1. Introduction
The maritime transport sector represents a backbone of the globalized economy [
1], and its digitalization is moving at different dynamics in different domains [
2]. Digitalization in the maritime transport sector refers to the implementation of a variety of digital technologies [
3], which may provide the enhanced productivity, efficiency, sustainability of business processes [
4], as well as transparency [
5]. It may also provide a competitive advantage by connecting all of the involved stakeholders in the value chain [
6]. Ships, seaports, and offshore facilities have become increasingly dependent on information and communication technologies [
7]. Despite opportunities, the digitalization and digital transformation in the maritime transport sector and seaports is slower compared to other transport sectors [
8].
After the analysis of the previous research on the topic of digitalization in maritime transport, it is possible to notice several directions. An analysis of digitalization in maritime transport was conducted by Sanchez-Gonzalez et al. (2019) [
2], in which the authors elaborated upon shipbuilding and ship design, in addition to maritime transport. Most authors have analyzed the impacts of a single technology/solution in maritime transport and seaports, such as the impact of Blockchain [
9,
10,
11], a Port Community System [
12], or the Internet of Things [
13]. For example, Aloini et al. [
14] analyzed the role of process coordination dynamics and information exchanges in maritime logistics, for which a case study in a mid-sized port supported by a Port Community System was developed. One of the issues regarding maritime transport digitalization is the vulnerability to cyber attacks, which can lead to the loss of vessels’ control or the loss of sensitive data [
15]. In this respect, digitalization brings along challenges that need to be addressed [
16]. In certain instances [
7,
15,
17,
18,
19], the security challenges of individual technologies or groups of technologies have been analyzed, such as phishing, malware, and data theft. Although these publications represent an important contribution to the current body of knowledge, there is a lack of a comprehensive overview of digitalization in maritime transport, with emphasis on the implementation of different ICT (Information and Communications Technology) solutions in various fields such as port operation planning, berth allocation, human resource planning, decision making, routing optimization, and information exchange.
In order to shape (plan) future research, it is important to first understand the current body of knowledge. The aims of this study were to provide a thorough overview of the current body of knowledge related to digitalization in maritime transport and seaports, considering the aforementioned fields, in order to address and provide answers to the main research questions arising from the digitalization process:
What are the key research areas dealing with digitalization in maritime transport and seaports?
What types of papers are most represented?
What type of research methodology is most used?
How many papers are published per year?
Which countries have actively participated in the research?
Which papers and authors are most cited?
Which research categories are most analyzed?
What are the keywords dealing with digitalization in maritime transport and seaports?
For this purpose, the bibliometric, content and thematic analysis of digitalization in maritime transport and seaports was conducted. In this way, it was possible to discover the research progress, the key themes of digitalization, and research gaps in maritime transport and seaports. Thus, this paper can assist scholars and practitioners in obtaining a comprehensive understanding of the status quo and further tendencies of digitalization in maritime transport and seaports.
The paper is structured as follows.
Section 2 deals with related work and the most relevant literature referring to previous research in the field, in order to place the proposed study in the contribution context.
Section 3 represents a systematic explanation of research analyses, and steps of particular phases. In
Section 4 and
Section 5, the final results are discussed through bibliometric, content ant thematic analyses, based on which the main findings are presented. The latter refer to answers to the addressed questions, expected future outcomes, and perspectives on digitalization in maritime transport.
2. Background
This section provides an overview of the existing papers in which literature review or bibliometric analysis were used as research methods. This step is important in order to further delineate the scientific gap(s) which is addressed in this study.
Through a systematic literature review, Sanchez-Gonzalez et al. (2019) [
2] have claimed that maritime transport has been accepting digitalization according to different dynamics in the different fields. They have analyzed state-of-the-art of maritime transport industry digitalization, giving an overview for ship design/shipbuilding, shipping and seaports, and defining eight domains to which the digitalization is currently applicable: “autonomous vehicles and robotics; artificial intelligence (AI); Big Data; virtual reality, augmented and mixed reality; Internet of Things; the cloud and edge computing; digital security; 3D printing and additive engineering”. Their research has demonstrated that domains exist in which almost no formal research has been conducted so far, concluding that several major areas require attention, e.g., the integration of the studies on AI in the industry, and the use of robotics in maritime transport [
2]. Although their focus has been on digitalization in maritime transport, they have also included, in their research, papers dealing with shipbuilding and ship design, which will not be analyzed in our paper. This paper focuses exclusively on the digitalization and implementation of various digital technologies in maritime transport and seaports. Given that digital technologies are rapidly evolving, the authors expect to identify new research directions in the field of digitalization.
