Scale Efficiency Research Articles

How can green finance promote the transformation of China's economic growth momentum? A perspective from internal structures of green total-factor productivity

Green financing is a crucial tool for promoting China's economic growth and helping to achieve carbon neutrality, but its implications on the internal dynamics of green economy remain uncertain. This study examines the impacts of green finance on China’s Green Total Factor Productivity (GTFP) and its internal factors, including technical innovation, industrial structure, balanced regional growth, scale, and resource allocation efficiency, by using a three-hierarchy meta-frontier Data Envelopment Analysis (DEA) and provincial panel data from 2008 to 2020. The findings show that: (1) regional green finance development may greatly boost the growth of GTFP, and the findings remain reliable after applying a series of robustness tests; (2) further research finds that green finance enhances GTFP by promoting technological innovation, facilitating the optimization of industrial structure, and improving resource allocation efficiency; and (3) there are significant spatial heterogeneities in this effect. The effect of green finance on GTFP is more pronounced in developed and market-oriented regions. This study helps to understand the pathways of green finance affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

An Improved Slack Based Measure Model for Evaluating Green Innovation Efficiency Based on Asymmetric Data

Nowadays, one of the main challenges facing green innovation management is how to enhance the performance of innovation processes by utilizing asymmetric input and output data. Therefore, this paper develops an improved SBM model analysis framework for evaluating the green innovation efficiency of asymmetric input and output data. The framework is applied to assess the technical (TE), managerial (PTE), and scale (SE) efficiencies of new energy companies under three input variables (R&D personnel input, R&D capital input, and comprehensive energy consumption input), two desirable output variables (green technology output and economic output), and one undesirable output variable (greenhouse gas emissions). Then, environmental factors and random factors are eliminated from the obtained input slack variables based on the SFA model, placing decision-making units in a homogeneous environment. The results demonstrate that TE, PTE, and SE are improved after eliminating environmental factors and random factors. Subsequently, based on the entropy method, this paper classifies companies’ green innovation patterns into four categories and provides targeted solutions. The purpose of this paper is to provide an evaluation method for new energy companies to understand green innovation efficiency and assist decision makers in identifying the most optimal resource allocation approach. The proposed improved SBM model contributes to the literature and to industry practice by (1) providing a reliable evaluation of green innovation efficiency under asymmetric input and output data; (2) determining effective improvement actions based on a slack analysis of environmental variables and random variables that lead to improved process performance; and (3) making fuzzy innovation performance efficient to facilitate understanding and managing innovation resource allocation quality.

A Sustainable Development Study on Innovation Factor Allocation Efficiency and Spatial Correlation Based on Regions along the Belt and Road in China

The level of development of the innovation factor plays a crucial role in supporting the high-quality sustainable development of China’s economy. In order to advance the sustainable development of regional innovation factor allocation efficiency along the Belt and Road this study introduces the super-efficient slacks-based measure (SBM)-data envelopment analysis (DEA)-Malmquist model for static and dynamic analyses of innovation factor allocation efficiency in 17 provinces along the Belt and Road from 2012 to 2021. This study used the Moran index model to analyze spatial correlation. The results show the following: (1) The overall innovation factor allocation efficiency along the Belt and Road is not high, and there are obvious differences among different regions. The eastern region’s efficiency is the highest compared to other regions. (2) According to the efficiency decomposition results, pure technical efficiency (PTE) is the main reason for the low innovation factor allocation efficiency. (3) Through the Malmquist index and decomposition index, it was found that pure technical efficiency (PECH) and scale efficiency (SECH) are key factors in improving technical efficiency (TECH). (4) The analysis of spatial correlation revealed a strong spatial agglomeration feature among the provinces along the Belt and Road. Innovation factor allocation efficiency is mainly manifested in the third quadrant. Finally, drawing on the results of the analysis, suggestions and policies are put forward to improve innovation factor allocation efficiency in the regions along the Belt and Road. This study is of great significance for promoting the sustainable development of the regional innovation level along the Belt and Road in China.

