Optimizing Sustainable Port Logistics in Spanish Ports with Emerging Technologies

Abstract

Maritime transport is essential to global trade, but port activities have a substantial environmental impact. This study develops and applies a structured evaluation framework—combining SWOT-CAME (Strengths, Weaknesses, Opportunities, and Threats–Correct, Adapt, Maintain, and Explore) analysis with Delphi Panel validation—to assess the digital transformation readiness of Spanish ports and to prioritize strategic actions that align emerging technologies with sustainability and operational objectives. Through expert-driven analysis, this study identifies and ranks strategic factors across four categories: strengths-opportunities (SO), strengths-threats (ST), weaknesses-opportunities (WO), and weaknesses-threats (WT). Among the highest priority actions are strengthening cybersecurity, implementing workforce training in digital competencies, and promoting public–private collaboration to support technology adoption. The resulting strategic map provides port authorities with a practical decision-making tool that supports the integration of technologies such as artificial intelligence, blockchain, and the Metaverse in alignment with the Sustainable Development Goals (SDGs). Future research could further explore the cost-effectiveness and long-term sustainability impact of these digitalization strategies.

1. Introduction

Maritime transport is the backbone of global trade, handling approximately 80% of international goods [1]. However, despite its economic significance, the maritime industry is one of the largest contributors to greenhouse gas emissions (GHGs), energy consumption, and environmental pollution [2]. Ports, as critical nodes in global supply chains, must transition towards sustainable operations to comply with international environmental regulations and reduce their ecological footprint. The United Nations Sustainable Development Goals (SDGs) emphasize the importance of decarbonization, innovation, and digital transformation in the logistics sector, particularly under SDG 9 (industry, innovation, and infrastructure), SDG 12 (responsible consumption and production), and SDG 13 (climate action) [3]. Consequently, achieving efficient, resilient, and low-carbon port logistics has become a priority for both industry stakeholders and policymakers.

The implementation of emerging digital technologies is revolutionizing logistics and operations management in ports, offering innovative pathways to sustainability. Among these technologies, the Metaverse, a virtual, data-driven environment powered by artificial intelligence (AI), the Internet of Things (IoT), and digital twins, has the potential to enhance port efficiency, resource allocation, and predictive decision making [4]. The integration of Metaverse applications into port logistics enables real-time monitoring of vessel traffic, digital twin simulations of cargo flows, and virtual training for personnel, all of which contribute to optimizing operations while minimizing environmental impact [5].

Despite the increasing attention towards port digitalization, most existing studies focus on individual technological applications, such as automation, blockchain, or digital twins [5]. However, there is a lack of comprehensive research that assesses the current level of digital maturity across ports, especially in the Spanish port system. This study aims to fill this gap by diagnosing the starting point for digital transformation, identifying the strengths, weaknesses, opportunities, and threats associated with emerging technologies in ports. Unlike previous studies that analyze the impact of a single technology, this research provides a structured assessment of digital readiness, offering a strategic decision-making framework for sustainable port development.

In addition to digital transformation, strategic methodologies are fundamental in diagnosing the current state of port digitalization and evaluating potential pathways for sustainable transformation. This study provides a structured framework to assess the readiness of Spanish ports for digitalization, identifying existing gaps and strategic priorities before implementation.

The SWOT-CAME (strengths, weaknesses, opportunities, threats—correct, adapt, maintain, explore) methodology, an advanced adaptation of the SWOT analysis framework, has proven to be a powerful tool for evaluating port sustainability, identifying competitive advantages, and structuring strategic actions [6]. By assessing strengths, weaknesses, opportunities, and threats (SWOT) and formulating corrective, adaptive, defensive, and offensive strategies (CAME), this approach enables data-driven decision making for long-term sustainability. Previous studies have demonstrated the effectiveness of SWOT-CAME in port planning, particularly when combined with expert-driven methods such as the Delphi Panel and Likert-scale questionnaires.

The CAME framework consists of four strategic categories: correct, adapt, maintain, and explore. These categories provide a structured approach to transforming the SWOT analysis into actionable strategies. To ensure consistency throughout the study, these terms are used uniformly instead of alternative descriptors such as corrective, adaptive, defensive, and offensive, which could lead to ambiguity in the interpretation of strategic actions.

Despite the increasing focus on port digitalization, most existing studies address specific technologies such as blockchain, artificial intelligence, or digital twins in isolation. However, there is a lack of research that systematically evaluates the overall readiness of ports for digital transformation, particularly within the Spanish port system. The absence of a structured assessment framework creates challenges for policymakers and port authorities when prioritizing investments and sustainability initiatives. This study aims to fill this gap by providing a comprehensive diagnostic of digitalization in Spanish ports through a strategic evaluation of strengths, weaknesses, opportunities, and threats (SWOT), structured within the CAME methodology. By identifying key strategic factors, this study provides a roadmap for sustainable digital transformation and contributes to the development of structured decision-making processes for port authorities.

This study aims to diagnose the current state of digital transformation in Spanish ports and evaluate the role of emerging technologies (such as AI, blockchain, and the Metaverse) in optimizing sustainability and operational efficiency. Using the SWOT-CAME methodology, this research identifies key strategic pathways for digitalization, providing a structured decision-making framework for port authorities. Using a Delphi Panel with industry experts and quantitative SWOT-CAME analysis, this research examines the current sustainability challenges of Spanish ports, assessing how digitalization can enhance operational efficiency, energy management, and emission reductions. The study also aligns its findings with global sustainability goals, ensuring that the proposed strategies contribute to the broader objectives of climate action and supply chain resilience.

