Digital Technique-Enabled Container Logistics Supply Chain Sustainability Achievement

Abstract

With the rapid development of digital technology, the smart sensor-based container equipment and intelligent logistics operations contribute to achieving the efficiency improvement and sustainability achievement of container supply chain under the IoT-based logistics 4.0 scenarios. This paper tries to study the state-of-the-art knowledge of the container logistics supply chain management motivated by digital techniques. Through data-driven analysis this review is performed to assist researchers and practitioners to better understand the container logistics management. The integrated research framework is designed by developing a bibliometric analysis study to address the research themes of the container logistics era. The related publications from the Web of Science database from 2003 to 2022 were indexed and 2897 reference samples are collected as the research data. In addition, the VosViewer is adopted to portray the network, co-occurrence, and co-word analysis by visualizing the collaborative relationships of collected samples. The results show that digital technology has been widely applied in container logistics supply chain management practices, contributing to resilience and sustainability improvement by intelligent operations. These research findings are also helpful for researchers by providing a deep penetrating insight into research opportunities and great potentials of container logistics supply chain by innovative digital technology-enabled practices.

1. Introduction

With the rapid development of the logistics industry and the continuous expansion of global trade, container transportation, as one of the main modes of modern cargo transportation, has become closely related to our daily lives and is gaining increasing attention [1,2]. The international shipping transportation mode plays a significant role in worldwide trading, which accounts for 80% of international trade volume. Due to the increasing volume and rapid development of container transportation, container liner transportation, as one of the three major sea transportation methods, has become an important component of world trade goods transportation due to its low transportation costs and the agile ability to connect different transportation methods, which undertakes more than 70% of international industrial supplies and general consumer goods transportation [3].

Driven by the rapid development of digital transformation and internet-based technology, the continuous innovation of information technology has also brought new opportunities to container transportation, contributing to container logistics supply chain (CLSC) innovations [4,5,6]. In recent years, the large-scale development of container liners and the advancement in information technology have further expanded international trade worldwide, leading to a rapid growth in global maritime container traffic. The global container traffic had reached over 20,100,000 TEUs (twenty-feet equivalent units) in 2022. At the same time, with the rapid growth of containerized shipping traffic, the carbon emission issue has also arisen. Likewise, it shifts our eyes to focus on the sustainable development of container logistics operations due to current global warming issues [7]. Faced with the escalating climate crisis, the international authority organization believes that the shipping industry lacks the driving force to respond to climate change. According to the International Maritime Organization (IMO), the global shipping industry’s carbon dioxide emissions exceeded 1 billion tons in 2022, accounting for approximately 2–3% of global emissions, and it will continue to have a growing trend. Based on the current economic development trend, it is estimated that the growth rate will reach from 50% to 250% by 2050 [8]. Therefore, it is imperative to implement environmentally sustainable development approaches for the container shipping industry by strictly controlling ship emissions and innovative management practices [9].

The 80th Marine Environment Protection Committee meeting, which was held by the International Maritime Organization in July 2023, revised the emission reduction strategy for the maritime industry [10]. By 2030, the global greenhouse gas emissions from the maritime industry will be reduced by at least 20% compared to 2008, and efforts will be made to achieve the 30% emission reduction target. By 2040, it will reduce emissions by at least 70%, strive to achieve the 80% emission reduction target, and promise to achieve net zero emissions by 2050 at the latest. With various environmental protection policies and emission reduction regulations, problems such as rising oil prices and fluctuating transportation capacity in container transportation have emerged one after another [11]. At the same time, the lack of technological innovation has led to the brutal growth of industry efficiency, organizational management, disorderly competition, and monopoly, which have gradually become prominent. The container transportation industry urgently needs to break through. During the IOT-based industry 4.0 era, technological innovation is the primary productive force, and advanced information technology has brought new possibilities for container transportation and supply chain management [12,13]. Digital technology, such as 5G, cloud computing, blockchain, and artificial intelligence, drives the upgrading and promotion of container supply chain management under the logistics 4.0 era [14,15].

Based on this background, this article will focus on the latest knowledge and research topics on CLSC management driven by digital technology through conducting a bibliometric analysis study. This research aims to present the state-of-the-art development of container logistics by learning from existing published references, as well as the recent operations management practices of the container supply chain. In addition, the research spots are investigated by implementing bibliometric analysis, which helps academic researchers to find research opportunities in related areas. Another purpose of our research is to assist in providing some guidance for industrial practitioners on CLSC management, which probes into insights on sustainability improvement for the container transportation industry from long run.

The rest of this paper is structured as follows. Section 2 presents the theoretical background of container logistics supply chain and digital technology. The research methodology and research design are proposed in Section 3, including research data, bibliometric study method, and research framework. Section 4 discloses the research findings and visualization of the collected research samples, and the research themes are summarized. Finally, we end this paper with conclusions.

2. Theoretical Backgrounds

This section describes the theoretical background of digital technologies and their industrial applications. In addition, the current status of container logistics and supply chain management practices are also presented to help better understand the industrial background of this area.

2.1. IoT-Based Container Logistics 4.0

Containers have advantages such as high efficiency, high quality, high capital density, specialization, and standardization, and their application in the logistics industry has broad prospects for development. The development of container transportation logistics reflects the degree of industrialization and modernization of a country [16]. Modern container logistics mainly involves multimodal transportation through various means such as public transportation, rail transportation, and sea transportation. The healthy competition among logistics systems composed of shipping companies, port companies, and railways promotes the development of China’s container logistics industry [17]. In addition, the comprehensive promotion of the leapfrog development strategy of railways has created a good market environment for China’s container transportation, promoting significant development in China’s container transportation. In 2003, the throughput of container ports in mainland China jumped to the top in the world. Since 2007, China’s container transportation industry has become mature, forming six major port clusters including the Pearl River Delta, Southeast Coast, Southwest Coast, Yangtze River Delta, Yangtze River Basin, and Bohai Rim [18]. In 2020, China’s coastal ports completed a throughput of 248 million TEUs, ranking among the top in the world [19]. At the same time, due to the impact of the epidemic, it is difficult to find a single container globally, and the shipping cost of containers has rapidly increased [20]. China’s container logistics have developed rapidly. At present, container transportation in China has become an important component of international logistics and plays a crucial role in global port transportation [21]. To promote the further development of container logistics, the introduction of blockchain technology with features such as decentralization, smart contracts, and traceability is aimed to solve the current logistics problems of containers.

