Logistics Industry In China Research Articles

Evaluation of Logistics Development Under the Visual Field of Low-Carbon Environmental Protection Based on Hierarchical Methods

The development of the modern logistics industry in China is relatively backward, and the logistics industry has always shown characteristics of high emissions, high energy consumption, and high pollution. The low-carbon transformation and development of the logistics industry has become a prominent issue. At present, research on low-carbon logistics mainly focuses on its definition and characteristics. The research on its influencing factors is mostly qualitative analysis, and there is relatively little research on performance evaluation. This article establishes a performance evaluation index system from the perspective of low-carbon environmental protection, including information technology level, warehousing, transportation, packaging, etc., and constructs a comprehensive evaluation model that combines an analytic hierarchy process with data envelopment analysis for low-carbon logistics performance evaluation. By reviewing the collected data and taking five logistics enterprises in China as examples, the feasibility of low-carbon logistics performance evaluation indicators and models was verified.

Examining the Factors that Influence the Employee Green Behavior in China Logistics Industry Using Social Identity Theory

Examining the Factors that Influence the Employee Green Behavior in China Logistics Industry Using Social Identity Theory

Analysis of Spatial Agglomeration Characteristics of Logistics Enterprises in Henan Province based on Poi

As an important industry connecting urban and rural areas and serving production and life, logistics enterprises, as the micro-foundation of the development of logistics industry, have a profound impact on the spatial reconstruction of regional economic and social development. National Development and Reform Commission issued the "Fourteenth Five-Year Plan" modern logistics development and "Fourteenth Five-Year Plan" modern circulation system construction planning "put forward new requirements for the development of logistics industry, emphasizing the optimization of logistics spatial layout and speed up the construction of national logistics hub, especially pointed out that to make up for the shortcomings of the central and western regions. As an important base for the development of China's logistics industry, the spatial layout of logistics enterprises in Henan province not only affects the high-quality development of the logistics industry in the province, but also plays an important role in the improvement of the national logistics network. In this paper, based on POI data, the mean nearest neighbor method, local Moran scatter plot analysis and kernel density visualization technology are used to analyze the spatial agglomeration characteristics of logistics enterprises in 157 counties in Henan Province. It is found that the spatial distribution of logistics enterprises in Henan Province has gradually evolved from multi-point dispersion to a single-core and multi-core collaborative model with Zhengzhou as the core, and presents a significant spatial positive correlation and agglomeration trend. This change has improved the logistics efficiency and promoted the strengthening of regional economic ties. At the same time, the agglomeration trend of logistics enterprises in Henan Province continues to strengthen, from the initial agglomeration in the core area to the diversified diffusion pattern, showing the continuous optimization and reconstruction of logistics network in the province.

Spatiotemporal Differentiation of Carbon Emissions from Logistics Industry at Provincial Scale in China Under the Background of High-quality Economic Development

Since 2010, the Chinese economy has transitioned from a high-speed growth model to a high-quality development model. During this period, the logistics industry has witnessed rapid growth, leading to significant carbon emissions and posing severe threats to the ecological environment. To investigate the spatiotemporal variations in carbon emissions in China's logistics industry, we conducted a correlation analysis using Moran's I index and a bivariate spatial autocorrelation model from 2010 to 2021. Additionally, we employed a geographically and temporally weighted regression model （GTWR） to examine the spatial heterogeneity of factors influencing provincial-level logistics-related carbon emissions. The results indicated that over the study period, there was a shift from insignificant spatial relationships to significant positive spatial correlations among provincial-level logistics carbon emissions in China. Furthermore, varying degrees of spatial clustering were observed. The findings regarding factor heterogeneity revealed that freight turnover volume, per capita GDP of the logistics industry, and infrastructure level exhibited positive spatial correlations with logistics-related carbon emissions, whereas energy intensity showed negative spatial correlations with such emissions. Comparing the results from the geographically weighted regression （GWR） and ordinary least squares regression （OLS）, it was evident that the adjusted R-squared values for the OLS, GWR, and GTWR models were 0.541, 0.567, and 0.838, respectively. This suggests that our adopted GTWR model provided a superior fit and offered better explanations for spatiotemporal heterogeneity between various influencing factors and logistics-related carbon emissions. These research findings can serve as valuable references for formulating province-specific strategies to reduce carbon emissions within China's economy under its high-quality development context.