The results of this research will provide key recommendations for policymakers, port authorities, and logistics operators, outlining a roadmap for digital transformation in sustainable port management. By leveraging emerging technologies and strategic decision-making frameworks, this study aims to position Spanish ports as international benchmarks in smart and eco-efficient maritime logistics. Future research should expand on the potential of AI, blockchain, and automation systems in further optimizing sustainability in the port industry.

The aim of this study is to develop and apply a structured evaluation framework—based on the integration of the SWOT-CAME analysis and Delphi Panel validation—to assess the digital transformation readiness of Spanish ports and prioritize strategic actions that align emerging technologies with sustainability and operational goals. This study analyzes the role of emerging technologies (such as artificial intelligence, blockchain, and the Metaverse) in enhancing port digitalization while ensuring sustainability. Using the SWOT-CAME methodology and a Delphi Panel, this research evaluates key factors affecting port digital transformation and provides a strategic framework to guide decision making in sustainable port operations. This study contributes to the existing literature by integrating structured analytical tools to assess digitalization strategies, offering insights into cybersecurity risks, public–private collaboration, and workforce adaptation to technological changes.

Despite growing attention to port digitalization, most studies focus on individual technologies rather than evaluating the overall readiness of ports for digital transformation. Additionally, while strategic planning methodologies exist, there is a lack of structured frameworks specifically designed to assess and prioritize digital adoption in port environments. This study addresses these gaps by developing a comprehensive diagnostic framework that integrates SWOT-CAME with Delphi Panel validation, ensuring that the strategies proposed align with both industry realities and sustainability objectives.

To guide the reader through the study, the remainder of the paper is structured as follows. Section 2 reviews the existing literature on port digitalization, sustainability frameworks, and emerging technologies, highlighting current trends and research gaps. Section 3 details the methodology, describing the SWOT-CAME framework and the Delphi Panel process used for expert validation. Section 4 presents the main results of the analysis and discusses the proposed strategic pathways. Section 5 provides the conclusions, outlines the theoretical and practical implications of the findings, and suggests directions for future research.

2. State of the Art

2.1. Digitalization and Emerging Technologies in Port Sustainability

The Metaverse refers to a virtual, immersive digital environment where real-world logistics operations can be simulated, optimized, and monitored using AI-driven analytics, digital twins, and blockchain technologies. This technology has been increasingly explored in industrial applications, yet its role in port logistics remains largely unexamined. In this study, we leverage the SWOT-CAME methodology to analyze how the Metaverse, alongside other emerging technologies, can contribute to port sustainability and efficiency [4].

Recent literature has begun to explore the application of Metaverse-related technologies—such as immersive virtual environments, digital twins, and real-time data integration—in the logistics and transport sector. For instance, the Port of Rotterdam has developed digital twin simulations that allow for predictive maintenance and operational planning, contributing to lower fuel consumption and increased berth availability [4]. These virtual platforms enable operators to test operational strategies in simulated environments, thus minimizing resource waste and inefficiencies in the real system. Additionally, training programs using VR-based simulations have been shown to reduce errors and improve worker readiness in complex logistics operations [6]. While full integration of Metaverse ecosystems in port logistics is still under development, such tools represent a clear opportunity for reducing emissions, optimizing processes, and improving strategic decision making based on real-time data [5].

Port logistics plays a fundamental role in global supply chains, but its environmental impact has led to growing concerns about sustainability. Ports are responsible for significant greenhouse gas (GHG) emissions, air and water pollution, and high energy consumption [2]. The transition toward eco-efficient port management has become a priority, particularly with international frameworks like the International Maritime Organization (IMO) decarbonization strategy and the European Green Deal, which aim to reduce maritime sector emissions by at least 50% by 2050 [7]. Research has emphasized the need for sustainable port planning, integrating environmental regulations, circular economy principles, and energy-efficient infrastructures [8].

The concept of smart ports has emerged as a key solution for sustainability in maritime logistics. These ports leverage big data, IoT, automation, and AI-driven analytics to optimize operations and minimize environmental impact [9]. The integration of real-time monitoring systems, predictive maintenance, and digital twins enhances efficiency, reducing delays and optimizing energy use [4]. Ports such as Rotterdam, Singapore, and Hamburg have pioneered AI-based automation and blockchain systems to streamline logistics and reduce carbon footprints [10].

Recent studies highlight the potential of emerging technologies, such as blockchain, AI, and the Metaverse, to enhance decision making, improve security, and drive sustainable innovation [11,12]. Meanwhile, AI-driven automation supports energy management and predictive logistics, helping ports anticipate and mitigate congestion and emissions hotspots [13]. The implementation of autonomous vessels and smart energy grids is also gaining attention as part of the decarbonization process [14].

The Metaverse is an innovative digital environment where virtual, augmented, and mixed realities are used to enhance operations, training, and real-time simulations. Its application in port logistics enables virtual management of cargo flows, predictive risk assessment, and remote workforce training [4]. By leveraging digital twins, ports can create real-time operational simulations that optimize supply chain decision making while reducing carbon emissions [15]. Studies indicate that the Metaverse will play a crucial role in future port sustainability strategies, allowing for virtual collaboration between stakeholders and data-driven operational planning [4].

Despite its potential, the digital transformation of ports faces several barriers, including high implementation costs, cybersecurity risks, and resistance to change [16]. Many ports lack the necessary IT infrastructure and expertise to adopt data-driven decision making models effectively [17]. Moreover, concerns over data privacy, interoperability, and standardization present challenges to blockchain and AI adoption [18]. Overcoming these obstacles requires policy support, investment in digital literacy, and public–private collaboration [19].

2.2. Current Research Trends in Sustainable Port Development

This section provides an overview of current research directions in sustainable port development based on recent advancements in digitalization, automation, and green logistics. The studies reviewed here serve as a foundation for identifying key research gaps and positioning the present study within the broader academic discussion.

