Reduce Logistics Costs Research Articles

The impact of industry structure on the value of national logistics costs/gross domestic product: Evidence from China

The proportion of national logistics costs to Gross Domestic Product (NLC/GDP) serve as a valuable indicator for estimating a country’s overall macro-level logistics costs. In some developing nations, policies aimed at reducing the NLC/GDP ratio have been elevated to the national agenda. Nevertheless, there is a paucity of research examining the variables that can determine this ratio. The purpose of this paper is to offer a scientific approach for investigating the primary determinants of the NLC/GDP and to advice policy for the reduction of macro-level logistics costs. This paper presents a systematic framework for identifying the essential criteria for lowering the NLC/GDP score and employs co-integration analysis and error correction models to evaluate the impact of industrial structure, logistics commodity value, and logistics supply scale on NLC/GDP using time series data from 1991 to 2022 in China. The findings suggest that the industrial structure is the primary factor influencing logistics demand and a significant determinant of the value of NLC/GDP. Whether assessing long-term or short-term effects, the industrial structure has a substantial impact on NLC/GDP compared to logistics supply scale and logistics commodity value. The research offers two policy implications: firstly, the goals of reducing NLC/GDP and boosting the logistics industry’s GDP are inherently incompatible; it is not feasible to simultaneously enhance the logistics industry’s GDP and decrease the macro logistics cost. Secondly, if China aims to lower its macro-level logistics costs, it must make corresponding adjustments to its industrial structure.

Facilitating Circular Transition in the Construction Industry: Optimizing a Prefabricated Construction Site Layout Using a Novel BIM-Integrated SLP-GA Model

Prefabricated construction is being developed as one of the pathways toward circularity in the construction industry. However, compared to traditional cast-in-place construction methods, the design of prefabricated construction site layouts presents unique challenges, such as managing the space for prefabricated components and lifting equipment, and coordinating the precise timing between off-site fabrication and on-site assembly. Existing research has primarily focused on traditional cast-in-place construction, leaving room for improvement in optimisation models for prefabricated site layouts. This study develops a BIM-based System Layout Planning-Genetic Algorithm (SLP-GA) model specifically tailored for prefabricated construction site optimisation. The proposed model improves the accuracy and visualisation of layout planning through BIM technology, enabling dynamic adjustments and real-time data integration. It also incorporates genetic algorithms to address complex multi-objective optimisation problems, avoiding local optima and overcoming the limitations of traditional SLP methods that rely on subjective judgements. Unlike previous studies that do not consider secondary handling, the optimisation objectives of this study focus on minimising material handling costs associated with secondary handling and maximising comprehensive relationships, including efficiency, safety and space utilisation. The application of this model in a case study shows a reduction in logistics costs of 8.58% and an improvement in comprehensive relationships of 11.61%, indicating significant improvements. This research advances optimisation methods for prefabricated construction site layouts, enriches optimisation objectives by considering secondary handling, and provides practical guidance for improving the efficiency and effectiveness of prefabricated construction projects.

Optimizing the organization of the first mile in agri-food supply chains with a heterogeneous fleet using a mixed-integer linear model

Consumers are increasingly demanding high-quality food, which presents significant challenges for agricultural supply chains. While the majority of research in the agri-food sector has concentrated on optimizing logistics costs and meeting demand by focusing on minimizing the last mile, the complexity of the first mile in the agricultural supply chain has been less explored. Farmers must efficiently manage the harvesting process and the transportation of harvested produce to consolidation centers to ensure the delivery of high-quality products. This paper addresses this research gap by introducing a mixed-integer programming model that leverages vehicle routing problem concepts to optimize the logistics processes involved in transporting harvested products from various fields to a central depot. The primary objective is to minimize total logistics costs associated with visiting different fields during a pick-up round using multiple vehicles. The model has been applied to a case study involving an agricultural cooperative in Greece as part of the European BBTWINS project, which aims to enhance agri-food value chain digitalization for improved resource efficiency. The results demonstrate that organizing the first mile of the agri-food supply chain with a cooled vehicle for pick-up rounds can reduce logistics costs by up to 40% compared to the current practices.