Fruth and Teuteberg (2017) [
20] provided a systematic literature review of the current state of digitalization in maritime logistics, and discussed existing problematic areas (e.g., the lack of theoretical studies regarding the future behavior of stakeholders in the maritime logistics chain). Furthermore, they presented potentials for improvement, e.g., by expanding their research into several areas where Big Data technology has already been implemented. Their research scope covered not only maritime transport, but also the logistics sector.
Bălan (2020) [
21] conducted a literature review and focused on future advanced ICT in cargo maritime transport: Big Data, the Internet of Things, cloud computing, and autonomous vessels (including unmanned ships/vessels) [
21]. The author claimed that advanced ICT will have a disruptive impact on maritime transport and supply chains in the future.
Gil et al. (2020) [
22] used bibliometric methods to depict the domain of onboard Decision Support Systems (DSS) for operations focused on safety insurance and accident prevention. Despite valuable results, their research focused solely on DSS. The authors noted that maritime transport faces new challenges related to safety due to increasing traffic and ship size, respectively. They concluded that new concepts related to DSS which support safe shipping operations in the presence of reduced ship manning are rapidly growing, both in academia and in industry.
Tijan et al. (2021a) [
23] performed a literature review of the drivers, success factors and barriers to digital transformation in the maritime transport sector. Due to a lack of research and scientific papers dealing with digital transformation in the maritime transport sector, the authors focused on publications which were not only related to digital transformation in the maritime transport sector but also to transport and digital transformation in general.
Yang et al. (2019) [
24] conducted a literature review regarding features of an Automatic Identification System (AIS), dividing it into three development stages: basic, extended, and advanced applications. They suggest potential digitalization fostering using the system when it is combined with supplementary databases.
The above presented studies offer an important, but not comprehensive, overview of current research achievements and future research directions related to digitalization in the field of maritime transport and seaports.
4. Results
4.1. Number of Papers per Year, and Countries
An analysis on an annual basis (
Figure 2) showed that the maximum number of selected papers was published in 2020 (60 papers), followed by 2019 (40 papers), 2017 (27 papers), and 2016 (23 papers). In 2021, only 26 papers were published, as the analysis covered papers published before October 2021.
The “country cooperation network” is presented in
Figure 3. Within the figure, the size of the letters indicates the representation of authors with affiliations from a particular country, while the larger purple circles indicating higher centrality.
As shown in
Table 2, the authors with Croatian affiliation published the largest number of selected academic papers (40 papers in total), followed by the authors with German and English affiliations. High centrality implied the importance of the nodes. The centrality of authors with German affiliation reached 0.77, indicating that they kept a wide range of cooperation with authors affiliated with various countries such as Italy, Sweden, Colombia, and the People’s Republic of China, etc. On the other hand, although authors with Croatian affiliation produced the largest output of academic papers, their poor collaboration with authors affiliated with other countries is visible, with the centrality of 0.07.
After this step, further analysis was performed.
4.2. Analysis by Paper Type
The largest number of publications were journal papers (176), followed by conference papers (94) and book chapters (10), as presented in
Table 3.
Most of the conference papers were presented at conferences held in Poland (11 papers), followed by Croatia (8 papers), and Russia (6 papers), as shown in
Table 4.
Considering journal papers and countries, most of the papers were published in journals from England (62 in total), followed by Croatia (21) and and Netherlands (20), as shown in
Table 5.
In order to recognize the core field journals, the number of articles per journal was calculated (
Table 6). TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation (Poland), with 14 published papers (accounting for 7.95%), is closely followed by the Scientific Journal of Maritime Research (Croatia) with 13 papers (accounting for 7.39%).
The classification (
Figure 4) shows that 73 publications were theoretical, 76 were qualitative, and 43 were quantitative, while 88 publications included mixed methods. The classification was made according to [
27].
The theoretical publications mainly included frameworks based on literature and practice reviews, and the analysis of key research fields. Qualitative research mostly referred to case studies and empirically-based simulations. Regarding quantitative publications, they mainly included surveys or manipulated pre-existing statistical data using various statistical methods.
4.3. Analysis of the Most Cited Papers and Authors
As per the WOS and Scopus databases, the authors had to analyze separately the most cited papers and contributors due to several reasons. Certain papers which were included in Scopus were not indexed in WOS, and vice versa. In addition, in all cases, for the same paper, the citation numbers between the two databases differed.