Effectiveness of Higher Education Financing: DEA and SFA Modelling

The article aims to assess the effectiveness of financial expenditures in higher education for 31 provinces in China, namely overall, technical and scale efficiency, and to determine whether the returns to scale are increasing or decreasing for each province. The main method used is the three-stage DEA analysis / Data Envelopment Analysis, and software DEAP2.1 and Frontier 4.1 are used for modelling. Financial expenditures on higher education form an input parameter in the DEA model. The output parameters (determining the efficiency of higher education) are the number of students, the number of full-time teachers and the new value added to fixed assets in higher education institutions. The modelling was carried out for 2008-2013 and 2014-2018 (the COVID-19 pandemic is not considered to avoid uncommon trends and unpredictable disturbances in the model). A comparison of the analysis results for these periods allowed the identification of new trends and patterns. The study takes into account three main groups of parameters: 1) endogenous (inefficiency of internal management processes); 2) exogenous (gross regional product per capita of each province in China; the extent of university clustering, which is determined by political and market decisions and does not depend on educational institutions; and the degree of fiscal decentralisation, which is estimated in the article as the ratio of local and state budget expenditures per capita, taking into account the distribution of total budget expenditures for each district and the total population of the respective territory); 3) random disturbances. At the first stage of the study, a BCC model focused on inputs (to assess the technical efficiency of financial expenditures on higher education in different provinces) was built. It does not consider exogenous factors and random disturbances. In the second stage, SFA (stochastic frontier analysis) was applied to account for the impact of all three groups of factors (endogenous, exogenous and statistical noise) on the efficiency of financial expenditures in higher education for each province in China. In the third stage, the adjusted and standardised input and output parameters are incorporated into the BCC models, and the actual value of efficiency caused by exogenous parameters and the influence of random factors is determined. A comparison of the results of each modelling stage for each stage in the study and each province in China allowed the establishment of how the influence of the determinants of higher education financing efficiency changed in chronological and spatial contexts.

Efficiency Evaluation of Forest Carbon Sinks: A Case Study of Russia

Forest carbon sinks in Russia are an integral part of the national “Low-carbon development strategy”. However, the influence of natural disasters and various land use policies in economic regions (ERs) raises the issue of forest carbon sink efficiency (FCSE). This study adopted a DEA-SBM model that considers undesirable outputs to measure FCSE, and the Malmquist index (MI) approach to analyze total factor productivity (TFP) of forest carbon sinks, using panel data from 2009 to 2021. The results show that the average FCSE was 0.788, with an improvement rate of 21.2%. Scale efficiency is the main factor constraining FCSE in Russia. In twelve ERs, forest carbon sinks are efficient only in the Kaliningrad and West Siberian ERs. In general, forest carbon sinks in Russia are inefficient mainly due to forest fires and other natural disturbances (82.33%); excessive logging activities (38.64%); and lack of carbon absorption capacity (31.70%). The average score of their TFP is 0.970, indicating a decline of 3% over the study period. This is primarily attributed to the decline of 1.6% in technological change. The productivity of forest carbon sinks remained static only in the Kaliningrad ER, while other economic regions performed deterioration trends. Therefore, Russia should enhance the efficiency of forest carbon sinks.

BUSINESS ANALYSIS OF HOUSEHOLD SCALE COW’S MILK INDUSTRY IN SARANGAN VILLAGE MAGETAN REGENCY

The purposes of this research were to determine the total costs, revenues, profits, efficiency, and risks in the household scale pasteurized cow’s milk industry in Sarangan Village, Magetan Regency. The basic method used is descriptive analysis. Determination of the research location purposively with nine respondents, were taken by the census method. Data collection techniques were collected through interviews, observation, recording, documentation, and questionnaires. The data analysis used is costs, revenues, profits, business efficiency, and risk. The results showed that the business has average total cost production in December 2021 of IDR 9.805.292,00/month. The average revenue is IDR 14.729.444,00/month. So that the average profit is IDR 4.924.152,00/month. The business is already efficient because the efficiency value is 1,54. Therefore, the coefficient of variation is 0,53, and the lower profit limit is minus IDR 253.175,00. These values mean that the business is at risk of experiencing a loss of IDR 253,175.00

