Development Of Green Logistics Research Articles

Evaluation of vegetable green logistics in Lanling County of China based on DEMATEL-ANP-FCE model

IntroductionDue to the problems of greenhouse gas emissions, noise pollution, and vegetable waste pollution during the transportation of vegetables, it is not conducive to the sustainable development of the environment. To mitigate the pollution of the environment during transportation, vegetable green logistics plays a pivotal role in promoting both environmental sustainability and high-quality economic development. Therefore, it is crucial to evaluate the development of vegetable green logistics.MethodsThis research builds a DEMATEL-ANP-FCE model to scientifically assess the development of vegetable green logistics in Lanling County. In the first place, the model uses DEMATEL to verify the relationship and degree of influence between the primary indexes. In the second place, the ANP approach with Super Decisions software to determine the weights of the indexes at each level. Lastly, evaluating and scoring vegetable green logistics in Lanling County based on FCE.Results and discussionThe results of the study show that there is an interaction relationship between the primary evaluation indexes, and its evaluation score is low, the vegetable logistics in Lanling County has not reached the degree of greening. Accordingly, the evaluation results obtained by the DEMATEL-ANP-FCE model in this work are in line with the actual situation of vegetable green logistics in Lanling County, which verifies that the model has good applicability. Moreover, managerial contributions for promoting the development of vegetable green logistics in Lanling County are put forward in response to the evaluation situation. Expecting to enhance the greening level of vegetable logistical development and advance agricultural sustainability. Finally, all four questions raised in this paper are well addressed. This study also provides a new perspective and evaluation model for future related research.

Green Logistics Development of Express Companies in the Context of “Dual Carbon” Strategy Research

In the context of "dual carbon", green logistics as an emerging concept type, not only plays an important role in environmental protection and sustainable economic development, but also can bring great economic benefits to express delivery companies. However, the current development of green logistics technology in China is not mature enough, resulting in the transformation of the courier company is facing the situation of opportunities and challenges. In this paper, we sort out the "dual carbon" background of the development of green logistics courier company status quo, analyze the courier company in the process of transition to green logistics problems and targeted to put forward the corresponding measures to solve them, and hope to be able to other courier company's green logistics development to provide reference and reference.

Research on Green Logistics Development in Chengdu-Chongqing Region under the Perspective of Game Theory

Chengdu-Chongqing Twin Cities Economic Circle is an important growth pole for the formation of high-quality development in western China and has a unique and important strategic position in the overall situation of national development. Chengdu-Chongqing two places not only vigorously promote the construction of logistics corridors and infrastructure connectivity, but also promote the logistics of all kinds of factors of production, including reasonable flow and efficient agglomeration, and strive to promote the Chengdu-Chongqing two places to the green logistics, cost reduction and efficiency to make effective exploration. The paper first analyzes the current situation and problems of green logistics construction in the Chengdu-Chongqing area, and then establishes an evolutionary game model between the government, enterprises, and consumers based on the game theory perspective, to try to put forward reasonable suggestions for the development and construction of green logistics in Chengdu-Chongqing area.

Study on the Synergistic Development of "Smart + Green" Logistics Industry in Chongqing

Under the background of "digital economy" and "double carbon", logistics industry, as a typical industry with high input, high energy consumption and high emission, is imperative for its intelligent and green transformation. Chongqing, located in the southwest, is an important logistics hub, and the synergistic development of its logistics industry "smart + green" is of great significance to the economic growth and high-quality development of the industry. This paper constructs the index system for the synergistic development of smart logistics and green logistics, and analyzes the development level of smart logistics and green logistics as well as the level of coupling coordination in Chongqing from 2010 to 2022 by using entropy value method and coupling coordination degree model, with the aim of providing a reference for the government to improve the logistics policy as well as the active development of the logistics industry. The study shows that the overall development level of smart logistics and green logistics in Chongqing is on the rise, and the gap between the two is gradually narrowing, and the development level is gradually changing from green logistics development to synergistic development. The development trend of the coupling coordination degree of smart logistics and green logistics is good, and the coupling coordination degree gradually develops into high-quality coordination, and the trend of the coupling coordination degree is consistent with the trend of the development level of smart logistics, and smart logistics has a stronger role in promoting the synergistic development of the two. Among the subsystems, the scale of development, transportation capacity and digitization level in smart logistics and the level of resource utilization and energy use efficiency in green logistics are the short boards restricting the coordinated development of smart and green logistics, and the coordinating role between the subsystems needs to be strengthened.

