DEAMalmquist index method.We conducted a regression analysis to measure the effect of western China’s undertaking of the transfer of the energy-intensive manufacturing industry.The findings of this study show that during 2000–2019,eleven provinces(as well as autonomous regions and municipalities)in western China undertook the transfer of the energy-intensive manufacturing industry from the eastern and central regions to varying degrees,exhibiting significant phase features regarding the rate and scale of transfers.Further investigation also demonstrated that the transfer of energy-intensive manufacturing industries has a U-shaped enabling effect on TFP in western China with the scale effect greater than the technology effect.Therefore,it is necessary to transition from“extensive industrial transfer”at the cost of the labor force,land,and resources to“modern industrial transfer”featured by technology and efficiency improvements to contribute to industrial restructuring in western China effectively.

Digitalization Enables Cultural,Commercial and Tourism Industries to Explore the Global Market

The recent 2024 National Tour ism Development Conference has clearly pointed out that China’s tourism industry has grown into the world’s largest domestic tourism market and has become an important destination in the international tourism sector,marking the rise of the tourism industry as a strategic pillar industry for the country.

Development Level and Dynamic Analysis of the Integration of Three Rural Industries in the Context of Rural Revitalization

As a key measure to comprehensively promote the strategy of rural revitalization,especially in the field of industrial prosperity,the integration of rural three industries is of great strategic significance.In this study,entropy method and TOPSIS method were employed to calculate the comprehensive evaluation index of integration of three industries and the ideal development value respectively.The development status of integration of three rural industries was systematically evaluated,and the development trend of different regions was compared and analyzed.The results indicate that the development index of integration of three industries showed a steady growth trend,among which the development level of Jiangsu Province ranked first,followed by Hubei Province,while the development level of Shaanxi Province was relatively low.When analyzing the Level I indicators of integration of three rural industries,the contribution of industrial integration behavior exceeded the performance of industrial integration.Among the behavioral indicators of industrial integration,the weight of agricultural multi-functionality and service integration was relatively large,which plays a significant role in promoting the development of integration of three rural industries.The scores and growth rates of Jiangsu Province in increasing farmers income,increasing agricultural production and rural economic development were higher than those of other regions,while Shaanxi Province still had a certain gap in rural industrial integration indicators compared with Jiangsu Province and Hubei Province.In view of this,we came up with some strategic recommendations for further promoting the development of integration of three rural industries.

Science and Technology Promotion Policies of Strategic Emerging Industries in Anhui Province

In recent years,based on advantages of industry,market,science and technology and other development environment,strategic emerging industries in Anhui Province are developing rapidly,and emerging industries such as new energy,new materials,new generation of information technology occupy an important market share in China and even the world.However,there are still a number of problems in the process of development,and the policy support has a greater impact.In this paper,the development status of strategic emerging industries in Anhui Province was discussed firstly,and then the challenges and problems of the development was discussed.Finally,some science and technology promotion policies of strategic emerging industries in Anhui Province were proposed.

Evolution of Handicraft Industries in the Textile Sector in Saudi Arabia: A Comprehensive Analysis of Trends and Innovations

This review explores the evolution of the textile handicraft industry in Saudi Arabia, emphasizing its cultural and economic significance. The study highlights the transition from traditional practices to modern innovations and examines the impact of globalization and technological advancements on the industry. Key innovations are discussed, demonstrating their role in enhancing textile production while preserving cultural heritage. Major challenges, such as competition from industrial textiles and the need for sustainable practices, are identified. Opportunities for growth are explored, including leveraging tourism and international markets to promote Saudi handicrafts. The social and cultural impacts of the sector are underscored, particularly in sustaining community traditions and providing economic opportunities for artisans. Strategic recommendations for supporting and advancing the industry are offered, ensuring its continued relevance and sustainability in a rapidly changing global market. This analysis provides a robust framework for understanding the current state and future potential of Saudi Arabia’s textile handicraft industry.

