Cold Chain Logistics Enterprises Research Articles

Research on the evolution game of low-carbon operations in cold chain logistics considering environmental regulations and green credit

To solve the problem of insufficient low-carbon operational motivation among cold chain logistics enterprises due to the high investment costs of low-carbon assets and considering the promotional effect of environmental regulatory policies and green credit, an evolutionary game model was constructed for the government, cold chain logistics enterprises, and financial institutions. The stability strategies of each participating entity and the stability of the system equilibrium point were analyzed, and the relevant conclusions were verified through numerical simulations. The research results indicated the following: (1) the initial willingness of the three parties to participate increased, the low-carbon operation of cold chain logistics enterprises and the speed of green credit services provided by financial institutions accelerated, and the rate of strict government regulation slowed down. (2) Moderate subsidies and taxes were conducive to the joint participation of the three parties. (3) Increasing the subsidy for green credit provided positive incentives for financial institutions to provide green credit services, while reducing credit interest rates accelerated the low-carbon operation rate of cold chain logistics enterprises.

Research on the Evolution Game of The Digital Transformation of Cold Chain Logistics Enterprises Under the Government's Participation

Whether cold chain logistics enterprises choose to carry out digital transformation is a process of evolutionary game. By analyzing the evolution and stability strategy in the process of digital transformation of cold chain logistics enterprises under the participation of the government, and using matlab for simulation, we discuss the influence of each parameter on the decision-making of cold chain logistics enterprises. The results show that the cost of digital transformation of cold chain logistics enterprises will hinder their transformation, and the increase coefficient of enterprise income, the increase of government subsidies and the reduction of tax rate will all promote the implementation of digital transformation of cold chain logistics enterprises. Finally, corresponding countermeasures are put forward to accelerate the digital transformation of cold chain logistics enterprises, so as to lay a solid foundation for the further economic development of the whole country.

Study on the Application of Activity-Based Costing in Cold Chain Logistics Enterprises under Low Carbon Environment

Currently, a large amount of greenhouse gas emissions has caused a series of problems such as serious environmental degradation, and China is facing enormous pressure to reduce emissions. In terms of meeting the needs of people’s lives, cold chain logistics has undergone faster development, and its carbon emissions are relatively high. In response to the government’s advocacy for green and low-carbon concepts, some technical measures taken will increase the cost of carbon emissions. Identifying measures to reduce carbon emissions using management methods is an ongoing problem that this paper intends to solve. To address the shortcomings of the traditional cost method that cannot accurately account for the cost of each calculation object and ignores the carbon emission cost, this paper constructs an activity-based cost model for cold chain logistics enterprises to more comprehensively account for the operation cost and carbon emission cost. Then, a typical enterprise YS cold chain logistics company is used as a case study for an empirical calculation and analysis. The following conclusions are drawn: (1) the results identify the main activity centers that affect the operating costs and carbon emission costs of different customers; (2) a comparison among the total cost of each project helps to identify high-quality customers; (3) clarifying the carbon emission cost of wasting resources is beneficial for further optimizing the match between production capacity and business volume. This paper provides a path reference for enterprises to efficiently implement logistics cost management and carbon emission control, which can help enterprises cope with cost reduction and efficiency enhancement in a low-carbon environment and promote the long-term development of the logistics industry and environmental protection.

Research on Cold Chain Logistics Transportation Scheme under Complex Conditional Constraints

A mathematical model is proposed to minimize the sum of vehicle fixed cost, fuel cost, carbon-emission cost, cooling cost, time-penalty cost and split-compensation cost, on the basis of considering the three-level cold-chain-logistics network of manufacturer, distribution center, and seller. The model is constructed based on the constraints of customer time window, vehicle load, demand-splitable, and semi-open driving of multiple distribution centers. We to divide the customer areas according to geographical locations and to carry out the transportation processes in stages. The target solution, which includes vehicle routing, service time and type, cargo details, etc., has been formulated. A two-stage hybrid-heuristic-path-scheme solution algorithm that combines a taboo table, a genetic algorithm, an optimal-path-generation algorithm, a load-capacity-constraint algorithm, and a time-window-constraint algorithm is designed in view of the complexity of the model and the uniqueness of the solution scheme. This paper aims to reasonably plan the resource allocation of cold chain logistics enterprises, reduce the comprehensive cost of cold chain transportation, improve customer satisfaction, and respond to the green logistics policy advocated by the state by reducing vehicle transit time and fuel consumption, and promote energy conservation and emission reduction.

