Modern Logistics Industry Research Articles

An analysis of logistics financing prospects in Singapore

Singapore is well-positioned as a global hub for logistics and supply chain management. Singapore’s modern logistics industry has five main characteristics: high efficiency, robust technology, strong professionalism, high service concentration and strength. Singapore is a foreign trade-driven economic model. With the prosperity of cross-border trade, companies in the logistics industry in Singapore seek diversification and expansion of supply chain technology and logistics finance. This paper mainly analyses the advantages of Singapore’s development of the logistics industry and the promotion effect of Singapore’s growth in the financial field on logistics industry financing. Factors such as the Internet of Things, blockchain, intelligent management, talent cultivation and policy support are enormous drivers for developing logistics financing in Singapore. Among them, the most representative and promising is the blockchain platform, which provides technical support for the Internet of everything, improves the security of multi-agent cooperation, and expands the scope of credit transmission. Although there are still some risks in developing logistics financing in Singapore, as a potent combination of the financial and logistics industries, logistics financing has a bright prospect.

Research on high quality development path of modern logistics industry

Research on high quality development path of modern logistics industry

Green Innovation in Regional Logistics: Level Evaluation and Spatial Analysis

Green innovation is imperative for the high-quality and sustainable development of the modern logistics industry. It is also key for achieving the goals of peak emissions and carbon neutrality. This study provides a way of thinking about the evaluation of the green innovation level of the logistics industry. The variance inflation factor-variance coefficient method was employed to construct an evaluation index system of the regional logistics green innovation level (RLGIL) from three dimensions. Empirical data were collected from statistical yearbooks covering 30 provinces in China from 2013 to 2017. Thereafter, the combination weighting-based GRA-TOPSIS method was applied to evaluate the RLGIL, and the spatial distribution differences and spatiotemporal evolution characteristics of inter-provincial green innovation levels were analyzed. The RLGILs in the 30 provinces were found to be generally unbalanced, and the differences between the eastern and western regions were significant. Guangdong, Jiangsu, and Zhejiang had stronger RLGILs, whereas most other provinces did not reach the average level. The RLGIL of the 30 provinces had a high positive spatial correlation and spatial aggregating effect. From a national perspective, the values for the RLGIL were generally higher in the eastern and southern regions and lower in the western and northern regions. Although significant differences were found in the RLGIL of these provinces, the overall development trend was stable.

Spatial-Temporal Evolution of Total Factor Productivity in Logistics Industry of the Yangtze River Economic Belt, China

The logistics industry plays a great role in the sustainable economic development of the Yangtze River Economic Belt (YREB). This paper measures the total factor productivity (TFP) of the logistics industry by using the DEA-Malmquist index method and analyzes its spatial-temporal evolution characteristics based on panel data of 11 provinces and cities in the YREB in 2003–2017. Lastly, a spatial autocorrelation analysis was conducted in conjunction with the exploratory spatial data analysis (ESDA) model. The results show that the overall development of the logistics industry has been relatively good, with an inverted “N” shape trend over the years. Technological progress is the main reason for the growth of TFP. From a regional perspective, it shows a spatial distribution pattern of high in the east and low in the west, with an overall upward trend of TFP levels. The spatial correlation between the TFP levels of logistics in each province and city is gradually increasing, but coordinated development between regions is still limited. Finally, according to the conclusions, policy recommendations are proposed to accelerate the coordinated development of regional logistics and the innovative development of the modern logistics industry.

A Correlative Study of Modern Logistics Industry in Developing Economy and Carbon Emission Using ARDL: A Case of Pakistan