Carbon capture for decarbonisation of energy-intensive industries:a comparative review of techno-economic feasibility of solid looping cycles

Carbon capture and storage will play a crucial role in industrial decarbonisation.However,the current literature presents a large variability in the techno-economic feasibility of CO_(2)capture technologies.Consequently,reliable pathways for carbon capture deployment in energyintensive industries are still missing.This work provides a comprehensive review of the state-of-the-art CO_(2)capture technologies for decarbonisation of the iron and steel,cement,petroleum refining,and pulp and paper industries.Amine scrubbing was shown to be the least feasible option,resulting in the average avoided CO_(2)cost of between 62.7∈t_(CO_(2))^(-1)for the pulp and paper and 104.6∈t_(CO_(2))^(-1)for the iron and steel industry.Its average equivalent energy requirement varied between 2.7(iron and steel)and 5.1MJ_(th)·kg_(CO_(2))^(-1)(cement).Retrofits of emerging calcium looping were shown to improve the overall viability of CO_(2)capture for industrial decarbonisation.Calcium looping was shown to result in the average avoided CO_(2)cost of between 32.7(iron and steel)and 42.9(cement).Its average equivalent energy requirement varied between 2.0(iron and steel)and 3.7(pulp and paper).Such performance demonstrated the superiority of calcium looping for industrial decarbonisation.Further work should focus on standardising the techno-economic assessment of technologies for industrial decarbonisation.

Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the world.However,there is no consensus on why and what is Industry 5.0 yet.In this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future development.We believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart societies.Steps are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Leveraging Blockchain with Optimal Deep Learning-Based Drug Supply Chain Management for Pharmaceutical Industries

Due to its complexity and involvement of numerous stakeholders,the pharmaceutical supply chain presents many challenges that companies must overcome to deliver necessary medications to patients efficiently.The pharmaceutical supply chain poses different challenging issues,encompasses supply chain visibility,cold-chain shipping,drug counterfeiting,and rising prescription drug prices,which can considerably surge out-of-pocket patient costs.Blockchain(BC)offers the technical base for such a scheme,as it could track legitimate drugs and avoid fake circulation.The designers presented the procedure of BC with fabric for creating a secured drug supplychain management(DSCM)method.With this motivation,the study presents a new blockchain with optimal deep learning-enabled DSCM and recommendation scheme(BCODL-DSCMRS)for Pharmaceutical Industries.Firstly,Hyperledger fabric is used for DSC management,enabling effective tracking processes in the smart pharmaceutical industry.In addition,a hybrid deep belief network(HDBN)model is used to suggest the best or top-rated medicines to healthcare providers and consumers.The spotted hyena optimizer(SHO)algorithm is used to optimize the performance of the HDBN model.The design of the HSO algorithm for tuning the HDBN model demonstrates the novelty of the work.The presented model is tested on the UCI repository’s open-access drug reviews database.

Analysis on Technical Structure and Competitiveness of ICT Manufacturing Industries

In order to analyze the technical structure and international comparative advantage of the information and communication technology(ICT)manufacturing industry,a complete set of ICT manufacturing product categories has been constructed by matching National Economical Industry Classification(GB/T4754-2017)with Harmonized System(HS)Codes,based on the relevant definitions in International Standard Industrial Classification(ISIC).The proposed definition overcomes inherent defects such as inaccurate scopes,lagging data and rough categories,which are characterized by commonly utilized product-level based classification approaches.Within the given framework,this paper has designed the technology content related indicators from the perspective of production distribution,and divided ICT product categories into high-end,medium-end and lowend manufacturing classifications according to respective global shares.Then,we have calculated international market shares(IMS),revealed comparative advantages(RCA),and market penetration rates(MPR)of ICT manufacturing exports for major economies from 2010 to 2021.Finally,development characterizations of ICT manufacturing industries for China’s Mainland are analyzed,and several practical suggestions are provided.

