Preparing the maritime workforce for the twin transition: skill priorities and educational needs

1 Introduction

Multiple economic operators, including data centers and cloud infrastructure providers, are expected to achieve climate neutrality and significantly improve energy efficiency by 2030 as part of the EU's broader climate and digital strategies. In this context, the European Commission has set specific targets for data centers to become climate-neutral, highly energy-efficient, and sustainable by 2030, while also promoting greater energy efficiency and circularity in cloud computing services (European Commission, 2026). In this scope, environmental sustainability and digital transformation have been aligned and merged under the term “Twin Transition.” Today, twin transition seems to be one of the most pressing priorities on the EU agenda enabling the progress across both domains (EURAXESS, 2025).

International shipping remains a non-negligible source of global greenhouse gas emissions, contributing a measurable share to total climate impacts (ICCT, 2026). This impact could grow substantially without intervention. The twin transition is not only advantageous but also essential. The International Maritime Organization's 2023 GHG Strategy includes ambitious targets for reducing carbon intensity and accelerating the uptake of low- and zero-emission technologies to help align the sector with climate goals such as those of the Paris Agreement (IMO, 2024). Furthermore, the incorporation of sophisticated digital tools, such as logistics optimization, real-time monitoring systems, and data-driven efficiency applications, alongside low-carbon technologies, has emerged as a crucial approach for mitigating environmental impacts within maritime operations (Ugrinov et al., 2025).

The Twin Transition now constitutes a core element of EU maritime policy, with climate and digital goals increasingly intertwined. Frameworks including the European Green Deal, Fit for 55, and the expansion of the EU Emissions Trading System (ETS) to encompass maritime transport, and the Renewable Energy Directive collectively foster decarbonization and the adoption of alternative fuels. Simultaneously, initiatives such as the Digital Transport and Logistics Forum and the EU Action Plan on the European Maritime Space facilitate the digitalization of shipping and port operations (European Commission, 2019, 2023, 2024; European Council, 2022). These policies collectively highlight the increasing demand for a maritime workforce possessing both green and digital proficiencies, which are crucial for adhering to regulations and ensuring the sector's enduring competitiveness and adaptability.

A key factor facilitating this shift is the presence of suitable skills, specifically the upskilling and reskilling of the maritime workforce. This is necessary for the adoption, operation, and maintenance of the novel digital and green technologies being integrated throughout the sector. Workforce skills are not merely a concern of the labor market; they are a fundamental driver of sustainability performance. Digital and green competences are decisive in determining a firm's capacity to implement resource efficiency, emissions tracking, circular logistics, and sustainable procurement practices. However, several studies highlight significant gaps in the skills required for the Twin Transition, including shortages of highly skilled workers and insufficient training in digital and critical-thinking competencies (Caesar, 2023; SAFETY4SEA, 2025; Theotokas et al., 2024). The purpose of this study is both diagnostic and prescriptive: (i) to map the green and digital skills embedded in key maritime occupations, and (ii) to derive evidence-based priorities for education, training, and workforce policies that support the Twin Transition and the circular economy.

2 Literature review

The accelerating green and digital transitions have become central pillars of economic and industrial policy within the European Union, reflecting the recognition that sustainability and digitalization are not separate objectives but mutually reinforcing challenges. Digital technologies are increasingly enabling the transition to a low-carbon economy by reducing resource consumption, improving energy efficiency, supporting remote collaboration, and optimizing industrial and agricultural processes, making the Twin Transition a cornerstone of Europe's future competitiveness and sustainability. However, the backbone of these transformations is the workforce itself, whose skills and competences determine the capacity of organizations to adopt new technologies, comply with sustainability requirements, and remain competitive in a rapidly changing environment. Policy frameworks such as the European Skills Agenda (European Commission, 2020) and Cedefop's work on the green transition (CEDEFOP, 2022a) emphasize that sustainability targets cannot be achieved through technological deployment alone but depend fundamentally on the availability of an appropriately skilled workforce.

Similarly, the ETF's skills anticipation and action framework (ETF, 2025) highlights the need for education and training systems to evolve in parallel with technological and environmental change. In this context, workforce skills are increasingly viewed as a foundational condition for organizational competitiveness, adaptive capacity, and effective climate action rather than merely as a labor-market outcome. However, labor markets face several structural challenges, including changing occupational tasks, shifting global value chains, job polarization, and the erosion of standard employment benefits (ETF, 2021).

Empirical research consistently shows that mismatches between labor-market needs and available competencies remain a structural feature of modern economies, particularly during periods of rapid technological change. Bessen (2014) argues that employers' difficulties in recruiting suitably qualified workers reflect genuine shifts in job requirements driven by technological advancement rather than temporary labor-market frictions. This finding is supported by evidence showing that the introduction of new digital technologies often changes the nature of work rather than simply replacing existing tasks. For instance, contrary to common perceptions, the adoption of digital technologies in the workplace frequently requires employees to assume new responsibilities and acquire additional skills, rather than merely reducing their workload or replacing their jobs (CEDEFOP, 2022b).

This conclusion is reinforced by empirical evidence from Malik and Venkatraman (2017) and Morris and Reed (2008), who identify persistent mismatches between employer expectations and workforce capabilities across a range of industries. Their findings suggest that technological and organizational transformations often generate demand for new competencies faster than education and training systems can respond. As a result, the demand for new skills frequently grows more rapidly than the capacity of labor markets to supply them, creating shortages that may constrain innovation, productivity, and sustainable development.