Decomposition and Driving Factors of Total Factor Productivity of Food Crops in the Yellow River Basin, China

The urgency of enhancing agricultural productivity within the Yellow River Basin cannot be overstated, given its critical role in ensuring food security amidst the challenges posed by climate change, natural disasters, and the increasing demand for food crops. Utilizing panel data from nine provinces within the Yellow River Basin for the period 2001 to 2020, this study examines the temporal characteristics and spatial distribution of Total Factor Productivity (TFP) for key grain crops—namely wheat, corn, and soybean—through the application of the Malmquist index which can be decomposed through the DEA-Malmquist index methodology. The empirical results demonstrate that TFP growth rates for these crops have exhibited significant phase variations, with soybean recording the highest TFP growth rate in the basin. Additionally, this study underscores marked regional disparities in soybean productivity. TFP decomposition reveals that the primary drivers of TFP improvement across these crops are attributed to technical progress, with gains in overall technical efficiency largely due to scale efficiency enhancements, whereas pure technical efficiency has shown limited progress. Regional analysis indicates that Inner Mongolia leads in TFP growth for all crops, while Ningxia, Sichuan, and Shaanxi lag behind in wheat, corn, and soybean. Additionally, our analysis delineates natural disasters as a significant barrier to Total Factor Productivity (TFP), notably obstructing technological advancements in wheat cultivation. The investigation further reveals a positive relationship between regional per capita income and the growth of wheat TFP, in contrast to a negative relationship with the TFP growth of corn and soybeans. Moreover, investing in agriculture, forestry, water management, and road infrastructure supports the growth of wheat TFP, while urbanization levels pose constraints. Conclusively, an uptick in annual rural electricity usage, along with improved per capita postal and telecommunication services, exerts a favorable influence on TFP for corn and soybeans.

Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: a DEA approach

Container ports play a pivotal role in international trade, facilitating the movement of goods and fostering economic development. While much attention has been given to the efficiency of ports in high-income countries, container ports in lower-middle-income (LMI) countries have received less attention. This paper addresses this research gap by assessing container ports' operational efficiency across diverse LMI countries and determining ways for their efficiency enhancement and management optimization. The cross-sectional data for the year 2012 was collected for 53 container ports in LMI countries. This research utilizes data envelopment analysis, which offers the advantage of considering multiple inputs and outputs. The results show that the overall technical inefficiencies of LMI countries' container ports are mainly due to pure technical inefficiency rather than scale inefficiencies, and the most efficient ports have a combination of large and hub ports. They also reveal that larger ports (as measured by throughput) are not necessarily more efficient than ports with a small production scale. The results of this research can provide government authorities, port authorities, terminal operators, and investors with valuable insights into resource allocation, competitive advantage, and optimization of operating performance.

The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China

Road freight transport, an essential component of the logistics sector, faces challenges: high cost, low efficiency, and environmental impact. The need has become urgent to achieve a synergistic balance between low-carbon and high-efficiency development. This study used a three-stage DEA–Malmquist index model to analyze the road freight efficiency of Wuhan and 16 other cities in China from 2015 to 2020, and we compared Wuhan’s performance with its peers. In addition, grey correlation analysis was used to evaluate the low-carbon development of urban road freight transport in Wuhan. Through the calculation of the degree of synergy between low-carbon development and freight transport efficiency, this study provides insights into the synergistic development of low-carbon and efficient road freight transport in Wuhan. The key findings show that the total factor productivity of road freight transport in Wuhan was generally on a downward trend from 2015 to 2020, and was lower than that of the average of the 17 selected Chinese cities. The carbon emissions of road freight transport in Wuhan inversely related to its scale efficiency. This study also points out that the synergy between low-carbon development and the economic efficiency of road freight transport in Wuhan is not high and needs to be further integrated and optimized.