Research on optimization of multimodal hub-and-spoke transport network under uncertain demand

In the cargo transportation system, the hub-and-spoke transport network can make full use of the scale effect between logistics hubs and reduce logistics costs. Joint transportation of multiple modes of transportation can give full play to the advantages of different modes of transportation, which not only reduces logistics costs but also improves transportation efficiency. Therefore, this paper combines the advantages of multimodal transportation and hub-and-spoke network, and establishes an optimization model of multimodal hub-and-spoke transport network under demand uncertainty. The model takes into account hub capacity constraints and customer satisfaction with respect to transportation time, and to facilitate the model solution, we utilize the fuzzy expected value method and the fuzzy chance constraints based on credibility to clarify the uncertain variables in the model. We use mixed coding to describe the selection of hubs, assignment of nodes, and choice of transportation modes in this study and use the NSGA-II algorithm with local reinforcement to solve the problem. Finally, numerical experiments are designed to verify the validity of the model and algorithm through sensitivity analysis of relevant parameters, determine the reasonable number of hubs and confidence level, and obtain the influence of the change of hub capacity limit and the ratio of single and double hub transit on the research objectives. The results show that: the NSGA-II algorithm with local reinforcement can significantly improve the convergence speed of the algorithm; There is benefit inversion between economic cost and time cost, and the pursuit of economic cost minimization and time cost minimization, respectively, will lead to different choices of the number of hubs; Increasing the ratio of goods transfer between hubs is beneficial for fully utilizing the scale effect between hubs, achieving the goal of reducing economic costs, but at the same time, it will increase time costs.

Mendorong Pertumbuhan Pangsa Pasar B2B untuk Sektor Ride-Hailing Menggunakan Segmentasi Pasar Strategis

The expansion of Indonesia's ride-hailing sector has been considerable, fueled by technological advancements and the widespread embrace of smartphones. Despite its swift growth, the industry faces difficulties concerning long-term viability, safety issues, and compliance with governmental regulations. Nevertheless, the integration of advanced technologies and strategic plans for service expansion into new regions presents significant opportunities. The competitive environment in Indonesia's ride-hailing market not only stimulates innovation but also shapes a lively and evolving market atmosphere. Originally designed for consumers, the ride-hailing sector has evolved into a versatile transportation solution for various business needs, including employee transportation and goods delivery. These services offer advantages for companies, such as enhanced operational efficiency and reduced logistics costs. Recognizing the diversity of the business market, segmentation becomes vital in comprehending customer needs. Through tailored marketing approaches, companies can deliver more pertinent solutions, boosting competitiveness and enlarging B2B market share. By using K-means clustering, it yields 5 clusters, namely cluster 1: Tech Innovators and Financial Players, cluster 2: Logistics Singular Focus, cluster 3: Logistics, Retail, and Automotive Synergy, cluster 4: Culinary, Logistics, and Travel Dynamics, cluster 5: Tech Titans, Healthcare Giants, and Financial Leaders. The analysis of user clusters on the B2B Ride Hailing Indonesia platform provides useful insights that guide strategic recommendations for improving service offerings, refining marketing strategies, and optimizing business operations. Targeting the millennial demographic through digital channels and influencers, examining marginal costs for high-traffic clusters to identify optimization opportunities, exploring expansion possibilities in clusters with growth potential, and tailoring business solutions for clusters with unique needs are among the recommendations. Keywords: K-means Clustering, Market Innovation, Market Share Expansion, Ride-Hailing Sector, Segmentation, Strategic Decisions.