In response to this growing misalignment, scholars have sought to clarify what constitutes green, digital and sustainability-orientated competences and how these can be systematically measured. Foundational frameworks by Wiek et al. (2011) and Brundiers et al. (2021) conceptualize sustainability skills as a combination of systems thinking, strategic action, normative competence and interpersonal capabilities. These skills enable individuals and organizations to understand complex socio-environmental systems and contribute effectively to sustainability transformations. At the same time, van Laar et al. (2020) and Li (2022) emphasize the growing importance of advanced digital, analytical, and adaptive skills in Industry 4.0 environments. Beyond basic digital literacy, modern workplaces increasingly require workers to manage data, interact with intelligent systems, solve complex problems, and continuously adapt to technological change. These conceptual advances have been progressively operationalised through large-scale skills intelligence systems such as ESCO (European Commission, 2022) and vacancy-based labor-market analytics (CEDEFOP, 2019), enabling a more systematic assessment of workforce readiness for digital and sustainability transitions. Evidence from the Sustainability Skills Survey (SOS, 2021) further suggests that environmental and green-transition competencies remain in particularly short supply. The study identifies sustainability-related skills as one of the most significant bottlenecks facing organizations seeking to meet climate, environmental, and ESG objectives, highlighting the growing need for targeted reskilling and upskilling initiatives.

While early studies primarily focused on identifying skills gaps, more recent research has concentrated on developing methods for measuring and anticipating future skills needs. In this regard, Koundouri et al. (2022, 2023) demonstrate how artificial intelligence and ESCO-based taxonomies can be used to classify occupations according to their green and digital content, enabling workforce requirements to be quantified rather than inferred. Their work introduces the concept of “Twin Skills,” referring to the combination of green and digital competencies required to support the Twin Transition. These approaches represent an important advancement in skills intelligence, as they provide policymakers, educators, and industry stakeholders with evidence-based tools for identifying emerging occupational requirements and designing targeted interventions. By linking occupational profiles with sustainability and digitalization objectives, they also create opportunities for more strategic workforce planning and policy design.

Within the maritime sector, these challenges are particularly acute. Shipping, ports, shipbuilding, logistics, and marine technology are simultaneously experiencing rapid digitalization and increasing pressure to decarbonise. Studies on maritime digitalization and workforce transformation show that shipping and port operations are increasingly integrating automation, data analytics, artificial intelligence, and smart systems into their operations (Cicek et al., 2019; Mgendwa, 2024; Theotokas et al., 2024). At the same time, environmental regulations and climate objectives are driving investments in cleaner technologies, alternative fuels, and more sustainable operational practices.

Human-factor research indicates that these changes place new cognitive, technical, and managerial demands on maritime workers, often without corresponding investments in training and workforce development (Bayrak and Muslu, 2025). Sector-specific assessments, including the MATES Project (2019, 2022). Studies by ETF (2020, 2024) and Caesar (2023), consistently identify shortages in green and digital competencies across shipbuilding, ports, offshore energy, and maritime transport value chains. More recent organizational surveys further confirm substantial skills and training gaps, particularly in areas related to digital technologies, environmental compliance, and sustainability management (Boile and Perra, 2025).

Despite the growing body of literature on maritime workforce development, most existing studies remain qualitative, sector-level, or focused on specific subsectors of the maritime economy. Limited attention has been devoted to systematically quantifying the green and digital content of individual maritime occupations and linking these characteristics to labor-market demand. This study addresses this gap by combining ESCO-based Twin Skills metrics with firm-level survey evidence to identify the occupations, skills, and educational requirements that are most critical for supporting the maritime sector's Twin Transition. By doing so, it provides a more granular understanding of workforce constraints and generates actionable insights for education, training, and policy development.

The purpose of this study is (i) to identify the green and digital skills associated with fundamental maritime professions, and (ii) to establish evidence-based priorities for educational, training, and workforce policies that facilitate the Twin Transition and the circular economy. The methodology integrates three components: (i) occupational and skills classification using the ESCO dataset version 1.1.1., (ii) algorithmic scoring of green and digital skill intensity based on the Twin Skills framework, and (iii) firm-level survey validation. This design allows the analysis to move beyond qualitative assessments toward a reproducible and transparent skills-intelligence pipeline.

2.1 Data sources and inclusion criteria

The initial phase involved the concentration of the maritime value chain's primary sectors. We conducted a comprehensive analysis of the marine industry, attempting to classify it into specific sectors by utilizing a variety of authoritative sources in the field of maritime studies and industry reports, including the (IMO, 2024; Stopford, 2009; UNCTAD, 2023). We identified 10 sectors as presented in Table 1. However, Maritech Talent expert group decided to focus on five out of these 10 sectors for this study, namely, (a) Shipping, (b) Ports and terminals, (c) Shipbuilding and ship repair, (d) Maritime logistics and supply chain management, and (e) Marine technology and equipment.

Table 1. Sectors within the maritime industry.