Methodological frameworks such as SWOT-CAME have been widely applied in strategic planning for sustainable port operations. The SWOT method assesses strengths, weaknesses, opportunities, and threats, while CAME (correct, adapt, maintain, explore) provides structured strategies to overcome challenges and capitalize on advantages [5]. Research has shown that combining SWOT-CAME with expert-driven methods, such as Delphi Panels, enhances decision-making efficiency. This methodology has been successfully used to optimize resource allocation, risk assessment, and sustainability planning in port environments [20].

The alignment of port digitalization efforts with the United Nations’ SDGs is essential for ensuring a balanced approach to environmental, social, and economic sustainability. Key SDGs related to port transformation include SDG 9 (industry, innovation, and infrastructure), SDG 12 (responsible consumption and production), and SDG 13 (climate action) [21]. Studies emphasize the role of public policies and financial incentives in accelerating the transition to green and smart port models [22]. Ports that successfully integrate circular economy principles and digital solutions contribute to resilient and sustainable global trade [23].

Emerging trends suggest that the next frontier in sustainable port logistics will involve AI-driven automation, blockchain-based security, and fully integrated digital twins [24]. Future research should explore the economic viability of the Metaverse in port management, focusing on cost–benefit analyses and scalability of digital solutions [4]. Additionally, further studies on cybersecurity frameworks, standardization policies, and interoperability of smart logistics platforms are crucial to ensuring the long-term sustainability of digitalized ports [25].

2.3. Research Gaps in Sustainable Port Digitalization

Despite the significant progress in port digitalization and sustainability research, several critical gaps remain. First, while studies have explored the role of smart ports and AI in logistics optimization, limited research has examined the economic feasibility and scalability of Metaverse-based applications in port operations [4]. Most existing studies focus on simulation-based models but lack empirical case studies demonstrating real-world implementation, cost efficiency, and return on investment [26].

Second, cybersecurity and data governance issues remain underexplored in the context of digitalized ports. The integration of blockchain, IoT, and digital twins raises concerns regarding data privacy, interoperability, and regulatory compliance, yet current studies lack a comprehensive framework to address these risks [25].

Further research is required to develop standardized security protocols and governance models for secure, transparent, and legally compliant digital port infrastructures [27].

Another gap lies in the human factor in port digitalization. While automation and AI-driven decision making enhance efficiency, research on workforce adaptation, digital training programs, and labor market transformation remains limited [28]. The implementation of Metaverse-based training environments for port personnel offers a promising avenue, yet its effectiveness, adoption rates, and potential for reducing operational risks require further empirical validation [4].

Lastly, although sustainability metrics and SDG alignment are increasingly integrated into port strategies, there is a lack of standardized, quantifiable sustainability performance indicators specifically tailored for digitalized port ecosystems [29]. Future research should focus on developing sustainability assessment models that incorporate energy efficiency, emission reductions, and circular economy principles in the context of smart and digitalized port operations [30].

Addressing these research gaps will be essential for the successful transition toward fully digitalized, AI-driven, and environmentally sustainable ports, ensuring that technological advancements translate into real-world operational improvements while maintaining economic viability and regulatory compliance.

The existing literature provides valuable insights into the role of emerging technologies in port logistics. However, most studies focus on isolated technological applications rather than evaluating the broader digital transformation landscape. Furthermore, while strategic planning methodologies have been explored in other sectors, their application in diagnosing digitalization readiness in ports remains underdeveloped. This study builds upon previous findings by integrating a structured evaluation of digital maturity in Spanish ports, ensuring that digital transformation strategies align with both technological feasibility and sustainability objectives.

To summarize, this study specifically addresses the following research gaps: (1) the lack of a structured assessment of digital transformation readiness in the port sector; (2) the absence of a validated methodology for prioritizing sustainability-related strategies in port digitalization; and (3) the need for expert-based evaluation methods that combine strategic frameworks and decision support tools. By integrating the SWOT-CAME methodology with Delphi Panel validation, this study offers a strategic roadmap that responds directly to these gaps, particularly in the context of Spanish ports.

3. Methodology

The SWOT-CAME methodology was applied as an evaluation framework to assess how emerging technologies influence sustainable port operations. Rather than integrating these technologies, this approach enables a structured analysis of their potential impact, challenges, and strategic adoption pathways. This study involved a Delphi Panel of industry experts who evaluated key sustainability factors in port digitalization. A statistical validation process, including mean and standard deviation analyses, ensured the reliability of responses before finalizing the SWOT-CAME framework. The identified strategies align digital transformation efforts with the Sustainable Development Goals (SDGs), providing a structured decision-making approach for port authorities.

The methodology followed to develop the study is made up of 6 large blocks that are summarized in Figure 1.

The selection of SWOT-CAME corresponds to the strategic factors identified in the SWOT analysis, forming the basis for the strategic response framework, and the Delphi Panel methodology was based on their ability to provide a structured, expert-driven assessment of port digitalization strategies. While various strategic planning methods exist, such as the Analytic Hierarchy Process (AHP) and econometric forecasting models, these approaches primarily focus on quantitative ranking and decision making, making them less suitable for evaluating emerging technologies in an evolving port environment. In contrast, SWOT-CAME integrates qualitative and strategic factors, offering a comprehensive framework that not only identifies strengths and weaknesses but also proposes actionable pathways for digital transformation. The Delphi Panel further enhances the reliability of this analysis by incorporating expert consensus through iterative feedback, ensuring that strategic priorities reflect real-world industry needs. This methodological combination allows for a more holistic evaluation of digitalization readiness, bridging the gap between theoretical technological potential and practical strategic implementation in ports.