The modern logistics industry in relation to economic growth and carbon emission has opened new strategic perspectives. Recent research work have analyzed such complex interference from a broad perspective. However, analyzing this overlap needs comprehensive insight into the logistics industry while simultaneously estimating its short-run and long-run effects from regional aspects due to continue-evolving factors and their impact on it. This paper competently analyzes logistics industry components in connection with economic prosperity, energy consumption, trade development, and carbon emission from a more specific regional perspective of a developing country. Methodologically, an autoregressive distributive lag model (ARDL) is employed using correlative evaluation of the dynamic factors and their interactive impact in short and long run on this relation, based on time-series data of Pakistan from 1990 to 2019. The study results endorse the previous studies’ outcomes by recognizing that an increase in carbon emission depends on trade development, energy usage, economic development, and the logistics industry’s various components except for air logistics. However, study results show a unidirectional long-run causality directing from economic development, logistics industry, energy utilization, and trade development to carbon emission. Moreover, these results reveal that this emission is the leading factor to introduce stringent emission standards that further overlap with regional demographics trends, i.e., carbon emission implications. These findings imply that economic development applies a substantial demand-pull impact on national logistics, i.e., regional economic development directs to the growth of the logistics industry in the corresponding region. Consequently, high-income geographical regions have higher long-run risk concerning contemporary developmental activities of the logistics industry when adhering to carbon emission standards. Particularly, the influence of upcoming emission standards must be prioritized when planning the future returns of contemporary research and development activities of the logistics industry in a given geographic area, such as CPEC. Given Pakistan’s perspective, the proposed empirical analysis can be exampled to other developing countries. This analysis may facilitate the design and development of strategies for upcoming financial funding in the modern logistics industry to seek its sustainable development-goals in developing economies.

Research on Passengers’ Preference for High-Speed Railways (HSRs) and High-Speed Trains (HSTs)

This paper aims to study passengers’ preference for High-Speed Railways (HSRs) and High-Speed Trains (HSTs) through a systematic literature review. The existing relevant literature was examined by using the Scopus application, and the Latent Dirichlet Allocation (LDA) method is applied to extract the topics of the selected documents. By comparing the contents of the relevant literature, the general overview of research in this field can be further understood, and the key factors that have been studied so far that affect passengers’ preference can be analyzed. As a green, safe, and sustainable transport mode, HSRs do not only play an essential role in serving passengers but could also be a novel option for freight transport as long as HSRs are able to adjust their technology to the requirements of the rapid growth of the modern logistics industry. The evaluation of passengers’ preference for HSRs/HSTs presents some gaps that need to be addressed in future studies: (1) the speed of the HST line ought to be introduced clearly; (2) more competing alternatives, such as maglev, autonomous vehicles, and other access–egress transport modes to terminals, such as subways and aero taxis, need to be included; (3) the analysis of passengers’ preferences needs to be extended to the new role that HSRs can play in the logistics industry as new cargo services have been developed with the participation of HSRs; and (4) some attributes related to environmental costs and carbon emissions for the transport modes, as well as segmentation variables that are proxies for different passengers’ attitudes towards climate change concerns, need to be included in the design of the choice experiment.

Implementation of Multidimensional Environmental-Economic Collaborative Management in IoT Environment

The Internet of Things (IoT) has gotten a lot of attention as a next-generation Internet application, and its realization, which connects things, people, and things, is the focal point of a new round of high-tech competition around the world. Network technology has a significant impact on people’s lives today, thanks to the rapid development of the Internet, and the Internet of Things (IoT) is a technological innovation of the times that promotes the development of information technology. The Internet of Things has given the logistics industry a new lease on life, allowing it to grow more intelligently. The modern logistics industry is a modern service industry that includes transportation, warehousing, freight forwarding, information, and other industries, and it is very important. This paper examines the technical system of the Internet of Things and the logistics economic management mode, as well as the impact of the Internet of Things on logistics economic management. A multidimensional collaborative management model of environment and economy is proposed, based on the background of IoT. It has laid the groundwork for the IoT’s application and development in the logistics economy.

Evolution of employee opinion in a crowdsourcing logistics company: a catastrophe-embedded RA model

Crowdsourcing logistics is a business model for the modern logistics industry. However, the employee behavior of crowdsourcing logistics remains unstable due to the dynamic nature of crowdsourcing logistics. With a small change in environmental factors, e.g., the delivery price, employee opinion may show frequent polarization or reversal that can lead to employee turnover. To explore the mechanism of sudden change in employee opinion and turnover, a cusp catastrophe model is embedded into the relative agreement (RA) model of opinion dynamics to form a catastrophe-embedded RA model. Text data about employee opinion of the crowdsourcing logistics company DaDa are collected for modeling and validation of the catastrophe-embedded RA model. Simulation experiments explore the impact of network structure and delivery price on employee opinion evolution and employee turnover. The catastrophe theory–embedded RA model extends the application of the RA model in the field of opinion dynamics with frequent polarization or reversal.