The analysis on the occupations and skills associated with these five sectors relies on the ESCO framework, which links occupations to structured sets of skills and knowledge elements across the European labor market. ESCO encompasses a total of 3,008 professions at Level 0. It is based on the International Standard Classification of professions (ISCO-08), which provides the hierarchical framework for ESCO's occupations pillar. Occupations are categorized into four levels: Level 1, Level 2, Level 3, and Level 4. Each level corresponds to a different number of occupation groups: 10 groups for Level 1, 42 groups for Level 2, 126 groups for Level 3, and 426 groups for Level 4. ESCO's skills pillar offers an extensive inventory of knowledge, skills, and competences that are pertinent to the European labor market. The dataset consists of 13,896 concepts, including 10,831 skills/competences and 3,059 knowledge concepts, organized in a hierarchical framework with four sub-classifications.

In ESCO v1.1.2, the skills pillar is organized in a hierarchical structure that consists of four sub-classifications: Knowledge, Language skills and knowledge, Skills and Transversal skills. The skills pillar in the ESCO database differentiates between skill/competence concepts and knowledge concepts by specifying the skill type. There is no differentiation between skills and competences. The Skills and Knowledge concepts are categorized into three levels: Level 1, Level 2, and Level 3. Level 1 corresponds to eight groups of skills and 11 groups of Knowledge Concepts. Level 2 corresponds to 74 groups of skills and 29 groups of Knowledge Concepts. Level 3 corresponds to 296 groups of skills and 86 groups of Knowledge Concepts.

The ESCO system also identifies skills categorized as green to facilitate the transformation of the EU labor market toward a more environmentally sustainable model (European Commission, 2022). In order to develop and deploy the net-zero technologies necessary to achieve climate neutrality by 2050, Koundouri et al. (2023) sought to identify the new set of Green and Digital Skills that will define the present and future course of action required to skill and upskill individuals within the EU and beyond.

Green skills are defined by the European Center for the Development of Vocational Training (Cedefop) as “the knowledge, abilities, values, and attitudes required to reside in, foster, and develop a resource-efficient and sustainable society” (CEDEFOP, 2012). Green skills are the skills required to mitigate environmental impacts and facilitate economic restructuring in order to achieve cleaner, more climate-resilient, and efficient economies that maintain environmental sustainability and offer acceptable work conditions. On the other hand, digital skills are a collection of skills that enable individuals to access and manage information through the use of digital devices, communication applications, and networks. They allow individuals to generate and distribute digital content, communicate, collaborate, and resolve issues in order to facilitate effective and innovative learning, work, and social activities (UNESCO, 2018). Entry-level digital skills, which are fundamental functional skills necessary for the basic operation of digital devices and online applications, are widely regarded as a critical element of a new set of literacy skills in the digital era, in addition to traditional reading, writing, and numeracy skills. Higher-level abilities that enable users to leverage digital technologies in transformative and empowering ways, such as the utilization of artificial intelligence (AI), machine learning, and big data analytics, are located at the advanced spectrum of digital skills (Koundouri et al., 2023).

A systematic review was conducted to map the ESCO occupations (level 3-−136 occupation groups) onto the five maritime sectors. Occupations were included if they met the following three criteria: (i) Appeared in the five selected maritime sectors (shipping, ports, shipbuilding, logistics, and marine technology); (ii) existed at ESCO Level-3; and (iii) had at least one green or digital ESCO skill attached, based on Koundouri et al. (2023) classification. The evaluation resulted in the identification of 33 occupations. These occupations were subsequently divided into two categories: “blue-collar” and “white-collar” jobs. “Blue-collar” workers are responsible for physically demanding manual tasks in manufacturing, construction, mining, and maintenance, and they may work outdoors or operate heavy equipment. “White-collar” professionals may work at desks in clerical, administrative, management, or executive roles. White-collar workers seldom engage in physical labor, in contrast to blue-collar workers (Investopedia, 2024).

Then, a structured survey shared with 150 organizations in Bulgaria, Cyprus, and Greece, of which 33 passed quality filters and were used for analysis, was designed. The survey was distributed via Survey Hero¹ and remained open for 3 months, from April to June 2024, in line with the timeline of the MariTech Talent project. The survey was divided into four sections and collected data on personal and organizational characteristics, as well as occupations and skills needs. It evaluated the presence of these 33 occupations on the payroll, the challenges associated with recruiting employees within these groups, and the level of interest in full-time employment within these groups. The top green and digital skills (level 3) identified by Koundouri et al. (2023) were employed to evaluate the most critical Green and Digital skills gaps that should be addressed by educational/training programs for the maritime sector. In addition, other questions addressed the frequency with which the skills and training requirements of their employees are reviewed, the vacancies that are currently available, the challenges in replacing vacant positions and the minimum education and training requirements for each occupational group for the above-mentioned occupations.

2.2 Model architecture: ESCO-based twin skills scoring

The occupational scoring framework applied in this study is based on a transparent, rule-driven methodology rather than on opaque machine-learning techniques. Each occupation is characterized through the structure of the ESCO classification, which links jobs to a detailed set of skills and knowledge elements. Using the Twin Skills taxonomy, these elements are labeled as green, digital, or jointly green and digital. The relative weight of these categories within each occupation is then calculated by comparing the number of tagged skills with the total number of skills associated with that occupation, yielding three complementary indicators that reflect its environmental, technological, and combined green–digital orientation (see Equation 1).

TwinSkillScorei=∑j=1Sgreen & digitalj+ ∑j=1kgreen & digitalknowledgejS+k×100(1)

Where S, number of Skills related to the ith Occupations or Skills group and k, number of Knowledge Concepts related to the ith Occupations or Skills Group.