The China Railway Group has disclosed that China–Europe trains operated a total of 1410 trains and transported 1.47 million TEUs in January 2023, with year-on-year growth of 6% and 13%, respectively. The railway department has expanded the domestic transportation capacity of the China–Europe freight train by an additional ton, with an average increase of about 8% in the container shipping capacity of a single China–Europe freight train [22]. Port operations have been optimized and adjusted, greatly improving the customs clearance efficiency of the China–Europe freight train. Among them, the number of China Europe trains operating in Yiwu reached 240, and the freight volume passing through the Alashankou Railway Port reached 1.114 million tons, and a year-on-year increase of 12.8%, ensuring the smooth flow of international logistics.

Due to the frequent outbreaks of domestic epidemics and the Russia–Ukraine conflict, China’s container multi-modal transport industry and the China–EU trains are increasingly resilient to adversity [23]. The port container throughput and the volume of sea rail inter-modal transport containers are growing steadily on the whole. The continuous growth in sea rail inter-modal container volume and the rapid recovery of China–Europe freight trains have ensured the stability of domestic and international supply chains. Due to the good development of multi-modal transportation by multiple port enterprises, national ministries are gradually supporting the development of multi-modal transportation [24]. Local governments and enterprises in various regions jointly promote the development of multi-modal transportation, enabling China’s multi-modal transportation to embark on a stable and rapid development path. Multi-modal transportation is a guarantee for the security and stable development of the supply chain [25]. To this end, the industry must unite and cooperate to find a path for the development of multi-modal transportation with Chinese characteristics.

During the process of increasing globalization, China’s freight container ports have developed rapidly [26]. The significant increase in container throughput and transportation volume has driven the rapid development of China’s container logistics transportation industry. At the same time, container logistics also face development challenges. When there are abnormalities in a container, it is difficult to monitor it. The emergence of multi-sensor information technology can monitor the abnormal status of containers. Multi-sensor information technology utilizes multiple sensor monitoring nodes in the container to form an effective network, which not only senses and acquires data from each node, but also processes and fuses the collected data. It optimizes information judgment through the connection and fusion of sensor information, and ultimately monitors an abnormal situation in a container and provides early warning. By applying multi-sensor information fusion technology to monitor the abnormal status of containers, real-time data can be obtained, and the status information of containers can be more accurately and comprehensively grasped. This enables real-time and accurate monitoring and warning of abnormal status in containers, ensuring the safety of goods, reducing damage, and improving the safety of container logistics transportation [27].

2.2. Container Supply Chain Management

Driven by digital technology and IOT-based techniques, the container supply chain tends to the higher integration and efficient management of various links and data in the container supply chain practice [28]. Digital technology and information systems are adopted to achieve full process monitoring, data sharing, and intelligent decision making in container transportation, improving transportation efficiency and management level [29,30].

With the continuous development of enterprise scale, the number of types of goods in logistics and supply chain management is constantly increasing, and the frequency of inbound and outbound operations is sharply increasing [31]. Container supply chain management has become very complex and diverse, and traditional manual warehouse operation modes and data collection methods are no longer able to meet the fast and accurate requirements of warehouse management, seriously affecting the operational efficiency of enterprises. Therefore, it is urgent to build an intelligent warehouse management system to improve logistics efficiency by warehouse space re-utilization and reasonable labor allocation [32]. In order to achieve effective optimization of human resources, equipment utilization, logistics, and supply chain management are used to improve the core competitiveness of the enterprise. Aslanzade developed an intelligent decision-making framework to evaluate the social responsibility level of container supply chain management [33]. Jeong, Y. formulated an integer linear programming model to implement an empty container management strategy, and the proactive measures were proposed to ensure container supply in high-risk areas [34].

Digital containers play an important role in global logistics, as they can provide many advantages and promote improvement in logistics efficiency and sustainability [35,36]. The efficiency and sustainability of global logistics is obviously improved by employing digital containers, which is achieved by real-time information sharing, transportation plan optimization, and paper-based work reduction. They have introduced more intelligent and data-driven elements to the logistics industry, driving innovation and development in logistics business [37,38]. Digital container supply chain management can also improve the transparency and flexibility of the supply chain, reduce errors in information transmission and operation, optimize resource utilization and reduce waste, improve transportation efficiency, and reduce costs [39]. At the same time, it can also provide better decision-making support and risk management capabilities, providing more accurate and timely information and analysis for enterprise strategic planning and operational decision making [40].

2.3. Digital Technology

With the continuous development of internet technology and the arrival of the era of digital economy globalization, performing innovations by adopting digital techniques is inevitable [41]. The development of the digital economy has become inevitable [2,42]. The digital economy is mainly a new form of economic development based on information technologies such as big data, blockchain, and artificial intelligence. As a new economic format, the digital economy can achieve cross time, space penetration, and dissemination of digital technology [43]. The application of digital technology among enterprises can achieve integrity in enterprises, and the information sharing and construction of a blockchain can achieve stable and sustainable development in the social economy.

The supply chain system in the digital era emphasizes the activation, empowerment, and risk prevention of the physical supply chain through supply chain finance [44]. Intelligent supply chain finance, supported by digital techniques, has penetrated into industrial chain trade scenarios and business transactions, which helps to pressure a reduction in subject credit, efficient monitoring of business capabilities, and effective supervision of business operations. In addition, it assists in achieving closed-loop monitoring of the entire supply chain system. Considering the traditional supply chain model will be replaced by digital ecosystems, it is critical for enterprises to create added value by incorporating digital ecosystems into the organizational economy [45].

With the continuous expansion of the application of digital technology, the application of digital techniques has penetrated into various aspects of containers logistics and supply chain processes, including logistics transportation, warehouse management, cargo handling, distribution network, and container port [46]. These digital techniques, including RFID technology, sensor technology, cloud computing technology, big data analysis technology, etc., have been widely adopted in supply chain practice in the industry 4.0 era. With the continuous development of digital technology, more and more logistics enterprises are beginning to realize the necessity and importance of digital transformation [47]. Digital logistics platforms are constructed by integrating digital techniques, and digital logistics are innovated to help firms achieve efficiency improvement and better service. For example, artificial intelligence will be applied to optimize and intelligently schedule logistics distribution routes, blockchain technology will be applied to encrypt and share logistics information, and intelligent logistics equipment will be widely used.