A Two-Echelon Multi-Trip Capacitated Vehicle Routing Problem with Time Windows for Fresh E-Commerce Logistics under Front Warehouse Mode

Given the swift expansion of fresh e-commerce, the front warehouse mode can respond quickly and ensure the quality of fresh products. However, the complexity of the supply chain structure under front warehouse mode poses a challenge in reducing logistics costs and improving distribution efficiency while meeting consumers’ immediate delivery demands. Therefore, this paper studies the vehicle routing problem of two-echelon fresh e-commerce under front warehouse mode. Considering trans-shipment time constraints between the two echelons and the characteristics of terminal distribution, this paper initially models the vehicle routing problem for front warehouses as a two-echelon multi-trip capacitated vehicle routing problem with time windows. A mixed-integer linear programming model is subsequently established. To solve the model, a hybrid genetic algorithm integrated with neighborhood search is developed. Matrix coding is employed to merge vehicle selection and route assignment decisions. Simultaneously, neighborhood search is applied to enhance the search capability of algorithms, thereby improving the quality of solutions. Furthermore, the effectiveness and efficiency of the model and algorithm are verified through experiments of varying scales. Finally, comparative strategies and sensitivity analysis highlight the advantages of multi-trip strategies and provide insights into the optimal vehicle capacity limit.

Logistics distribution route optimization of electric vehicles based on distributed intelligent system

Abstract The data management system of health cloud authentication plays an important role in the optimization of logistics vehicle routing. It can not only help logistics vehicles choose the best distribution path, but also save time and cost and improve economic efficiency. At present, logistics has not yet formed a complete service system. High distribution costs and low distribution efficiency limit the development of the entire logistics. The reduction of logistics costs and the improvement of distribution efficiency have become the top priorities of the society. The optimization of the distribution route is the key to cost saving and distribution logistics. It is particularly important to study and optimize the distribution route, because the distribution route affects the logistics transportation efficiency and the loss cost during transportation. Therefore, this paper adjusted the scheduling system of logistics vehicles through a distributed intelligent system, and optimized the path of logistics vehicles according to the improved genetic algorithm, thereby reducing the transportation cost of logistics and improving the efficiency of logistics distribution. This article first explains the definition, classification, and main components of the delivery vehicle routing problem. Then, using cloud authentication path optimization, a distributed intelligent system is constructed. Finally, an improved ant colony algorithm is used to analyze and study the distance constraints of vehicles. By improving the ant colony algorithm, it can be seen that the optimized path pheromone concentration and the optimized sub-function have gradually increased with time. The mean pheromone concentration was 40 %, and the seventh day was 15 % higher than the first. The mean value of the optimized subfunction was 0.34 %, and the seventh day was 20 % higher than the first. The distribution cost and distribution efficiency of the optimized logistics vehicle distribution path were much higher than those of the traditional logistics distribution path. Moreover, the distribution cost of the logistics distribution path was 9 % lower than the traditional one, and the distribution efficiency was 13 % higher. The average smoothness of the optimized logistics path is about 90 %, and the seventh day is 11 % higher than the first day. The average fitness of the optimized logistics path is 88 %, and the seventh day is 14 % higher than the first day. In a word, the data management system can uniformly schedule logistics vehicles and improve the efficiency of distribution.

Development of Gresik – Mojokerto Railway Infrastructure to Accelerate Economic Growth in Gerbangkertosusila