This procedure allows occupations to be compared in a consistent and replicable way across sectors and countries. Because all classifications rely on publicly available ESCO labels and a clearly defined tagging scheme, the scoring process can be reproduced or audited by other researchers using the same data sources. At the same time, the method avoids dependence on proprietary algorithms or subjective expert weighting, ensuring that results are driven entirely by the underlying structure of the occupational and skills data.

2.3 Validation and cross-checking

Two validation layers were applied. First, an internal validation was performed with the occupational scores being checked against ESCO skill hierarchies and sector relevance from maritime desk research (IMO, UNCTAD, and Stopford). This ensured that occupations with high environmental or technological content scored higher, as expected. The external validation was achieved via survey responses on hiring difficulties, demand for full-time jobs and required education for each occupation, which were statistically compared with Twin Skill scores. A positive correlation between green-digital intensity and labor-market demand confirms the model's empirical validity.

2.4 ESG and ethical safeguards

To address ethical and methodological risks, several safeguards were embedded in the analytical design. Potential bias is mitigated by relying on ESCO classifications, which are publicly curated and subject to EU-level validation and auditing. Opacity is avoided by using simple, transparent ratio-based scoring rather than black-box machine-learning models, allowing all results to be traced directly to their underlying data. The risk of discrimination is eliminated because the analysis does not use any personal, demographic, or individual-level information, focusing exclusively on occupations and skills. Finally, reproducibility is ensured because all inputs—including ESCO data and the Twin Skills taxonomy—are openly available or fully documented, enabling the analysis to be independently replicated.

3 Results and discussion

3.1 Descriptive statistics

The results were analyzed using the same methodology derived from Koundouri et al. (2023), who created a framework to categorize occupations and skills according to their degree of “Greenness,” “Digitalization,” and “Greenness and Digitalization” by utilizing the aforementioned setup and the classifications and hierarchies provided by the ESCO API. The calculation of a score, which is defined as the proportion of green, digital, and jointly green and digital skills and knowledge concepts in each occupation or occupation group, is a component of their data-driven methodology. The score spans from 0 to 100.

Major industry stakeholders, such as associations, government departments, and large shipping firms located in these three countries, were among those who participated in the survey. Their responses gave significant and representative viewpoints on the issues that the sector is currently facing and the requirements that it will have in the future. A total of 33 responses were utilized for the analysis after a data cleansing process in which we eliminated respondents with a very low response time, response inconsistencies, and very low variance across the various questions. Table 2 displays the frequency distribution of socio-demographic characteristics of the sample. The frequency distribution of the socio-demographic characteristics of the sample shows that it is sufficiently heterogeneous. The study sample comprised more females (60%) and, consequently, fewer males (40%). In terms of age, the frequency distribution across the five categories is quite balanced. However, people aged less than 25 were under-represented (4%). Furthermore, the majority of the respondents hold a master's degree or an MBA (60%), while 32% have a PhD, thus implying an under-representation of the less educated people. Lastly, the majority of respondents are employed in a freelance status or in a position of top or intermediate management.

Table 2. Socio-demographic profile of the survey respondents.

Table 3 illustrates the organization information statistics of the survey sample. The heterogeneity of the organizations' profiles is evident in their frequency distribution. The sample of the survey consisted of a greater number of responses from Bulgaria (50%), compared to a quarter from Greece and Cyprus, respectively. The frequency distribution across the five categories is quite balanced in terms of the number of personnel within the organization, as defined by OECD (2020). Nevertheless, the majority seems to be small and medium-sized enterprises (SMEs) that employ fewer than 250 people (60%), while large enterprises are well-represented (28%). There are 16.5% (weighted average) of employees who are under the age of 30.

Table 3. Organisational profile of the survey respondents.

Additionally, the ports and terminals sector is over-represented, while the shipbuilding and ship repair sector is under-represented. There are several studies showing that ports have been at the forefront of implementing EU green and digital policies, often earlier than shipbuilding firms, because ports are directly exposed to EU environmental regulations, logistics digitalization initiatives, and reporting requirements. For example, ESPO (2024) finds that environmental sustainability, energy transition, digitalization, and smart-port technologies are among the highest investment priorities for European ports, while another study argues that ports are becoming digital innovation hubs through the adoption of automation, digital platforms, IoT, and smart logistics systems, driven by both competitiveness and regulatory requirements (Heilig et al., 2017).

The majority of respondents (62.5%), consisting primarily of representatives from shipping companies and port authorities, indicated that they are unaware of the existence of an Environmental, Social, and Governance (ESG) report within their organization. This finding may indicate either limited ESG reporting practices or insufficient internal communication of ESG-related information, although the survey does not allow the underlying reason to be determined. This is in line with a study by Aguinis and Glavas (2019) who argue that organizations often engage in sustainability reporting without effectively communicating sustainability objectives and performance internally to employees.