Urban green total factor productivity in China: A generalized Luenberger productivity indicator and its parametric decomposition

In this study, by taking the distance elasticity shares as the input weights in the production function, the generalized Luenberger productivity indicator (GLPI) was proposed to analyze the urban GTFP in China, and the stochastic frontier analysis (SFA) was used for parametric decomposition to obtain the technological change (TC), technical efficiency change (TEC), and scale efficiency change (SEC). The results show that the entire model and specific parameters passed the test, and the production function equation has good economic and statistical significance, which shows that it is feasible to use the parameter approach to measure and decompose the GLPI. Second, the value of the GLPI showed a rapid growth trend between 2000 and 2019, with a cumulative increase of 140.59%, indicating that various inputs were saved by 3.43% in a specific proportion, and that remarkable achievements have been made in the sustainable development of Chinese cities. Third, TC, TEC, and SEC all showed significant spatiotemporal heterogeneity, in which SEC was the main numerical component and TC was the driving force of the GLPI. Through mathematical proof in theory and data matching in reality, it is confirmed that the GLPI proposed in this study is scientific and applicable.

COVID‐19 and Efficiency, Technology and Productivity Change in Australian Private Health Insurance Funds*

We calculate efficiency change, technological progress and productivity growth in Australian private health insurance (PHI) funds using Malmquist indices from 2016/2017 to 2021/2022. Starting in January 2020, the COVID‐19 pandemic and the various policy responses to it brought significant disruption to the PHI industry with restrictions placed on elective surgery, and hence insured hospital days, and the use of extras cover for dental, physiotherapy, optical and other services. Lockdowns also saw PHI funds implement work‐from‐home arrangements and invest to improve policyholder services; the share of Australians with PHI cover grew counter to trend; global financial markets experienced significant volatility, impacting PHI investment revenue and PHI funds delayed even refunded premiums to offset financial pressures on policyholders. We show that productivity declined during the first 18 months of the pandemic and then grew very strongly. We also find the typical PHI fund is 36.5% more productive at the end of the period than the beginning, with most gains being technological (38.3%), involving a large upward shift in the industry frontier, countering much smaller losses from scale (−0.2%) and pure technical (−1.1%) inefficiency. This suggests that the PHI industry responded well to the disruption associated with the COVID‐19 pandemic.

The Impact of Financial Liberalization Policies on Income Inequality

<p style="text-align:justify"><br /> <span style="font-size:10.5pt"><span style="font-family:等线"><span dir="ltr" lang="EN-US" style="font-family:"Cambria",serif">This paper examines impacts of China’s financial liberalization policy on income inequality, through three channels: financial scale, financial structure and financial efficiency, an empirical analysis based on panel data of 30 provinces in China from 1996 to 2013 is conducted. The results confirm the Kuznets effect between financial scale, financial structure and income inequality. As the size of the financial sector expands, the financial structure is tilted toward direct financing, and the income gap among residents will experience a "reverse U-shaped" trend that rises first and then falls. Most of China has not yet passed the turning point, and is still in the upper bound of the "inverted U-shaped" curve. Financial liberalization policies will continue to exacerbate income inequality. The impact of financial efficiency on income distribution is quite different in different regions of China. After dividing the whole China into three regions according to the degree of economic development, it is found that the financial efficiency of the eastern and western regions has a Kuznets effect on the income gap, but compared with the eastern region, more provinces and cities in the western region have entered the stage of reducing the income inequality, and the financial development has a great impact on the western region. The effects of financial development on central China are weak, and income inequality increases with financial efficiency.</span></span></span></p>

Collaborative optimization algorithm for electric vehicle industry chain based on regional economic development needs