3.1. Research Design: Development of the SWOT Matrix

The application of the SWOT-CAME methodology in this study is not merely a theoretical exercise but an essential tool for diagnosing the current state of digital transformation in ports. While SWOT analyses are commonly used in strategic assessments, this research innovates by integrating it with the CAME framework to prioritize actionable strategies tailored to port logistics. Additionally, the use of the Delphi Panel enhances the robustness of the findings by incorporating expert consensus, reducing subjectivity, and validating the identified strategic pathways. Unlike previous studies that analyze digitalization through technical feasibility assessments, this study offers a structured decision-making approach that considers both technological potential and strategic implementation factors.

This study employs a quantitative research approach based on strategic analysis using the SWOT-CAME methodology, with numerical evaluation of strategic factors validated through a Delphi Panel, a focus group, and statistical analysis.

The SWOT-CAME methodology was applied to evaluate the potential impact of Metaverse technologies in port logistics. Unlike previous studies focusing solely on digital twins, this research considers a broader digital ecosystem that includes immersive environments for operational training, AI-driven analytics for real-time decision making, and blockchain-based security frameworks. While digital twins are well-established, the integration of these advanced technologies into a unified Metaverse ecosystem remains underexplored in the port industry.

This methodology aligns with the Strategic Framework of the Spanish Port System, ensuring that the formulated strategies are applicable to the Spanish port context.

3.2. Development of the Square SWOT Matrix

A square SWOT matrix (n × n) was constructed with n strategic factors, categorized into four groups:

• Strengths (S) = {S₁, S₂, …, S_n};
• Weaknesses (W) = {W₁, W₂, …, W_n};
• Opportunities (O) = {O₁, O₂, …, O_n};
• Threats (T) = {T₁, T₂, …, T_n}.

This initial SWOT matrix enables the interaction of each strategic factor with all others, ensuring a comprehensive assessment of the internal and external environment affecting port sustainability.

The selection of SWOT-CAME combined with the Delphi Panel was driven by the need for a structured yet flexible evaluation framework that accommodates both qualitative insights and expert-driven validation. While methodologies such as the Analytic Hierarchy Process (AHP) offer robust multi-criteria decision making, they primarily rely on quantitative pairwise comparisons, which may not capture the complexity of digitalization challenges in port environments. SWOT-CAME enables the identification of key strategic factors while maintaining adaptability in decision making, and the Delphi Panel enhances its rigor by refining expert consensus through iterative rounds. This methodological approach ensures a holistic assessment of digital readiness while allowing for the incorporation of strategic uncertainty and expert judgment.

The construction of the SWOT matrix followed a structured methodology based on international benchmarking and expert validation. Initially, a comprehensive literature review and benchmarking analysis were conducted, comparing best practices from leading digitalized ports, such as those in Rotterdam, Singapore, and Los Angeles. This process helped identify recurring strategic factors relevant to port digitalization. These factors were then refined through a Delphi Panel, where experts rated their relevance and applicability to the Spanish port context. The final selection included the most frequently cited and highly rated elements, ensuring that the SWOT factors reflected both global best practices and local industry needs.

3.3. Numerical Evaluation of the SWOT Matrix Through a Survey

To numerically assess the SWOT matrix, a Google Forms survey was designed using a Likert-type scale (1–5), where a Delphi Panel of Experts evaluated the relevance and impact of each factor.

For a given strategic factor X_i, experts assigned a score P_i on a Likert scale:

P_i ∈ {1, 2, 3, 4, 5}

where:

• 1: No impact;
• 2: Low impact;
• 3: Moderate impact;
• 4: High impact;
• 5: Critical impact.

Survey responses generated a numerical SWOT matrix, allowing for the quantification of each strategic component.

3.4. Statistical Validation: Means and Standard Deviations

To validate survey results, means (1) and standard deviations (2) were computed for each category (S, W, O, T):

$$\overline{X}={\displaystyle \frac{1}{n}}\sum _{i=1}^n{P}_i$$

(1)

$$\mathsf{\sigma }=\sqrt{{\displaystyle \frac{1}{n}}\sum _{i=1}^n{\left(P_i-\overline{X}\right)}^2}$$

(2)

where:

• $\overline{X}$ represents the average expert score for each factor.
• $\sigma$ indicates the variation in expert responses.

A high standard deviation (σ > 1) suggests discrepancies in expert evaluations, requiring adjustments through a Focus Group to enhance reliability.

The threshold for standard deviation in the Delphi Panel analysis was determined based on methodological best practices in expert consensus studies. A high standard deviation (σ > 1) was considered indicative of significant variability among expert opinions, requiring further deliberation to ensure consistency. This approach aligns with prior research in strategic decision making, where sigma thresholds are used to refine expert assessments and reduce subjectivity in weighting factors. Factors with a standard deviation greater than one underwent an additional review round to achieve greater alignment among expert responses, ensuring robust and reliable results.

Additionally, to validate the robustness of the SWOT-CAME model, the following statistical analyses were performed:

• Inter-rater reliability assessment:

The Cronbach’s Alpha coefficient was calculated to measure the consistency of expert responses in the Delphi Panel (3):

$$\mathsf{\alpha }={\displaystyle \frac{k}{k-1}}\left(1-{\displaystyle \frac{\sum {\mathsf{\sigma }}^2}{{\mathsf{\sigma }}_T^2}}\right)$$

(3)

where:

• k represents the number of evaluated factors.
• σ² is the variance of each factor.
• ${\mathsf{\sigma }}_T^2$ is the total variance of the sample.

Sensitivity analysis of strategies:

The impact of changes in weightings and factor adjustments within the SWOT matrix was assessed, ensuring that the final strategies remained robust and replicable.

To assess the internal consistency of the expert evaluations, the Cronbach’s Alpha coefficient was estimated. The result was α = 0.81, indicating a high level of reliability and coherence among the responses collected during the Delphi process. This value was calculated using the aggregated Likert-scale responses in a spreadsheet following standard procedures, ensuring the robustness of the dataset used in the strategic analysis.