Government Role in Fostering Emerging Technological Industries:A New Perspective for Industrial Policy Research

Mainstream industrial policy research cannot fully explain how government interventions have helped China’s mobile communications industry catch up with and overtake those of advanced nations.China’s mobile communications industry made breakthroughs in 3G,caught up with advanced nations in 4G,and gained a leadership position in 5G due to the implementation and improvement of a strategy of industrial competition that accommodates mainstream standards and prioritizes the mid-band spectrum based on the integrated“technology,standard and industry”deployment system and swift decision-making.The introduction of a perspective of a strategy of industrial competition may supplement industrial policy research in the following ways:First,when the concerted actions of numerous innovators are important for industrial competition performance,an effective strategy of industrial competition can be devised and overall coordinated by the government provided that is compatible with the catch-up development of emerging technological industries.Second,an industrial policy becomes effective when it is complementary with the strategic factors for long-term industrial performance such as the strategy of industrial competition and avoids serious disruptions to market-based mechanisms.

Arithmetic Optimization with Deep Learning Enabled Churn Prediction Model for Telecommunication Industries

Customer retention is one of the challenging issues in different business sectors,and variousfirms utilize customer churn prediction(CCP)process to retain existing customers.Because of the direct impact on the company revenues,particularly in the telecommunication sector,firms are needed to design effective CCP models.The recent advances in machine learning(ML)and deep learning(DL)models enable researchers to introduce accurate CCP models in the telecom-munication sector.CCP can be considered as a classification problem,which aims to classify the customer into churners and non-churners.With this motivation,this article focuses on designing an arithmetic optimization algorithm(AOA)with stacked bidirectional long short-term memory(SBLSTM)model for CCP.The proposed AOA-SBLSTM model intends to proficiently forecast the occurrence of CC in the telecommunication industry.Initially,the AOA-SBLSTM model per-forms pre-processing to transform the original data into a useful format.Besides,the SBLSTM model is employed to categorize data into churners and non-chur-ners.To improve the CCP outcomes of the SBLSTM model,an optimal hyper-parameter tuning process using AOA is developed.A widespread simulation analysis of the AOA-SBLSTM model is tested using a benchmark dataset with 3333 samples and 21 features.The experimental outcomes reported the promising performance of the AOA-SBLSTM model over the recent approaches.

Carbon emission efficiency of forest processing industries in China

This paper uses an input-output table of China's provinces(2007-2016) to measure carbon emissions of these industries.It employs a Malmquist-Luenberger(ML) index with expected and undesired outputs,and an absolute β convergence and a conditional β convergence model,to conduct an in-depth analysis of dynamic changes and spatial convergence.Carbon emission efficiency of forest processing industries in 25 regions,including Shanghai,Chongqing,Zhejiang,and Jiangsu are increasing,whereas those of Tianjin,Liaoning,Heilongjiang,and Tibet are decreasing.The main contributing factors of carbon emission efficiency in three major regions vary over time.Further,carbon emission efficiency in the eastern,central,and western regions all have absolute β convergence and conditional β convergence,indicating that different regions are developing toward their own goals and industry,yet regions with lower efficiency are catching up with those where with more efficient strategies in place.Finally,this paper proposes according recommendations.

Can Industrial Structure Upgrading Restrain Industrial Land Expansion?Evidence from China

China has made great achievements in industrial development and is transforming into a powerful manufacturing country.Meanwhile,the industrial land scale is also expanding.However,whether industrial structure upgrading achieves the purpose of restraining industrial land expansion remains unanswered.By calculating the industrial land structure index(ILSI)and industrial land expansion scale(ILES),this study analyzed their temporal and spatial distribution characteristics at both regional and city levels from 2007to 2020 in China.Results show that industrial land expansion presents a different trend in the four regions,the ILES in the eastern region is the largest,and the speed of industrial land expansion has declined since 2013,but it has gradually increased since 2016.The ILSI of the eastern and central regions is higher than that of the western and northeastern regions.Furthermore,a spatial Durbin model(SDM)has been established to estimate the spatial effect of industrial structure upgrading on industrial land expansion from 2007 to2020.Notably,industrial structure upgrading has not slowed industrial land expansion.The eastern and western regions require a greater amount of industrial land while upgrading the industrial structure.The improvement of the infrastructure level and international trade level has promoted industrial land expansion.