Abstract With the development of the economy, many regions have experienced a slowdown in economic growth. In order to promote the development of the electric vehicle (EV) industry, the country has also begun to introduce various policies to encourage the development of the EV industry. In this context, many local governments have begun to introduce policies and measures related to the development of the EV industry, such as increasing land use for the development of the EV industry and increasing support for the new energy automobile industry. These policy measures have played a positive role in promoting the development of the EV industry, but there are also some problems. For example, when many local governments introduce policies to support the development of the new energy automobile industry, their support for the EV industry is not significant. This article studied the collaborative optimization of the EV industry chain in response to issues such as insufficient technical strength, imbalanced supply-demand relationship, and insufficient downstream service chain capabilities in the EV industry chain. This article analyzed the composition of the EV industry chain and established an EV industry chain model to address these issues. This article used collaborative optimization algorithms to analyze the production volume of EVs in the EV industry chain, as well as the comprehensive efficiency, pure technical efficiency, and scale efficiency values of upstream, midstream, and downstream. Through experimental analysis, it was found that the comprehensive efficiency value of the upstream of the EV industry chain after using the collaborative optimization algorithm was 0.0792 higher than before. The research results of this article have provided reference significance for the analysis of collaborative optimization algorithms in other fields.

The influence of financial flexibility on firm performance: the moderating effects of investment efficiency and investment scale

PurposeFinancial flexibility and investment efficiency are of vital importance in strategic choices at boardrooms, particularly in post-crisis recovery strategies. This study examines the moderating effects of investment efficiency and investment scale on the relationship between financial flexibility and firm performance.Design/methodology/approachThe authors use sample of 10,755 US-listed firms over the period 2010–2021 to examine the relationships between investment scale, investment efficiency, financial flexibility and firm performance. Particular attention is paid to overinvestment and underinvestment.FindingsFindings of this study reveal that financial flexibility mitigates investment inefficiency through reducing overinvestment. Financial flexibility contributes to boost a firm’s accounting and market performance. Additionally, investment efficiency and investment scale have moderating effects on the relationship between financial flexibility and firm performance. However, the influence of investment efficiency is greater than the influence of investment scale. Finally, the authors find that the direct and indirect effects of financial flexibility are stronger on market performance than accounting performance, implying that market is more sensitive to corporate financial policies.Research limitations/implicationsFindings of this study have implications for scholars, decision-makers policymakers, investors and other stakeholders.Practical implicationsThis study has its own limitations due to the sample selection issues, country context and the research model adopted by this study.Originality/valueThe novel contribution to the extant literature is incorporating the influence of investment scale and investment efficiency into the relationship between financial flexibility and firm performance.

Efficiency Characteristics and Evolution Patterns of Urban Carbon Metabolism of Production-Living-Ecological Space in Beijing-Tianjin-Hebei Region

This study explored the carbon metabolism efficiency of a production-living-ecological space system, which is of great significance for regional factor integration and spatial optimization. In this study, the material flow analysis method was introduced to establish a framework for evaluating the carbon metabolism efficiency of the production-living-ecological space system, and the super-efficiency DEA model and Malmquist index were used to empirically analyze the spatio-temporal distribution, dynamic change, and evolution patterns of the carbon metabolism efficiency of production-living-ecological space in the Beijing-Tianjin-Hebei Region, China, from 2000 to 2020 on the basis of the urban metabolic perspective. The results showed that:① the carbon metabolism efficiency of the production-living-ecological space showed a fluctuating growth trend, indicating the significant spatial differentiation of carbon metabolism efficiency in each city. There was a low overall carbon metabolism efficiency level, with a distribution pattern of being high in the middle and low in the north and south. ② The Malmquist index showed that the Total Factor Productivity (TFP) of carbon metabolism efficiency was greater than 1, and both the Technical Change (TC) and Pure Efficiency Change (PEC) were less than 1, in which the TFP showed an increasing trend, whereas there was no significant contribution of technological progress or pure technical efficiency to carbon metabolism efficiency. The total factor productivity of more than 50% of the cities showed an improving trend, only 38.46% of which made technological progress in improving carbon metabolism efficiency, and more than half of the urban pure technical efficiency showed a decreasing trend, in which the technical efficiency change and scale efficiency change were greater than 1 in most cities. ③ There were different types of carbon efficiency characteristics in each city, and according to the movement rules of the corresponding points in the quartile map, the evolution patterns of tourism industry efficiency were classified into stable, reciprocating, progressive, and abrupt. Therefore, local governments should adopt differentiated strategies to reasonably allocate spatial resources of production-living-ecological space and improve the technical level and scale efficiency, so as to improve the efficiency of urban carbon metabolism.