The potential consequences for organizations operating in national (40%), European (23.3%), and global (33.3%) markets are substantial due to the lack of awareness regarding ESG. Companies that exhibit low awareness of or limited engagement with ESG reporting may face increasing challenges in accessing investment, participating in sustainable value chains, and meeting the expectations of regulators, customers, and other stakeholders. As ESG considerations become more deeply embedded in corporate governance, financing decisions, and supply-chain requirements, organizations that lag behind in ESG disclosure and performance may be at a competitive disadvantage (Koundouri et al., 2024). This knowledge deficit could impede competitiveness, restrict access to funding, and generate reputational risks in European and global markets, where ESG regulations and sustainability standards are more stringent. Additionally, organizations that neglect to incorporate these practices may encounter challenges in expanding beyond national markets and satisfying the sustainability expectations of international stakeholders as ESG compliance becomes a critical criterion for clients, investors, and regulatory bodies.

3.2 Demand for white- and blue-collar jobs in the maritime industry

Figures 1, 2 present the demand for white- and blue-collar jobs, respectively. The respondents were requested to indicate whether they concurred with the following statements for each occupational group: (A) This occupational group is represented among the employees of my organization; (B) My organization is experiencing difficulty in locating employees within this occupational group; and (C) My organization is actively seeking full-time employment within these groups. The results are presented as a heatmap in which darker shades represent higher response frequencies and lighter shades represent lower response frequencies. All indicators use the same 0–10 scale, allowing direct comparison across occupational groups and survey dimensions. Almost all white- and blue-collar occupations are represented within the respondents' organizations, with the exception of Business Services Managers, which validates the initial desk work mapping of “blue” occupations for the five selected sectors. The open-ended question regarding the presence of any additional occupational groups among employees of their organization did not indicate any new occupational group of Level 3.

As we can see, in Figure 1, the majority of respondents agree that almost all indicated occupations can be found within their organizations, which shows that the organization employs individuals from these occupational groups. This may indicate that the organizations possess the requisite knowledge and skills within the team, which could potentially enhance operational efficiency and expertise. In regard to the question B, a prospective skills shortage in the labor market for this specific occupational category is indicated by the high levels of agreement with this statement. This could demonstrate that the demand for these positions exceeds the supply of qualified candidates. The organizations that seek these professionals, such as business service agents, engineering, finance, IT or PR professionals, may be prompted to consider strategies for talent acquisition, such as investing in training programs for prospective employees, offering competitive compensation or enhancing recruitment efforts, in light of these findings.

Finally, the last column shows if the organizations are seeking full-time employment within these categories. Here, we see a low level of agreement. One possible explanation, supported by previous maritime workforce studies, such as Theotokas et al. (2024), is a growing reliance on subcontracting and project-based employment or a lack of available positions. However, for legal professionals, we observe an active recruitment strategy, which signifies that the organizations acknowledge the significance of these roles in their operations.

Responses in Figure 2, on the other side, exhibit a substantial degree of variation (with some individuals disagreeing), which may indicate a lack of diversity in skills or a requirement for training and development in these specific occupations. Here, we observe that fewer than 40% of respondents confirm statements A and B, which can be attributed to underrepresentation in the workforce, hiring challenges, low demand for full-time roles, or even a shift toward part-time, freelance, or temporary contracts. This is in line with the findings of the MATES project (2019), which identified that several maritime technical occupations suffer from limited workforce availability due to aging workers, insufficient recruitment of younger personnel, and weak attractiveness of maritime careers. Low agreement on the first statement suggests that these professions are either underrepresented or not a strategic focus, potentially impacting the organization's ability to innovate or meet operational needs. As Bessen (2014) argues, when firms cannot access workers with the required skills, they often struggle to implement new technologies and organizational innovations, which can hinder productivity and competitiveness.

The low confirmation of statement B may indicate either limited recruitment activity or difficulties in attracting suitably qualified candidates. Such challenges are commonly associated with skills mismatches, shortages of specialized competencies, and changing occupational requirements resulting from technological and organizational transformation (Bessen, 2014; Malik and Venkatraman, 2017). Low confirmation of statement C may indicate limited demand for expanding these occupational groups through permanent employment. This could reflect a shift toward more flexible workforce arrangements, including subcontracting, temporary contracts, or project-based employment, driven by changing organizational needs, technological developments, or budgetary constraints. Theotokas et al. (2024) show that shipping companies increasingly obtain specialized digital expertise through external providers and project-based arrangements rather than through permanent in-house staffing. Overall, these findings highlight the need for organizations to address these challenges and ensure a diverse workforce for innovation and operational success.

3.3 Classification of green and digital occupations in the maritime industry

By utilizing the setup presented above and the classifications and hierarchies provided by the ESCO API, we have created a framework that categorizes occupations according to their level of “Greenness,” “Digitalization,” and “Greenness and Digitalization.” We applied the data-driven methodology used in Koundouri et al. (2023), which is available in Appendix—Technical and involves the calculation of a score that ranges from 0 to 100. This score is defined as the proportion of green, digital, and jointly green and digital skills and knowledge concepts in each occupation or occupation group. Table 4, which adheres to our methodology, displays the classification of the top 15 occupations at Level 3 in accordance with their scores on “Greenness,” “Digitalization,” and “Greenness and Digitalization,” individually. The vast majority of the top green and digital occupations are white-collar and correspond to the ESCO groups 1, 2, and 3.

Table 4. Top 15 green, digital and green and digital occupations in the maritime industry.

