Logistics Companies Research Articles

A computer vision system for recognition and defect detection for reusable containers

Small load carriers (SLCs) are standardized reusable containers used to transport and protect customer goods in many manufacturers. Throughout the life cycle of the SLCs, they will be collected, manually checked for defects (wear, cracks, and residue on the surface), and cleaned by specialized logistic companies. Human operators in small to medium-sized companies manually evaluate the defects due to the variety and degree of possible defects and varying customer needs. This manual evaluation is not scalable and prone to errors. This work aims to fill this gap by proposing a computer vision system that can recognize the SLC type for inventory management and perform defect detection automatically. First, we develop a camera portal, consisting of standard components, that capture the relevant surfaces of the SLC. A labeled dataset of 17,530 images of 34 different SLCs with their defect status was recorded using this camera portal. We trained a classification model (ConvNeXt) using our dataset to predict the different types of SLCs achieving 100% class prediction accuracy. For defect detection, we explore eight state-of-the-art (SOTA) anomaly detection models that achieved high rankings in the MVTec industrial anomaly detection benchmark. These models are trained using default hyperparameters and the two highest-scoring models were chosen and fine-tuned. The best-fine-tuned models based on “Area under the Receiver Operating Characteristic Curve (AUROC)” are PatchCore (0.811) and DRAEM (0.748). These results indicate that there is still potential for improvement in the automation of defect detection of SLCs.

Developing and implementing AI-driven models for demand forecasting in US supply chains: A comprehensive approach to enhancing predictive accuracy

Demand forecasting has long been a critical challenge in the US supply chain operations, plagued by disruptions, fluctuating demand, and price volatility. Developing and implementing AI models that can accurately predict demand is essential in response to these issues. This study aimed to investigate the feasibility of applying machine learning techniques to demand forecasting, particularly in supply chain operations. A comprehensive analysis was conducted using historical data from a logistics company in the USA, which was used to train five traditional demand forecasting methods: Linear Regression, ElasticNet, Random Forest, MLPRegressorn, and XGBoost. Additionally, feature selection, data normalization, and dimensionality reduction techniques were employed to improve the accuracy of these models. Strategic metrics were used to evaluate the model's performance: Random Mean Squared Error, Mean Absolute Error, and R-squared score. The results of this study indicate that AI models have shown significant promise in predicting target sales in supply chains with Linear Regression emerging as the most effective model with the lowest RMSE, MAE, and an R-squared score close to 1. Practical implications of implementing such AI models in the US supply chain include optimized inventory management, reduced costs, and enhanced customer satisfaction. This research contributes to the existing body of knowledge on AI applications in demand forecasting, highlights the importance of traditional methods being supplemented by machine learning techniques, and provides practical recommendations for businesses seeking to improve their supply chain operations.

Exploring high-performance green innovation in China’s logistics companies: a TOE framework based on fsQCA

In recent years, the Chinese logistics industry has experienced rapid development. However, this expansion is accompanied by significant challenges, including high energy consumption and greenhouse gas emissions. Despite these issues, the key factors improving logistics firms’ green innovation remain insufficiently explored. This study fills this gap by utilizing the Technology-Organization-Environment (TOE) framework as a foundation, introducing a comprehensive analytical model to investigate the dynamics of green innovation in logistics companies. Moreover, after employing fuzzy-set Qualitative Comparative Analysis (fsQCA) with data from 83 logistics firms in China, the research examines the complex interplay between technological, organizational, and environmental factors and their strategic influence on green innovation performance. The study yields three pivotal findings: (1) High-level green innovation performance is not predicated on a single factor. (2) Logistics firms can attain superior green innovation performance through two driving paths: Core competencies and market pressure driven as well as technological innovation and government subsidies driven. (3) The analysis of low-level green innovation performance reveals that four distinct paths can culminate in this outcome, with the lack of digitalization, organizational slack, and market pressure being instrumental in this result. These insights highlight the principles of “multiple concurrency” and “different paths leading to the same goal,” significantly enhancing the current knowledge base on green innovation performance and deepening our understanding of the multifaceted drivers of high-performance green innovation in logistics companies. Moreover, the discoveries offer practical implications for firms and the government to improve green innovation performance within the logistics industry.

Implementation of integrated services of intelligent supply chains by leading Chinese logistics companies.