Study on Coordination Evaluation of Modern Logistics Industry and Regional Economy High-Quality Development in Hunan Province

Objectives: We calculate the coupling coordination degree between modern logistics industry and high-quality development of regional economy in Hunan Province from 2008 to 2019. Methods: In this study, the coupling coordination degree model is constructed and the calculation is carried out based on Principal Component Analysis (PCA). Results: (1) The degree of coupling coordination between modern logistics industry and high-quality development of regional economy in Hunan province is generally on the rise from 2008 to 2019. (2) From 2013 to 2019, the development of modern logistics industry and regional economy in Hunan Province has been in a state of "high-level coordination". The 19th National Congress clearly put forward high-quality development. From 2018 to 2019, the degree of coupled and coordinated development between modern logistics industry and high-quality development of regional economy in Hunan Province showed a state of "high-level coordination". According to this conclusion, Combined with the "three highs and four new" strategy and the urban requirements of the new development concept in Hunan Province, this paper puts forward some suggestions on promoting the modern logistics industry in Hunan Province and promoting the coordinated development of regional economy with high quality.

The Application of Order Scheduling Algorithm for Food Delivery Logistics Based on Historical Data

With the improvement of China’s social and economic development, the requirements for delivery efficiency of foreign logistics orders are becoming more and more stringent. Big data technology is the current direction of vigorous development. With the development of the Chinese era, in order to better promote the development of China’s urbanization. With the continuous innovation of big data technology, various industries are undergoing industrial upgrading and format conversion. This article mainly discusses the order scheduling algorithm of takeaway logistics based on historical data. Through in-depth research and analysis of the algorithm, the researched scheduling algorithm is reasonably applied to the delivery industry of takeaway logistics, and the scheduling algorithm of big data technology is used for accurate calculation. The supply-demand relationship between food delivery and customers in historical data and the optimal path of actual logistics delivery provide algorithmic support for the selection of time and path of food delivery. Making good use of big data technology can not only accurately predict customers’ habits of ordering food, but also play a role in optimizing delivery. With this technology, the automation level of food delivery can be effectively improved, and foreign media can be delivered to customers in a more timely manner. In its hands, it highlights the application value of big data technology and promotes the development of China’s modern logistics industry, making it possible to develop in the direction of intelligence and automation. The experimental results show that the food delivery industry has great convenience and higher efficiency for ordering and transportation of food delivery under the condition of combining big data technology.

People-Oriented Optimization Model Of Warehouse Staff Scheduling Problem

With the development of e-commerce, China is actively promoting the construction of logistics informatization and intelligence, and simultaneously promoting the standardized and efficient development of warehousing industry, one of the important links of logistics. It is clearly pointed out in the "Medium and Long Term Plan for the Development of the Logistics Industry" issued by the State Council that "The warehousing industry is not only the main body of the traditional logistics industry, but also an important part of the modern logistics industry. In the process of material flow, the level of storage cost has a greater impact on the development of the logistics industry." This paper chooses Sinotrans Logistics Company as the research object. Sinotrans Logistics Company is the largest integrated logistics provider in China and a national 5A comprehensive logistics enterprise. The main problems in Sinotrans warehousing management include: increased operation difficulty of cross-warehouse inventory, large order volume and delayed processing, unreasonable scheduling of warehouse staff, more idle time for warehouse staff and large difference in human efficiency per hour, etc. The key elements of these problems are the work efficiency of employees. Therefore, warehouse management needs to carry out fine scheduling of warehouse staff to improve the completion rate of orders and reduce the waste of labor costs. Keywords: Warehouse staff scheduling problem, integer programming, linear regression model, people-oriented

Driving performance grading and analytics: learning internal indicators and external factors from multi-source data