The spatial spillover impact and transmission mechanisms of logistics agglomeration on eco-efficiency: A case study in China

This study employs spatial durbin model (SDM) and spatial mediation model to empirically investigate the relationship between logistics agglomeration (LA) and logistics eco-efficiency (LEE), as well as the transmission mechanism role of technological innovation (TI) and advanced industrial structure (AIS), using panel data on inter-provincial logistics in China from 2008 to 2020. The findings indicate a U-shaped relationship between LA and LEE. The early development of LA in China was accompanied by environmental sacrifices. Further analysis of the curves reveals that LA has spatial spillover effect on LEE. That is, insufficient concentration of LA has a siphon effect on the LEE of surrounding areas, whereas appropriate concentration of LA has a radiation effect on the LEE of surrounding areas. Spatial mediation analysis indicates that enhancing TI and developing AIS are essential channels through which LA bolsters LEE. Additionally, this study innovatively incorporates topography ruggedness and altitude as instrumental variables to account for potential endogeneity issues in the empirical model. Theoretical and practical significance is attributed to this research for China's logistics industry, particularly shedding light on the optimization of efficiency and long-term improvement of LEE through spatial reform via agglomeration zones.

Analysis on the spatial correlation network and driving factors of carbon emissions in China's logistics industry

Promoting the green development of the logistics industry has become a focal point of attention in China. This study combines an improved gravity model and social network analysis method, focusing on the nineteen provinces of the Yangtze Economic Belt and Yellow River Basin. It constructs a spatial correlation network of carbon emissions in the logistics industry from 2010 to 2021, exploring its formation mechanism and spatial evolution characteristics. The study utilizes a quadratic assignment procedure model to investigate internal driving factors. Building upon this, the study employs an improved STIRPAT model to predict the emission reduction path of the future logistics industry. Results are as follows: (1) Carbon consumption is most pronounced in Shandong, Jiangsu, and Shanghai. The carbon emission shows the characteristics of larger downstream; (2) The bridges of carbon emission-related networks gradually shift from Shandong to Shanxi, Anhui, and Sichuan. Carbon emissions in each sector and spatial spillover effects exhibit dynamic correlations and interactive influences; (3) Energy intensity, freight volume, and the spatial correlation network of the logistics industry are highly correlated; (4) The overall carbon emissions from the logistics industry show a decreasing trend in the future. Anhui and Shaanxi provinces will have high carbon emissions in 2035. The conclusions aim to provide policy suggestions for the region's low-carbon transformation.

Revitalizing the Economy: The Impact of Free Trade Areas on the Logistics Industry Agglomeration in Post-COVID China

This study examines the impact of free trade areas on China's logistics industry and its economy in the post-COVID era. The paper primarily focuses on key regions, utilizing the Location Quotient (LQ) method to analyze relevant trends. Notably, Hainan demonstrates substantial growth in the logistics sector, whereas Shanghai and Guangdong exhibit increased output despite declining LQ values, indicative of a shift towards services and innovation. Furthermore, logistics agglomeration promotes cross-industry collaboration, efficient value-added services, job creation, and career mobility, all of which address the economic challenges faced by China. This study emphasizes the crucial role played by free trade areas, such as Hainan, in stimulating logistics agglomeration and driving economic recovery, trade expansion, and employment opportunities in the post-pandemic landscape, thereby offering valuable insights for future growth.

