Smart Logistics Research Articles

The Rising Trends of Smart E-Commerce Logistics

Smart Logistics (SL) offers a competitive advantage for e-commerce by utilizing Information and Communication Technologies (ICT) such as IoT, AI, Blockchain, Cloud computing, 5G, etc. This technology automates, optimizes, and enables real-time tracking and monitoring of shipments, predicts, and prevents delays, and optimizes delivery routes and schedules. It also provides greater visibility and control, allowing e-commerce businesses to react quickly and efficiently to changes in demand or supply. The purpose of this study is to investigate the impact of digitalization on trade logistics in e-commerce, emphasizing the significance of smart logistics for the e-commerce industry. We reviewed 288 articles published in the last decade in the Scopus database to assess the maturity of research in this area. For researchers, this study provides a better understanding of smart e-commerce logistics and identifies research gaps in the literature. For e-commerce professionals, it can help them adopt the latest technological trends in their logistics. Through a systematic literature review and network analysis approach, the study has contributed by identifying 5 clusters related to ICT application fields in e-commerce and 5 clusters related to important ICT enablers in smart logistics. We also identified several research gaps and areas for future study, including the underutilization of computer vision technology and the need for further research on product quality inspection and accessibility for people with disabilities. Additionally, we suggest exploring the power of deep learning to solve Vehicle Routing Problems (VRP) and optimizing sensing data volume for minimizing costs associated with data storage and transfer. This study provides a comprehensive overview of the state of the art in smart logistics for e-commerce and serves as a guide for future research in this field.

Innovations financing risks in logistics companies

Introduction. The field of modern logistics cannot be imagined without innovative technologies, the implementation of which requires financial resources and is constantly associated with a number of risks. The purpose of the article is to analyze the risks of financing innovations and provide recommendations on reducing their impact on the activities of logistics companies. Method (methodology). The work uses general scientific research methods. The method of analysis and synthesis was applied during the study of factors that encourage logistics companies to introduce innovative technologies in their activities, the main ones of which are profit maximization, cost minimization, improvement of competitiveness and quality of goods and services, increase of speed and efficiency of work, adaptation to external challenges. The method of systematization and generalization was used to characterize the terms "Logistics 4.0" and "Smart logistics" and to provide examples of management, organizational and technological innovation solutions that are used within these categories. The methods of observation and comparison were used to analyze the innovations implemented in the activities of domestic and international logistics companies, namely: robots and cobots, automated unmanned shuttles and drones, the Internet of Things, cloud solutions and applications, blockchain, 3D printing, Digital Marketplaces, Digital Twins, augmented reality technologies. Examples of active implementation of innovation are shown on the examples of international and domestic logistics companies. Results. Factors on which the risks of financing innovations in logistics companies depend are given. It is proposed to consider the risks of financing innovations in logistics companies from three positions – from the side of logistics companies, their customers, and potential investors and creditors. It was determined that the main risks during the financing of innovations are the lack of own financial resources of the logistics company, errors in forecasting the demand for the innovative product, shortcomings in risk management, distrust of the innovative product, low qualification of labor resources, insufficient economic efficiency of the investment project, insufficient information and awareness among the participants of financing the innovation process, external factors. Recommendations are provided for minimizing the risks of financial support for innovations in logistics companies, the most significant of which are the diversification of sources of financial resources for innovative solutions; taking into account the economic feasibility of introducing innovations and information about the demand for them in the market; involvement of insurance companies; increasing requirements for personnel qualifications; taking into account the geopolitical and economic situation in the region; conducting regular monitoring of the effectiveness of the use of invested resources.

5G in Logistics 4.0: potential applications and challenges

The transition of logistics processes towards Logistics 4.0 (or Smart Logistics) – the specific application of Industry 4.0 in the logistics systems – contributes to the increasing need to establish reliable and efficient communication networks, to manage considerable amounts of data exchange between equipment, products, vehicles and workers. The combination of the Internet of Things (IoT), big data, cloud computing, and artificial intelligence, allows improvements and optimisation in many logistics processes, but claims for advanced stable real-time communication. The fifth generation of Mobile Communication Networks, the so-called 5G, has the potential to meet these requirements and substantially support the development of Smart Logistics. Through a systematic literature review, this paper aims to identify the main logistics areas and activities in which 5G can be implemented, pointing out the expected benefits and the related technologies that can boost its large-scale adoption. The literature review also allows identifying the main challenges that currently prevent the 5G adoption in logistics processes, suggesting future research directions.