Analysis of the Development of Green Logistics Based on Blockchain

There has been a wave of technological change and industrial transformation at home and abroad, and blockchain technology has played a non-negligible role in the change. "Blockchain + logistics" has become a hot topic in society. Blockchain technology is a typical decentralized technology, which can effectively make up for the weak links in the logistics industry, so as to provide strong technical support for the development of green logistics. Therefore, this article analyzes the development of blockchain in green logistics, and discusses them one by one from the aspects of transportation, distribution, recycling logistics, and supply chain.

Green Logistics Research Review Report

With the rapid development of the social economy, the modern logistics industry is, on the one hand, an important part of supporting the development of the national economy and enhancing the national economic competitiveness. On the other hand, logistics activities are also one of the main factors leading to the deterioration of the ecological environment and the waste of social resources, the development of green logistics has become the key to the transformation of the logistics industry. The article uses CiteSpace software to conduct a quantitative analysis of the literature on the theme of "green logistics", aiming to sort out the knowledge structure and research hot spots in the field of green logistics, summarize the research process of green logistics at home and abroad; secondly, classify the research and development directions of logistics Explore.

Assessing the impact of green logistics performance on vietnam's export trade to regional comprehensive economic partnership countries

This article uses a gravity model framework to examine the impact of green logistics on Vietnam's exports to countries participating in the Regional Comprehensive Economic Partnership (RCEP). The study uses a generalized least squares (GLS) estimation method based on panel data for the period 2010-2018 and has reliable sources. The results of empirical research have found the following main findings: (i) Logistics performance, encompassing cost, reliability, and time-related factors, significantly and positively influence Vietnam's exports; (ii) The interaction effects between supply chain input components (customs, infrastructure, and services) and CO2 emissions from the transportation sector have a positive impact on Vietnam's exports; (iii) The supply chain input components demonstrate direct and positive effects on exports when implemented in conjunction with their interaction effects with CO2 emissions from the transportation sector; (iv) The emissions of CO2 from Vietnam's transportation sector exert a negative influence on exports; (v) Adopting a green logistics approach that focuses on reducing CO2 emissions from the transportation sector demonstrates a positive influence on Vietnam's exports. This influence is observed through direct and moderating effects, indicating the potential for sustainable practices to foster export growth. These research findings provide valuable insights for managers and policymakers in the formulation of informed decisions related to the development and promotion of green logistics. By embracing sustainable practices and aligning export growth with environmental goals, Vietnam can enhance its competitiveness while contributing to a greener future.

JD Logistics Acquisition of Deppon Express: A Case Study Based on SWOT Analysis

JD Logistics and Deppon Express, both leading express delivery and logistics service providers in China, chose to cooperate in March 2022. While JD Logistics acquired Deppon Express, the two companies maintained independent operations. Based on JD Logistics' acquisition of Deppon Express, this paper will use SWOT analysis to analyze the operating conditions and market status of the two companies before and after the acquisition, and conclude that the strengths of the two companies after the acquisition are to make up for the shortcomings and increase the market share, the weaknesses are the uncertain profit model, and the opportunities are the changes in the logistics industry pattern and the development of green logistics. The threats include the risk of resource integration and the threat of competitors, and from this, the following suggestions are put forward for the future development of the two companies: accelerate resource integration, establish a new profit model, and accelerate the upgrading of the industrial chain.

Tracing the evolution of green logistics: A latent dirichlet allocation based topic modeling technology and roadmapping.