3.5. Refinement Through a Focus Group

The definition of strategies followed a structured, multi-phase approach rather than relying on the subjective opinions of the authors. The process began with the identification of key factors affecting port digitalization through a SWOT analysis. Each factor was evaluated quantitatively via a Delphi Panel, where experts assigned weighted scores to assess relevance and impact. The results were then integrated into the CAME matrix to develop strategic responses. Each proposed strategy was derived from the prioritization of high-impact factors identified in the SWOT-CAME analysis, ensuring an objective, data-driven approach. To enhance validity, statistical methods were applied to measure dispersion and ensure consistency across expert evaluations.

To improve consistency in evaluating strategic factors, a Focus Group was conducted with the same Delphi Panel experts.

• Factors with higher standard deviations (σ > 1) were discussed.
• Evaluation criteria were reviewed, and final scores were refined.
• Adjusted means (${\overline{X}}_{adj}$) and new standard deviations (σ_adj) were recalculated.

These refinements were incorporated into the final SWOT matrix, ensuring improved consensus and accuracy.

3.6. Conversion from SWOT to CAME and Strategy Development

With the adjusted values, the CAME matrix was constructed to transform findings into actionable strategies.

The CAME framework structures strategies into four categories:

• Correct (C_i): Eliminating internal weaknesses.
• Adapt (A_i): Adjusting to external opportunities.
• Maintain (M_i): Reinforcing internal strengths.
• Explore (E_i): Maximizing external opportunities for innovation.

Given a set of strategic factors, the weighted impact of each strategy was computed using normalized weighting (4):

$$E_i={\displaystyle \frac{{\sum }_{j=1}^n{P}_{ij}\cdot W_j}{{\sum }_{j=1}^n{W}_j}}$$

(4)

where:

• P_i is the score of factor jj within strategy ii.
• W_j is the assigned weight for each factor.
• E_i is the final score for strategy ii.

The result was a prioritization of strategies, emphasizing those with the highest strategic impact.

To illustrate the application of the methodology, a simplified example is presented below using Formulas (1)–(4). To illustrate the methodology, we provide a simplified example based on actual evaluation procedures from the Delphi process. For instance, for the factor “Implementation of digital training programs”, five experts assigned the following scores using a Likert scale: 4, 4, 5, 3, and 4.

Using Formula (1), the arithmetic mean is calculated as:

$$\overline{X}={\displaystyle \frac{4+4+5+3+4}{5}}=4.0$$

Applying Formula (2), the standard deviation is:

$$\begin{array}{c}\\ \sigma =\sqrt{{\displaystyle \frac{(4-4{)}^2+(4-4{)}^2+(5-4{)}^2+(3-4{)}^2+(4-4{)}^2}{5}}}\approx 0.63\end{array}$$

If the normalized value is needed (Formula (3)), a maximum possible score of 5 is considered:

$$X_{norm}={\displaystyle \frac{4}{5}}=0.80$$

If the factor was refined after the Focus Group, the updated mean became 4.2 (Formula (4)):

$${\overline{X}}_{adj}=4.2$$

These basic statistical operations were applied to each evaluated factor. The resulting values were used to build the numerical SWOT-CAME matrix, ensuring consistency and comparability in the strategic analysis.

3.7. Alignment with the Sustainable Development Goals (SDGs)

Finally, all developed strategies were linked to the SDGs, identifying their contributions to:

• SDG 9 (industry, innovation, and infrastructure) → Enhancement of digital port infrastructure.
• SDG 12 (responsible consumption and production) → Efficient resource management in logistics.
• SDG 13 (climate action) → Emission reduction through digital transformation.

Each strategy was associated with impact indicators to ensure alignment with global sustainability objectives.

The identification of strategic actions followed a structured evaluation process, ensuring that the strategies developed were not only theoretically sound but also aligned with industry needs and expert opinions. The process began with the selection of critical factors through the SWOT analysis, where each element was categorized based on its impact on port digitalization. To ensure objectivity, these factors were assessed by a Delphi Panel composed of industry experts, who rated their relevance and feasibility using a Likert scale. Statistical validation was applied to measure the consistency of responses, with factors demonstrating high variability (σ > 1) being re-evaluated in a second round of expert feedback.

The final selection of factors was based on their aggregated scores, prioritizing those that had both high strategic relevance and practical feasibility. These factors were then mapped into the CAME framework, categorizing them into corrective, adaptive, maintaining, and exploiting strategies. This structured prioritization ensured that the proposed strategies were grounded in empirical data rather than subjective judgment. Additionally, a cross-analysis with sustainability objectives was conducted to align strategic recommendations with the Sustainable Development Goals (SDGs), reinforcing the long-term environmental and operational benefits of the proposed digital transformation pathways.

Furthermore, the validation process incorporated a sensitivity analysis to assess the robustness of the selected strategies under varying conditions, confirming that the strategic recommendations remain applicable across different port operational scenarios. This methodological approach ensures that the study’s findings offer a scalable and transferable framework for other ports seeking to enhance their sustainability through digitalization.

The selection of experts followed predefined criteria to ensure balanced representation and relevant expertise. Participants were required to have a minimum of ten years of professional experience in the maritime port sector and demonstrable involvement in digital transformation, sustainability, innovation, or strategic planning projects. Priority was given to individuals holding mid-to-senior-level positions in public port authorities, private terminal operators, logistics firms, academic institutions, and technology providers. The final Delphi Panel consisted of fifteen experts, ensuring a multidisciplinary perspective and comprehensive evaluation of the strategic factors identified in this study.