CiteSpace-based Logistics Distribution Center Site Selection Research

: China's logistics industry is developing at a high speed, but the distribution efficiency can't match with it, to reduce the waste of resources and costs on the way of distribution, it is crucial to study and improve the distribution center siting issue. Taking the 494 core journals on the study of logistics distribution center siting in Knowledge Network as the basic data, CiteSpace is used to visualize and analyze the related literature in this research field. Through the keyword clustering analysis, this field can be divided into four directions: the main body of research, the influence factors of site selection, the purpose of site selection, and site selection methods, and the comprehensive analysis shows that the early focus of China's research is on the site selection methods, such as genetic algorithm and center of gravity method, and the future research direction is the joint optimization of the site selection-path and the two-layer planning.

Empirical Analysis of the Factors Affecting the High-quality Development of the Logistics Industry

This paper selects China from 2006-2023 panel data, with cargo quantity as explained variable to measure the logistics industry development level, and the social logistics total cost as a proportion of GDP, the first industry output value, the second industry output, the tertiary industry, total retail sales of social consumer goods and total import and export as the main explanatory factors, establish multiple linear regression model, the development of China's logistics industry high quality impact factors empirical analysis, and combined with the present situation of China's logistics industry development and influence factors concluded and put forward Suggestions.

Analysis on the Low-carbon Transformation Path of China's Logistics Industry under the Background of Carbon Neutralization

Under the background of “carbon neutrality”, green and low-carbon have gradually become a broad consensus of the whole society. As an important part of social and economic development, the logistics industry consumes a large amount of energy and urgently needs low-carbon transformation.This paper analyzes the problems encountered in the low-carbon transformation development of our country's logistics industry and puts forward the necessary solutions, which will not only promote the development of the low-carbontransformation of our country's logistics industry, but also promote the realization of the goal of "carbon neutrality" as soon as possible. Based on the economic and social development of our country under the "double carbon" policy, facing the dilemma of low-carbon transformation of logistics industry in China, this paper puts forward the general and concrete ideas of low-carbon transformation of logistics industry in our country, and puts forward the specific path and method under the guidance of the thought of low-carbontransformation, hoping to provide some references for the low-carbon transformation of logistics industry in China.

Environmental regulations, technological innovation, and low carbon transformation: A case of the logistics industry in China

China is the world's largest emitter of carbon dioxide. The logistics industry is the second largest source of CO2 emissions, second only to the manufacturing industry. Therefore, developing effective environmental regulations to achieve low-carbon transformation in the logistics industry is an urgent task for government managers. Based on the 2005–2021 panel data of China's 30 provinces, this article adopts a data-driven nonparametric additive model to investigate the role of environmental regulations in CO2 emission reduction in the logistics industry. The results display that overall, environmental regulations contribute to carbon reduction in the logistics industry (an inverted N-shaped effect). After endogeneity test and various robustness tests such as replacing the variable value of core variable, this conclusion still has good reliability. Further heterogeneity analysis indicates that the carbon reduction effect of mandatory environmental regulations fluctuates frequently (a W-shaped impact). However, the carbon reduction impact of incentive environmental regulations has gradually shifted from insignificant in the early stages to prominent in the later stages (an inverted U-shaped pattern). Regional heterogeneity analysis shows that the impact of environmental regulations on carbon reduction in the eastern, central, and western regions also has significant nonlinear characteristics. Finally, this article verifies that technological innovation and energy consumption structure are effective intermediate mechanisms for environmental regulations to affect emission reduction. The research findings provide practical inspiration for the government to formulate relevant environmental policies and promote the green development of the logistics industry.

The Historical Evolution of China Logistics Industry and the Modernization Process Driven by E-business

The Historical Evolution of China Logistics Industry and the Modernization Process Driven by E-business

Research on Cost Management of Logistics Enterprises from the Perspective of Value Chain

In recent years, the rise of online platform transactions has led to the rapid development of the logistics industry. On the other hand, the extensive management mode of China's logistics industry can be changed to precise management, which has more advantages in international competition. This paper adopts a combination of literature research and case analysis to analyze how SN Holdings can use value chain cost management to optimize and allocate internal and external resources in the process of cost management, reduce energy consumption and improve resource efficiency, so as to maintain the long-term competitive advantage of the enterprise.