Multi-objective route optimization of urban cold chain distribution using electric and diesel powered vehicles

Increasingly serious urban road congestion and environmental pollution have led some cities to impose restrictions such as limiting certain types of vehicles and the areas in which they can operate and introducing subsidies and other incentives for electric refrigerated vehicles. As a result, both internal combustion engine (ICE) refrigerated vehicles and electric refrigerated vehicles will be used together in urban cold chain distribution for a long time into the future. Most current studies are concerned with mixed vehicle type allocation or mixed vehicle routing problems. Although there are some studies that combine the two, there has been little research into the effects of low carbon emission and multiple objective optimization on distribution and routing for a mixture of vehicle types. This paper describes the creation of an optimized decision-making cold chain distribution model that includes different types of distribution vehicles and different route optimization criteria that represent the three enterprise objectives of minimal cost, minimum carbon emissions and minimum distance. The decision criteria are influenced by conflicting benefits offered by ICE and electric refrigerated vehicles as well as government subsidies for electric refrigerated vehicles and carbon emission trading by logistics enterprises. A chaotic particle swarm optimization algorithm was used to analyze a cold chain distribution system in Wuhan, Hubei Province, China. The results show that: (1) The choice of enterprise distribution models and the vehicles and routes determined are closely related to enterprise goals. To minimize total cost, ICE refrigerated trucks with less load capacity and electric refrigerated trucks with greater load capacity are preferred. To minimize carbon emissions, ICE refrigerated trucks and electric refrigerated trucks with less load capacity are preferred. To minimize total distance, ICE refrigerated trucks and electric refrigerated trucks with greater load capacity are preferred. (2) As the value of government subsidies increases, the total load capacity of electric refrigerated vehicles also increases, the distribution routes change, and total carbon emissions and total distribution costs decrease. (3) When carbon emission trading prices increase, the number of electric refrigerated vehicles gradually increases, the distribution path changes, the total distribution costs increase, and total carbon emissions decrease. Some suggestions are made for government to determine subsidies for electric refrigerated vehicles and carbon emission trading policies that will guide the choice of distribution vehicles and affect the criteria used for route optimization by cold chain logistics enterprises.

Collaborative site selection study for cold chain distribution centers under low carbon policies

In order to solve the problem of cross-layout of cold chain logistics network and optimize the resource allocation of small and medium-sized cold chain logistics enterprises, based on the concept of low-carbon economic development and with the aim of minimizing the total cost, this paper constructs a cold chain distribution center location model including refrigeration cost and carbon emission cost from the microscopic perspective of enterprises, and selects two small and medium-sized cold chain logistics enterprises for simulation, and the simulation results show that the model can achieve the effect of saving operation cost, goods flow cost, carbon emission cost and refrigeration cost.

The Development Trend of China’s Agricultural Product Cold Chain Logistics from the Perspective of Big Data

With the gradual prosperity of social economy, people’s demand for agricultural products consumption has also gradually increased. Through the efficient introduction of big data technology, we can optimize and innovate the management system of agricultural cold chain logistics enterprises, realize the modernization of enterprise logistics management, and effectively improve the management efficiency of agricultural cold chain logistics enterprises. Using big data technology can improve the efficiency of information docking, improve the stickiness of enterprise customers, and speed up the value-added of cold chain logistics data. This study introduces the common clustering algorithms in the field of cold chain logistics, with emphasis on the spectral clustering algorithm. The spectral clustering algorithm not only reduces the error rate but also significantly reduces the time spent in the clustering process, which shows the effectiveness and feasibility of the application of spectral clustering algorithm in China’s agricultural cold chain logistics industry.

The electric vehicle promotion in the cold-chain logistics under two-sided support policy: An evolutionary game perspective

Many countries, industries, companies and end consumers have actively switched from fuel cars to electric vehicles (EV) to combat global warming via emission control. However, given cost and research and development uncertainties, refrigerated truck manufacturers (RTMs) and cold-chain logistics enterprises (CCLEs) are hesitant to update and employ electric refrigerated trucks (ERTs). Government support, notably subsidies, is vital in the ERT promotion. Thus, this study investigates the optimal two-sided support policies of the government (i.e. subsidies for CCLEs and RTMs) to explore how it achieves the best incentive for ERT promotion in the cold-chain logistics with limited resources. The study develops an evolutionary game model to analyse the influence of multiple factors on ERT upgrade and penetration strategies, clarify dynamic subsidy policy adjustment measures based on industrial evolution under multiple-factor interactions, and discuss the dynamic adjustment priority of the two-sided subsidy policies. The results indicate that the two-sided hierarchical subsidy policy can improve the promotion of ERTs and stimulate the electrification development of the cold-chain transportation industry. Finally, the decision-making preferences of RTMs and CCLEs in multiple scenarios are discussed and feasible management suggestions for government and enterprises are proposed accordingly.