Перспективи впровадження блокчейн-технології в транспортну логістику та управління ланцюгами поставок

The article, based on the account of features, advantages, varieties of blockchain, highlights its weaknesses and strengths in terms of implementation in transport logistics and supply chain management. The study of the external environment of the introduction of blockchain in the logistics industry has revealed the opportunities and threats that accompany this process in the modern economy of countries and may arise in the future. Based on structuring the research results on the strengths and weaknesses of blockchain technology, opportunities and threats of its implementation in the logistics industry, a SWOT analysis of this technology was carried out in terms of its use in transport logistics and supply chain management. As strategies that allow taking advantage of blockchain and taking into account the possibilities of the external environment, the development of intelligent transport systems (ITS) using blockchain together with its use in rail, sea and air international cargo transportation has been determined. Nine main strategies for the use of blockchain were allocated, which determine long-term benchmarks of activity at different institutional levels of the economy: micro, meso and macro levels. The proposed strategies are relevant in the context of using blockchain in the areas of urban and humanitarian logistics; logistics of meta- and meso-logistic systems of supply chains formed in the process of international trade; logistics of macro-logistic systems of countries and sectors of their economies; information logistics; financial and smart logistics and related to sectors of economies B2B, B2C, C2C, G2B, G2C, B2G. An integrated approach to the implementation of blockchain in the transport industry and supply chain management based on certain strategic benchmarks will allow the most measured implementation of the basic principles of the logistics management concept, such as transparency, efficiency, reduction of overall costs, confidentiality, trust, authentication, cooperation, integration, and optimization.

Overview of supply chain management challenges

Purpose: The article aims at presenting possible challenges faced by supply chains in the upcoming years. Design/methodology/approach: The article employs analysis of the literature on the subject. Findings: As a result of the critical analysis of the literature, the authors have highlighted what they consider to be the most significant challenges facing supply chain managers in the coming years. These include meeting increasing customer demands for on-time delivery, the skillful use of new technologies and an increasing emphasis on environmental issues in supply chain management. These are challenges arising from changes in the business environment. The last few years, and many examples of broken supply chains, have shown that changes in the way we think about how supply chains operate are required in many areas. Trends in the environment are forcing the challenges listed above to be addressed urgently. These challenges are closely interconnected. For example, changes in purchasing behaviour are also increasingly concerned with environmental issues, which translates into the need to 'green' supply chains. Also, customer expectations for greater visibility of processes in supply chains and increasing pressure to deliver as quickly as possible (which is linked to the growth of e-commerce), are driving the need for new technologies, including automation. Research limitations/implications: The authors have focused on the most important trends and challenges and the article certainly does not cover all the topics studied. It is to some extent a subjective selection made by the authors. In addition, it should be noted that dynamic changes in the environment may influence the emergence of new challenges that are not presented in the article. Practical implications: The supply chain management challenges presented in the article may be of interest to those responsible for the operations of supply chains within companies. Originality/value: The article is a subjective indication of the most important trends in supply chain management and stems from a review of the literature on the subject. Although the issues analysed are present in other research papers, here we have the authors’ choice. Keywords: supply chain management, smart logistics, GSCM. Category of the paper: Viewpoint.

Трансформація концепцій логістичного і проєктного менеджменту в контексті цифровізації та євроінтеграції

The paper is devoted to the essence of logistics, project, logistics and project management. The comparative analysis of the logistics efficiency index was carried out in Ukraine in comparison with the countries of the European Union, which made it possible to note its low values in our country both under martial law and in the pre-war period, as well as the components of this index (customs, infrastructure, international shipments, logistics competence and equality, timeliness, tracking and tracing). The consequences of the impact of digitalization on the transformation of logistics and project management, which are manifested in the reduction of time for information exchange, saving of resources and acceleration of all processes, have been determined. It was established that in the realities of the digital economy, increased risk and uncertainty, the Agile approach, smart logistics and electronic logistics are relevant approaches. The importance of increasing the adaptability and flexibility of management activity, which allows for ensuring the sustainable functioning of economic entities in conditions of high risk and uncertainty, rapid and unpredictable changes in the surrounding environment, is noted. The directions for improving logistics and project management in conditions of digitalization in the field of personnel support and human resources development (including the development of digital culture and digital skills, increasing the competence of personnel in the field of application of modern digital tools and information and communication technologies, minimizing the digital divide), financial and investment support, organizational support, material and technical support (including software products and technologies) and information security were carried out.