Green logistics (GL) is the main development trend of modern logistics. The analysis of green logistics topics and their evolution is helpful in grasping its development trend and doing research facing the international frontier. Focusing on the hot topics and evolution process of green logistics, this paper analyzes from four aspects: firstly, this study divides the green logistics development progress into three stages based on life cycle theory, which are the emerging stage (1993-2003), slow growth stage (2004-2014) and rapid growth stage (2015-2021). Then, based on latent dirichlet allocation (LDA) topic model, this study summarizes and confirms related words and meaning of each topic in different stages. Furthermore, this study calculates the text similarity in each development stage of green logistics and analyzes the trend of hot topics in green logistics. Finally, this paper visualizes the development roadmap of green logistics and explores the progression among three stages. There are 4, 5, and 7 topics defined respectively in three development stages. The revolution of green logistics is analyzed, and the results show that "model and management on sustainable development of GL", "related issues and potential threats of GL", and "optimization analysis of low-carbon vehicle routing and time" are the primary development trends of green logistics. This study fills the gap in considering the evolution process of green logistics through topic modeling and roadmapping method. It provides a particular theoretical significance for the green and sustainable development of logistics.

Analysis on the Development Path of Green Logistics under the Background of "Double Carbon"

Under the background of the establishment of the goal of "double carbon", the awareness of low-carbon environment in the whole society has been obviously improved, and green and low-carbon development has become the main goal of various industries. Taking the logistics industry as an example, it is necessary to take green logistics as the main development content under the background of "double carbon" goal, promote the green transformation of the logistics industry by reducing energy consumption and carbon emissions, and finally realize the benign and sustainable development of the industry. As far as the current situation is concerned, although the development of green logistics in China has achieved phased results, it has encountered some bottlenecks in its further development, which makes the green transformation of the logistics industry unsustainable. In view of this, this paper starts from the related overview of "double carbon" goal and green logistics, focuses on the bottlenecks encountered in the development of green logistics in China under this background, and puts forward some development countermeasures and suggestions, hoping to provide effective reference for related.

Green Transportation Model in Logistics Considering the Carbon Emissions Costs Based on Improved Grey Wolf Algorithm

The use of new energy vehicles in transportation can effectively promote the development of green logistics. This study selects heavy–duty diesel trucks as traditional logistics vehicles and heavy–duty electric trucks as new energy logistics vehicles. A green transportation model considering carbon emission costs is established to analyze whether new energy logistics vehicles should be used in long–distance freight delivery and how to arrange the use of two types of logistics vehicles. The model is solved using a grey wolf optimization algorithm, which incorporates good point sets, dynamic adaptive inertia weights, and memory–guided location update equations. The model is then applied to three logistics companies in Zhejiang province, China. In addition, considering the time constraints of the logistics industry, the model is used to simulate the arrangement of logistics transport companies for two types of vehicles in long–distance transportation of goods under realistic situations. Finally, this paper studies the future arrangements for long–distance transportation of goods by logistics companies considering the growing popularity of charging piles and advancements in production technology for new energy vehicles. The results show that the involvement of more new energy logistics vehicles in long–distance transport results in lower transportation costs and reduced pollution generated during transportation.

The time-dependent electric vehicle routing problem with drone and synchronized mobile battery swapping

Logistics enterprises are moving towards high efficiency and green. As an emerging technology, unmanned aerial vehicle (UAV, also known as drone) is very useful to cope with flexible and fast delivery. Electric vehicles (EVs), as new energy vehicles, are the technical support for green logistics development. This paper considers the last-mile delivery system in which a fleet of homogeneous EVs, equipped with a UAV each, serve a set of customers, and meanwhile battery swapping vehicles (BSVs) offer mobile battery swapping service for EVs. A mixed integer programming (MIP) model is formulated to minimize the sum of depreciation cost, driver wages and energy consumption cost of EVs, UAVs, and BSVs, by considering the nonlinear energy consumption of each vehicle, time-dependent speeds of EVs and BSVs and monetary time value on depreciation cost. A large neighborhood search algorithm based on Q-learning (LNS-QL) is designed in which Q-learning is used to select a combination of tailored destroy and repair operators to solve three sub-problems, (1) the UAV multi-visit problem, (2) the EV and UAV synchronized scheduling problem, (3) the EV and BSV synchronized mobile battery swapping problem. Besides, this paper also designs Lagrangian relaxation algorithm for comparison with LNS-QL. Extensive experiments verify the correctness of the model by testing small-scale instances. Further analysis demonstrates the accuracy and stability of LNS-QL on medium and large-scale instances as well as computational time and verifies the effectiveness of the mobile battery swapping mode in the cooperative delivery system of EVs and UAVs. Actual cases analyze the characteristics of EV delivery from the cost and emissions perspectives by comparing with FV delivery.

