scholarly journals Ecological Efficiency Evaluation and Spatiotemporal Characteristics Analysis of the Coupling Coordination of the Logistics Industry and Manufacturing Industry

2021 ◽  
Author(s):  
Juan Su ◽  
Tong Shen ◽  
shuxin jin
Keyword(s):  
Carbon Emissions ◽  
Spatial Data ◽  
Manufacturing Industry ◽  
Spatial Differentiation ◽  
Manufacturing Industries ◽  
Spatial Data Analysis ◽  
Sustainable Supply Chain ◽  
Ecological Efficiency ◽  
Logistics Industry ◽  
Positive Effects

Abstract The coupling coordination of the logistics industry and manufacturing industry conducive to the sustainable development of logistics and manufacturing and the stability of sustainable supply chain. The logistics and manufacturing industries are not only the basic industries that support social development, but also the industries with high carbon emissions. Firstly, this paper classifies the carbon emissions from the logistics industry and manufacturing industry as undesirable outputs, evaluates the ecological efficiency of the logistics industry (LEE) and manufacturing industry (MEE) in the Yangtze River Delta from 2006 to 2019 by using the unexpected slacks-based measure (SBM) model. Secondly, the coupling coordination method is used to analyze the coupling coordination scheduling of industrial ecological efficiency. Thirdly, the paper analyzes the spatial differences of the coupling coordination ecological efficiency between logistics industry and manufacturing industry (MLCC) by using the exploratory spatial data analysis method. Finally, the spatial econometric model is used to analyze the driving factors of the MLCC. The results show: The ecological efficiency of the manufacturing industry has steadily improved. The ecological efficiency of the logistics industry presents the rising trend in fluctuation. The level of the coupling coordination development between the logistics and manufacturing industries is high. The results of the spatial heterogeneity analysis show that the spatial differentiation of high-high agglomeration and low-low agglomeration is obvious. The spatial agglomeration characteristics are relatively stable, and the spatial diffusion effect is strong; In space, the MLCC shows a trend of developing from multiple agglomeration areas to one agglomeration area. The results of driving factor analysis show that foreign direct investment(FDI), government intervention(GI) and human capital(HP) have positive effects on the MLCC, while industrial structure(IS), environmental regulation(ER) and energy intensity(EI) have negative effects on the MLCC.

scholarly journals Spatial Agglomeration of China’s Forest Products Manufacturing Industry: Measurement, Characteristics and Determinants

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1006
Author(s):  
Zhenhuan Chen ◽  
Hongge Zhu ◽  
Wencheng Zhao ◽  
Menghan Zhao ◽  
Yutong Zhang
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Economies Of Scale ◽  
Forest Products ◽  
Spatial Data Analysis ◽  
Forest Protection ◽  
Spatial Agglomeration ◽  
Continuous Space

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

scholarly journals Using a Novel Grey DANP Model to Identify Interactions between Manufacturing and Logistics Industries in China

2018 ◽  
Vol 10 (10) ◽  
pp. 3456 ◽  
Author(s):  
Peng Jiang ◽  
Yi-Chung Hu ◽  
Ghi-Feng Yen ◽  
Hang Jiang ◽  
Yu-Jing Chiu
Keyword(s):  
Manufacturing Industry ◽  
Multiple Criteria Decision Making ◽  
Value Added ◽  
Manufacturing Industries ◽  
Direct Influence ◽  
Key Factors ◽  
Logistics Industry ◽  
Influence Matrix ◽  
Factors Affecting ◽  
Two Factors

As a crucial part of producer services, the logistics industry is highly dependent on the manufacturing industry. In general, the interactive development of the logistics and manufacturing industries is essential. Due to the existence of a certain degree of interdependence between any two factors, interaction between the two industries has produced a basis for measurement; identifying the key factors affecting the interaction between the manufacturing and logistics industries is a kind of decision problem in the field of multiple criteria decision making (MCDM). A hybrid MCDM method, DEMATEL-based ANP (DANP) is appropriate to solve this problem. However, DANP uses a direct influence matrix, which involves pairwise comparisons that may be more or less influenced by the respondents. Therefore, we propose a decision model, Grey DANP, which can automatically generate the direct influence matrix. Statistical data for the logistics and manufacturing industries in the China Statistical Yearbook (2006–2015) were used to identify the key factors for interaction between these two industries. The results showed that the key logistics criteria for interaction development are the total number of employees in the transport business, the volume of goods, and the total length of routes. The key manufacturing criteria for interaction development are the gross domestic product and the value added. Therefore, stakeholders should increase the number of employees in the transport industry and freight volumes. Also, the investment in infrastructure should be increased.