The most important economic area in East Java is the Gerbangkertosusila (GKS) area. The GKS area between Gresik – Mojokerto is not yet connected directly, almost all goods have to go through Surabaya and Sidoarjo first. This results in high logistics costs and long travel times. The research method used in this research is a qualitative research method on economic growth factors in the GKS area. The factors considered in economic growth are population, number of people of productive age, number of people who are not yet working, minimum income/month, number of poorer people, percentage of poorer people, length of roads, number of people accessing the internet, number of telecommunication towers, length of roads damaged, investment value, export value, import value, and gross regional domestic product (GRDP). The analytical tool used in the research is a descriptive method to measure and assess the quality of economic growth and changes in regional economic growth factors, assisting strategic planning for the construction of new railway lines as the right solution for developing regional economic growth. Therefore, to accelerate economic growth and reduce logistics costs in the GKS area, a new railway line between Gresik - Mojokerto should be built. If logistics costs are low, it will reduce the price of goods and increase the opportunity to order goods and open up new jobs. If new job opportunities are opened, it will be possible to reduce the number of unemployed people by 375,392 people and the poorer population by 719,944 people. So it is hoped that it will increase economic growth to reach 7%. Only the Gresik and Sidoarjo regions have met this economic growth. Mojokerto’s economic growth is still 5.56% and lags behind other regions. If the construction of the new Gresik – Mojokerto train line is realized, then economic growth in the GKS region of at least 7% will not be difficult to achieve.

Design of Rural E-commerce Logistics Information Management System Based on Spring Boot

With the improvement of science and technology, the Internet has more and more affected people's daily life. People can stay at home and learn the latest information, movies, animations, music, etc. through the Internet. They can also buy goods, learn knowledge, and even find jobs through the Internet. It can be seen that the development of the Internet has brought great convenience to people's lives, and many industries have been born. As an emerging Internet industry, e-commerce has provided a large number of job opportunities for the market. Merchants can promote through e-commerce platforms, and customers can purchase goods through the platform. To ensure the normal and orderly flow of this business activity, efficient logistics systems are indispensable. With the rise of the concept of smart logistics, it not only requires employees to have professional theoretical knowledge and management service knowledge, but also professional technical knowledge such as electronic information technology. Designing an efficient logistics information management system requires cultivating smart logistics talents. E-commerce logistics, through information management systems, can not only achieve intelligent management and control of the logistics process, improve logistics efficiency and reduce logistics costs, but also enhance the automation and intelligence level of logistics, promoting the development of the logistics industry towards a more intelligent, efficient, and sustainable direction.

Edge intelligence empowered delivery route planning for handling changes in uncertain supply chain environment

Traditional delivery route planning faces challenges in reducing logistics costs and improving customer satisfaction with growing customer demand and complex road traffic, especially in uncertain supply chain environment. To address these challenges, we introduce an innovative two-phase delivery route planning method integrating edge intelligence technology. The novelty of our approach lies in utilizing edge computing devices to monitor real-time changes in road conditions and dynamically adjust delivery routes, thereby providing an effective solution for efficient and flexible logistics. Initially, we construct a mixed-integer programming model that minimizes the total cost under constraints such as customer destinations and time windows. Subsequently, in the cloud-edge collaborative mode, edge computing devices are utilized to collect real-time road conditions and transmit it to the cloud server. The cloud server comprehensively considers customer demand and road condition changes and employs adaptive genetic algorithms and A-star algorithms to adjust the delivery routes dynamically. Finally, comprehensive experiments are conducted to validate the effectiveness of our method. The results demonstrate that our approach can promptly respond to changes in customer demands and road conditions and flexibly plan the optimal delivery routes, thereby significantly reducing overall costs and enhancing customer satisfaction.