The article examines the restructuring of global supply chains within the framework of the active development of China’s logistics services market. It is established that with the continuous improvement of the country’s digital economy, these services can become one of the important directions for the development of large Chinese companies operating in this industry. The purpose of the work is to study the implementation of integrated intelligent supply chain services, analyze the practice of their application, and their impact on the growth of turnover and income of leading logistics enterprises in the country — Xiamen C&D Group Corp. Ltd., SF Express Holding, YTO Express — in 2021–2023. The paper describes the step-by-step mechanism of the intelligent supply chains of Chinese companies and its innovative component. It is determined that the studied organizations adhere to the principle of digital excellence, promote digital industrialization, jointly create a common logistics big data platform (the country’s digital logistics ecosystem), and apply new business formats and a modern logistics model to facilitate the industrial transformation and modernization of China’s economy. To achieve the goals of the study and analyze the restructuring of global supply chains within the framework of the active development of China’s logistics services market, methods of scientific analysis of scientific literature and economic analysis of reports of leading logistics companies in China, comparative analysis, content analysis, and case studies were used to study examples of the implementation of intelligent supply chains in Xiamen C&D Group Corp. Ltd., SF Express Holding, YTO Express. The results of the research can be useful for international organizations and partners of China engaged in joint logistics projects and initiatives to enhance cooperation and coordination efforts.

Supply and demand prediction by 3PL for assortment planning

To underscore the critical role of predictive capabilities in third-party logistics (3PL) companies for assortment planning, particularly within the rapidly evolving e-commerce sector and business to business (B2B) flows. This study employs a comprehensive literature review on the forecasting capabilities of 3PL firms, enriched by empirical research across nine logistics facilities. It leverages statistical tools and the ARIMA_PLUS algorithm to evaluate the precision and dependability of demand and supply forecasts generated by these companies. The research reveals that 3PLs possess the ability to generate accurate demand and supply forecasts utilizing advanced forecasting tools. The effectiveness of these forecasts is closely linked to the quality of data available, and the expertise of the personnel involved. Challenges arise in forecasting for smaller order volumes, which are more common in e-commerce flows. The study also highlights that technological advancements and investments in data analytics are pivotal in enhancing forecast accuracy. The investigation focuses on a select group of 3PL companies, potentially limiting the generalizability of the findings. Moreover, the study underscores the necessity for further exploration into how technological innovations impact forecasting capabilities. By emphasizing the significance of 3PL firms' predictive abilities, also for e-commerce assortment planning, this paper addresses a notable gap in existing research. Its insights are invaluable for businesses contemplating logistics outsourcing and for 3PL providers aiming to advance their forecasting proficiency. The findings stress the importance of integrating advanced forecasting models and analytics to stay competitive in the dynamic e-commerce landscape.

Managing Cash Flow and Financial Efficiency in Logistics Companies: Analyzing Practices and Their Impacts

Managing Cash Flow and Financial Efficiency in Logistics Companies: Analyzing Practices and Their Impacts

A Study on the Impact of ESG Management Activities of Distribution and Logistics Companies on Financial Performance: Application of Panel 2SLS Analysis Considering Endogeneity

A Study on the Impact of ESG Management Activities of Distribution and Logistics Companies on Financial Performance: Application of Panel 2SLS Analysis Considering Endogeneity

물류기업 ESG 공시가 기업의 재무성과와 기업가치에 미치는 영향 연구

Corporate social responsibilityand sustainability has increasingly emphasized the impact of ESG factors on corporate management in recent years. maximizing financial benefits and creating social value in this context, this study comparatively analyzed the impact of ESG disclosures on Korean logistic companies’ financial performance and market value during 2010-2023. ESG disclosure was measured via Bloomberg's ESG Disclosure Score. The analysis revealed that companies with higher ESG disclosure scores had significantly greaterfinancial outcomes and market value. Furthermore, ESG disclosures had a notable effect on financial performance. Thus, ESG disclosures are a critical element of corporate management. Finally, the varying effects of ESG disclosure on logistics companies highlight the need for country-specific ESG strategies.