At the same time, digital containers play an important role in global logistics, effectively promoting improvement in logistics efficiency and sustainability [2]. The intelligent container and digital operations contribute to efficiency improvement in logistics activities. Digital containers can be equipped with various sensors and communication devices to monitor the location, status, and environmental conditions of a container in real-time. This makes the transportation process of goods more transparent, allowing logistics companies and customers to keep track of the real-time location and status of goods at any time, reducing the risk of loss and damage to goods. By collecting and analyzing data, digital containers can provide logistics companies with real-time information about cargo transportation [48]. This is beneficial for optimizing transportation plans, improving air or repeat transportation, reducing logistics costs, and resource utilization. Digital containers can help to predict the tax time of goods and avoid congestion through intelligent route planning and coordination, thereby reducing the allocation time at transit stations and ports. In addition, digital devices can help to achieve real-time monitoring and anti-theft functions, effectively preventing the risk of goods being stolen or damaged through technologies such as GPS positioning, seals, and security sensors. Digital containers also provide a platform for sharing information among different logistics participants, including manufacturers, suppliers, logistics companies, transportation companies, etc. This helps to improve cross-border cooperation and information exchange, promoting harmonious operation of the entire supply chain [14].

3. Research Design

This review analysis is conducted by adopting bibliometric study, and the cooperative publication visualization is presented to help better understand the evolutionary process of container logistics area. Furthermore, the research design, as well as the data samples, have been proposed, which facilitates the investigation of the CLSC practices driven by digital technology.

3.1. Data Sources and Reference Collection

Previous publications related to the CLSC topic were collected to be the research samples. For better understanding of the state-of-the-art of this topic for academia, the Web of Science database was selected to be the database for further analysis, which was crucial for accessing global academic information [49].

To ensure the accuracy and comprehensiveness of the relevant literature retrieval, and to avoid literature omissions and false detections, it was necessary to select search terms that could comprehensively describe and accurately reveal information related to CLSC driven by digital technology. Therefore, the following four steps were proposed to determine the relevant search terms for digital technology-empowered CLSC management.

Step 1

Initial keyword selection. Based on the research title “digital technique-enabled container logistics supply chain”, we found that “digital technique”, “container logistics”, and “container supply chain” could be regarded as the initial selection words for literature retrieval.

Step 2

Expand the range of keyword indexing. We needed to make sure that the main journals and references related to the research topic occurred in the indexing results. In addition, the textual words that clearly describe the research topic could be the extended keywords based on the title, abstract, chapter names, and professional terminology that initially occurred in indexing results, such as “green container supply chain”, “sustainable port”, “Blockchain”, “IoT”, and “maritime transportation”.

Step 3

Remove irrelevant keyword search terms. The irrelevant research items and publications should be removed based on the indexing results through the expanded keywords searching. In this stage, the irrelevant expanded keywords needed to be identified and removed, such as “telecommunications”, “automated control”, and “container manufacturing”.

Step 4

Repeat Step 2 and Step 3 until the searching results fully meet the review study requirements of the objective research topic. In other words, the comprehensive literature samples could be retrieved in the research data sample.

To perform the bibliometric study, the searched references based on expanded keywords were collected to be the data sample. In order to further understand the state-of-the-art of CLSC management, more than 4402 authoritative and high-quality academic papers worldwide were collected in the fields of engineering science, social sciences, arts, and humanities. A total of 2897 research papers published during 2003–2023 were indexed as the review research sample.

3.2. Bibliometric Review Study

The collected references were regarded as the research sample for the bibliometric study. To help better understand the massive references collected from the WOS database, and excavate strategic insights on CLSC management, the bibliometric analysis approach was employed to investigate the state-of-the-art knowledge in this area.

Bibliometric analysis is a quantitative research method based on the statistical study of collected references and has been widely used for structural overview studies in certain fields [50]. The collected references are reviewed, summarized, and portrayed in academia to better understand research opportunities and state-of-the-art knowledge in related research areas. In addition, it also facilitates industrial managers to probe into research hotspots, which provides insightful guidance for industrial practices. Statistically, bibliometric analysis has been applied to different industry sectors, contributing to finding research trends, challenges, and opportunities in certain area [51]. Therefore, this study tries to disclose the state-of-the-art knowledge of CLSC development by performing a bibliometric analysis.

To help better discover the hot topics of the related area, a visualization study was conducted to perform a systematic analysis under the assistance of the VosViewer, a free Java-based software developed by the Technical Research Center of Leiden University in the Netherlands [52,53,54,55]. The similarity index, Similarity (A, B), was defined to reflect the correlation intension and overlap degree of each two items. The similarity index was non-negative and its value range satisfied $Similarity\left(X,Y\right)\ge 0$ for every two items. In addition, the similarity index formula has a symmetry feature, that is $Similarity\left(X,Y\right)=Similarity\left(Y,X\right)$, which means that these two objective items have no similarity or overlapping topic when $Similarity\left(X,Y\right)=0$ [56]. The similarity value was calculated and portrayed by the VosViewer software using the spacing distance in a realized two-dimensional figure, facilitating a better understanding of the research spots. This graphical ability, as a powerful analysis tool, facilitates the display of complicated evolutionary correlations and cross-over relationships among different knowledge groups.

3.2.1. Co-Word Analysis

Co-word analysis, proposed by Turner and Callon, has been widely used to disclose research spots in the objective field with great advantages [57,58]. It facilitates researchers and practitioners to better understand certain research areas by identifying key words and overlap degree. In addition, it can display a hierarchical clustering of representative items by this kind of content analysis method, which contributes to revealing the complicated interactions and cross relationships among items. Co-word analysis has great potential in investigating research opportunities and overlapped research teams in different fields.

To perform the co-word analysis, the VosViewer clustering analysis was adopted to portray the co-occurrence network diagram of collected keywords. In addition, the evolutionary process of CLSC was also presented, which facilitated the identification of the overall development tendency and research opportunities of this area.