Carbon emission efficiency of China's logistics industry: Measurement, evolution mechanism, and promotion countermeasures

Improving carbon emission efficiency of the logistics industry (LCEE) is important in achieving carbon neutrality. We examine the carbon emissions of 31 provinces and cities in China that aim to reduce emissions and increase efficiency in the logistics industry. We construct the evaluation index system of LCEE, using the Super-EBM-unexpected model to measure it. Moreover, the global Malmquist–Luenberger index and the spatial autocorrelation model are used to analyze its temporal and spatial evolution mechanisms and identify its influencing factors via the spatial Durbin model. The results show a very low average LCEE value and a decreasing gradient distribution in space for China. The average pure technical efficiency is the main driving force for improving LCEE. Environmental regulation and the residents' consumption level positively affect LCEE. However, economic level, industrial structure, government input, and energy intensity have a negative impact. Countermeasures and recommendations are proposed to improve LCEE and provide theoretical and methodological support for its research and management. The study provides implications for policymaking related to ecosystem protection and sustainable development in the logistics industry.

Cold Chain Logistics Management and Operations: Problems and Suggestions in the Post-Epidemic Era

The outbreak of the COVID-19 epidemic has brought unprecedented challenges to global food supply chains, and cold chain logistics, which involves the transportation and storage of temperature-sensitive foods, has become a key area of concern. The ongoing incidence of infections from abroad that are imported due to the cold chain, which has negatively damaged the cold chain logistics sector. In China, monitoring and maintaining cold chain logistics still presents a few challenges despite the industry's fast expansion. Therefore, it is essential to conduct a comprehensive analysis of the problems and challenges faced by the cold chain logistics industry in China and to develop effective strategies and measures to enhance the management and control of the cold chain logistics industry. The purpose of this study is to offer insightful analysis and suggestions for enhancing the security and effectiveness of China's cold chain logistics sector in the post-epidemic age.

Social Network and Resources Integration Within Logistics Industry in China --- With Case Study of Cainiao Network

The business network in logistics industry is essential for integrating resources and establish firms own advantage of compettitiveness in the market, as well as providing more comprehensive services that facilitate firms to gain its revenue. Construction of intermediary platforms has therefore been an effective mean. Cainiao, a subdivided branch of Chinese giant enterprise Alibaba, has seized this opportunity. Though the debate about how social networks function to boost the high-quality development of firms has been very hot over the last three decades, few studies have mentioned and worked to understand to the linkage between social network analysis (SNA) and logistics chain management. Hence, the purpose of this research is to identify the construction of a business network by the giant Chinese logistics companies and its enhancing function of collaboration among firms and embeddedness for the success of Cainiao, which constructs the whole network. This paper will be carried out in concept explaination of essential terms in SNA and the practice of them into operation of Cainiao Network, as well as some diagrams made by Ucinet software will be applied. Results of the study show that through the early alliance of giant express enterprises, Cainiao has gained a wide network map that permits it to utilize abundant resources for the firms prosperity, and boosts the conjunction between the other companies and customers.