Business model innovation risk factors based on grounded theory: A multiple‐case analysis of cold chain logistics companies in China

The article focuses on the risk factors of the business model innovation, and the interaction mechanism between risk factors and business model innovation. The grounded theory was used to analyze the business model innovation of four cold chain logistics enterprises. Results reveal that the main risk factors of business model innovation in cold chain logistics are management, technical, and environmental risks. The risk factors suggest that cold chain logistics enterprises need to optimize the internal management to improve the innovation ability and strengthen the development of cold chain technology to improve market competitive.

Research on Cold Chain Logistics Distribution Route Based on Ant Colony Optimization Algorithm

The cold chain logistics distribution industry not only demands all goods can be timely distribution but also requires to reduce the entire logistics transportation cost as far as possible, and distribution vehicle route optimization is the key problem of cold chain logistics transportation cost calculation. The traditional optimization method spends a lot of time to search so that it is tough to find the globally optimal path approach, which results in higher distribution costs and lower efficiency. To solve the abovementioned problems, a cold logistics distribution path optimization solution, ground on an improved ant colony optimization algorithm (IACO) is formulated. Specially, other constraints, e.g., the transport time factor, transport cooling factor, and mean road patency factor, can be added to the unified IACO. Meanwhile, the updating mode of traditional pheromone is improved to limit the maximum and minimum pheromone concentration on the road and change the path selection transfer probability. The simulation results and experiment make clear that the IACO algorithm is lower than the chaotic-simulated annealing ant colony algorithm (CSAACO) and the traditional ACO algorithm in terms of convergence speed, logistics transportation distance, and logistics delivery time. At the same time, we have successfully obtained the optimal logistics distribution path, which can provide valuable reference information for improving the economic benefits of cold chain logistics enterprises.

Research on Optimization Strategy of Cold-chain Logistics Car Scheduling

In this paper, aiming at the vehicle information supervision problem existing in the transportation process of the third-party small and medium-sized cold chain logistics enterprises, combined with the actual monitoring demand of the vehicle, the cold chain logistics vehicle dynamic monitoring system is designed, and the vehicle scheduling optimization algorithm in the system is carried out. The study. In the aspect of vehicle scheduling in the system, an optimized genetic algorithm is used to find the optimal transportation path and reduce the transportation cost before transportation by planning the transportation sequence and path of the site.

Two-Stage Robust Optimization Model for Fresh Cold Chain considering Carbon Emissions and Uncertainty

Sustainable development is an everlasting theme and lasting strategy in today’s era. Low-carbon economy is an inevitable approach to the implementation of sustainable development. Cold chain logistics has become one of the main sources of carbon emissions. However, in the research on location planning of cold chain logistics, the costs of carbon emissions have not been taken into consideration in previous studies. The two-stage stochastic optimization (TSSO) model was established based on the comprehensive consideration of transportation costs, time penalty costs, and carbon emission costs. In this case, it is extremely difficult to deal with uncertainty in TSSO model. Therefore, this paper constructs a two-stage robust optimization (TSRO) model using data-driven method and robust optimization theory and verifies the validity of this model through an actual case. The application of this method to a cold chain logistics enterprise showed that the service level of logistics cannot be guaranteed by stochastic optimization model. In the TSRO model, the costs increase by 2.18% at the price of robustness, whereas logistics service level shows an upward trend (from 85.83% to 92.75%). In the TSRO model, enterprises are forced to choose a better distribution path when carbon tax increases, which not only helps enterprises save costs but also achieves low-carbon environmental benefits.