PurposeThe purpose of this paper is to deal with the practical challenge faced by modern logistics enterprises to accurately evaluate driving performance with high computational efficiency under the disturbance of road smoothness and to identify significantly associated performance influence factors.Design/methodology/approachThe authors cooperate with a logistics server (G7) and establish a driving grading system by constructing real-time inertial navigation data-enabled indicators for both driving behaviour (times of aggressive speed change and times of lane change) and road smoothness (average speed and average vibration times of the vehicle body).FindingsThe developed driving grading system demonstrates highly accurate evaluations in practical use. Data analytics on the constructed indicators prove the significances of both driving behaviour heterogeneity and the road smoothness effect on objective driving grading. The methodologies are validated with real-life tests on different types of vehicles, and are confirmed to be quite effective in practical tests with 95% accuracy according to prior benchmarks. Data analytics based on the grading system validate the hypotheses of the driving fatigue effect, daily traffic periods impact and transition effect. In addition, the authors empirically distinguish the impact strength of external factors (driving time, rainfall and humidity, wind speed, and air quality) on driving performance.Practical implicationsThis study has good potential for providing objective driving grading as required by the modern logistics industry to improve transparent management efficiency with real-time vehicle data.Originality/valueThis study contributes to the existing research by comprehensively measuring both road smoothness and driving performance in the driving grading system in the modern logistics industry.

A Comparative Study on the Influence of Artificial Intelligence Robot Distribution and Traditional Logistics Distribution Mode

With the increasing level of intelligence of logistics enterprises in China, the mode of artificial intelligent logistics distribution has become a new strategy for the development of modern logistics industry. In the logistics industry of artificial intelligence, logistics robot has occupied the market and become the key link of logistics distribution. It is of great significance to study the distribution mode of artificial intelligence robot. With the development of our national economy and the improvement of people’s living standard, the demand for logistics service quality and distribution efficiency is higher and higher. At present, most enterprises in our country abandon the traditional manpower distribution operation mode. This paper expounds the basic concepts of “artificial intelligence” and “intelligent robot” through the literature research method and the research method of combining theory with practical cases, and obtains the cognition of the current technology of intelligent logistics by collecting, processing and sorting the relevant documents. The emergence of artificial intelligence makes large amount of data fast and accurate, while artificial intelligence robot makes logistics management system, object transportation, distribution and order quantity processing intelligent, and produces the integration of production, the production chain is greatly reduced, the communication between logistics enterprises and intelligent robots is closer, the corresponding cost can be greatly reduced, and the enterprise can manage and operate effectively.

Research on the Route Pricing Optimization Model of the Car-Free Carrier Platform Based on the BP Neural Network Algorithm

The car-free carrier platform is a product of the rapid development of the modern logistics industry and has a vital strategic value for promoting the construction of a country’s comprehensive transportation. However, due to the unreasonable platform pricing model, the industry is currently in a bottleneck period. In order to solve this problem, we established a gray correlation model to calculate the degree of correlation between each characteristic index and platform pricing based on the massive historical transaction data of a certain platform and performed K-means clustering on the results to discover the main factors affecting platform pricing. Based on the abovementioned results, we created a pricing optimization model based on the BP neural network, with the structure of 8-13-1 to predict the freight pricing of the order and test the prediction results. The test shows that the goodness of fit (R2) of the predicted value is close to 1, and the prediction error range is less than 3.7%, which proves the accuracy and effectiveness of the BP neural network model and provides an effective reference for the optimization of the pricing model of the car-free carrier platform.

Gantry type rotating platform obstacle avoidance crane

The rapid development of modern logistics industry has higher requirements for logistics machinery and equipment. As an important equipment for material handling, cranes are used more and more widely in the modern production process. At present, cranes have problems such as large size, inconvenient movement, and inaccurate positioning. Based on the above background, the project team designed a gantry type rotating platform obstacle avoidance crane. The crane breaks through the transportation limitations of the original crane. It uses the direct rotation of the pan-tilt and the movement of the spreader on the track to accurately avoid obstacles, which improves the flexibility and accuracy of transportation; the entire transportation process is fully automatic control, which combines the machinery with The combination of intelligence improves transportation efficiency and realizes the accurate transportation of multiple goods.

Optimization of Palletized Unit Implants Dispatch Considering Less than Truckload Transportation in Auto Parts Industry

In recent years, the acceleration of economic globalization has played an irreplaceable role in promoting the development of modern logistics industry. Reducing production and operating costs, reducing logistics costs, and increasing enterprise competitiveness have become new challenges of the rapid development for the logistics industry. At the same time, the demand for automobiles has also increased significantly which has strongly driven the development of auto parts industry. A method to optimize palletized unit implants dispatch in auto parts industry which adopts less than truckload (LTL) transportation is proposed in this paper. An optimization model of palletized unit implants dispatch is constructed with the goal to minimize the total transportation cost and the constraints including dispatching demand, dispatching time and so on. And the effectiveness of the model and algorithm is verified by case study. The results show that the dispatch optimization model of shared palletized unit implants considering less than truckload transportation is 7.5% less than full dispatch mode and 146.6% less than full lease mode.