중국 물류산업의 경제적 파급효과에 대한 분석

This study analyzed the economic impact of the logistics industry in Shandong Province by utilizing the 2007, 2012, and 2017 industry linkage tables published by the Shandong Provincial Bureau of Statistics, which aimed to understand the economic impact and to serve as a policy reference for the future development of the logistics industry in Shandong Province. The results of the analysis are as follows. First, the column sum of the output induced coefficient of the logistics industry in Shandong Province of China, that is 1.407 in 2007, 3.658 in 2012, and 5.050 in 2017. Meanwhile, the row sum is 2.142 in 2007, 2.910 in 2012, and 3.291 in 2017. Except for manufacturing, the logistics industry in Shandong Province is generally considered to be an immature industry with low output induced effect, which means that the logistics industry in Shandong Province has a greater impact than other industries. Second, the sensitivity coefficient of Shandong’s logistics industry was 0.495 in 2007, 1.097 in 2012, and 1.423 in 2017, and the influence coefficient was 0.721 in 2007, 0.873 in 2012, and 0.928 in 2017. This indicates that the logistics industry in Shandong is sensitive to changes in the final demand of other industries and has a strong influence on others Third, the income induced coefficient of the logistics industry in Shandong is lower than that of other industries, which means that the opportunities for the entire logistics industry to create added value are mostly domestic. Fourth, the income induced by the final demand of the logistics industry in Shandong Province was 437.5 billion RMB in 2007, 230.19 billion RMB in 2012, and 207.08 billion RMB in 2017, indicating that the income induced by the final demand of the logistics industry is constantly increasing as the output scale of the logistics industry in Shandong Province continues to grow. Fifth, in 2007, 2012 and 2017, the total labor induced effects of the logistics industry in Shandong Province were 13,057.5, 793,569.9 and 479,856.5 respectively, of which the logistics industry accounted for 987.6, 21,308.5 and 15,687.3 respectively. As a result, it can be seen that with the continuous increase in the output scale of the logistics industry in Shandong Province, the income generating effect logistics industry’s final demand is growing. As a national strategic industry, it can lead other industries in China and be great potential to be listed. The logistics industry in Shandong Province needs government policy support and the development of a new “informationized logistics model”

Analysis of JD.com's Acquisition of Deppon

The old logistics company Deppon. founded in 1996, whose market value after listing was as high as 30 billion yuan. Contemporarily, the era of Internet e-commerce has arrived, the main express Deppon wants to share in this market in 2018 to optimize the original business, expand the transportation business of large express delivery. However, this transformation has put it into decline. Its new business growth was sluggish, and express revenue growth declined and market value has been falling. After the sharp drop in value, JD Logistics a logistics giant with a market value of more than 100 billion yuan, made an acquisition. After this acquisition, the two companies have integrated their businesses, complemented each other's advantages, and achieved great advantages in the fierce market competition. According to the analysis, the acquisition will improve the concentration of logistics industry in China and is beneficial to the healthy development of logistics industry. Overall, these results shed light on guiding further exploration of the significance of mergers and acquisitions.

Scenario prediction of carbon peaking in China's logistics industry based on SVR

As a strategic, basic and leading industry for the development of China's national economy, the logistics industry shoulders the important mission of implementing the national "dual carbon" goal. It is urgent to keep up with the pace of the times and accelerate the green and low-carbon process of the logistics industry. Based on the relevant data from 1998 to 2020, this paper selects 8 indicators such as fixed asset investment in the logistics industry, freight turnover, passenger turnover, freight volume, the number of trucks, PM2.5 concentration and per capita GDP. The scenario analysis method is combined with the SSA-SVR model to establish a scenario prediction model for China's logistics industry's carbon peaking. The research results show that: under the baseline scenario, the carbon emissions of China's logistics industry will peak in 2047; under the low-carbon scenario, carbon emissions will peak in 2038; under the enhanced low-carbon scenario, carbon emissions will peak in 2029. 55.94 million tons. Combined with the trend analysis results under different scenarios, China should continue to strengthen the construction of the carbon trading market, optimize the industrial structure, and accelerate the progress of carbon peaking.

Research on the Evolution of Technological Innovation Network in China's Logistics Industry

Based on the basic requirements of cost reduction and efficiency increase in China's modern logistics industry and the necessity of innovation network connection, this paper uses the data of patent transfer in logistics industry from 2003 to 2021 to build the logistics industry technology innovation network based on the research paradigm of evolutionary economic geography, summarizes the development stages of China's logistics industry technology innovation based on the industrial life cycle theory, uses the social network analysis method, and analyzes the network characteristics and spatial evolution of the network from the perspective of "subject-relationship" of the network. The network characteristics and spatial evolution of the logistics industry technology innovation network in the innovation subject dimension and urban spatial network in China are analyzed from the perspective of network "subject-relationship" with the help of Ucinet, Gephi and ArcGIS software.