3.4 Highly ranked occupations and their corresponding skills

The findings of Sections 4.2 and 4.3 suggest a statistically significant and unambiguous positive correlation between the demand of occupations and their degree of digitalization and greenness. Recent labor-market evidence points to a sustained upward trend in demand for both digital and environmentally related competences over the past decade (CEDEFOP, 2024b). Based on the survey results regarding the maritime industry's requirements, Table 5 displays the top 10 of the most sought-after maritime occupations. To identify the skills associated with each occupation, the study utilized the ESCO Skills–Occupations Matrix 3.3 (ESCO, 2026), which maps 296 Level 3 skills and knowledge concepts to 125 Level 3 occupation groups. The matrix provides a weighted representation of the relationship between occupations and skills, allowing the identification of the most relevant competencies for each occupational group. These skills were then matched against the ESCO-based Twin Skills classification framework to identify their sustainability and digitalization content. Skills classified as digital are marked with (^*), those classified as green with (^**), and those classified as simultaneously green and digital with (^***). Because the analysis was conducted at Level 3 of both the occupation and skill hierarchies, the resulting skill profiles capture a relatively detailed but still comparable representation of occupational requirements across sectors.

Table 5. Top 10 ranked maritime occupations and their most critical associated skills (^*digital skill; ^**green skill; ^***green and digital skill), according to the ESCO (2026) assessment.

The results reveal a clear distinction between occupations, which are primarily associated with analytical, managerial, regulatory, and knowledge-intensive competencies, and technical occupations, which rely more heavily on operational, maintenance, and safety-related skills. Engineering professionals are strongly linked to research, design, and computer-aided modeling activities, while finance professionals require expertise in financial analysis, risk management, and resource allocation. Similarly, occupations in sales, marketing, legal services, and business support are characterized by competencies related to communication, compliance, planning, stakeholder engagement, and organizational coordination, reflecting the increasing complexity of the regulatory and commercial environment in which maritime firms operate.

Beyond occupation-specific requirements, several skills appear repeatedly across multiple occupational groups, suggesting the existence of a common competency foundation for the maritime workforce. For example, complying with health and safety procedures is identified among the most important skills for physical and engineering science technicians, machinery mechanics and repairers, and mining and mineral processing plant operators, highlighting the safety-critical nature of maritime operations. Likewise, installing wooden and metal components appears across several technical occupations, reflecting the continued importance of maintenance, repair, and infrastructure-related activities within maritime value chains. Other recurring competencies, including interpreting technical documentation and diagrams, maintaining operational records, conducting academic or market research, and operating lifting or moving equipment, demonstrate that modern maritime work increasingly combines technical expertise with documentation, monitoring, analytical reasoning, and operational coordination. The repeated appearance of these skills across different occupations indicates that workforce adaptability and transferable competences are becoming as important as occupation-specific expertise.

The table also reveals the growing significance of twin competencies in the maritime sector. Of the 42 skills identified across the 10 most demanded occupations, approximately 83% are classified as green, digital, or simultaneously green and digital according to the ESCO-based Twin Skills framework. More specifically, 26% are digital skills, 31% are green skills, and 26% belong to both categories. Green skills, such as ensuring compliance with legislation, implementing new procedures, managing budgets, and promoting products and services, are particularly prominent in occupations related to legal services, business support, sales and marketing, and technical maintenance. Digital skills are concentrated in engineering and ICT-related occupations through competencies such as computer-aided design, risk analysis, protecting ICT devices, managing digital data, setting up computer systems, and resolving computer problems. The presence of jointly green and digital skills in engineering, technical maintenance, and operational occupations suggests that the maritime transition is not characterized by separate environmental and technological transformations, but by their increasing integration within day-to-day work activities.

These findings are consistent with previous research highlighting the emergence of hybrid skill profiles in response to the Twin Transition. Studies conducted within the (MATES Project 2019, 2022), the European Training Foundation (ETF, 2024), and (CEDEFOP, 2024a) have similarly found that maritime employers increasingly require workers who combine technical expertise with environmental awareness, regulatory compliance, data management, and problem-solving capabilities. The results therefore support the argument that future workforce development strategies should move beyond traditional occupational training and focus on developing integrated skill sets that combine digital competences, sustainability-related knowledge, and transferable transversal abilities. Such skill combinations are likely to become a critical determinant of workforce resilience and competitiveness as the maritime sector continues its transition toward climate neutrality and digital transformation.

3.5 Twin skills-gap

In the final segment of the survey, participants were asked to identify the isolated green and digital skills that they believe that are lacking within their organization and should be the focus of educational/training programs, as identified in Koundouri et al. (2023). Table 6 displays the order based on which isolated twin skills are demanded by the industry. As we can see “complying with environmental protection laws and standards,” “environmental protection technology,” and “monitoring environmental conditions” are the dominant green and digital skills in the maritime industry as a whole. The shipping industry is a significant contributor to environmental pollution, which includes the discharge of hazardous substances into oceans, oil spills, and carbon emissions. It also poses a threat to marine life by causing disturbances to marine habitats, noise pollution, and the discharge of ballast water. Specialized expertise in environmental protection measures is necessary to adhere to more stringent environmental regulations, including the International Maritime Organization's MARPOL Convention and emission control areas. In order to mitigate environmental impact, the maritime sector is implementing new technologies, including energy-efficient ship designs, alternative fuels, and emission-reducing systems. Additionally, ship operations are being optimized through the implementation of digitalization and monitoring, necessitating that employees possess both digital and green competencies. The demand for green and digital skills in the shipping sector is being driven by sustainability demands and alignment with global sustainability objectives.

