Logistics In China Research Articles

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.

Measurement and spatial and temporal characterization of logistics efficiency--Based on a three-stage DEA model

The logistics industry is an essential component of economic and social development. Enhancing its efficiency contributes to national economic progress. However, the sector faces challenges such as high costs and pollution. This paper conducts an empirical study on the logistics efficiency of 30 Chinese provinces (excluding Xinjiang Uygur Autonomous Region) from 2004 to 2021 using a three-stage DEA model. Findings reveal that before adjustment, five provinces, including Beijing and Shanghai, were on the efficiency frontier, reduced to three after adjustment. Other provinces exhibit room for improved logistics efficiency, particularly in addressing cost and pollution issues. The key to enhancing efficiency lies in technical and scale efficiency adjustments. External environmental factors significantly influence logistics efficiency; social retail goods consumption positively correlates, while Gross Regional Product negatively correlates. Overall, China's logistics efficiency displays an upward trend but with notable regional disparities, indicating higher efficiency in the eastern region and lower efficiency in central and western regions, resulting in an overall "high in the east, low in the west" pattern.

China's logistics evolution: A study of development characteristics and catalytic effects on economic growth.

The impact of logistics development on the economy covers many aspects, such as production, cost, employment, international trade, etc. It is an indispensable part of the modern economy, which helps to improve overall economic efficiency and social prosperity. This study studies the spatiotemporal dynamic evolution characteristics of China's logistics development from 2008 to 2018 and explores its impact on economic growth in multiple dimensions of time and space. The research findings indicate the following: (1) From 2008 to 2018, China's logistics development level (LDL) exhibited a clear upward trend. The differences between the eastern, central, and western regions showed fluctuating downward patterns, ultimately converging towards a high-level concentration. Concerning spatial distribution, China's logistics development demonstrated a trend towards the west and south. However, the spatial pattern of "strong in the east and weak in the west " has existed for a long time. Moreover, the "T-shaped" pattern between coastal provinces and those along the Yangtze River Basin deepened, and the LDL in the central and western regions significantly improved. (2) The advancement of China's LDL effectively promotes its economic growth, confirming that the Belt and Road Initiative enhances the role of logistics development in driving economic growth. Regarding regional differences, logistics development positively influences economic growth in the eastern and western regions, with a less significant impact on the central region. Regarding the strength of influence, logistics development has a more substantial effect on promoting high-ranking provinces in the entire country, the eastern region, and the central region, as well as boosting economic growth in low-ranking provinces in the western region.

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.

Low Carbon Logistics Research Review

The logistics industry is one of the main industries of "carbon emission", and low-carbon logistics is also related to the realization of the goal of "carbon peak" and "carbon neutrality". This paper uses the literature research method, takes the concept of low-carbon logistics as the starting point, and combs the relevant research progress. Firstly, this paper introduces the concept of low-carbon logistics from the perspective of low-carbon and circular economy, and introduces the realization method of low-carbon logistics. Secondly, it reviews the progress of literature research from the aspects of low-carbon transport, low-carbon packaging, low-carbon storage, and low-carbon policy. It is concluded that the main direction of future research will be to shift from traditional local low-carbon research to systematic low-carbon research, use modern information technology and intelligent tools to help low-carbon logistics, and pay attention to the local problems brought by China's logistics practice.

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.

Study on the Influencing Factors of Regional Logistics on Regional Economy in Shanxi Province

With the acceleration of the pace of Belt and Road construction and the strategic deployment of the high-quality development of China's logistics service industry, the logistics industry has occupied an increasingly important position in the whole national economy and even the world economy. Shanxi Province is rich in coal resources and has a large demand for logistics and freight transportation. Therefore, the economic growth of Shanxi Province has put forward higher requirements for the development and progress of the logistics industry. In this situation and background, the development of regional logistics will be of great help to the progress and growth of the overall industrial economy in Shanxi Province. This paper takes the theory of modern logistics, regional economic growth and regional coordinated development as guidance, and discusses the coordinated development of logistics industry and economic sustainable development in Shanxi Province. Firstly, a series of theoretical analysis on the coordinated development of modern regional logistics, regional economy and the correlation between regional logistics and regional economy with the aid of data analysis software stata and the research results are summarized and summarized, trying to make some suggestions for the sustainable development of logistics and economy in Shanxi Province.