3.2.2. Network Analysis

By comparing the co-word analysis focused on research items and keywords, network analysis is another effective research method, concentrating on cooperative interactions between researchers and affiliations in certain research area. Social network analysis was first proposed and applied in psychology research, which is widely used in other fields [59,60]. Regarding its use as an effective data mining tool in the massive literature, a network of keywords, organizations, and nations are categorized and analyzed by exploring the complicated relationships, wherein objective items are presented by nodes. Network analysis can help provide an overall overview of digital technologies and application scenarios. In addition, the co-occurrence analysis on key words with high-frequency in the collected samples could contribute to the discovery of research spots and recent development in container logistics area. The network study could also be performed by the VosViewer software through statistics analysis of the collected references, which probes into insightful ideas for researchers and practitioners from both micro and macro viewpoints.

3.3. The Proposed Research Framework

This research conducts a bibliometric study by addressing previous publications in the digital technology-enabled CLSC area, and related publications in the Web of Science (WOS) database are regarded as the objective research samples. The proposed bibliometric analysis framework is developed in Figure 1.

As Figure 1 illustrates, the review study was designed and the bibliometric analysis was performed to help scrutinize the CLSC practice driven by digital technology. Firstly, the theoretical backgrounds of CLSC practice and digital technologies were reviewed to elaborate the current status of related areas. It was obviously common that digital technology could help promote the performance of container logistics operations and supply chain services through the literature review. Secondly, the bibliometric study was employed and presented to discover the complex interactions and network visualizations of digital technology-enabled CLSC using the VosViewer software. In addition, the reference source and objective database were addressed, as well as the detail implementation steps. Finally, the statistics analysis was portrayed through a visualized diagram, and the research topics were summarized to help related researchers and practitioners better understand the state-of-the-art of digital technology-empowered CLSC practices. The research hotspots and research themes were also highlighted, which aimed to help probe into insights on research opportunities in CLSC management.

4. Research Findings

4.1. Overview Analysis Results

4.1.1. Source-Level Analysis

To analyze container academic research papers, we collected 4402 relevant papers from Web of Science’s core database by searching keywords such as “container logistics”, “container supply chain”, and “digital technology”. After de-duplicating and cleaning the reference data, 2897 valid papers were obtained and regarded as research samples. From Figure 2, we found that academic research on containers began in 2003 by retracing the collected literature. Between 2003 and 2017, the related research was in the early stage of development and grew steadily but slowly. In 2018, the related research ushered in a period of rapid development, and it has maintained a growth rate with new breakthroughs compared with the previous stage.

The results of the double-plot overlay of the journals show the position of the research in this topic relative to the main research disciplines [61]. Each point on the map represents a journal, and the map is divided into two parts, the citing map on the left and the cited map on the right. Curves are citation lines, which fully show the ins and outs of citations. The overlay of journals in the field of containers is shown in Figure 3.

In the figure on the left, the ellipse represents the number of publications corresponding to each journal and shows the ratio of authors to publications, the length of the ellipse represents the number of authors, and the width of the ellipse represents the number of publications (the more papers a journal publishes, the longer the vertical axis of the ellipse; the larger the number of authors, the longer the horizontal axis of the ellipse) [62]. The curves between the left and right parts of the map are citation links, and the trajectory of these links provides an understanding of the interdisciplinary relationships in the field. The z-Scores function highlights stronger, smoother trajectories, with higher scores represented by thicker connecting lines. In this case, publications in Mathematics, Systems, and Mathematical (red track) are influenced by the publications in the following areas: systems, computing, computers (z = 8.64, f = 7052), economic, politics (z = 4.52, f = 3826), psychology, education, and social science (z = 2.1, f = 1936).

The overlay plot shows that there are two areas that are relatively active in the citation graph, namely computer science and information science. Common journals in the computer field include the European Journal of Operational Research, Transportation Research Part E, Ocean Engineering, etc. Journals in the field of information science include Risk Analysis, Industrial Management and Data Systems, and IEEE Transactions on Engineering Management.

4.1.2. Author-Level Analysis

The top 10 organizations that published the most papers in the related fields are shown in

Table 1. Top 10 organizations in sample publications.

Organization	Country	Papers
Shanghai Maritime University	China	98
Norwegian University of Science and Technology	Norway	89
The Hong Kong Polytechnic University	China	78
Dalian Maritime University	China	75
Wuhan University of Technology	China	72
Istanbul Technical University	Turkey	56
National University of Singapore	Singapore	50
Nanyang Technological University	Singapore	37
Liverpool John Moores University	UK	33
Aalto University	Finland	31

. It can be seen from Table 1 that 4 of the top 5 organizations are from China, and the number of articles published in China far exceeds that of other countries, which shows that China attaches great importance to containers and their applications.

Table 2. Top 10 countries in container-related research.

Country	Published Papers
China	791
USA	413
UK	205
Germany	175
South Korea	151
Norway	139
Italy	128
Canada	120
Singapore	105
Australia	103

presents the top 10 countries in container research by the number of publications. China ranked first with 791 papers produced, followed by the United States and the United Kingdom. However, the number of publications in China even exceeds the sum of the United States and the United Kingdom. China’s research in the field of containers far exceeds that of other countries, which is closely related to China being a major exporter in the world and the Silk Road policy. The global distribution of container publications shows that scholarly research on containers is being published in various regions of the world.

In order to understand the degree of cooperation among countries in containers, the cooperation of 61 countries was compared and analyzed, the top 30 countries in terms of cooperation intensity were selected for visualization, and the results are shown in Figure 4. The larger nodes in Figure 4 indicate a larger number of joint publications, and the thicker connectors indicate a greater number of joint publications between the two countries.

Figure 4 shows the cooperation network map of the top 30 countries in terms of cooperation intensity. It can be seen from Figure 4 that China has the highest cooperation intensity with other countries (the highest cooperation intensity is 390), and it forms the five countries with the highest cooperation intensity with the United States, the United Kingdom, Canada, and Norway. In addition, we observed that China cooperates most closely with the United States, the United Kingdom, and Singapore.