영남지방 초기 국의 등장 배경과 사로국 구조

Through the long-distance trade network and ritual structures of base settlements that were intensively developed in the Yeongnam region in the 2nd century BC, the background of the establishment of the early politics and the method of solidarity were examined. Long-distance trade beyond the Yeongnam region is concentrated in the 2nd century BC, and the bases where foreign trade is active overlap with regions(mainly Daegu, Gyeongsan, and Gyeongju) found in the early days of the clustering of wooden tombs. In some regions, politics that internally united regional units appeared in order to form a socio- economic coalition suitable for logistics distribution, redistribution, cost reduction, and information solidarity amid intensively developed foreign trade in the 2nd century BC. Thus, it is inferred that the clustering of wooden tombs appeared from the time when these early politics reached villages and townships as local political bodies to maintain active foreign trade, iron production, and distribution. In this situation, by linking topographic conditions, traffic routes and literature records, and archaeological data, focusing on Saro-guk, the composition of the euprak and the structure of the country were explained. Around the middle of the 2nd century BC, it is expected that the early Saroguk was established, and it is interpreted that the 6 villages, symbolized as major towns and villages, were united through the conference. Early Saroguk is a device that binds and maintains local communities while showing various forms for each town and village, and the phenomenon of establishing altar-style stone tombs, high- altitude enclosure, standing-ritual structures, and early wooden tombs by base is similar. In addition, the title of ChaChawoong, which was mentioned in early literature records, also weighed on the ideological and religious power base. Given the ritual structure of the settlement base and the power base of the early ruler, it was difficult to sustain the national structure only by pursuing the interests of foreign trade, and it is assumed that even by transforming the traditionally important megalithic monuments and high-altitude enclosure, it led to community cohesion.

Research on a Joint Distribution Vehicle Routing Problem Considering Simultaneous Pick-Up and Delivery under the Background of Carbon Trading

In order to explore the positive impact of the joint distribution model on the reduction in logistics costs in small-scale logistics enterprises, considering the demand on enterprises for simultaneous pick-up and delivery, as well as the cost of carbon emissions, this study considers the vehicle routing problem of simultaneous pick-up and delivery under a joint distribution model. First of all, an independent distribution model and a joint distribution model including fixed transportation, variable transportation, time penalty, and carbon emissions costs are established; second, by adding the self-adaption cross-mutation probability and the destruction and repair mechanism in the large-scale neighborhood search algorithm, the genetic algorithm is improved to adapt to the solution of the model in this paper, and the effectiveness of the improved algorithm is verified and analyzed. It is found that the improved genetic algorithm is more advantageous than the original algorithm for solving the problems of both models designed in this paper. Finally, the improved genetic algorithm is used to solve the two models, and the results are compared and analyzed. It is found that the joint distribution model can reduce the total cost by 6.61% and the carbon emissions cost by 5.73%. Additionally, the impact of the carbon trading mechanism on the simultaneous pick-up and delivery vehicle routing problem under the joint distribution model is further explored. The results of this study prove that enterprises can effectively reduce costs, improve profits, reduce carbon emissions, and promote the sustainable development of logistics enterprises under the condition of joint distribution.

Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations

Background: Brazil is one of the largest consumers of fertilizers and is highly dependent on the international market to meet its demand for agricultural production inputs. The complexity of the fertilizer supply chain motivated us to carry out this study on redesigning the fertilizer logistics chain and evaluate strategies for reducing logistics costs by redesigning the fertilizer mixing network in Brazil, a country that is heavily dependent on imported fertilizers for agriculture. Methods: We introduce a multi-product mixed-integer linear programming optimization model encompassing the logistics network, from import ports to mixing factories and agricultural fertilizer supply centers. This model includes logistics infrastructure and taxes, accounting for greenhouse gas emissions (specifically carbon dioxide) in fertilizer logistics. Results: The results indicate that expanding the port capacity for fertilizer importation can significantly reduce logistics costs and greenhouse gas emissions by up to 22.5%, decreasing by 23.9% compared to the baseline. We also observed that removing taxes on fertilizer importation can reduce logistics costs by approximately 11%, but it increases greenhouse gas emissions by 2.25% due to increased reliance on road transport. We identified 15 highly resilient regions for establishing mixing factories, evaluated various scenarios and determined the importance of these locations in optimizing the fertilizer supply network in the country. Moreover, the results suggest a significant potential to enhance the role of Brazil’s Northern Arc region in fertilizer import flows. Conclusions: Public policies and private initiatives could be directed toward encouraging the establishment of mixing factories in the identified regions and increasing transport capacity in the Northern Arc region. Improving the logistical conditions of the fertilizer network would contribute to food security by reducing the costs of essential inputs in food production and promoting sustainability by reducing greenhouse gas emissions.