New evidence of the driving forces behind Brazil's agricultural TFP growth—A stochastic frontier analysis with climatic variables and land suitability index

AbstractUsing panel data from 510 Brazilian micro‐regions in three census years (1995, 2006 and 2017), this study presents a productivity decomposition for the Brazilian agricultural sector using stochastic production frontier methods that account for the effects of rainfall, temperature and the land suitability index. We also calculated the total factor productivity (TFP) index and decomposed it into technical efficiency, technological change, scale efficiency and environmental efficiency. This article thus provides a new and more realistic assessment of recent Brazilian agricultural productivity growth. In recent decades, Brazilian agriculture has become widely known for presenting fast productivity growth; however, our results suggest that a lower TFP growth rate than previous estimates (1.96% per annum) and the overall effects of climate change could potentially compromise Brazilian agricultural TFP growth in the long run. Our findings might thus generate insights for agricultural and regional policies to increase efficiency in the sector and promote sustainable agricultural development in Brazil, which will contribute to the sector's competitiveness in international markets, the country's social and economic welfare, and environmental conservancy.

A facile heterogeneous catalytic approach for one-pot synthesis of fused benzoxazinones using Cuβ zeolite and Evaluation of biological activities

A simple heterogeneous catalytic process has been established for the single-step synthesis of fused benzoxazinones, quinazolinones, and thiadazines through Markownikoff's hydroamination followed by intramolecular cyclization using Cuβ zeolite. The probability and limitations of this catalytic approach were explored using various substrates. The efficiency and feasibility of scaling up the current catalytic system were demonstrated through gram-scale experiments. Moreover, the catalyst was reused for up to five cycles with no noticeable decrease in its catalytic effectiveness. Furthermore, the synthesized compounds were subjected to in vitro assessment to determine their potential as anticancer agents against human cervical epithelioid carcinoma (HeLa), mouse breast cancer (4T-1), and human lung adenocarcinoma (A-549) cell lines. Cytotoxicity studies revealed that 3f, 3b′, 3d′, and 3g′ compounds exhibit anti-cancer activity against breast, cervical and lung cancer cells. Additionally, their antimicrobial activity against bacteria and yeast was also evaluated. The compound 3i exhibited superior antifungal activity against Candida albicans.

A Comparative Performance Analysis of Non-Life Insurance in Tanzania and Kenya

This study compares the performance of non-life insurance in Tanzania and Kenya. Specifically, the study compares the Technical and Scale Efficiency (TSE) of non-life insurance in the two countries. It further explores the sources of technical inefficiency in non-life insurance in Tanzania and Kenya. The study employs Data Envelopment Analysis (DEA) to estimate the efficiency of the non-life insurance firms by adopting two inputs: management expenses and commission paid, while premiums written, and net investment income were used as output variables. Data were extracted from the annual reports of non-life insurance companies in Tanzania and Kenya for the years 2014-2017 (four years). The study revealed that non-life insurance firms in Tanzania were more technical and scale efficient compared to their Kenya counterparts. When technical efficiency was further decomposed into pure and scale efficiency to examine what largely caused inefficiency, it was revealed that in both Tanzania and Kenya, inefficiency is largely derived from a lack of technical efficiency, which reflects issues of innovation in the sector, inappropriate management practices, operating at sub optimal size of operation and misallocation of resources in production system. This study offers information relevant for investors and policymakers to make informed decisions in the insurance sector in both countries. It further guides insurance firms on the important inputs and proper allocation of the resources in the production system. The findings also contribute to our growing understanding of the effectiveness of non-life insurance in the insurance markets of the two nations.