Empirical Analysis of the Influence of Dongguan’s Modern Logistics Industry on Import and Export Trade

In recent years, with the rapid economic development and the deepening of global economic integration, import and export trade has developed rapidly. With the development of international trade, international logistics has emerged. Modern logistics is a necessity for import and export trade, and the development of logistics has a direct influence on the development of import and export. In order to adapt to the rapid development of import and export trade, the modern logistics industry is developing in the direction of quality, diversity and efficiency. As the manufacturing capital, Dongguan has great potential for trade development. Relying on the superior geographical environment and the original industrial system, and further integrating resources on this basis, Dongguan vigorously develops its modern logistics industry and promotes a high degree of connection between international trade and characteristic industries, promoting the development of Dongguan’s import and export trade. Taking Dongguan as the research object and combining the data of Dongguan’s import and export trade and modern logistics industries, this paper established a quadratic curve fitting model to analyze the relationship between the total transportation volume and the total import and export volume, conducted elasticity and marginal analysis based on the empirical results, and put forward feasible suggestions for the development of Dongguan’s logistics and import and export trade.

The influence of e-commerce and modern logistics on regional economic structure and scope

With the rapid development of Internet and information technology, the space and time boundaries between regions have been broken. With the advent of the "Internet plus" era, the rapid development of e-commerce based on Internet and information technology has promoted the development of regional economy and modern logistics industry. The application level of e-commerce and the development of modern logistics also have an important impact on the regional economic structure and scope. Therefore, it is of great significance to study the impact of e-commerce and modern logistics on the scope of regional economic structure for promoting the coordinated development of e-commerce and modern logistics.

Research on the Evaluation and Development Strategy of Environmental Logistics in Hebei Province

Environmental logistics has become the irreversible trend of logistics development in the future, and it is also an inevitable choice to promote the transformation of China's modern logistics industry. Regions that want to develop environmental logistics must scientifically evaluate the current status of environmental logistics development. This paper builds a regional environmental logistics evaluation system, horizontally compares the data of Hebei Province and 13 other provinces in 2017, and longitudinal evaluation of data from 2013 to 2017 in Hebei Province, and obtains the ranking of the development status of environmental logistics in Hebei Province and its development trend in the past five years. Based on the evaluation results, countermeasures and suggestions are proposed for improving the level of environmental logistics in Hebei Province, including increasing the comprehensive utilization rate of waste; reinforcing the investment in related fixed assets; reducing the energy consumption of the logistics industry; improving the operating mileage of public railways, and increasing the freight volume.

A Correlative Analysis of Modern Logistics Industry to Developing Economy Using the VAR Model: A Case of Pakistan

The modern logistics industry has opened new strategic perspectives in establishing its interrelation with economic growth. In recent years, understanding such an overlap has become a policy issue considering ever-increasing factors and their influence on this relation. Most existing studies have explored this interaction from a general perspective, or for developed countries. This paper explores time-series analysis of the dynamic variables and their inter-related influence in both the short and long run on the relationship between modern logistic industry and economic growth—a more specific perspective, particularly for developing countries. Accordingly, we exemplify our analysis by employing the vector autoregression (VAR) model to the most updated time series data of investment in the logistics industry and the economic growth of Pakistan from 1990 to 2018. The empirical findings endorse the previous studies’ outcomes and recognize the importance of sustainable economic development concerning continuously improving the logistics industry. However, a unidirectional relation is observed that economic growth leads to developing the logistics industry—economic growth exerts a significant demand-pull effect on Pakistan’s logistics. It implies that logistic industrial development is comparatively quicker in the geographical areas where economic growth is higher than those areas where economic growth is low. To conclude this study’s findings, logistics industry reforms should prioritize the selected geographical areas in improving the economy that would lead to the modern logistics industry’s development. As the model adopts Pakistan’s context, the overall statistical analysis can be generalized to other developing economies. These results would be of particular interest to strategy makers working in developing countries and help them design and develop modern transportation and logistics, coupled with interlinked technological factors, which would attract investment in the logistics industry for sustainable economic development.