Research on the Development and Countermeasures of Green Logistics in Enterprises

With the increasing attention paid by the country to the impact of logistics activities on the environment, green logistics is an important foundation for achieving sustainable development, and packaging is an important link in logistics, which plays a significant role and significance in logistics activities. This article studies the development of green logistics packaging in enterprises. It not only identifies the problems that exist in green logistics packaging, but also improves the greening of logistics packaging processes, reduces the time and environmental impacts caused by unreasonable packaging processes, and contributes to the long-term development of green logistics in enterprises.

Analysis of technological innovation on provincial green development levels of logistics industry in China.

The transition from traditional logistics to green and low-carbon logistics is crucial and inevitable due to the pressure of climate change and sustainable development in China. Meanwhile, technological innovation is perceived as an important factor affecting the development of the logistics industry. To explore the impacts of technological innovation and other factors and to propose proper policies based on the results, this study utilizes a generalized estimating equations (GEE) regression model to analyze panel data of 30 provinces during 2001-2019. Firstly, the entropy weight method is applied to calculate the green logistics development level based on an index system considering green factors. Secondly, a GEE model which considers the correlation among different observations is used to investigate the impacts of crucial factors on the green logistics development level. Moreover, regional heterogeneity is also analyzed in this paper by comparing the regression results of the Eastern region, Central region, and Western region. Based on the above analysis, several conclusions are drawn: (1) In terms of the average green logistics development levels, the Eastern region ranks 1st, the Central region ranks 2nd, and the Western region ranks 3rd. (2) GEE regression model is proved effective in our sample. (3) For the full sample, technological innovation, trade openness, and logistics infrastructure positively affect the green logistics development level; while, government regulation and energy intensity negatively influence the green logistics development level. (4) Regional heterogeneity is confirmed in our sample. Related policy recommendations are proposed based on our regional regression results. Take the Eastern region as an example, the local governments in the Eastern region should upgrade the manufacturing industry, reduce government financial investment in the transportation sector, and enhance environmental control expenditure in the transportation sector.

The Development of Renewable Energies and Green Logistics: Reflections on Three Countries in Latin America

The Development of Renewable Energies and Green Logistics: Reflections on Three Countries in Latin America

The dynamic relationships among growth in the logistics industry, energy consumption, and carbon emission: recent evidence from China

In the post-pandemic era, there is a need to achieve the dynamic and coordinated development of growth in the logistics industry, energy consumption, and carbon dioxide (CO2) emissions in China’s four major economic regions to ensure the high-quality development of green logistics in China. Using the data indicators of growth in the logistics industry, energy consumption, CO2 emissions, and fixed asset investment in 30 Chinese provinces from 2004 to 2018, a panel vector autoregressive model was established for the four major economic development regions of central, east, west, and northeast China. The model coefficients were estimated using the systematic generalized matrix estimation method (System-GMM), which was evaluated by a Granger causality test. The model coefficients were estimated using the System-GMM method, and the dynamic relationships between growth in the logistics industry, energy consumption, and CO2 emissions was obtained through a Granger causality test, impulse response analysis, and variance decomposition. The results showed that the growth of the logistics industry in the four major economic regions had a positive impact on energy consumption and CO2 emissions, with the degree of contribution being smaller in the east and central regions, and larger in the west and northeast regions. Fixed asset investment had a negative impact on energy consumption and CO2 emissions, with the degree of contribution being largest in the northeast, larger in the east than in the central region, and smallest in the west. Finally, according to the conclusion and analysis of the results, from the aspects of government guidance and policy support, low-carbon logistics technology innovation, and infrastructure investment, we propose the need to pay attention to the role of government guidance, accelerate the pace of energy adjustments using the structure of the logistics industry, and increase the investment in renewable energy infrastructure, while focusing on strengthening the cooperation between regions and exploring new models of low-carbon logistics development between regions. This will ensure that the country achieves its goal of reaching peak carbon by 2030 and carbon neutrality by 2060.