Table 6. Top 10 green and digital skills for the maritime industry, as revealed by sector experts.

As shown in Table 6, many of the prioritized green and digital competencies are overlapping with those in Table 5. Specifically, competencies related to digital data management, ICT systems, analytical thinking, engineering design, and compliance are present in both lists, suggesting that the maritime sector's most demanded occupations are increasingly shaped by the same green and digital capabilities that maritime organizations identify as training priorities. This supports the argument of Koundouri et al. (2023) and CEDEFOP (2024b) that workforce shortages associated with the Twin Transition are emerging not only at the occupational level but also at the level of underlying competency domains, reinforcing the need for targeted education and training interventions.

3.6 Bridging the gap between skills and demand for education

Figure 3 indicates the minimum education required for the 10 most demanded (both white- and blue-collar) jobs. The results are presented as a heatmap, where darker shades represent a higher number of responses for each educational category and lighter shades represent fewer responses. A common 0–10 response scale is used across all educational levels to enable direct comparison between occupational groups. Advanced degrees are often required for certain professional roles due to their complexity, specialized knowledge, and critical thinking skills. Engineering professionals, such as civil, chemical, and mechanical engineering, require a Master's degree for specialized study in complex areas like systems design, materials science, and project management. Finance professionals, particularly in investment banking, risk management, and economic analysis, often require an MBA or Master's degree in finance, economics, or accounting. Sales, Marketing, and Public Relations professionals often require MBAs or other advanced business degrees for higher-level roles, covering strategic skills like market analysis, consumer behavior, and data-driven decision-making. ICT Operations and User Support Technicians, particularly those involving system design, network security, or data management, increasingly demand specialized MSc degrees in information technology or cybersecurity. Legal professionals, like JDs, LLMs, require advanced degrees for a sophisticated understanding of the law, legal precedents, and courtroom procedures.

However, a bachelor's degree or vocational education and training (VET) degree is typically required for roles such as Physical and Engineering Science Technicians, Mining and Mineral Processing Plant Operators, Machinery Mechanics and Repairers, and Transport and Storage Laborers. These positions require technical skills and specialized knowledge to perform safely and effectively. Physical and Engineering Science Technicians assist engineers and scientists in conducting tests, collecting data, and analyzing results. Mining and Mineral Processing Plant Operators handle heavy machinery, complex equipment, and hazardous materials, requiring training in mining technology, environmental safety, and machinery operations. Machinery Mechanics and Repairers have a detailed understanding of mechanical systems, hydraulics, and electronics, requiring hands-on training and theoretical knowledge for troubleshooting and maintenance. Transport and Storage Laborers manage logistics, organize inventory, and handle materials, often requiring training in forklift operation, warehousing technology, and inventory software.

The MariTech Talent program is intended to provide a standardized service for green and digital skilling and upskilling that is tailored to the industry's distinctive needs. It also endeavors to make a substantial contribution to the “human-centered and ethical development of digital and industrial technologies” destination. It focusses on the implementation of a systemic approach to the utilization of technologies in industry and society, with a particular emphasis on the needs of maritime companies and their personnel. This training approach is innovative in that it standardizes the development of tandem skills and competencies through technological adoption, thereby promoting the modernization of the maritime industry.

4 Policy and curriculum implications

The results demonstrate that the maritime labor market is undergoing a structurally uneven Twin Transition. White-collar occupations such as engineering, finance, ICT, legal, and business services display both high demand and high green-digital intensity, yet, firms report persistent difficulties in recruiting suitably qualified candidates. At the same time, blue-collar roles that are critical for the physical operation of vessels, ports, and industrial systems, such as machinery mechanics, technicians and plant operators, are under-represented, weakly demanded, and could be increasingly shifted toward flexible or non-permanent employment. This combination of strong skill intensity, recruitment difficulty and fragmented employment patterns signals a growing mismatch between workforce supply and the operational needs of a decarbonising and digitalising maritime sector.

These mismatches can be interpreted through the lens of the European Skills Index (ESI), a composite indicator developed by CEDEFOP (2024a) to assess the performance of skills systems across the European Union. The ESI is structured around three interrelated pillars: skills development, which captures the capacity of education and training systems to generate relevant competences; skills activation, which reflects the extent to which labor markets create opportunities to use these skills; and skills matching, which measures how well workers' competences align with employers' needs. These pillars are operationalised through 15 indicators drawn from multiple international sources (see Figure 4). The patterns observed in this study suggest weaknesses across all three dimensions in the maritime sector, particularly for occupations with high green and digital content, indicating that education systems, labor markets and matching mechanisms are not evolving in step with technological and environmental change.

The Twin Skills classification further reinforces this diagnosis. Occupations with the highest green and digital intensity are overwhelmingly concentrated in white-collar roles, especially in engineering, ICT and managerial functions, while blue-collar occupations also carry significant digital and environmental skill requirements but receive far less structured training investment. This creates a dual risk: firms face shortages of advanced green-digital specialists, while operational staff responsible for implementing energy-efficient equipment, environmental monitoring and automated systems remain insufficiently supported. In ESI terms, this reflects both a development gap—insufficient provision of appropriate training—and a matching gap, where the skills produced do not fully correspond to evolving job requirements.