Carbon emission efficiency of land use in urban agglomerations of Yangtze River Economic Belt, China: Based on three-stage SBM-DEA model

Exploring regional differences in land use carbon emission efficiency (LUCE) and the path of collaborative emission reduction in the Yangtze River Economic Belt (YREB) are of immense importance to achieve the sustainable regional development. Firstly, based on the estimation method of land use carbon emissions, this paper scientifically calculates the carbon emission of land use of the Yangtze River Delta urban agglomeration (YRD), the middle reaches of the Yangtze River urban agglomeration (MRYR), and the Chengdu-Chongqing urban agglomeration (CC) from 2010 to 2021 in the YREB. And the carbon emission of land use of each city in urban agglomerations was obtained, which was regarded as the unexpected output in the efficiency evaluation index system. Secondly, the three-stage SBM-DEA model was used to reveal the LUCE and its spatiotemporal characteristics in different regions from a static perspective. The empirical results of the second stage SFA showed that the level of economic development, urbanization rate, industrial structure, non-agricultural conversion rate of agricultural land, the level of scientific and technological innovation and government intervention had significant effects on LUCE. By comparing the efficiency values and their decompositions in the first and third stage of various urban agglomerations, it was found that after eliminating environmental and random factors, the average ranking of comprehensive technical efficiency (TE) of land use carbon emission changed from YRD > MRYR > CC to YRD > CC > MRYR due to the cross influence of pure technical efficiency (PTE) and scale efficiency (SE). Thirdly, Malmquist index model was used to analyze the change of total factor productivity index (TFPch) and its spatiotemporal pattern from a dynamic perspective. It was found that the TFPch, technological progress index (TC), pure technical efficiency index (PEC) and scale efficiency index (SEC) of land use carbon emission of the three major urban agglomerations all showed varying degrees of increase after adjustment. Finally, to further analyze the impact of technological progress, PTE and SE on LUCE, a regression model was constructed with LUCE of each city in urban agglomeration as the dependent variable, and TC, PEC and SEC as independent variables. It was concluded that technological progress was the main factor to promote the improvement of LUCE in the whole YREB. The trend of changes of LUCE in various urban agglomerations was closely related to its management level, technology level and factor structure adjustment. The above conclusions provide support for the coordinated emission reduction path of urban agglomerations in the YREB from the perspective of land use, which is conducive to actively and steadily promoting the realization of carbon peak and carbon neutrality goals.

Dynamic Coupling Analysis Between Scale of Network Retail Market and Green Circulation Efficiency

Abstract A sound circulation system is an important carrier for the development of the retail industry, and the promotion of green circulation efficiency (GCE) plays an important role in driving the market scale expansion of network retail (NR). This study uses the development status of China’s NR and circulation industries as basis to estimate the total carbon emissions (CE) of the circulation industry by using the system dynamics method. Moreover, this research measures China’s GCE by combining data envelopment analysis (DEA) and Malmquist index to construct a coupling analysis model to empirically investigate the dynamic coupling relationship between the NR scale and green circulation efficiency. Results indicate that China’s GCE is generally increasing, but growth rate fluctuates significantly. Additionally, the improvement of the quality and efficiency of China’s circulation industry has not yet formed a steady green path. China’s NR market scale continues to expand, but NR at this stage is still mainly concentrated in the eastern region. The efficiency of green circulation and scale of the NR market show a good coupling trend, but there is still a significant gap between the central and western regions. Accordingly, this study proposes that the construction of a green circulation system should be strengthened, and that the development of a green and efficient circulation industry should be taken as the engine of the NR scale expansion.