Creating innovations for solutions of logistics problems: opportunities, risks, and limitations

The article provides an assessment of innovation activity state in logistics companies in the second half of 2022 and 2023 as well as the potential consequences of low level of investment in innovation. The relevance of the article is determined by the objective features of the development of the logistics industry in the Russian Federation, primarily in the context of international import and export trade under the conditions of sanctions restrictions as well as increased competition of logistics companies on the market and competitive pressure from international logistics companies which enter the Russian market. The purpose of the study is to assess the characteristics of the functioning of the logistics industry and the prospects for its development, which can have a significant impact on the international movement of goods. An assessment is made of companies’ strategies to maintain their market share, increasе this share through interaction with the labour market as well as tо use additional tools for obtaining and maintaining a market advantage. A conclusion is drawn about the influence of a number of factor criteria on the further development of the industry and those resources associated with investments in innovation that the company’s owners have for the future development of their business.

The Impact of Industry 4.0 in The Conditions of Globalization: An Overview of Logistics Companies Originating from Turkiye

The main purpose of this study is to investigate the impact of Industry 4.0 technologies on the survival and competitiveness of logistics companies based in Turkiye, a developing country, within the global landscape. From a qualitative study perspective, it aims to elucidate the positive and negative effects of Industry 4.0 applications on the logistics sector while also discussing recommendations to mitigate or eliminate these negative impacts. Based on the results of the semi-structured interview analysis, it can be asserted that the positive impacts of Industry 4.0 applications increase proportionally with the scale of a firm. Besides, if the R&D investments are enhanced in the logistics industry operating in Turkiye, it is expected that the negative effects will be more likely to be mitigated. According to findings from interviews, the preliminary anticipated effect of Industry 4.0 applications on the logistics sector is improved efficiency, while the primary barrier to its adoption is identified as the inadequacy of infrastructure and education.

Data-Driven and Sustainable Transportation Route Optimization in Green Logistics Supply Chain

In the green logistics supply chain, transportation route optimization faces urgent problems such as high energy consumption and environmental pollution. This paper aims to achieve sustainable optimization of transportation routes through a data-driven approach. First, a large amount of transportation-related data is collected, including vehicle operation information, cargo characteristics, road conditions and meteorological factors. Big data analysis technology is used to clean and extract features from the data, and a transportation demand forecasting model is constructed. Then, a new optimization model is designed using the particle swarm optimization algorithm, with the goal of minimizing transportation costs and carbon dioxide emissions. In actual application cases, by optimizing the transportation routes of a logistics company, the results showed that the lowest transportation cost was 1,512 dollars and the lowest carbon dioxide emissions were 1.2 tons. Data-driven transportation route optimization not only improves logistics efficiency, but also promotes environmental sustainable development.

Competitive Analysis of Cross-border E-commerce Business of Logistics Enterprises: The Case of Rookie Wrap Company

This paper discusses the competitiveness of logistics companies in cross-border e-commerce business, using Rookie wrap as an example. Through a comparative analysis of the development history, characteristics and comparison with other logistics companies (e.g., S.F.Holding Co.,Ltd), this paper summarizes the key factors affecting the competitiveness of logistics companies, including market size, revenue capacity, business diversification, growth rate, technological innovation and service innovation. It is found that Raiding Bird Wrapped, relying on the strong background of Alibaba Group, has a huge potential scale and influence in the field of e-commerce logistics, and actively lays out intelligent logistics and overseas markets. In contrast, SF has a more comprehensive business layout, including express delivery, supply chain management, e-commerce logistics and international business, showing a stronger anti-risk ability. The article points out that the key to enhance the competitiveness of logistics enterprises is to actively explore the market, increase market share, and adjust and optimize the business structure, focusing on the development of business strengths, while trying to expand new businesses. Through continuous technological innovation and service upgrading, logistics enterprises can consolidate their position in the fierce market competition and realize sustainable development.

THE IMPACT OF TECHNOLOGY ON LOGISTICS SERVICES IN SAUDI ARABIA

This research strives to explore the impact of technological advancements which have transformed logistics services in Saudi Arabia in line with Vision 2030 goals. It examines key technologies viz. Big Data, Internet of Things (IoT), Blockchain, autonomous vehicles and drones etc. which have enhanced operational efficiency, reduced costs and improved service quality, thereby significant operational improvements to the logistics companies in Saudi Arabia. Case studies have been taken from local companies which demonstrate successful implementation of these technologies. Given the inherent challenges like regulatory requirements, infrastructure developments etc., the research also highlights the potential of autonomous vehicles and drones to further revolutionize transportation and last-mile delivery services. Overall, this study concludes that technological integration is critical for driving efficiency, competitiveness, and sustainability in the logistics sector, aligning with Saudi Arabia's broader economic transformation goals.