A Review of Industry 4.0 Maturity Models: Adoption of SMEs in The Manufacturing and Logistics Sectors

The purpose of this paper is to critically review the current available (large/SMEs) Maturity Models (MM) for Industry 4.0 (I4.0) adoption in manufacturing and logistics sectors, as well as recognize the specific requirements of SMEs for a MM adoption. In total, 16 MM were studied with various scopes, where 5 studies applied on SMEs. To this end, this paper identified manufacturing SMEs specific requirements, conducted a review of current MM, and identified the main MM scopes for SMEs and large enterprises as well. This study found that Smart Manufacturing, Smart Supply Chain (SC), Product Development, Digitized Data collection & Analytics, Technological Infrastructure, Smart Logistics, Performance Evaluation, and Employee participation are the main scopes used for SMEs.

DETECTION OF FOOD SPOILAGE USING IOT

Food safety plays important role in countries economy and human health. The integrated IoT-based online monitoring approach using smart logistics can address the critical needs of reducing food waste, increasing transportation efficiency, and tracking food contamination. Majority of consumers only pay attention to the ingredients used and their nutritional value. The parameters like humidity, bacteria, and temperature are major factors on which the rate of decomposition of food depends on. If the temperature of the storage is between 40F to 140F, it is a danger zone because, bacteria grow rapidly, doubling its number in 20 min. Similarly, the humidity in the food storage room should be around 50-55%.So in this IoT project, a Food Monitoring device is implemented to monitor the real-time values of the temperature, humidity, and methane gas, which are prime measures in food quality, will be measured and displayed.

Financial performance evaluation of Chinese smart logistics enterprises

Under the background of "Industry 4.0" and "Internet +" development, the intelligent logistics system is the only way for the development and transformation of China's logistics industry. However, at present, the scientific research investment and intelligent equipment purchase and repair costs of the smart logistics transformation of logistics companies is huge, and it is difficult to maintain the balance between the production cost and profit. Therefore, how to evaluate objectively, fairly and effectively the business performance of enterprises has become an urgent problem to be solved by China's smart logistics enterprises. Based on this, this paper selects the wisdom of 18 listed companies in the logistics industry financial performance evaluation, financial indicators and the financial indicators for soft, respectively from five different dimensions to establish index system, using the entropy method of objective evaluation, finally get the enterprise financial performance evaluation, and according to the industry situation put forward the corresponding policy Suggestions.

Research on Coordinated Development of Smart Logistics System of Agricultural Products in Beijing-Tianjin-Hebei under the Background of Big Data

Research on Coordinated Development of Smart Logistics System of Agricultural Products in Beijing-Tianjin-Hebei under the Background of Big Data

Retracted: Evaluation System of Smart Logistics Comprehensive Management Based on Hospital Data Fusion Technology.

[This retracts the article DOI: 10.1155/2022/1490874.].

Research on the Development Direction of Smart Logistics Based on Blockchain Technology

Blockchain was only applied into underlying technology of Bitcoin system in the past. After years of development, its applications have been expanded to fields such as logistics, supply chain, finance, medical health, and public affairs. E-commerce expands globally, which brings opportunities and challenges caused by blockchain technology to logistics industry, a critical hub for online e-commerce and offline users. However, in China, logistics industry faces problems namely high costs, inefficient information exchange, and poor performance. Therefore, future intelligent logistics transformation depends on multi-party collaboration. With aid of deep integration of blockchain technology, it is able to trace source, cut down intermediate links, ensure secure goods delivery, and improve logistics efficiency.

Artificial Intelligence in Smart Logistics Cyber-Physical Systems: State-of-The-Arts and Potential Applications

Logistics creates tremendous economic value through supporting the trading of goods between firms and customers, thereby improving the welfare of the society. In order to continuously improve the quality of logistics service, a great variety of cyber-physical techniques have been utilized in the modern logistics systems, which help tackle the grand challenges in multiple aspects including time efficiency, economic cost, safety risk and cyber-security. The fast development of artificial intelligence (AI) has gained significant popularity and success in various domains, and hence, it has been adopted to construct high-quality solutions that can facilitate the monitoring, operation and decision in logistics systems. Furthermore, the deployment of advanced sensoring and computing components forms a cyber-physical system (CPS) infrastructure, which promotes the capability and scalability on data acquisition, transmission, storage and processing, thereby enabling the further penetration of AI technologies. Based on the existing advances, this paper is devoted to conducting a comprehensive survey of the AI applications in the modern logistics CPSs. In specific, we focus on the AI-based research and industrial solutions that can improve the time/economic efficiency, safety and cyber-security of logistics systems. The potential applications of AI to tackle the remaining challenges are also discussed to investigate the way to continuously improving the quality of logistics service.