In WOS, the most cited paper is “A fuzzy logic method for collision avoidance in Vessel Traffic Service” [
32], with 95 citations, followed by “Maritime shipping digitalization: Blockchain-based technology applications, future improvements, and intention to use” [
33], with 66 citations (
Table 7).
In Scopus, the most cited paper was the same as it was previously, with 101 citations, followed by the paper “The importance of information technology in port terminal operations” [
34], with 80 citations (
Table 8).
4.4. Analysis of the Categories
Categories can reflect the development level of research on a specific subject during a given period [
26]. The related literature in both databases was comprised of approximately 75 subject categories, the most frequent of which are shown in
Figure 5.
The top five subject categories (
Table 9) include Transportation, Engineering, Computer Science, Business and Economics, and Transportation Science and Technology. The distribution of the categories suggests that issues in transportation, engineering, computer science, business and economics were highly prioritized in research.
4.5. Analysis of the Keywords
In the analysis, the authors included Author Keywords and Keywords Plus in the Term Source field. Once the synonyms for each term were merged (e.g., “Port Community System” and “PCS”), the keywords emerged as shown in
Table 10.
The most prominent keyword in the field of digitalization in maritime transport and seaports was the term “Port”, with the highest frequency (41). It was followed by the terms “Port Community System” (27), and “Big Data” (26). In terms of technologies, the keyword “Port Community System” appeared the most times, and it was the term used in one of the 75 search strings the authors used for this topic. However, “Big Data” was not one of the chosen keywords. Nevertheless, it was at the very top according to frequency. In this respect, modern technologies such as the Internet of Things, Big Data, and Blockchain, etc., are also playing an increasing role in the digital transformation in the maritime transport sector and seaports.
4.6. Content and Thematic Analysis
During the content and thematic analysis, 15 themes were identified (as shown in
Figure 6); the order descends according to the number of matches from the analyzed text.
The themes are the following: “system”, “technology”, “data”, “port”, “ship”, “study”, “stakeholders”, “time”, “container”, “model”, “network”, “organizations”, “innovation”, “goods”, and “AIS”.
The concept map consists of themes (colored circles) and the concepts that form each theme (the black text within the themes). The importance of the themes is shown as a “heat map” (the brighter the theme, the more often it was found in the analyzed text) and size (the larger the theme, the more concepts were combined in it) [
27].
The concept map also shows the overlapping of the themes, e.g., “technology” and “innovation”, and which concepts are shared between two themes. Equally, the concept “digital” lies in the overlap of the themes “technology” and “innovation”, along with which relationships between the concepts maintain relationships between the themes, e.g., “process”, “digital”, “adoption” and “innovation”.
As the themes “technology” and “system” have the highest number of occurrences, and for the sake of clarity, the results were discussed first from a technology and then from a system perspective.
4.6.1. The “Technology” Perspective
The concept map shows that the theme “technology” overlaps with the following themes:
4.6.2. The “System” Perspective
The resulting overlapping of the “system” theme with others, as presented in
Figure 7, is elaborated in the continuation.
“Port”: “Infrastructure” as a concept is shared between both the themes of “system” and “port”. In this respect, several studies analysed the following: [
53] quoted the authors Hlali and Hammami, according to whom the seaport may be defined as a multidimensional system combining between an economical function, an infrastructure system, a geographical space and trade. John et al. (2018) [
56] claim that seaport facilities may be considered as critical infrastructure systems which are vulnerable to various risks due to their complex structures. Thus, it is necessary to protect them from threats by using robust and sophisticated security systems, and measures for early detection. Regarding the themes “port” and “system”, several authors refer to the Port Community System, which improves data exchange between stakeholders, for example [
12,
19,
36,
57,
58].
“Container”: The theme “container” overlaps with “port” and “system”. The authors of [
59] analysed processes including the Port Community System, containers, and involved stakeholders. The authors of [
60] mentioned the truck appointment system that enables truck drivers who want to deliver or collect containers at the terminal to provide, in advance, their administrative details to the terminal operator’s e-portal.
“Time”: One path connects themes “time” and “system”, which leads to the concepts “system”, “control” and “planning”, or “system”, “control”, and “vehicles”. For example, [
61] claim that automated transfer vehicles are one of the most obvious examples of the importance of information and communication technologies in container terminals, as they allow a higher flow of containers and significantly reduce the time needed for serving ships.
Although the theme “system” does not overlap with the themes “ship” and “AIS”, the aforementioned themes are closely connected. For example, [
62] analysed the system that controls and operates the ship, and which—among others—enables the monitoring of autonomous ships from onshore control centres. Furthermore, [
63] analyzed 5G-based ship AIS intelligent control systems. The system can, among other features, process the information of vessels in the navigational area in a systematic manner, and can automatically arrange the vessel information in real time, providing feedback.