Spatial Patterns and Drivers of Intelligent Manufacturing from a‘Glob-allocal'Perspective:A Study of China's Industrial Robotics

The advancement of the intelligent manufacturing industry(IMI)represents the future direction for the world's manufactur-ing sector,offering a promising avenue to bolster national competitiveness and enhance industrial manufacturing efficiency.In this study,we took the industrial robot industry(IRI)as a case study to elucidate the spatial distribution and interconnections of IMI from a geographical perspective,and the modified diamond model(DM)was used to analyze the influencing factors.Results show that:1)the spatial pattern of IRI with various investment attributes in different industrial chain links is generally similar,centered in the southeast.Key investment areas are in the east and south.The spatial distribution of China's IRI covers a multitude of provinces and obtains differ-ent scales of investment in different countries(regions).2)The spatial correlation between foreign investors and China's provincial-level administrative regions(PARs)forms a network,and the network of foreign-invested enterprises is more stable.Different countries(regions)have distinct location preferences in China,with significant spatial differences in correlation degrees.3)Overall,the interac-tion of these factors shapes the location decisions and correlation patterns of industrial robot enterprises.This study not only contributes to our theoretical knowledge of the industrial spatial structure and industrial economy but also offers valuable references and sugges-tions for national IMI planning and relevant industry investors.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Technological anxiety:Analysis of the impact of industrial intelligence on employment in China

Employment is the greatest livelihood.Whether the impact of industrial robotics technology materialized in machines on employment in the digital age is an“icing on the cake”or“adding fuel to the fire”needs further study.This study aims to analyze the impact of the installation and application of industrial robots on labor demand in the context of the Chinese economy.First,from the theoretical logic and the economic development law,this study gives the prior judgment and research hypothesis that industrial intelligence will increase jobs.Then,based on the panel data of 269 cities in China from 2006 to 2021,we use the two-way fixed effect model,dynamic threshold model,and two-stage intermediary effect model.The objective is to investigate the impact of industrial intelligence on enterprise labor demand and its path mechanism.Results show that the overall effect of industrial intelligence on the labor force with the installation density index of industrial robots as the proxy variable is the“creation effect”.In other words,advanced digital technology has created additional jobs,and the overall supply of employment in the labor market has increased.The conclusion is still valid after the endogeneity identification and robustness test.In addition,the positive effect has a nonlinear effect on the network scale.When the installation density of industrial robots exceeds a particular threshold value,the division of labor continues to deepen under the combined action of the production efficiency and compensation effects,which will cause enterprises to increase labor demand further.Further research showed that industrial intelligence can increase employment by promoting synergistic agglomeration and improving labor price distortions.This study concludes that in the digital China era,the introduction and installation of industrial robots by enterprises can affect the optimal allocation of the labor market.This phenomenon has essential experience and reference significance for guiding industrial digitalization and intelligent transformation and promoting the high-quality development of people’s livelihood.

China’s Industrial Modernization:Development Rationale,Current Status,and Policy Directions

Economies that have effectively escaped the“middle-income trap”demonstrate common traits in their industrial restructuring as they progressed to high-income status.These include a relatively stable share of an economy’s manufacturing sector,a reasonable economic structure,enhanced industrial capabilities,and growth driven by innovation.However,late-moving countries face a number of hurdles as they strive to cross this threshold.China’s development advantages include,among other things,a complete industrial system,a more balanced industrial structure,growing indigenous innovation capabilities,continual expansion and upgrading of domestic demand,and a greater degree of openness.These capabilities have provided continuous momentum for industrial growth,allowing China to capitalize on the next wave of technological and industrial revolutions while also promoting long-term,steady industrial development.During its modernization efforts,China has seen substantial changes in the external environment surrounding its industrial development.We must not only recognize the increasing complexity,intensity,and uncertainty of these changes,but also take proactive steps to solve diverse issues and capitalize on opportunities arising from global digital and green transitions.Equal focus should be placed on strengthening reforms and promoting high-level openness,improving policy coordination and consistency,and pursuing an innovation-driven strategy.This will speed the development of a modern industrial system and encourage the formation of new,high-quality productive forces.