4. Results and Discussion

The study achieved its objective by applying a structured framework to evaluate digitalization readiness and define priority strategies that link emerging technologies with sustainable port development.

This section presents the findings obtained through the application of the SWOT-CAME methodology. The quantified values in the numerical SWOT matrix, the standard deviations to assess the variability of the data, the adjustments made through the Focus Group, and the conversion to CAME strategies, aligned with the Sustainable Development Goals (SDGs), are included.

This research directly addresses several of the gaps identified in the literature. First, it provides a structured approach to evaluating digital readiness in ports, filling the absence of diagnostic frameworks in this area. Second, it applies a validated methodology—SWOT-CAME combined with Delphi Panel consensus—to prioritize sustainability strategies, thereby operationalizing strategic planning in a way that is replicable and transparent. Third, it demonstrates how expert-based methods can be effectively employed to align technological innovation with sustainability goals in a real-world port context.

The Delphi Panel included 25 experts with backgrounds in port operations, digital transformation, and sustainable logistics. The selection criteria ensured that each participant had at least 10 years of experience in the maritime sector and had previously worked on port innovation projects.

The empirical evaluation involved the participation of fifteen experts from the Spanish port logistics sector. These professionals were selected for their extensive experience in areas such as digital transformation, port operations, sustainability, and strategic planning.

Table 1. Profile of Delphi Panel experts.

Area of Expertise	Number of Experts	Typical Position	Type of Organization
Port operations and logistics	5	Middle or senior manager	Port authorities, operators
Digital innovation and technology	7	IT director, innovation lead	Tech providers, consultancies
Sustainability and environment	6	Strategy advisor, environmental manager	Public agencies, engineering firms
Academic and policy research	7	Professor, policy consultant	Universities, public institutions

presents the professional background and roles of each participant in the Delphi Panel, providing a clear overview of their qualifications and relevance to the study. These professionals were grouped into four main areas of expertise: port operations and logistics, digital innovation and technology, sustainability and environmental management, and academic or policy research. The selection aimed to ensure a balanced and multidisciplinary perspective, incorporating both strategic and technical viewpoints relevant to port digitalization and sustainability. Experts held mid- to senior-level positions and were affiliated with public port authorities, private terminal operators, research institutions, and technology consultancies.

4.1. SWOT Analysis

To ensure methodological consistency in the SWOT-CAME analysis, five strategic factors were selected for each quadrant of the matrix—strengths, weaknesses, opportunities, and threats. This approach allowed the matrix to maintain a balanced, square structure, which is essential for assigning weights and performing subsequent calculations without bias. The selected factors were those that obtained the highest aggregated scores from the Delphi Panel, considering both their relevance and feasibility. This standardization also facilitated comparative analysis across strategic combinations, strengthening the internal consistency of the model.

The SWOT matrix on which the research is based is as follows (Figure 2):

To quantify the strategic factors, a Delphi Panel was held in which experts in port logistics, sustainability, and emerging technologies evaluated the relevance and impact of each factor on a Likert scale from 1 to 5 (

Table 2. Obtaining the numerical SWOT from the survey.

Factor	O1	O2	O3	O4	O5	T1	T2	T3	T4	T5
S1	3.96	4.04	4.57	4.52	4.00	4.52	4.48	4.09	4.09	4.17
S2	4.13	3.91	3.96	4.57	3.96	3.74	4.00	4.17	4.17	3.78
S3	4.17	4.43	4.22	3.65	4.00	4.52	4.00	4.00	4.00	4.00
S4	3.70	4.65	4.48	4.33	4.13	4.13	4.00	4.17	4.17	3.91
S5	3.57	4.09	4.35	3.83	4.00	4.13	4.00	4.13	4.00	3.91
W1	3.09	3.87	3.61	3.83	3.74	3.83	3.96	3.83	3.96	3.87
W2	3.17	4.22	4.17	4.70	4.00	4.00	3.96	3.91	3.91	3.91
W3	3.17	3.74	3.74	4.70	4.13	3.91	3.96	3.91	4.35	4.35
W4	3.70	3.96	4.17	3.96	3.91	3.91	3.87	3.74	3.74	4.17
W5	3.09	3.65	3.26	3.39	3.70	4.00	3.96	4.00	3.87	3.87

).

The results show that factors related to digitalization and sustainability scored the highest in opportunities and strengths, while regulatory threats and technological challenges were the most prominent in weaknesses and threats.

Standard deviations (σ) of each factor were calculated to assess the dispersion of the experts’ responses. (

Table 3. Standard deviation matrix.

Factor	O1	O2	O3	O4	O5	T1	T2	T3	T4	T5
S1	0.8245	0.8245	0.5898	0.6653	0.7057	0.7305	0.5931	0.8341	0.9002	0.9341
S2	0.8689	1.1644	0.7674	0.5898	0.6381	0.6887	0.8245	0.8245	0.9367	0.9514
S3	0.8341	0.7278	0.7313	0.6887	0.6887	0.7578	0.6503	0.6503	0.8528	0.7928
W1	1.2761	0.8149	0.9409	0.9367	0.8643	0.9841	0.7385	0.7688	0.8779	0.8388
W2	1.1929	0.7359	0.4910	0.4705	0.6255	0.6564	0.9673	0.5473	0.3482	0.6473
W5	1.0407	1.1524	1.0539	1.0762	0.9740	0.8528	0.7674	0.7977	0.7570	0.8689

).

Factors with a standard deviation greater than 1.0 indicate high dispersion in expert opinions. This justified the realization of the Focus Group to adjust the assessments and achieve consensus.

The Focus Group allowed for refining the values of the factors with greater variability. The following points were adjusted:

• Reduced uncertainty in regulatory threats.
• Greater consensus on technological opportunities.
• Correction of outliers in strengths and weaknesses.