Exploring the cost–carbon trade‐off in using a mixed fleet of hydrogen trucks and diesel trucks

AbstractHydrogen trucks (HTs) offer promising potential for decarbonizing the transportation sector. Based on current technologies, they have significant advantages over electric trucks (ETs) in terms of range, refueling time, and performance in cold conditions. However, HTs are costly, and there are insufficient hydrogen refueling stations (HRSs). Gradually integrating HTs into the existing diesel truck (DT) fleet is a practical approach for many freight logistics companies. In this article, we formulate a mathematical model to route a mixed fleet of HTs and DTs, and we propose an algorithm called the curve descent search (CDS) to generate the Pareto set based on cost and carbon emissions. We find that CDS can generate better Pareto sets compared to existing algorithms in the literature. We use CDS to comprehensively explore the cost–carbon trade‐off in using a mixed fleet. This question differentiates our study from previous research and is motivated by discussions with one of the largest third‐party logistics companies in North America. Detailed experiments reveal important managerial insights, such as: (1) Achieving a significant reduction in carbon emissions (e.g., a 30% reduction compared to the current diesel fleet) does not need a very dense refueling infrastructure; (2) The cost–carbon trade‐off for mixed fleets is relatively insensitive to variations in customer density and demand, suggesting that HTs can be applicable across a wide range of scenarios (including different sectors or regions); and (3) Although ETs are cheaper to use compared to HTs, their shorter range limits their competitiveness in terms of decarbonization efficiency and customer service.

Training for Digital Resilience: A Business Continuity Planning Case Study

In a world experiencing rapid digital transformation, the need for robust Business Continuity Planning (BCP) has never been more critical for companies. This article explores the increasing necessity for businesses to develop comprehensive BCP strategies, particularly in response to IT-related threats. Focusing the research on a service center of an international logistics company, the paper delves into the dynamics of BCP iterations. Emphasizing the often-overlooked human component, this study highlights the importance of fostering digital resilience among employees. It addresses critical questions such as: Are our teams adequately prepared to withstand disruptions? Have we identified key roles that require succession planning to ensure continuity of critical processes? Moreover, it examines how organizations can ensure redundancy in essential competencies across all roles supporting resilience, thus preparing for potential disasters. By focusing on both strategic and operational aspects of BCP, this article provides a comprehensive approach to enhancing organizational resilience in the face of digital threats through a framework of resilience assessment and training.

Актуализация информационного обеспечения бизнес-процессов агентирования и фрахтования морских судов

Improving information support and introducing digital analytical tools is one of the ways to improve the efficiency of cargo transportation management. The aim of this study was to analyze maritime cargo transportation, identify reserves for improving the information support of business processes in the agency and chartering of vessels. For this purpose, general scientific approaches and research methods were employed, including trend analysis of data, visualization tools from the World Bank, and modeling of business processes. The research yielded several key findings: an upward trend in the dynamics of container maritime transportation in the Russian Federation was identified over the first two decades of the 21st century; deficiencies in the information support of transport processes were uncovered; models of business processes for agency and chartering of maritime vessels were constructed; and the necessity for improvement and directions for modernization of existing vessel and cargo chartering information systems under modern conditions were substantiated. These findings indicate potential practical applications in the operations of transport and logistics companies.

SIMULATION MODEL OF THE FUNCTIONING OF THE LOGISTICS SYSTEM FOR THE SUPPLY OF GRAIN CARGOES FROM UKRAINE TO THE COUNTRIES OF THE WORLD

The article analyses the existing developments in the logistics of grain and similar cargoes in international systems. Due to the increase in logistics costs, Ukrainian agricultural companies receive a lower price compared to world market prices - they have to bear the costs caused by an inefficient logistics system. Therefore, it is necessary to develop a simulation model of the logistics system for the supply of grain cargo from the producer to the seaport of departure, as the main hub of communication with ports around the world. And the modelling will allow us to determine the level of influence of the obtained data on the transport material flow on the efficiency of decision-making. It is proposed to build models based on Petri nets, which allow to study the behaviour of an object in real time by assessing the performance of the system without forecast data. Today, the logistics system of grain cargo delivery in Ukraine has a structure based on the interaction of participants: agricultural companies as producers and organisers of grain exports, farmers, transport and logistics companies, as well as the existing infrastructure of Ukrainian and foreign ports, railways, and roads. This principle of interaction allowed us to build a structural model of functional interaction in the grain supply system. Based on this interaction and the principles of organising the supply of grain cargoes from production (harvesting) to the port of departure, a two-tier model of the functioning of this logistics system was developed. At the top are models of data collection and processing by an agricultural company, and at the bottom is a simulation model of the logistics system. A simulation model of grain cargo movement from the sender to the seaport of departure based on Petri nets has been built, which reflects the structure of relationships between the elements of the system and the dynamics of changes in its states in a compact form. On the basis of the built model, a simulation was carried out for three variants of distribution of cargo flow by two modes of transport. It has been determined that the option of uniform distribution of grain cargo between road and rail transport allows to save time.