Intensification of oil production through the use of hydraulic fracturing fluid based on polyacrylamide

The article considers the technology of Hydraulic Fracturing (HF) based on polyacrylamide (Co-PAM), identifies parameters for evaluating the quality of the fluid both on a guar and polyacrylamide base. Fluid viscosity is a main criteria of success of HF operations. Thus, fluid thermal stability, determine the pumping time. The composition of the Co-PAM-based HF fluid differs from the guar-based one, consisting of two main chemical reagents - a gelling agent and a crosslinker(x-linker), in that only a synthetic gelling agent is used. Recommended concentration starts from 4 l/m3. At this concentration the synthetic gel starts to exhibit properties of a sand-carrying fluid, suitable for standard pump rate (4.0-5.0 m3/min) HF. A significant advantage is compliance with the requirements for HF fluids which not only improves the filtration properties of the formation but also considers the economic feasibility of using such a chemical reagent. Co-PAM gel using provides reduction of logistics costs, water heating. Also it allows to exclude hydration unit, reduced crew, decreased wear on pumping units, including reduced consumption of lubricants during the HF operation.

The Collaborative Application of Internet of Things and Artificial Intelligence in Smart Logistics

This article introduces the current application status and development trends of the Internet of Things and artificial intelligence technology in smart logistics, analyzes how the Internet of Things and artificial intelligence technology work together to achieve efficient operation of smart logistics systems, as well as the challenges and opportunities they face. This article believes that the Internet of Things and artificial intelligence technology are the core driving forces of smart logistics. They can achieve informatization, automation, and intelligent processing in various aspects of logistics, improve logistics efficiency, reduce logistics costs, and promote green and sustainable development of logistics.

Chinese Loan to Africa in the lens of Pragmatism Economics

This paper examined the reasons behind China’s decision to provide loans to African states, a group that had been traditionally been considered not creditworthy by MDBs. Utilizing a descriptive-explorative research method, primary to secondary data ranged from 1999 to 2022, and the framework of economic pragmatism, this paper analyzed and found some pragmatic implications. The findings concluded that China’s lending strategy was mostly motivated by a pragmatic approach aimed at gaining early access to African markets, securing vital natural resources, assisting Chinese corporations, and creating economic dependence. China’s loans were used to fund infrastructure projects, reducing logistics costs for Chinese businesses and diversifying foreign exchange reserves. This paper posited that China’s policy was driven by empirical facts, adaptiveness to global economic conditions, and a focus on concrete economic benefits, such as increasing imports from China and gaining access to natural resources. Therefore, this paper describes China’s efforts to strengthen its influence and obtain tangible economic advantages through its lending practices in Africa Keywords: Africa, China, Development Loan, Economic Gains, Political-Economy

Replacing home deliveries by deliveries to parcel lockers: cost, traffic, emissions, and societal cost effects of locker network expansions in greater Oslo

ABSTRACT This study assesses the effects of using parcel lockers as an alternative to home deliveries, combined with different locker network expansions. We use empirical shipment data and real-world routing optimisation procedures to demonstrate that increased parcel locker use can reduce logistics costs, traffic, and emissions from last-mile distribution of a logistics service provider. Unlike many existing studies, we also comprehensively estimate overall societal effects, including recipients’ pick-up trips, using detailed travel behaviour data. For society overall, we find a robust and considerable potential for CO2 reductions (13–32 percent) by replacing home deliveries with parcel locker deliveries, even under conservative assumptions on travel modes and pick-up trips. Similarly, we find reductions in external (societal) damage costs, driven by reduced traffic. We further highlight several important dynamics between network expansion strategies, recipient coverage, last-mile efficiency, and pick-up trips, that are highly relevant for the decision-making of logistics service providers and policy-makers.