The adjusted values allowed us to generate strategies in the CAME matrix.

The results of the analysis were consolidated in the final SWOT matrix, where the main strengths and opportunities that can be enhanced were identified, as well as the weaknesses and threats that require mitigation strategies once a focus group has been developed and the values rescaled to have a greater visualization (

Table 4. Final SWOT matrix (adjusted mean after Focus Group and linear rescaling).

Factor	O1	O2	O3	O4	O5	T1	T2	T3	T4	T5
S1	3.65	3.80	4.76	4.57	3.80	4.67	4.00	4.04	3.89	4.04
S2	3.96	3.73	3.55	4.76	3.55	3.80	3.25	3.80	3.80	3.73
S3	4.04	4.51	4.13	3.09	4.20	4.36	4.04	3.73	3.73	3.89
S4	2.81	4.91	4.60	4.51	4.27	4.27	3.80	3.04	2.81	3.73
S5	2.95	3.89	4.36	3.41	4.51	3.96	1.91	4.04	3.02	3.56
W1	1.55	3.49	3.02	3.41	3.25	1.91	3.73	4.27	3.56	3.42
W2	1.91	4.13	4.04	5.00	3.96	4.44	4.04	4.36	3.96	3.96
W3	2.22	3.73	3.25	4.09	3.41	3.41	3.73	3.49	3.56	3.73
W4	3.18	3.65	4.04	3.80	3.65	3.56	3.56	3.56	3.25	4.04
W5	1.00	3.73	1.91	4.09	3.49	3.73	3.65	3.73	3.49	3.49

).

The results of the SWOT matrix show that technological strengths and innovation capacity represent a key strategic asset for the sector, while dependence on external suppliers and organizational resistance to change remain critical points that need to be addressed urgently.

4.2. CAME Analysis: Strategy Development

The strategic recommendations presented in this study are the result of a systematic, multi-step validation process. The initial SWOT analysis identified the key factors influencing digital transformation in ports. These factors were then evaluated through expert input in a Delphi Panel, where consensus was reached on their relevance using weighted scoring techniques. Statistical analysis of standard deviations ensured consistency among expert evaluations, reducing bias. The final prioritization of strategies was determined through the CAME matrix, linking SWOT factors to corrective, adaptive, maintaining, and exploiting strategies. As a result, the strategies presented in this study are data-driven and validated through industry expertise.

The move from SWOT to CAME made it possible to generate strategies aligned with the current and future challenges of the port sector. Strategic actions were prioritized in four key quadrants, based on their score (

Table 5. Strategies generated after the SWOT-CAME analysis.

Quadrant	Strategy	Punctuation
SO	Implementation of the Metaverse in port logistics.	100.62
ST	Cybersecurity reinforcement through AI and blockchain.	95.69
WO	Promotion of public–private collaboration to reduce external dependence.	83.60
WT	Training programs to mitigate resistance to change.	92.76

).

The prioritization of strategies in the strategic quadrants revealed key trends in the transformation of the sector:

• Offensive Strategies (SO): With the highest score (100.62 points), leadership in digitalization and the implementation of the Metaverse as a tool for logistics optimization and global competitiveness stand out.
• Defensive Strategies (ST): These reached 95.69 points, underscoring the need to strengthen cybersecurity and the protection of digital infrastructures against regulatory risks and external threats.
• Survival Strategies (WT): With 92.76 points, these strategies aim to reduce resistance to change and improve staff training in emerging technologies.
• Adaptive Strategies (WO): These obtained the lowest score (83.60 points), which indicates the need to overcome dependence on external suppliers and promote strategic alliances for technological development.

These results reflect the importance of prioritizing strategies aimed at innovation and digital resilience, ensuring that Spanish ports can face the technological and regulatory challenges of the future.

This reflects the need to establish a comprehensive strategic framework that guarantees the competitiveness and sustainability of the port sector through the adoption of emerging technologies and innovative management models.

• Offensive Strategies (SO): Technology Leadership

The SO quadrant highlights digitalization and the adoption of the Metaverse as a fundamental pillar for the transformation of the sector. Previous investigations [4] have shown that the implementation of virtual platforms in port logistics improves operational efficiency by 15–20%, optimizing the use of resources and reducing costs.

• Offensive Strategies (SO): Driving Innovation and Technological Leadership

The quadrant of offensive strategies highlights the port sector’s ability to leverage its internal strengths (advanced technological infrastructure, sustainability expertise) in tandem with external opportunities (public–private collaboration, technological advancements in the Metaverse).

Key strategies include:

• S4-O4: Strengthen the training and specialization of personnel in advanced technologies through access to financing and public–private collaboration. This will optimize critical processes, accelerate the implementation of innovative projects, and consolidate the position of the port sector as a global benchmark in innovation and sustainability.
• S1-O3: Exploit existing technological infrastructure to develop digital platforms and services based on the Metaverse, virtual reality, and artificial intelligence. This will improve operational efficiency and reduce costs, positioning Spanish ports as leaders in technological competitiveness.
• S3-O2: Implement simulators and virtual reality platforms to improve staff training, reduce operational errors, and strengthen security in port operations.

These strategies drive the digital transformation of the port sector, facilitating the adoption of advanced technologies to optimize logistics, improve sustainability, and boost international competitiveness.

• Defensive Strategies (ST): Threat Protection

The ST quadrant underlines the importance of strengthening port cybersecurity through artificial intelligence and blockchain. According to [31], 65% of European ports have experienced cyberattacks in recent years, highlighting the need to automate the protection of port data and operating systems.

• Defensive Strategies (ST): Threat Protection and Cybersecurity

Defensive strategies underscore the need to use internal strengths to mitigate external threats, especially in the cybersecurity and regulatory arena.