Spatial Disequilibrium Development and its Policies of Central China: The Case of Hubei Province

2013 ◽  
Vol 361-363 ◽  
pp. 160-167
Author(s):  
Yun Liu ◽  
Li Li Chang ◽  
Chong Peng
Keyword(s):  
Spatial Data ◽  
Statistical Data ◽  
Global Analysis ◽  
Spatial Differentiation ◽  
Hubei Province ◽  
Central China ◽  
Spatial Data Analysis ◽  
Economic Space ◽  
Reasonable Choice ◽  
Disequilibrium Theory

Central China is progressively paving its way to the second carrier of Chinese population after the east coastal areas with disequilibrium theory as the guidance of provincial spatial development. Based on ESDA (exploratory spatial data analysis) with statistical data of GDP per capita of Hubei Province by county-level (2000-2010), this paper reveals the spatial differentiation characteristics of economic differences among counties in Hubei Province. According to global analysis of ArcGIS and GeoDA095i, economic space of the county presents the trend of climbing up and then declining. Besides, differences between counties are remarkable. The LISA clean-cut indicates different developed and underdeveloped districts. Finally, contrasting to policy response that the provinces cope with disequilibrium theory in Central China, the results show that the Central China continues to promote disequilibrium development is a reasonable choice, and it’s also indispensible to pay attention to controlling magnification of differences in regional development.

Manufacturing Migration and Trade Embodied Carbon Transfer: Empirical Evidence From China and Thailand

2021 ◽  
Author(s):  
jian wu ◽  
Chunying Cui ◽  
Xiaolong Mei ◽  
Qingsong Xu ◽  
Pu Zhang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Industrial Structure ◽  
Manufacturing Industries ◽  
Investment Environment ◽  
The Sustainable Development ◽  
Embodied Carbon ◽  
Carbon Transfer ◽  
Asean Countries

Abstract At present, China's carbon emissions rank first in the world, which not only brings huge challenges to the sustainable development of China's economy, but also brings more pressure from public opinion in the international community. In 2020, ASEAN has become China's largest trading partner, and Thailand, due to its unique industrial structure and investment environment, will surely become one of the main ASEAN countries to undertake the transfer of China's manufacturing industry. Over the years, the shift of carbon emissions by the continuous transfer of a large number of basic manufacturing industries from China to Thailand promoted the release of China's carbon emission pressure. In this article, on the basis of the data of import and export commodities between China and Thailand from 2012 to 2017, the input-output model is carried out to analyze the energy consumption of China's various industries, and three periods, namely 2012, 2015, and 2017, are used to be key periods to calculate the embodied carbon of China's manufacturing migration and Sino-Thailand trade. The empirical results show that the transfer of China's manufacturing to Thailand from 2012 to 2017 has continued to rise. The transfer of Chinese manufacturing to Thailand is positively correlated with the carbon emissions of trade between the two countries, which has promoted the relief of China's pressure on energy conservation and emission reduction. Therefore, government departments should formulate differentiated and stable domestic manufacturing policies; spend on the development of advanced manufacturing industries with low energy consumption and high technology density; encourage the relocation of industries with low technology density and high carbon emissions to effectively reduce environmental pressure in China.

scholarly journals Study on the Level and Type Identification of Rural Development in Wuhan City’s New Urban Districts

2020 ◽  
Vol 9 (3) ◽  
pp. 172 ◽  
Author(s):  
Liang Jiang ◽  
Jing Luo ◽  
Chunyan Zhang ◽  
Lingling Tian ◽  
Qingqing Liu ◽  
...  
Keyword(s):  
Rural Development ◽  
Spatial Data ◽  
Rural Areas ◽  
Urban Areas ◽  
Socioeconomic Development ◽  
Spatial Differentiation ◽  
Principal Component ◽  
Spatial Data Analysis ◽  
Balanced Development ◽  
Urban Districts