Robust optimization approach to two-echelon agricultural cold chain logistics considering carbon emission and stochastic demand

Cold chain logistics has become one of the main sources of carbon emissions. Meanwhile, the implementation of low-carbon economy has become an inevitable way to promote sustainable development. However, previous studies on the cold chain inventory routing problem (IRP) paid less attention to the cost of carbon emissions. In this paper, a linear programming (LP) model is established, which takes the costs of vehicle transportation, time window and carbon emission into consideration. Although the simple LP model is easy to be solved, it cannot handle the problems with uncertainty. Therefore, in order to overcome the influence of uncertainty, the proposed LP model is developed into three low-carbon robust optimization (RO) models. In addition, this paper takes a cold chain logistics enterprise in Yangtze River Delta as an example for empirical analysis. The results of the case study prove that the RO models can quickly solve the problems with uncertainty and still maintain robustness, while the LP model has failed. Specifically, the R-ellipsoid model produces the best result among the three RO models. It is suggested that when the carbon emission tax increases, the decision makers tend to choose a better path planning scheme, which will not only reduce the total cost, but also obtain environmental benefits. Finally, the findings of this paper generate some implications for the low-carbon transformation of cold chain logistics enterprises.

Curriculum System Construction of Cold Chain Logistics Direction for Applied Undergraduate Based on Post CompetencyApplied university; Cold chain logistics; BEI key event interview; Curriculum system formatting.

Cold chain logistics is replacing the traditional logistics and becoming a new profit growth point. Therefore, it is urgent to cultivate professional cold chain talents to adapt to the development of the industry. Starting from the competency requirements of cold chain logistics enterprises, this paper constructs the competency model of cold chain logistics basic posts by means of BEI key event interview and questionnaire survey. Based on the application-oriented teaching concept, this paper studies the theory of cold chain logistics characteristic direction of logistics management major and the setting of teaching course system, in order to further improve the teaching effect of cold chain logistics management major courses and ensure the teaching effect to prove the accuracy of personnel training.

Model and Algorithm of Two-Stage Distribution Location Routing with Hard Time Window for City Cold-Chain Logistics

Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic algorithm is designed based on coupling and collaboration of the two-stage routing and transfer stations. The validity and feasibility of the model and algorithm are verified by conducting a randomly generated test. The optimal solutions for different objective functions of two-stage distribution location-routing are compared and analysed. Results turn out that for different distribution objectives, different distribution schemes should be employed. Finally, we compare the two-stage distribution location-routing to single-stage vehicle routing problems. It is found that a two-stage distribution location-routing system is feasible and effective for the cold-chain logistics network, and can decrease distribution cost for cold-chain logistics enterprises.

Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

Due to the rise of social and environmental concerns on global climate change, developing the low-carbon economy is a necessary strategic step to respond to greenhouse effect and incorporate sustainability. As such, there is a new trend for the cold chain industry to establish the low-carbon vehicle routing optimization model which takes costs and carbon emissions as the measurements of performance. This paper studies a low-carbon vehicle routing problem (LC-VRP) derived from a real cold chain logistics network with several practical constraints, which also takes customer satisfaction into account. A low-carbon two-echelon heterogeneous-fleet vehicle routing problem (LC-2EHVRP) model for cold chain third-party logistics servers (3PL) with mixed time window under a carbon trading policy is constructed in this paper and aims at minimizing costs, carbon emissions and maximizing total customer satisfaction simultaneously. To find the optimal solution of such a nondeterministic polynomial (NP) hard problem, we proposed an adaptive genetic algorithm (AGA) approach validated by a numerical benchmark test. Furthermore, a real cold chain case study is presented to demonstrate the influence of the mixed time window’s changing which affect customers’ final satisfaction and the carbon trading settings on LC-2EHVRP model. Experiment of LC-2EHVRP model without customer satisfaction consideration is also designed as a control group. Results show that customer satisfaction is a critical influencer for companies to plan multi-echelon vehicle routing strategy, and current modest carbon price and trading quota settings in China have only a minimal effect on emissions’ control. Several managerial suggestions are given to cold chain logistics enterprises, governments, and even consumers to help improve the development of cold chain logistics.

Analysis of the Efficiency of China’s Cold Chain Logistics Enterprises from the Perspective of Green Supply Chain

China’s economy is developing rapidly, and the development of cold chain logistics is on the right track. With the expansion of market demand, people have put forward higher requirements for the safety and quality of cold chain logistics, which provide opportunities for the development of cold chain logistics enterprises. In recent years, due to the deterioration of the world environment and the continuous consumption of resources, green sustainable development has become an inevitable trend of society and the development of the times. The drawbacks of the traditional cold chain logistics continue to be highlighted. If the cold chain logistics enterprises with high energy consumption and serious pollution want to obtain the opportunity of survival, they must integrate the concept of green development into the company’s operation and management. Based on this, the paper builds a performance evaluation system for cold chain logistics enterprises based on green supply chain, and uses fuzzy analytic model to evaluate enterprise efficiency. After research, it is found that the scale but the low efficiency is an important reason that affects the development of China’s cold chain logistics enterprises. In order to achieve green and efficient operation, enterprises must accelerate capital management, and at the same time optimize talents and technology to gain market share in the wave of green sustainable development.