5. Discussion and Future Research Perspectives
In order to understand the frequency of publication, an analysis of published papers per year was conducted. The maximum number of selected papers was published in 2020. The development of new technologies is accelerating, and an increasing number of researchers are focusing on digitalization and the impact of digital technologies in maritime transport and seaports.
The authors with Croatian affiliation published the largest number of selected academic papers, followed by authors with German and English affiliations. The authors with German affiliation maintained extensive cooperation with authors affiliated with other countries, including Italy, Sweden, Colombia, the People’s Republic of China, and others. On the other hand, despite the fact that the authors with Croatian affiliation published the most papers, there was a lack of engagement with authors affiliated with other countries.
Regarding the conference papers and countries, most conference papers were presented at conferences held in Poland, followed by Croatia and Russia. In order to recognize core field journals, the number of articles per journal was calculated. According to the results, journals focused on maritime transport had the most published papers. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation (Poland), was the journal with the largest number of published papers relating to this research.
Comparing the Web of Science and the Scopus citations, a different number of citations for the same publications is visible. There are several reasons for this, such as the citations being affected by the size of the databases, and different citation practices between publication types existing, etc. Despite this, in both databases, the most cited paper was “A fuzzy logic method for collision avoidance in Vessel Traffic Service” [
32]. The top five subject categories are Transportation, Engineering, Computer Science, Business and Economics, and Transportation Science and Technology.
It is necessary to compare the results from the Leximancer tool, which was used to analyse key concepts and themes, and the CiteSpace tool, which was used to analyse categories. Several differences can be noted. Firstly, full access to a paper is a precondition for the detailed analysis. The results from Leximancer are not terms consisting of several words. In this respect, it is necessary to compose a term from the obtained results (words i.e., concepts or themes). For example, in CiteSpace, one of the top 10 keywords is “Information System”. In Leximancer, “system” is a theme, and “information” is a concept which is part of the aforementioned theme. The words that are most often repeated in both tools are: Port, Community, System, Data, Information, Chain, Model, Management, Technology, Blockchain, Ship, Logistics, and Smart. However, in Leximancer, “Internet of Things”, “Big Data” and “Artificial Intelligence” are missing. For comparison, in CiteSpace, the keyword “Big Data” is in third place in terms of frequency. On the other hand, two of the concepts are “ship” and “autonomous” in the Leximancer tool. In CiteSpace, the keyword “autonomous ships” is not among the 17 most frequently mentioned keywords. In this respect, for a successful analysis, it was necessary to approach the topic from several perspectives.
Through the analysis of keywords, categories and themes, the most and least researched areas were identified. Based on this, topics that are not explored well enough (as they have the lowest number of hits) and should be more researched at the level of the maritime transport sector will be explained below.
5.1. Future Research Directions Based on the Results Obtained by CiteSpace and Leximancer
As was already mentioned, the Leximancer results differ from the CiteSpace results. In other words, using Leximancer, the most frequently mentioned terms are isolated, i.e., they formed the so-called groups; however, in order to understand the meaning of these terms, it was necessary to manually review the papers and derive a conclusion (which may be considered as one of the limitations). For example, the term “goods” is not the main focus” in numerous papers, but this term is mentioned when introducing a particular issue. Therefore, it was necessary to analyse the publications that contain the term “goods” in order to be able to derive future research directions.
On the other hand, regarding the CiteSpace results, the term can contain more words. In this case, for future research directions, the authors also used the terms with the lowest number of hits based on keywords; however, some keywords were not included, such as: “efficient”, “usage”, and “marine transport”, etc., because it was not possible to derive meaningful conclusions (which may represent a limitation of the CiteSpace tool). Our suggested future research directions were also based on future research directions suggested by authors in their papers.
Table 11 shows the terms that had the lowest number of hits in Leximancer and CiteSpace. In addition,
Table 11 shows what has been researched in the papers and what is missing in the papers, on the basis of which future research directions have been presented.
It can be noticed that—in some publications—the terms are overlapping, as in the case of “innovation” and “organization”. Organizations are most often mentioned in the context of “cooperation between organizations”, “specifics of individual organizations”, and “competitiveness between organizations”, etc., but as introductory sentences to a particular issue.