A quantitative analysis of rural development is required to comprehend the spatial differentiation of a rural area and promote rural sustainable development under the pressure of urbanization and industrialization, especially areas with dramatic changes in rural socioeconomic development of China and other developing countries. Taking Wuhan as the case study, this paper developed an index system including rural settlement, land, industry and human settlement environment for evaluating the level of rural development. Then, using the exploratory spatial data analysis, the principal component analysis and the cluster analysis, this paper analyzes the spatial differentiation and correlation and categorizes the types of rural development. The results are as follows. (1) The spatial differentiation of the level of rural development in Wuhan City’s new urban districts is obvious and the areas with a high level of rural development are mainly distributed at the intersection of the new and central urban areas and gradually decrease outward. (2) There is a significant spatial agglomeration of the developed rural areas and the structure of the spatial change in these areas resembles a certain continuity, specifically a circle of “central heat surrounding cold”. (3) Rural development in the new urban areas can be divided into the following five types: the ecological leisure type, the traditional farming type, the balanced development type, the industrial-and-agricultural mixed type and the industrial promotion type. The corresponding development path is proposed in combination with different types of rural development to provide a theoretical basis and decision-making reference for rural revitalization.

The Provincial Carbon Footprint and Trade

2012 ◽  
Vol 524-527 ◽  
pp. 3514-3518 ◽  
Author(s):  
Yan Wang ◽  
Na Li
Keyword(s):  
Carbon Footprint ◽  
Carbon Emissions ◽  
Industrial Development ◽  
Manufacturing Industry ◽  
High Energy ◽  
Manufacturing Industries ◽  
Total Carbon ◽  
Low Carbon ◽  
Demand Structure ◽  
High Energy Consumption

Based on the data of provincial input-output model and the carbon footprint model, the analysis is focused on provincial carbon footprint and the space transfer of carbon emissions. The results have shown that: (1) There are significant differences of provincial total carbon footprint amounts: resource-rich provinces have high total carbon footprint amounts, followed by processing and manufacturing provinces and municipalities; Regions with high energy efficiency have low carbon footprint amounts, so does southwestern region where economic and industrial development level is relatively low. (2) The provincial differences of carbon footprint per capita are related to demand structure: the amounts of carbon footprint are high in provinces with higher demand of consumption and investment, especially those provinces with strong demand for construction and processing industries. The amounts of carbon footprint are low in provinces which are non-resource-based, have limited investment and construction, and its economic structure is not dominated by processing and manufacturing. (3) Interprovincial trades have a significant impact on carbon footprint and carbon emissions. Provinces with well developed infrastructure have net CO2 emissions flow-in that are directly induced by high energy consumption products; southwestern region, where processing and manufacturing industry is relatively less-developed, has main CO2 emission flow-in, which are induced by the demand of processing and manufacturing industries; resource-intensive provinces and provinces with well-developed processing and manufacturing industries have net CO2 emission flow-out, which are induced by interprovincial trades.

scholarly journals Optimizing a Sustainable Supply Chain Inventory Model for Controllable Deterioration and Emission Rates in a Greenhouse Farm

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 495
Author(s):  
Umakanta Mishra ◽  
Abu Hashan Md Mashud ◽  
Ming-Lang Tseng ◽  
Jei-Zheng Wu
Keyword(s):  
Supply Chain ◽  
Carbon Emissions ◽  
Trade Credit ◽  
Numerical Study ◽  
Inventory Model ◽  
Green Technology ◽  
Solution Technique ◽  
Emission Rates ◽  
Sustainable Supply Chain ◽  
Green Technologies

This study investigated how greenhouse managers should invest in preservation and green technologies and introduce trade credit to increase their profits. We propose a supply chain inventory model with controllable deterioration and emission rates under payment schemes for shortage and surplus, where demand depends on price and trade credit. Carbon emissions and deterioration are factors affecting global warming, and many greenhouse managers have focused on reducing carbon emissions. Carbon caps and tax-based incentives have been used in many greenhouses to achieve such reduction. Because of the importance of reducing carbon emissions for developing a green supply chain, various studies have investigated how firms deal with carbon emission constraints. In this continuation, we have used green technology to curb the excessive emissions from the environment or make it clean from CO2. In a seller–buyer relationship, the seller can offer a trade credit period to the buyer to manage stock and stimulate demand. Deterioration may become a challenge for most firms as they are under time constraints control, and preservation technology could help. This study proposes three novel inventory strategies for a sustainable supply chain (full backorder, partial backorder, and no backorder), linking all these important issues. The solution optimizes total annual profit for inventory shortage or surplus. We conducted a numerical study with three examples to evaluate the model’s authenticity and effectiveness and demonstrate the solution technique. The deterioration and emission rates can be included in a trade credit policy to increase greenhouse profits. The results suggest that greenhouse managers could apply the proposed model to manage real-world situations.

Sign in / Sign up

Export Citation Format

Share Document