Platform ecological circle for cold chain logistics enterprises: the value co-creation analysis

PurposeThe purpose of this paper is to propose a framework of value co-creation in platform ecological circle for cold chain logistics enterprises to guide the transformation and development of cold chain logistics industry.Design/methodology/approachThis paper establishes a conceptual framework for the research on the platform ecological circle in cold chain logistics, utilizes a structural equation model to investigate the influencing factors of the value co-creation of the platform ecological circle in the cold chain logistics enterprises and elaborates the internal relations between different influencing factors regarding the value co-creation and enterprises’ performance.FindingsResults show that resource sharing in logistics platform ecological circle can stimulate the interaction among enterprises and this produces a positive influence on their dynamic capabilities, which, in turn, affects the they to work together to plan, implement and solve problems, so as to achieve the goal of improving enterprise performance.Practical implicationsThe shared resources and value co-creation activities in the platform ecological circle are very important for the transformation and development of cold chain logistics enterprises. Therefore, enterprises should promote value co-creation through realizing resource sharing and creating a win-win cooperation mechanism.Originality/valueThis paper targets at incorporating the resource sharing in platform ecological circle for cold chain logistics enterprises, explores from an empirical perspective the role of the resource sharing in cold chain logistics enterprises in enhancing the dynamic capabilities of enterprises, thereby encouraging the value co-creation behavior, and ultimately boosts enterprise performance and stimulates business development.

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

In order to improve the performance and change the current situation of the cost minimization model widely used in the cold chain logistics distribution process, a multi-objective optimization model based on cost, carbon emissions and customer satisfaction is proposed. Considering the characteristic of this proposed optimization model, we design an improved ant colony algorithm with a multi-objective heuristic function to solve it, termed as ACOMO. Experimental results show that the proposed ACOMO can effectively solve the vehicle routing problem of the multi-objective optimization model, and outperforms the classic ant colony algorithms, resulting in more Pareto optimal solutions. It offers an environmentally friendly distribution solution for the problem. Specifically, the distribution path obtained by the improved ant colony algorithm manages to achieve the above multiple goals, including reduction of distribution costs and carbon emissions, and improvement of customer satisfaction. In addition, compared with a single-target model that only provides one single distribution route to cost minimization, multi-objective optimization can provide a variety of distribution route options for logistics companies in practice. Finally, through the sensitivity analysis of temperature changes and cargo damage coefficients, the proposed system successfully provides reference for the optimization of the path of cold chain logistics enterprises, and promotes logistics enterprises to effectively arrange their work and to be more socially responsible.

Optimizing decision-making of regional cold chain logistics system in view of low-carbon economy

With the increasing demand for low-carbon cold chain logistics, corresponding subsidy policy and carbon emissions trading policy are needed to guide cold chain logistics enterprises in energy-saving and emission reduction transformation of cold storage. However, current research mainly focuses on energy-saving and emission reduction through improving the energy efficiency of equipment or optimizing the operation and management of cold chain logistics enterprises, rarely considering the government policy. This paper constructs a decision-making model of cold chain logistics system by using the method of bilevel programming. The upper level is the government's goal, pursuing the total cost minimization of the whole cold chain logistics system. The lower level is the goal of the cold chain logistics enterprise, pursuing the cost minimization of the enterprise. Chaotic particle swarm optimization (CPSO) was developed to improve this model, and this method was applied to the decision-making of cold chain logistics system in Wuhan City, Hubei Province, China. The study reveals: (1) The joint use of carbon emission reduction subsidies and carbon emission quota optimization measures is more effective in promoting energy-saving and emission reduction of enterprises than using them separately; (2) The carbon emission quota set by the government should not be too high or too low; (3) The government subsidy limits for carbon emission reduction have a significant impact on the carbon emission reduction of enterprises; (4) The subsidy rate per unit carbon emission reduction can adjust the total carbon emissions and total carbon emission reduction of enterprises. This study provides a scientific basis and inspires the government and enterprise in decision-making to improve the energy-saving and emission reduction of the whole society.