5.2. Future Research Directions Related to Advanced Digital Technologies in Maritime Transport
Despite the numerous benefits that Leximancer and CiteSpace provide, it was necessary to read the publications manually in order to ensure that all of the important publications were included. What was missing were, for example, the keywords that mention “5G”, which is a promising research direction. In this regard, the authors have singled out some topics that could be analysed. These topics refer to advanced digital technologies which represent the main drivers of digitalization and digital transformation [
23]. The importance of advanced technologies has been recognized by the European Commission as well. In this respect, certain strategies have been developed, such as the AI strategy, which aims to streamline research and policy options for AI regulation [
85].
As was demonstrated by the keyword analysis, Artificial intelligence is gaining increasing attention from a number of researchers. AI is usually mentioned in combination with other digital technologies. The combination of AI and “unnamed vessels” refers to vessels that can learn from situations, and can consequently plan and implement a journey. However, AI implemented in procedures related to unmanned vessels can be dangerous. It is important to explore what cybersecurity measures need to be implemented in order to avoid negative consequences separately for various system types (e.g., storyless systems). In addition, one of the research directions is the definition of digital technologies’ combinations which is required in order to minimize or eliminate the negative consequences, such as data breaching, spoofing, or data manipulation. Furthermore, with the combination of AI and Big Data, it is possible to improve the usage of all of the available information. However, possible policy guidelines need to be explored further in order to reap the full benefits of such technologies without compromising data security and privacy.
The lack of research was noticed in the field of AI and optimized port operations. One of the AI applications in seaport operations was analysed by [
3]. According to their research, AI can be used determine which container to stack or unload first.
Regarding Artificial Intelligence and machine learning, this combination led to the creation of smart AI-enabled automation systems that can process large amounts of data, evaluate alternatives, and execute decisions [
76]. However, machine learning is sensitive to errors, which can go undetected for a long time. Therefore, future research should focus on safety related to machine learning in combination with artificial intelligence. Artificial intelligence and sensors can also be combined. This combination may enable improved decision making, optimized business processes, and reduced harmful environmental impacts.
According to [
86], AIS data combined with various artificial intelligence techniques will play an important role in shipping analysis services. It will be easier to approach strategic and operational information on any vessel or fleet of vessels at the global level. However, despite the numerous system opportunities, AIS has numerous vulnerabilities and pitfalls, as it is an open system transmitting on dedicated VHF frequencies. Further research is needed in order to ensure that data can be used without negative consequences (such as AIS spoofing).
The applications and benefits of the Internet of Things in the maritime transport sector are widely analysed, and their shortcomings should also be considered. For instance, the combination of the Internet of Things and sensors may provide data on cargo status in a timely manner, which consequently improves decision making. On the other hand, there appears to be an increased risk of security breaches and potential data manipulation.
Another research direction may be focused on smart ports and automation. The combination of various digital technologies and automation may improve monitoring, control, and planning of business processes in the maritime transport sector and seaports. However, it is necessary to bear in mind that “the more complex the system, the greater the probability of errors and disturbances in the system” [
87].
A promising research direction is 5G network application in maritime transport. The authors of [
63] analyzed a 5G communication ship traffic intelligent analysis platform, which can fundamentally strengthen the performance related to information collection. If 5G and AI are combined, the AI vulnerabilities may be exploited in cyber-attacks, while the “deployment of 5G network infrastructure will expand the attack surface area” [
7].
Although PCSs have already been implemented in numerous ports, with the advent of new digital technologies it is possible to expand the PCSs’ functionalities. For example, Blockchain technology may foster business processes and cost reductions. On the other hand, and especially if there are weak network security measures, PCSs are prone to intentional attacks. In this context, it is important to analyse what combination of digital technologies and security measures are required in order to minimize various types of negative consequences.
Several limitations exist in the paper. First of all, the tools recognized only the most frequent keywords, relations between them, and conceptualizations of themes. The research is based on a literature review and, considering the nature and evolution trends of the elaborated topic, the presented state-of-the art could soon fall into the previous research category, as was found for numerous related pieces of research. Nevertheless, the proposed research reflects the current digitalization progress in the field, and it can serve as a sound basis for consequent, similar studies. Furthermore, only two (although leading) databases were used—Web of Science and Scopus—and articles that were not written in the English language were excluded. On the other hand, bibliometric, content and thematic analysis provided a comprehensive overview of the current body of knowledge, and facilitated the identification of the research gaps.
The authors applied a methodological approach for the processing of publications dealing with digitalization in maritime transport and seaports. Furthermore, the aim was to answer fundamental research questions while also defining the main key points in the current maritime and seaport digitalization processes.