Influencing factors and countermeasures on intelligent transformation and upgrading of logistics firms: A case study in China.

This study explores the influencing factors on intelligent transformation and upgrading of China's logistics firms under smart logistics, and designs the corresponding framework to guide the practice of firms. By analyzing the characteristics of smart logistics and the transformation and upgrading needs of traditional logistics, from the micro perspective of logistics firms, this paper constructs influencing factor index system of smart transformation and development from four dimensions: logistics technology innovation, logistics big data sharing, logistics management upgrading and logistics decision-making transformation. Logistics firms are divided into firms with medium scale and above and small and medium-sized firms according to their scale. Then EWIF-AHP model is proposed to measure the weight of index system and score the decision-making, so as to evaluate the impact of various influencing factors on transformation and development of logistics firms. The results show that, for logistics firms above medium scale, logistics technology innovation and logistics big data sharing have the most significant impact on transformation and development, followed by logistics management upgrading and logistics decision-making transformation. For small and medium-sized logistics firms, the biggest factor is the upgrading of logistics management, followed by the upgrading of logistics technology, which is almost as important as the influencing factors of the upgrading of logistics management, and followed by the sharing of logistics big data and the transformation of logistics decision-making. Therefore, corresponding countermeasures and suggestions for intelligent transformation of logistics firms have been put forward.

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.

Does the Design of Investor Relations Section Affect Enterprise Performance?

With the development of the major e-commerce platforms in recent years, China's logistics enterprises have entered a stage of rapid development. A large number of logistics enterprises have resorted to external capital to seek development. Related research about website investor relations management arises at the historic moment. Based on the analysis of website content of listed logistics enterprises, this paper constructed an evaluation index of the website investor relationship management. The index includes motivating information factor, health information factor, and information transmission channels factor. Then the authors analyze and test the value effect of the website investor relations management of the listed logistics companies. The results show that health information factor has a positive impact on the current performance of enterprises, and this effect presents inverted u-shaped characteristics. The influence of incentive information on performance is characterized by u font. Information transmission channel factors have no significant impact on company performance.

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.

The Convergence of IoT, Big Data, and International Logistics: Enhancing Supply Chain Efficiency

This paper explores the transformative convergence of the Internet of Things (IoT) and Big Data within the realm of international logistics, focusing on their collective potential to enhance supply chain efficiency. We delve into the IoT's foundational technology, its role in international logistics, and its adoption within China's logistics networks. Additionally, we examine the significance of Big Data analytics, its applications in supply chain management, and its specific utilization in China's international logistics operations. The paper also highlights the convergence of these technologies, emphasizing their impact on supply chain efficiency and data-driven decision-making. Privacy and security concerns, the cost of technology adoption, workforce training, and international cooperation are addressed as critical challenges. Finally, the paper presents policy recommendations and a forward-looking perspective on the future development of IoT, Big Data, and international logistics.

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.

Research on the Evaluation and Spatial Difference of China's Regional Logistics Digital Innovation Ability Based on Entropy Weight — Toptsis

With the transformation of economic development and the innovation and promotion of high-tech, the logistics industry is also entering an important stage of transformation and upgrading. With the progress of science and technology, the traditional logistics industry is bound to transform to the direction of digital logistics. In this process, the digital innovation ability of logistics is the key to transformation and upgrading. After combing the relevant research, this paper constructs the evaluation index system of logistics digital innovation ability, uses entropy weight method to calculate the comprehensive weight of each index, and uses TOPSIS method to calculate the score, analyzes the index panel data of 30 provinces and cities in China from 2016 to 2020, and compares the four plates in space According to the logistics digital innovation ability of the eight special economic zones, this paper analyzes the spatial differences of China's logistics digital innovation ability, and puts forward the existing problems and future prospects.