RESEARCH ON UAV IN LOGISTICS DISTRIBUTION

This article takes the COVID-19 epidemic as the starting point, and analyzes the difficulty of delivering drones in the "last mile" in the context of a severely aging population. The last mile delivery means that after customers shop through e-commerce, the purchased items are delivered to the distribution point, and then the goods are delivered to the customer from a sorting center through a certain means of transportation to achieve door-to-door service. The "last mile" of distribution is not a real mile, but refers to the distance from the logistics sorting center to the customer, and the process of delivering the goods to the customer through the means of transportation. Because it is a short distance, it is called one-kilometer delivery as the saying goes. This short-distance distribution is the last link of the entire logistics link and the only link that directly contacts customers face-to-face, which is of great significance. With the maturity of artificial intelligence technology, UAV distribution has emerged. This paper expounds the distribution scope, distribution process and technical equipment of the current development of UAV distribution, analyzes the problems of UAV endurance, airspace restrictions, and distribution safety, and puts forward corresponding countermeasures. Intelligent computing can reconstruct the logistics operation process. With the development of artificial intelligence, the logistics process may be decomposed into several parallel processes. Within the scope of the logistics system, using artificial intelligence technology, many activities such as automatic decision-making, automatic detection, and automatic repair can be automatically sorted according to the process. These activities can also not enter the cloud computing center platform, greatly improving the system computing efficiency and responsiveness. Because of its light weight and fast speed, UAVs can avoid urban traffic congestion and can cross special terrains such as mountains and lakes. The use of UAVs can shorten logistics delivery time and reduce logistics costs, so that its application scope of logistics distribution is getting wider and wider. In recent years, due to the strong contagiousness of the new crown epidemic, contactless distribution has attracted widespread attention, which has promoted the promotion and application of cutting-edge logistics distribution tools such as drones, drone vehicles and delivery robots.

Integrated information management of supply chain in logistics parks based on the IoT

AbstractLogistics park is a strategic choice for the growth of logistics industry, and it needs to build a public platform for supply chain management (SCM) suitable for logistics parks. To solve the problems of poor adaptability, high investment risk, and incomplete functionality of the supply chain integrated information management (IM) platform in logistics parks, it is necessary to use Internet of Things (IoT) technology to improve the supply chain integrated IM platform, improve the timely interaction of logistics information and reduce logistics costs. This article analyzed the factors that affect the integrated management of logistics park supply chain, analyzed the architecture of logistics park supply chain, integrated IM under the IoT, and implemented the platform architecture using relevant technologies. In the experiment, the resource allocation, resource scheduling, and resource monitoring effects of the supply chain integrated IM platform were analyzed. The results showed that the supply chain IM platform of logistics parks under the IoT has improved infrastructure by 0.14 compared to traditional platform, resource allocation by 0.16, logistics service level by 0.14, and industrial layout by 0.14. The IoT can effectively enhance the resource allocation and industrial layout rationality of logistics parks and has important significance in improving logistics information security and information exchange.

중국 소매업의 물류서비스품질이 고객만족도 및 고객충성도에 미치는 영향에 관한 연구

Purpose: This study verifies the relationship between customer satisfaction and customer loyalty with logistics service quality selected as a leading factor. The mediating effect of customer satisfaction is also verified in the relationship between logistics service quality and customer loyalty.
 Research design, data, and methodology: The design and hypothesis setting of the research model are based on previous studies, and SPSS 19.0 is used for basic data analysis, reliability, validity, correlation analysis, multiple regression analysis, and hierarchical analysis of a survey.
 Results: Economic feasibility, which is the quality of logistics services, did not significantly affect customer satisfaction. Speed, accuracy, and convenience had a significant effect on customer satisfaction, while customer satisfaction had a significant effect on customer loyalty. Customer satisfaction had a mediating effect on the relationship between logistics service quality and customer loyalty.
 Conclusions: The logistics industry is in a period of rapid development, and the introduction of logistics talent should be increased to improve the core competitiveness of the retail industry, increase work efficiency, reduce logistics costs, and promote the improvement and development of corporate management levels.