About the number of publications among countries yields, we found that among the top 30 countries in terms of intensity of cooperation, European countries accounted for the majority, followed by Asia and North America. It is not difficult to see that relevant research in the field of containers has swept the world. With the stabilization of the epidemic and the recovery of production, countries should strengthen cooperation and strive to explore new directions for the development of containers.

4.2. Network Analysis Results

4.2.1. Literature Analysis

Table 3. Highly cited papers in container-related research.

Item	Journal Name	Theme	Source	Total Citations
1	OR Spectrum	Container terminal operation and operations research—a classification and literature review	[63]	869
2	OR Spectrum	Operations research at container terminals: a literature update	[64]	722
3	Transportation Science	Ship routing and scheduling: status and perspectives	[65]	459
4	European Journal of Operational Research	Transshipment of containers at a container terminal: an overview	[66]	440
5	European Journal of Operational Research	Ship routing and scheduling in the new millennium	[54]	359
6	Reliability Engineering & System Safety	A Bayesian belief network modelling of organizational factors in risk analysis: a case study in maritime transportation	[67]	317
7	Transportation Research Part C: Emerging Technologies	Speed models for energy-efficient maritime transportation: A taxonomy and survey	[68]	311
8	Transportation Science	Containership routing and scheduling in liner shipping: overview and future research directions	[69]	293
9	Journal of Transport Geography	The dry port concept: connecting container seaports with the hinterland	[70]	281
10	Transportation Science	Ship scheduling and network design for cargo routing in liner shipping	[71]	275
11	Transportation Research Part C: Emerging Technologies	Tramp ship routing and scheduling with speed optimization	[72]	213
12	Reliability Engineering & System Safety	Maritime transportation risk analysis: review and analysis in light of some foundational issues	[73]	209
13	Reliability Engineering & System Safety	A framework for risk assessment for maritime transportation systems—a case study for open sea collisions involving RoPax vessels	[74]	172
14	Transportation Research Part C: Emerging Technologies	Maritime routing and speed optimization with emission control areas	[75]	164
15	Transportation Science	A base integer programming model and benchmark suite for liner-shipping network design	[76]	158

lists the 15 most cited papers in the field of container research. Based on highly cited papers, the mainstream research directions were excavated. Among the 15 articles, there were more review articles, including reviews on container terminal operations, berth allocation, transportation operations, etc. However, there is still little literature on digital technologies for container sustainability. Most of the articles were published in Transportation Science and Transportation Research Part C: Emerging Technologies. By classifying the decision-making problems arising in container terminals, an attempt was made to find quantitative models to solve the problems for further research topics.

Through the statistical analysis of the highly cited literature from 2003 to 2022, we found that the combination of digital technology and containers will bring new changes to container ports, supply chains, and even the shipping industry. In addition, digital technology has been applied in fields such as medical care, media, and finance, but there is still little literature on the container supply chain empowered by digital technology and its potential future trends.

4.2.2. Co-Word Analysis

To help better understand the research topic and key words in the container logistics area, a co-word analysis was conducted, which was based on the proposed formula $T=\left(-1+\sqrt{-1+8I_1}\right)/2$, where $I_1$ represents the number of words with frequency 1, and $T$ denotes the minimum frequency value of high frequency words [77]. The VOSViewer software was adopted to extract and analyze the contained keywords of objective references, where a total of 11,093 keywords were found and identified for further investigation. Furthermore, the T-value of this study was calculated to be 26. Therefore, we chose keywords that appeared more than 26 times as the analysis content to ensure the validity of the network graph, as shown in Figure 5.

The VOS clustering algorithm was employed to help better categorize references by clustering analysis. In order to better reflect the research hotspots, nodes with a frequency greater than 60 were selected for cluster analysis, and a total of 5 cluster groups were obtained, as illustrated in Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10. In Figure 5, the larger the node of the keyword, the higher the frequency of occurrence. Based on the clustering results, there are five fields being focused on in academia.

Figure 6 demonstrates the optimization of all aspects of the container, including container transportation, operation, scheduling, strategy, etc. In the actual business of the container terminal, it is necessary to rationally allocate multiple resources such as vehicles, ships, berths, and mechanical equipment, which achieves the purpose of improving work efficiency and delivering economic benefits [78]. There are many optimization scenarios, and the quality and effect of optimization are directly related to the operating cost and production efficiency of an entire container terminal. Therefore, how to make full use of operations research knowledge and design efficient optimization algorithms has become a hot issue in the academic circle.

Figure 7 focuses more on the container management aspect, caring about container performance, sustainability, cost, energy consumption, and other aspects. From the optimization of liner operations by controlling fuel consumption and carbon emissions to the increased investment in technology to ensure the continuous and steady development of the container shipping industry [79]. Consider how to pursue cost economy as well as environmental sustainability during container shipping.

Figure 8 focuses on the risks of container transportation. Through Bayesian network, fault tree analysis, and other methods, the risks in the transportation process were systematically simulated, analyzed, and evaluated, and the real-time monitoring of risks was realized by using artificial intelligence data [80,81]. Improving measures were taken in a timely manner for security weak links to ensure the safety and reliability of the transportation link.

The center of gravity in Figure 9 is the container port. Major ports are vigorously promoting intelligent construction, continuously improving their operating capabilities, and providing strong support for ensuring the smooth flow of trade supply chains and industrial chains. As the central link of the transportation network, container ports are the vane of global trade. How to effectively improve the competitiveness of container ports has become an important issue for the survival and development of ports.

Figure 10 shows the application of digital technology in the field of containers, including blockchain, IoT, cloud computing, artificial intelligence, radio frequency identification, and other technologies. Digital technologies are changing and subverting the existing pattern of the container transportation industry [82]. These technologies can be used for cargo tracking, empty container positioning, etc. However, the integration of new technologies and new ideas into the traditional mode of operation will definitely bring many challenges to the digital transformation of the container industry.

In order to provide a clearer understanding of the development of container research path in recent years, the results of the explosive words analysis of the literature data are shown in Figure 11. The years of the explosive words are from 2012 to 2022.

Burst keywords refer to the phenomenon of any keyword appears frequently in a specific period. This information can not only reflect the evolution of research hotspots, but also reflect the research trends in recent years, and may predict future research trends. Figure 11 shows the 25 discovered burst keywords from 2012 to 2022.