Machine Learning Based Logistic Decision Support System for Intelligent Vehicles and Transportation Systems

One-third of the freight expense is spent on transportation and transport networks, thus significantly impacting the logistics sector's efficiency. Artificial Intelligent logistics strategies are designed to alleviate the impact on metropolitan areas exacerbated by increased freight transport. The city of logistics is widely employed as a modern study area, has a significant social and economic influence, and has extensively explored the key elements and components. Most recent experiments concentrate on traffic management and logistics monitoring, even though no research studies have tried to detect drivers' distractions. Since drivers are one of the major parts of logistic service, this study incorporates existing logistics DSS with the cognitive model for predicting driver distraction. This paper presents a Machine Learning Integrated Decision Support System (MLIDSS) architecture and core components based on simulationoptimization modules to assist the smart logistics DSS with an eye to service delivery driver distraction level. The ML algorithms perform real-time driver distraction predictions for smooth logistics transportation. The viability of such a transportation system is often illustrated in the real world. The findings result in the highest-performing intelligent decision support system compared to existing models.

Application of AI and ML in the Field of DevSecOps

Security is a paramount concern in DevOps. The adoption of Infrastructure as Code (IaC) has increased the potential impact of even minor flaws, particularly in critical domains like healthcare and maritime applications. Existing solutions typically focus on either Static Application Security Testing (SAST) or run-time behavior analysis. This paper introduces the IaC Scan Runner, an open-source tool developed in Python for inspecting various IaC languages during application design, and LOMOS, a run-time anomaly detection tool. Both tools work together to enhance the security of DevOps processes. In today’s rapidly evolving technological landscape, the vulnerability of infrastructure and applications is growing due to a combination of factors. Attackers are becoming more sophisticated, leveraging improved intelligence to exploit weaknesses. At the same time, there is a lack of technical capability in many organizations to effectively secure their systems. This paper explores a dual approach to cybersecurity: static security monitoring through rule matching and the application of self-supervised machine learning. By combining these approaches, organizations can better defend against cyber threats. One area of focus is supply chain resilience and smart logistics, where the integration of these methods is particularly critical. This approach emphasizes a self-learning and self-healing approach, allowing systems to adapt and respond to new threats autonomously. Integrating Artificial Intelligence (AI) and Machine Learning (ML) into DevSecOps practices is essential for improving security, efficiency, and innovation in software development and deployment. This paper delves into strategies and best practices for leveraging AI/ML within the DevSecOps framework. It discusses automated threat detection, predictive analytics for vulnerability management, and intelligent automation for continuous integration and deployment. However, this integration also presents challenges, such as data privacy, algorithm transparency, and ethical implications. The paper addresses these challenges and showcases how organizations can use AI/ML to optimize their DevSecOps pipelines, mitigate security risks, and foster continuous improvement. The adoption of Infrastructure as Code (IaC) has increased the potential impact of even minor flaws, especially in critical domains like healthcare and maritime applications. Existing solutions typically focus on either Static Application Security Testing (SAST) or run-time behavior analysis.

SELECTING SUSTAINABILITY KEY PERFORMANCE INDICATORS FOR SMART LOGISTICS ASSESSMENT

The application of smart technologies and applications is becoming increasingly common in the logistics processes of companies and supply chains. However, standard logistics indicators are still used to evaluate their performance, which contradicts the sustainable development strategy of many industrial enterprises and their supply chains. Thus, the article aims to design a methodology for selecting sustainability key performance indicators (SKPIs) suitable for assessing smart logistics and its technologies and applications. The research relies on cluster analysis of the SKPIs recommended in the relevant literature, frequency analysis of indicators used in practice and their comparison. The cluster analysis showed that the primary attention in the references is given to sustainability’s economic and environmental dimensions. Most frequently, the authors highlighted the importance of the following indicators: production-related costs and investments, planning performance and quality, customer satisfaction, energy efficiency, waste intensity and treatment, emissions, and resource efficiency. On the contrary, the frequency analysis corroborated that leading industrial enterprises paid more-or-less balanced attention to all areas of sustainability, but at the company level. The article’s primary result constitutes a methodology comprising six steps, respecting the results of the analyses carried out: (1) Sustainability objectives definition; (2) Establishing SKPIs cluster pool; (3) Definition of criteria for selecting SKPIs clusters; (4) Selection of SKPIs clusters; (5) Definition of SKPIs and their parameters; and (6) Development of SKPIs hierarchical structure.