Research on Countermeasures for the High Quality Development of Green Logistics in China under the "Double Carbon" Target

Carbon emission reduction and green logistics have received widespread attention from all walks of life in recent years, and the introduction of the "double carbon" target has made it urgent and imperative to achieve high-quality development of green logistics. This paper, based on the existing research results and the current situation of green logistics development, takes the shortcomings of China's green logistics development under the "double carbon" target as the starting point, conducts an in-depth analysis from three levels: awareness, policies and regulations and professional talents, and puts forward feasible suggestions and improvement countermeasures to realize the high-quality development of China's green logistics, specifically These include: cultivating social consensus on the development of green logistics, improving the green logistics policy and regulation system, and strengthening theoretical research and talent training on green logistics. It is of great practical significance to effectively promote the green development and "double carbon" goal of the whole Chinese society.

E-Commerce Logistics System Based on Discrete Dynamic Modeling Analysis

The development of green logistics in a low-carbon environment is an important way for logistics companies to reduce operating costs, and it is also a strategic measure to strengthen the construction of ecological civilization. This study improves the bat algorithm for single-delivery express delivery and multi-delivery, determines the optimal target and seeks the optimal solution, establishes the optimal logistics distribution scheme combined with corporate profits, and finally, compares it with other algorithms to verify the feasibility of the model. In the same experimental environment, it is proven that the performance of the built model is about 20% higher than that of other methods, and the planned path is the most reasonable. In the future application of e-commerce logistics system, it is a more efficient, reasonable, and perfect discrete logistics model.

Electric vehicle routing models and solution algorithms in logistics distribution: A systematic review.

With the development of green logistics and the promotion of new energy vehicle development policies domestically and abroad, electric vehicles have been put into logistics and distribution as an alternative to traditional fuel vehicles. The Electric Vehicle Routing Problem (EVRP) has attracted widespread attention from the academic community. This paper comprehensively examines the latest research progress on electric vehicle routing models and solution algorithms in logistics and distribution. Firstly briefly introduces EVRP models considering battery losses; secondly, based on the composition of the EVRP objective function and constraints, EVRP models are classified into four types: EVRP considering load and battery life constraints, EVRP with a time window and considering charging strategies, the study of vehicle routing problems for hybrid fleets, and EVRP combined with charging/swapping station location. Then, briefly introduce exact algorithms, traditional heuristics, meta-heuristics, and hybrid algorithms for solving EVRP models. Moreover, it analyzes the main meta-heuristics that are more widely used. Finally, this review points out the development trend of EVRP theoretical methods.

A multi-cycle and multi-echelon location-routing problem for integrated reverse logistics

PurposeThe rapid development of smart cities and green logistics has stimulated a lot of research on reverse logistics, and the diversified data also provide the possibility of innovative research on location-routing problem (LRP) under reverse logistics. The purpose of this paper is to use panel data to assist in the study of multi-cycle and multi-echelon LRP in reverse logistics network (MCME-LRP-RLN), and thus reduce the cost of enterprise facility location.Design/methodology/approachFirst, a negative utility objective function is generated based on panel data and incorporated into a multi-cycle and multi-echelon location-routing model integrating reverse logistics. After that, an improved algorithm named particle swarm optimization-multi-objective immune genetic algorithm (PSO-MOIGA) is proposed to solve the model.FindingsThere is a paradox between the total cost of the enterprise and the negative social utility, which means that it costs a certain amount of money to reduce the negative social utility. Firms can first design an open-loop logistics system to reduce cost, and at the same time, reduce negative social utility by leasing facilities.Practical implicationsThis study provides firms with more flexible location-routing options by dividing them into multiple cycles, so they can choose the right option according to their development goals.Originality/valueThis research is a pioneering study of MCME-LRP-RLN problem and incorporates data analysis techniques into operations research modeling. Later, the PSO algorithm was incorporated into the crossover of MOIGA in order to solve the multi-objective large-scale problems, which improved the convergence speed and performance of the algorithm. Finally, the results of the study provide some valuable management recommendations for logistics planning.