Undoubtedly, since 2012, the combination of operations research and heuristic algorithms with containers began to attract academic interest to a large extent and continued to receive attention for some time. On the other hand, container logistics, terminals, and berth allocation have been widely discussed since 2014. Since 2019, the container supply chain, sustainable development, and the application of big data in containers have become a recent research boom.

4.3. Container Supply Chain Promotion by Digital Technology

The bibliometric analysis of CLSC on recent trends reveals that digital technology could help to improve the intelligence, efficiency, resilience, and sustainability of container supply chain activities. This section concentrates on revealing the updates to digital technology-empowered container supply chain management practice, exploring the industrial application scenarios.

4.3.1. Intelligent Container-Driven Efficiency Improvement of Logistics Operations

(1)

Innovative management of intelligent container stacking mode

The loading and unloading efficiency of container ports is a crucial part of ensuring the normal operation of the container supply chain. In the recent era, it was urgent to improve the loading and unloading efficiency since the port congestion had spread globally and exacerbated global supply chain delays [83]. If the efficiency of container loading and unloading operations in ports is too low, it can lead to port congestion and prolong the turnover time of ships and transportation vehicles in the port hinterland, ultimately leading to a delay in the entire supply chain cycle. With the development of port digitization and the requirements of operational efficiency improvement, the innovative management of container loading and unloading forms has attracted much attention by practitioners.

The adoption of advanced technologies, digital equipment, and intelligent decision-making systems helps to improve loading and unloading efficiency by enhancing the automation degree of ports. For instance, the entire yard of the Shanghai Waigaoqiao Container Terminal is fully enclosed, relying on intelligent container operation equipment to achieve fully automated unmanned operation [84]. The yard adopts a fully automated high- and low-rack rail crane relay loading-and-unloading system. The loading and unloading trucks and the yard storage box operations are completed through the low rack rail crane and the elevated rail crane, respectively. The high and low rack rail cranes are connected through a transfer platform. The highly automated intelligent container stacking mode helps to enhance the intelligent level of containers and to achieve intelligent coordination of the supply chain by controlling the operational efficiency of loading and unloading activities [85].

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Intelligent Container IoT System Empowered by Digital Technology

As key equipment for international multimodal transportation, 90% of international trade freight is completed through container transportation. At present, approximately 40 million containers that meet international standards are circulating globally through sea freight. However, such large-scale container information collection, tracking, and management are still mostly completed manually, resulting in delays in information transmission and a lack of data throughout the entire supply chain of containers. The rise and continuous development of Internet of Things technology have provided effective technical means for the container industry to solve this dilemma [86]. Therefore, fully utilizing IoT technology to build an intelligent container trade ecosystem has become a trend.

The current intelligent container Internet of Things system refers to a container system with global positioning, remote monitoring, and data interaction. The purpose is to achieve visualization of containers under the Internet, ensure the security of the global container supply chain, improve supply chain management efficiency, and improve efficiency by tracking and monitoring containers globally [87]. In recent years, the digital construction of the Tianjin Port has continuously promoted the construction of an intelligent container information management center, the application of RFID radio frequency identification technology in the port area, and the comprehensive development of OCR, sensing technology, 5G, etc., effectively gathering logistics, information flow, and capital flow, further enhancing the core competitive advantage of the port area, and radiating and driving the development of various industries in the region. Building an intelligent, efficient, convenient, reliable, and safe intelligent container IoT system has become an inevitable choice for terminals to improve production efficiency.

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Intelligent Container Defect Monitoring System Based on Video AI Algorithm

Containers, as loading containers and carriers for long-distance transportation of large amounts of goods, are usually leased and used by customers with freight needs to specific companies. However, in long-distance transportation and the circulation between multiple transfer stations, containers are prone to over 50 types of damage and form defects, such as deformation, rust, cracks, and missing components [88]. These defects need to be detected in a timely manner to assess whether the container can continue to be used technically and whether immediate repairs are needed.

For instance, the Tencent Technology Co., Ltd. (Shenzhen, China) has independently developed an intelligent container defect detection system (hereinafter referred to as the “system”) for scenarios such as port/yard gates, container inspection, and shore cargo handling in container transportation by utilizing advantages such as artificial intelligence, image processing, and deep learning. The system can be applied to the entry and exit gates of docks or external storage yards; or in the scene of shore cargo tallying, quickly and accurately identifying box information and defect information on containers passing through the gates; and on the storage yard or on the shore, ensuring that containers passing through the gates meet the requirements and achieving efficient, intelligent, and automated management. The dangerous evidence collection process in traditional processes has been completed by machines instead. The system automatically alarms after detecting defects and can work 24/7 with minimal manual intervention or confirmation, greatly reducing the labor intensity of container inspectors, improving inspection efficiency, and reducing the waiting time of container truck drivers. In addition, thanks to the leading technological advantages of high-precision artificial intelligence algorithms, the accuracy of automated container deformation detection exceeds 99%. The box and residue inspection operation has been shortened from the original ten to a few minutes from the beginning of detection to the confirmation of results, with an overall efficiency improvement of over 50%.

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Intelligent container transportation relying on modern transportation systems

The traditional container distribution method has shortcomings such as weak connectivity, long transportation cycles, and susceptibility to congestion, resulting in high logistics costs, low transportation efficiency, and trouble loading and unloading goods at ports. The air rail intelligent container transportation system is a system that utilizes air rail to organically connect logistics systems such as railways, waterways, highways, and aviation, achieving interconnectivity between containers or various transportation unit distribution centers, meeting the requirements of zero distance transportation and seamless connection [89]. It solves the problems of weak connection, high cost, and low efficiency in traditional transportation methods such as highways, railways, and waterways, and has strong scalability and good compatibility. The characteristic of strong adaptability is a safer, more efficient, more environmentally friendly, and more economical new three-dimensional transportation method. The transportation efficiency is nearly five times that of ordinary transportation, representing the future development direction of smart transportation in cities, ports, and logistics.