From a curriculum and policy perspective, these findings imply that maritime education and training must shift from broad, undifferentiated upskilling toward occupation-specific Twin Skills pathways. Engineering, finance, ICT, legal, and business curricula should embed sustainability regulation, emissions analytics, and data governance as core components, while vocational and technical programs must integrate electronics, automation, environmental technologies and digital data handling. The combined use of ESCO-based Twin Skills metrics and the ESI framework enables policymakers to identify whether deficiencies arise from weak training provision, limited labor-market absorption, or poor skills matching, thereby allowing resources to be targeted where they will most effectively support decarbonization, digitalization, and the long-term sustainability of the maritime sector.

5 Conclusions

The Twin Transition is a comprehensive strategy for addressing the multifaceted challenges of sustainability, as it integrates digital and ecological initiatives into a single transformation pathway. In addition to fostering a sustainable and resilient future across multiple sectors, including the strategically important maritime industry, it is central to achieving the European Union's climate and energy objectives. This study extends existing policy and academic perspectives by demonstrating that the Twin Transition is a workforce transformation that occurs unevenly across occupations in addition to a technology or regulatory change. The maritime sector is particularly affected by this dual transformation, as it must simultaneously decarbonise and digitalize in order to remain compliant, competitive, and operationally viable.

This transition is essential for the achievement of broader sustainability goals, as the maritime sector remains a significant contributor to global greenhouse gas emissions. The adoption of digital and green technologies is therefore not merely advantageous but increasingly unavoidable. These changes are already reshaping the operational landscape of the industry through the uptake of renewable fuels, the deployment of smart port systems, and the growing reliance on automated tools for emissions monitoring, reporting, and route optimization. However, their successful implementation relies on the availability of workers who are able to operate, interpret and govern them. In other words, skills are a binding constraint on the sector's decarbonization pathway.

This study aimed to investigate three interconnected research questions: the maritime jobs now in highest demand, the occupations with the greatest concentration of green and digital skills, and the minimal educational qualifications necessary to fulfill these demands. The survey results indicate that the most in-demand positions encompass Business services agents, Engineering professionals, Finance professionals, Sales, Marketing and Public Relations professionals, ICT operations and user support technicians, Legal professionals, Physical and Engineering science technicians, Mining and mineral processing plant operators, Machinery mechanics and repairers, and Transport and storage laborers. The integration of these results with ESCO-based Twin Skills rating indicates that high-demand occupations exhibit the highest intensity of green and digital skills, hence affirming a structural correlation between labor market pressures and the Twin Transition.

The analysis also highlights a pronounced skills gap in the maritime workforce, particularly in competencies related to environmental compliance, digital data management and automated systems. A workforce proficient at navigating increasingly intricate regulatory and technological environments is essential for marine companies to effectively execute decarbonization and digitization initiatives. Rather than broad, generic upskilling, the findings point to the need for occupation-specific Twin Skills pathways, especially for roles where high green-digital content coincides with recruitment difficulty. The identification of priority skills for the top 10 demanded occupations (Table 5) provides a concrete basis for aligning education and training provision with real market needs.

The maritime sector is therefore not only experiencing a technological transformation, but also a reconfiguration of its labor structure. Occupations related to engineering, finance, ICT, and law increasingly necessitate advanced qualifications for regulatory compliance, data-driven operations, and sustainability governance, while technical and operational roles demand updated vocational pathways to facilitate electronics, automation, and environmental technologies. The limited demand for blue-collar jobs further amplifies this imbalance, risking a divide between highly trained green-digital specialists and a fragmented operational workforce. Aligning education levels, training formats and skills content with these realities is essential if the maritime industry is to realize a sustainable blue economy that combines economic performance, environmental protection, and technological innovation.

A limitation of the ESCO-based mapping approach is that occupation–skill relationships are inherited directly from the ESCO classification and therefore reflect labor-market patterns across all economic sectors. While this ensures consistency and comparability, it may occasionally generate skill associations that are less relevant to the maritime context. Consequently, the identified skills should be interpreted as indicators of occupational skill profiles rather than as definitive statements about the exact competencies required in every maritime workplace. Future research could refine the methodology by incorporating sector-specific expert validation or weighting procedures to improve the contextual relevance of the occupation–skill mapping.

In order to evaluate and improve the ESCO-based Twin Skills scoring against bigger and more varied datasets and enable predictive validation of the relationship between skills profiles and labor-market and sustainability outcomes, future research should build on the current framework by integrating machine-learning techniques. By demonstrating how variations in national training programs and labor-market organizations influence the speed and efficacy of the Twin Transition among maritime economies, cross-country benchmarking would enhance the analysis even more. By elucidating the manner in which particular professions, training trajectories, and skill sets impact model outputs, the incorporation of explainable artificial intelligence techniques may increase transparency and promote more responsible investment and policy choices. Lastly, future research could directly evaluate how workforce capabilities translate into quantifiable environmental outcomes by connecting occupational skills profiles to actual emissions and energy-efficiency performance at the firm or port level. This would strengthen the empirical basis of skills-based decarbonization strategies.

Correction note

A correction has been made to this article. Details can be found at: 10.3389/frevc.2026.1949874.

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Footnotes

Edited by: Emy Zecca, University of Ferrara, Italy

Reviewed by: Riccardo Colantuono, University of Ferrara, Italy

Fabiola Onofrio, University of Ferrara, Italy

Footnotes

Available online at: https://www.surveyhero.com/c/7pyp3zqf.