Use of Unmanned Aircraft in the Logistics Support of Military Formations

The present development describes an experiment using an unmanned aerial vehicle (UAV) conducted at the Vasil Levski National Military University - the town of Veliko Tarnovo, and the purpose of the experiment is to determine the possibilities of using a drone in the logistical support of military formations of tactical level. The experiment was carried out in field conditions, and for this purpose a logistics company from the composition of a mechanized battalion was deployed in field conditions in rugged terrain. The drone used is a DJI MAVIC PRO 2.

Impact of global capabilities on performance in international logistics companies

PurposeIn order to make a difference in a globally competitive environment, companies should analyze their competitors, which is one of the factors around them, well, do research, observe the environment and know how to adapt. For this purpose, the research examines the effects of competitive intensity and marketing and sales capabilities, together with the global capabilities of logistics companies operating internationally (third-party logistics companies (3PL)), which are examined.Design/methodology/approachTo establish and test the model, a sample of 504 participants working at senior levels in internationally operating logistics companies (third-party logistics companies (3PL)) with their headquarters in Istanbul was taken and a scale consisting of a total of 32 statements was presented to them. Analyses were performed using Jamovi and SmartPLS 3.3.5. This program was used because, in addition to estimating path models with latent variables, it also calculated standard results evaluation criteria. First, the results of factor analysis are given. After these analyses were completed, the hypotheses were tested.FindingsThis research is supported by hypotheses as a result of the analysis that global capabilities are an important factor for logistics companies at the international level, and that the competitive intensity also affects the performance outputs and that marketing and sales capabilities also have an impact.Research limitations/implicationsSince data are collected from logistics companies operating globally, it is necessary to pay attention when the analysis results are compared with different sectors. Because the intensity of competition may vary depending on the sector and market in which companies operate. At the same time, the data were collected from authorized white-collar employees working at a senior level in logistics companies. Because, in terms of the level of being able to answer the questions about the variables examined in the research model, data were collected from high-level officials.Practical implicationsIt is getting harder and harder to compete on a global scale by going beyond national borders. The results of the analysis show how important the global capabilities of logistics companies are, especially the increasing importance of logistics activities for countries. For this reason, logistics companies operating on an international scale need to attach importance to the competitive intensity and develop their marketing and sales capabilities.Originality/valueThe research is original in that it examines the global capabilities of logistics companies in their international activities and the effects of competition intensity. In addition, it is important for companies in this sector to examine the effects of marketing and sales capabilities so that logistics companies can reach more customers in their international activities and be more effective in the market compared to their competitors.

Study on Stock Price Fluctuation of DHL after Cross-border Merger and Acquisition

In the 21st century, global logistics companies have launched a huge wave of mergers and acquisitions (M&A), including many international logistics giants launching crazy M&A to adapt to the expansion strategy of globalization. The cross-border logistics market is an extremely attractive cake in the logistics market, but the express delivery business in many low tier cities in many countries has long been dominated by many local enterprises, and its market has not been fully developed and does not meet international standards. The world has experienced five waves of M&A, and now this trend is affecting the development of DHL and has a significant impact on the evolution of the logistics industry. This article introduces the background of the topic selection, research objectives and significance, as well as the examination of whether M&A are necessary. This article uses the ARIMA-GARCH model to predict DHL's future stock price, and confirms the relationship and impact between its stock price and M&A behavior by comparing actual data. Based on the company's stock liquidity, the M&A effect is evaluated. The research results indicate that M&A can enable companies to quickly acquire the resources needed for development, generate synergies through integration, establish core competitiveness, and gain competitive advantages.