Eagle Rail, located in Chicago, USA, has developed an air rail intelligent container logistics system suitable for handling container transportation between ports and multimodal intermodal terminals. It is an ideal choice for circular transportation within ports, intermodal terminals, and among terminals. The system adopts fully electric drive to replace heavily polluted container transportation and reduce carbon dioxide emissions by more than 60%. This system will overturn the existing transportation mode of the dock. For old docks with limited space, it can extend the operation site through rail transportation, which to some extent alleviates the operational pressure of the dock. For new terminals and deep-sea terminals, through preliminary planning, the construction cost of the terminal can be greatly reduced, and new energy such as electricity and solar energy can be used to assist in energy conservation and emission reduction in the terminal, achieving sustainable development.

4.3.2. Container Supply Chain Resilience Improvement via IoT-Based Platform and AI

The container supply chain is a new manifestation of the supply chain concept in international trade activities, including container transportation, scheduling, transit, and reporting [90]. With the development of international container transportation, the transportation coverage in the container supply chain is wide, involving multiple subjects, difficult coordination of internal and external activities, a low level of informatization, safety and risks, and other issues which are becoming increasingly prominent. Supply chain resilience refers to the ability of the supply chain to recover to its original or more ideal state after being disrupted. Since the outbreak of the epidemic, the stability of global industrial and supply chains has faced severe challenges. In the past few decades, the dynamic balance has been disrupted, highlighting the lack of supply chain resilience. The resilience of container supply chains urgently needs to be improved. The employment of digital technology, such as Internet of Things, artificial intelligence technology, and blockchain technology can assist in container intelligence, container terminals intelligence achievement, and the dynamic optimization of container shipping routes. The development of an intelligent container transportation system assists to improve the flexibility and resilience of the container supply chain, promoting the high-quality development of the container supply network.

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The container intelligence achievement driven by IoT

The Internet of Things is a network constructed on the basis of the computer internet, utilizing technologies such as RFID and wireless data communication to cover everything in the world. Its essence is to use radio frequency automatic identification (RFID) technology to achieve the automatic identification of items, interconnection, sharing of information through the computer internet. The application of RFID technology in container transportation can achieve the full tracking and traceability of container logistics [91]. The establishment of the Internet of Things can integrate information, optimize the entire logistics supply chain and circulation network, and achieve efficient container transportation. At present, most of the container number recognition technologies used globally are based on container number image recognition, which has a low recognition rate and is greatly affected by weather and container damage. Therefore, it is necessary to apply IoT RFID technology to containers and develop intelligent and information-based containers. This will greatly improve the resilience of the container supply chain by addressing the lag and loss of control in container management work, which helps to allocate containers, vehicles, and ships. It also reduces the empty container rate of containers and avoids container stacking, thereby improving transportation capacity and economic benefits.

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Intelligent container terminals driven by AI technology

The application of artificial intelligence technology in the container transportation industry includes fields such as fully automated docks, intelligent ship loading, intelligent scheduling, and can also be applied in unmanned ships, intelligent scheme design, and other fields. Intelligent ship stowage and intelligent scheduling are important directions for the application of artificial intelligence. Through artificial intelligence technology and algorithm optimization, an optimal loading diagram can be automatically completed by combining information such as ship container volume distribution, container type proportion, port of call, cargo storage, mechanical equipment status, liner routes, berths, and cargo sources, achieving safe and efficient loading of goods and effectively improving ship loading efficiency. By utilizing artificial intelligence technology and ship positioning, combined with information such as dock scheduling, route setting, cargo flow direction, and ship maintenance plans, intelligent optimization solutions are provided for ship scheduling to improve ship utilization efficiency. Artificial intelligence technology has been applied and practiced in container terminals, greatly improving production efficiency [92]. For instance, Shanghai Yangshan Port (China) has achieved intelligent operation throughout the entire process of container terminal loading and unloading, horizontal transportation, and yard operations through the application of the Terminal Intelligent Production Management Control System, the Intelligent Control System, and the Terminal Automatic Guided Transport Vehicle.

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Multimodal transportation network optimization considering carbon emission

As an advanced organizational form, multimodal transportation combines and connects multiple modes of transportation to reduce transportation costs for enterprises and improve the efficiency of the cargo transportation process. In the process of multimodal transportation, each mode of transportation incurs its own transportation costs, time, and carbon emission costs. Due to the influence of weather, traffic conditions, and other factors, the transportation time often exhibits randomness. The dynamic optimization algorithms and AI technology are adopted to address the multimodal transportation network design with multiple time windows, contributing to improving the timeliness of overall planning paths [93].

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Construction of an intelligent container transportation system

The construction of an intelligent container transportation system facilitates improvement in the elasticity and resilience of the container supply chain by dynamic scheduling [94]. The container transportation system should not only moderately cater to the construction of major port container terminals and promote the coordinated development of regional port groups through government enterprise cooperation, but also focus on enhancing the international shipping hub status and shipping center construction of trunk ports. The high-end service functions, such as fuel refueling, empty container transportation, international transit, and shipping finance, have been addressed. At the same time, based on the comprehensive three-dimensional transportation network, the national container logistics channel should be expanded, and a comprehensive logistics service network with a multimodal transportation system could also be developed to promote the high-quality development of the container transportation.

4.3.3. Digital Technology-Empowered Container Supply Chain Sustainability Achievement

Container supply chain sustainability is improved through digital technology adoption, which is achieved by location monitoring, route optimization, resource collaborative utilization, transparency traceability, and automation intelligence [95]. It provides positive support for reducing energy consumption and emissions, which improves the efficiency and security of CLSC. These achievements contribute to achieving sustainable development goals and promoting coordinated development of the economy, environment, and society. There are three dimensions to the digital technology-empowered container supply chain sustainability achievement, that is, the strategic dimension, the technological dimension, and the operational dimension.

The application of digital technology has promoted the strategic transformation of the container supply chain and achieved sustainable development strategy. Through digital platforms and networked collaboration, enterprises can achieve comprehensive connectivity and information sharing in all aspects of the supply chain, thereby improving the overall efficiency and sustainability of the supply chain. For example, digital technology can help enterprises achieve accurate demand forecasting and inventory management and reduce inventory waste and supply chain disruptions, which improves resource utilization efficiency. In addition, digital technology can also achieve traceability and visibility in the supply chain, helping enterprises optimize their supply chain structure and choose more sustainable suppliers and logistics service providers.