Autonomous vehicle path planning for smart logistics mobile applications based on modified heuristic algorithm

In this study, a heuristic algorithm is used to find an optimal route for smart logistics loading and unloading applications. Various environments, such as traditional building blocks, satellite images, terrain environments, and Google map environments are developed by converting into a binary occupancy grid and used to optimize the viable path in the smart mobile logistics application. The proposed autonomous vehicle (AV) route planning navigation approach is to forecast the AV’s path until it detects an imminent obstacle, at which point it should turn to the safest area before continuing on its route. To demonstrate the path navigation results of proposed algorithms, a navigational model is developed in the MATLAB/Simulink 2D virtual environment. The particle swarm optimization (PSO) method, the Bat search algorithm, and its proposed variants are used to identify a smooth and violation-free path for a given application environment. The proposed variants improve the algorithm’s effectiveness in finding a violation-free path while requiring less time complexity by using cubic spline curve interpolation and its improved constriction factor. Extensive simulation and benchmark validation results show the proposed standard PSO has a significantly shorter violation-free path, quick convergence rate and takes less time to compute the distance between loading and unloading environment locations than the cooperative coevolving PSO, Bat algorithm, or modified frequency Bat algorithms.

What Prevents Sustainable Last-Mile Delivery in Industry 4.0? An Analysis and Decision Framework

Industry 4.0 (I4.0) has revolutionized every sector in the last decade. A huge demand has been created in the supply chain for doorstep delivery services. However, many barriers are hindering the progression of I4.0 implementation to last-mile delivery (LMD) operations. In this study, these hindrances need investigation for improving customer satisfaction levels in LMD. The present research is focused on analyzing barriers to adopting I4.0 technologies for sustainable smart supply chains with a special focus on LMD operations. The published literature is critically investigated to determine the crucial factors which are acting as barriers to I4.0 implementation in LMD. The interpretive structure modeling (ISM) approach is adopted to evaluate different levels with their hierarchal order for analyzing the I4.0 barriers to digitalized logistic networks. Delivery capacity emerged as the major barrier to LMD operational networks due to insufficient technological and hardware support for I4.0 cyber-physical systems in logistics. Infrastructure for I4.0 emerged as the most basic requirement for the smart logistics management criteria for efficient LMD. The need to adopt I4.0 technologies for developing inventory hubs and warehouse management has evolved recently. There is scope for customized and specific case studies for the supply chain to achieve a higher level of sustainability. A conceptual framework for a smart and sustainable supply chain is presented and future directions for sustainable LMD are discussed.

An Improved IoT/RFID-Enabled Object Tracking and Authentication Scheme for Smart Logistics

An Improved IoT/RFID-Enabled Object Tracking and Authentication Scheme for Smart Logistics

End-of-life fishing gear in Spain: Quantity and recyclability

European Commission has approached the challenge of End-Of-Life (EOL) fishing gear and Abandoned, Lost, or otherwise Discarded Fishing Gear (ALDFG) by focusing on circular economy. Current directives highlight the need to provide a proper management to EOL fishing gears, fostering their separate collection, transport, and treatment from a circular perspective. They also request Member States to set collection and treatment targets. However, this is far from being widely implemented in a coordinated manner. In the quest to explore the Spanish case, this contribution aims at providing insights on the amount and type of EOL fishing gear and management practices carried out in different Spanish ports, as well as recycling options for such gears. Data was collected through an online survey, interviews to stakeholders, and visits to ports. Composition, degradation and mechanical recyclability of EOL samples were assessed. Yearly, 1643 tonnes of EOL fishing gear (mainly nets) are discarded in Spanish ports from trawling (97.5%), gillnet/trammel nets (2.3%) and purse seine (0.2%) fisheries. High-density polyethylene (from trawling nets) is the most common discarded polymer, followed by polyamide 6 (from gillnets/trammel net and purse seine nets). EOL fishing gear management is diverse in Spain as it depends on the nature of the port (who governs it, either regional or national govern), special agreements between local fishers’ guilds and waste managing companies, the waste managers in port, etc. Polyamide nets are degraded but in good condition to be recycled mechanically; for trawl nets chemical recycling is more suited due to their degraded state. Currently, few recycling companies exists in Spain that are engaged on mechanical recycling of EOL fishing gears, none in chemical recycling. Therefore, a more comprehensive analysis, coordination, and smart logistics are needed to make the collection and recycling of EOL fishing gear possible.