Digital technologies have been widely adopted and applied in container supply chain practices for their technical advantages. On the one hand, the Internet of Things and sensor technology can help achieve container tracking and monitoring, helping enterprises achieve safe and efficient transportation of goods. On the other hand, big data and artificial intelligence technology can provide optimization suggestions for reducing operational costs and environmental impacts by analyzing the massive data of supply chain processes. From the technological viewpoint, the following aspects are mainly applied for container supply chain sustainability improvement driven by digital technologies.

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The operational status could be dynamically monitored due to the adoption of sensors and IoT technology, such as the location, temperature, humidity, and other environmental conditions of goods in real-time. In addition, effective data mining under the IoT scenario could help to predict the arrival time of goods and potential problems during transportation, facilitating an improvement in sustainability by reducing cargo detention and damage.

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The container supply chain network could be optimized to minimize the cost and carbon emission by adopting a big data-driven optimization technique, as well as the distribution routes and transportation mode. In addition, digital technology can also provide real-time traffic information, contributing to dynamic route adjustment and congestion avoidance.

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Information sharing and resource coordination will also be achieved among different container supply chain participants relying on digital techniques, which helps to improve resource utilization. For instance, empty containers can be quickly found through digital platforms to avoid empty or prolonged stays.

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Blockchain technology has proved to be effective in establishing the transparency and traceability of the container supply chain by disclosing the source, production process, and delivery of goods [55]. This helps to prevent counterfeit products and illegal activities and improve the quality and security of the supply chain.

In addition, the employment of digital technology has also changed the operational mode of container supply chains [96]. Traditional container supply chain operations typically require a lot of manual labor and paper document processing, posing risks of errors and delays. And digital operations can greatly improve the accuracy and efficiency of operations. For instance, enterprises can achieve the automation and digitization of various operational processes through electronic data exchange and online platforms, which reduces errors and time costs. Digital technology can also support instant messaging and collaborative work in the supply chain, promoting cooperation and communication among various parties involved in the supply chain.

5. Discussions

This research shifts our eyes to the bibliometric study on CLSC management practice, aiming at probing into insights on further research and better practice in terms of container logistics. In this section, the theoretical contributions and practical implications are summarized and addressed for stakeholders of the maritime industry.

5.1. Theoretical Contributions

This study performs a quantitative review analysis of CLSC by employing a bibliometric-based approach, and the existing publications are analyzed to help better understand the state-of-the-art of knowledge on container logistics practices. The research framework was designed from the viewpoint of taxonomy by investigating the collected reference samples. It provides theoretical insights and systematic understanding on the innovative management practices of CLSC for academia and practitioners, especially in the intelligent development of the container logistics management. In addition, this study fills research gaps in the specific impacts of digital technology on CLSC management, while enriching innovative container industry development by providing potential research opportunities and industry practice.

5.2. Practical Implications

Regarded as the main form of modern freight transportation, container transportation has been increasingly focused on under frequently global trading. With the deepening development of economic globalization and trade integration, the global container traffic continues to grow, which requires better service regarding the efficiency of container terminal operations. This study also provides practical guidance for industrial stakeholders by promoting digital technology application in container logistics, which facilitates innovation in industrial practices during the container supply chain processes. Specifically, the related research topics are discussed and highlighted regarding intelligent container digital transformation. The implications to practice are introduced from different perspectives, including enterprises, government, and related industries.

For industrial enterprises, digital technology facilitates data sharing, dynamic tracing, visualization, and business process optimization of the container supply chain. Digital containers can be equipped with various sensors and communication devices to monitor the location, status, and environmental conditions of the container in real-time. This digitization makes the transportation process of goods more transparent and reduces the damage risk to the goods by tracing the real-time location and status of the commodity. In addition, it helps container logistics enterprises to achieve lean management by transportation plan optimization, resource allocation, and energy-consumption saving using massive real-time information. Digital technology can also be applied to container logistics to help achieve real-time monitoring and anti-theft functions, which reduce the risk of goods being stolen or damaged through technologies such as GPS positioning, seals, and security sensors. Digital technology application also provides a platform with information sharing for container logistics participants, including manufacturers, suppliers, freight forwarders, logistics companies, leasing firms, and transportation sectors. It also helps governmental organizations and industrial associations to achieve effective cross-border cooperation management, which is conducive to regulative supervision and harmonious operation of the container supply chain.

Digital technology has promoted business innovations and creative operations of CLSC by introducing more intelligent and data-driven elements. This paper also provides inspiring research ideas for academia engaged in digital CLSC, and it reveals insightful inspiration for those stakeholders who would like to perform an in-depth application of digital techniques in CLSC.

6. Conclusions

This paper aims to study the updates of digital technology application in CLSC by analyzing the relevant literature. Firstly, based on the bibliometric analysis, we found that digital technology has effectively improved the operational efficiency of container logistics activities. It also promotes innovative management practices of the container supply chain process. Secondly, the related publications were collected to scrutinize the recent trend in digital technology-empowered CLSC management. We found that research related to digital technologies had a steadily increasing trend, and that the research hotspots mainly concentrated on intelligent operation, resilience, and sustainability improvement by different kinds of digital techniques. By promoting the digital technology application in container supply chain management practice, the specific roles of digital technology-empowered containers are also discussed and addressed to assist in finding better potential opportunities.

The increasing globalization trend will greatly motivate the integration and expansion of container supply chains, promoting closer cooperation and trade exchanges worldwide. The widespread application of digital technology will make the supply chain more intelligent and efficient, improving visibility and decision-making capabilities. The container industry will continue to embrace dynamic changes by employing new digital technologies and strategic operations to improve efficiency and sustainability, ensuring smooth global trade. It will be regarded as a great triumph in performance improvement if the innovative management practices of CLSC can be performed and adopted in terms of location monitoring, path optimization, resource collaborative utilization, transparency and traceability, automation, and intelligence.

Industrial managers can promote innovative CLSC management by positively adopting digital technologies. Moreover, we hope this research serves as a future direction for both academia and engineering on lever-aging digital technologies to improve the operational efficiency and sustainability performance of CLSC. The increasing role and impact of digital technology in international trade have brought new opportunities and challenges to the development of the container industry. With the booming development of the digital technology, the innovative management practices of CLSC will continue to promote the transformation, upgrading, and innovative development of international trade.