• S1-T1: Leverage existing technology infrastructure to mitigate global competitive risk by adopting emerging technologies and advanced automation.
• S3-T2: Develop pilot projects that comply with European regulations, anticipating regulatory changes and ensuring sustainable operational efficiency.
• S5-T2: Implement digital platforms to monitor critical processes and ensure regulatory compliance, reducing the risk of sanctions and strengthening operational transparency.

The increase in cyberattacks on critical infrastructures and the increasing regulatory complexity make these strategies essential to ensure the security and stability of the sector.

• Adaptive Strategies (WO): Reducing External Dependencies

The WO strategy emphasizes the importance of strengthening the technological autonomy of the port sector, reducing dependence on external suppliers through public–private partnerships and investments in internal development of logistics technologies.

• Adaptive Strategies (WO): Reduction of Dependencies and Technological Development

This quadrant emphasizes the need to reduce dependence on external suppliers and foster innovation through strategic partnerships.

• W2-O4: Establish collaborations with technology companies to access innovative solutions and overcome financial constraints in the adoption of emerging technologies.
• W4-O3: Implement operational restructuring and flexibility processes to reduce organizational rigidity and facilitate the integration of digital innovations.
• W5-O1: Develop training and job adaptation programs to reduce resistance to change and facilitate the adoption of the Metaverse in port operations.

These strategies seek to ensure that ports not only adopt new technologies but also have the necessary internal capabilities to manage them efficiently.

• Corrective Strategies (WT): Organizational Change Management

The results show that resistance to change remains a structural problem in the sector. According to [4], more than 40% of port staff are resistant to the adoption of new technologies, underscoring the urgency of establishing training and awareness-raising programs.

• Survival Strategies (WT): Change Management and Digital Training

The strategies in this quadrant focus on mitigating external risks by minimizing internal weaknesses, ensuring the stability of the sector in a dynamic environment.

• W2-T1: Establish alliances with cybersecurity companies to develop technological solutions with low initial costs, mitigating the risk of cyberattacks.
• W3-T4: Implement training programs in cybersecurity, automation, and technology maintenance to reduce dependency on third-party vendors.
• W5-T3: Develop training campaigns in cybersecurity and adoption of new technologies through practical simulations in virtual environments.

Organizational change management is a key factor for the digital transformation of the sector. Lack of training and resistance to change remain barriers that need to be addressed with targeted strategies to ensure a smooth transition to more digitalized and sustainable ports.

The results obtained from this study have direct implications for the sustainability and competitiveness of the Spanish port sector (

Table 6. Direct implications for the sustainability and competitiveness of the Spanish port sector and actions to be developed.

Involvement in Sustainability and Competitiveness	Actions
Resource Optimization and Energy Efficiency	The digitalization of port operations and the adoption of the Metaverse allow for better management of resources, reducing energy consumption and the emission of polluting gases.
Risk Reduction and Increased Safety	Strengthening cybersecurity and modernizing operating systems ensure more effective protection against cyberattacks and regulatory threats.
Training and Job Adaptation	Training in emerging technologies and the integration of digital simulations facilitate the transition of port staff to a more digitized and efficient work environment.
Global Competitiveness and Technological Development	Investment in innovation and automation positions Spanish ports as benchmarks in the adoption of advanced technologies, improving their attractiveness for investors and logistics operators

).

Together, these findings provide a clear roadmap for the digital and sustainable transformation of the port sector, aligning its development with the Sustainable Development Goals (SDGs) and ensuring its competitiveness in the global market.

From all of the above, it is highlighted that:

• The Metaverse and port digitalization are key to sustainability and competitiveness.
• Cybersecurity strategies must be strengthened in the face of growing threats.
• Public–private collaboration is essential to ensure technological viability.
• Staff training is critical to the digital transformation of the sector.

The potential of the Metaverse to reduce energy consumption and emissions lies in its capacity to virtualize key decision-making and planning processes. Through real-time simulations and digital twin platforms, operators can anticipate congestion, reroute movements, or optimize resource allocation without deploying physical infrastructure. For example, immersive training modules eliminate the need for on-site training sessions, reducing vehicle usage and associated emissions. Furthermore, digital modeling can aid in identifying underperforming assets and suggest energy-efficient alternatives, as evidenced in pilot studies across other smart port initiatives [4,11].

The main outcome of this study is the development of a strategic evaluation tool that combines SWOT-CAME analysis with expert validation through a Delphi Panel. This tool enables port authorities to assess digital transformation readiness and identify high-priority sustainability strategies. Among the strategies evaluated, those in the SO (strengths–opportunities) quadrant emerged as the most impactful, with a score of 100.62. These include the implementation of advanced training programs supported by public–private collaboration (S4–O4) and the development of digital platforms based on Metaverse applications and artificial intelligence (S1–O3). These strategies were prioritized due to their alignment with current infrastructure capabilities and external opportunities in innovation and funding. The final weighted matrix and strategy ranking provide a clear roadmap for port decision makers.

The strategic tool developed in this study offers not only a diagnostic framework but also a prioritized set of sustainability actions. The SO quadrant strategies, which combine internal strengths with external opportunities, are particularly relevant for ports aiming to lead digital innovation while pursuing environmental goals. Their prioritization reflects both expert consensus and methodological robustness. By focusing on these strategies, port authorities can invest in initiatives with higher feasibility and potential return in terms of efficiency, training, and emissions reduction. This approach transforms abstract objectives—such as digitalization or sustainability—into actionable and ranked strategic alternatives.

4.3. Strategic Alignment with the Sustainable Development Goals (SDGs)

The digital and sustainable transformation of the Spanish port sector requires strategic integration with the Sustainable Development Goals (SDGs) established by the United Nations. Based on the analysis of the CAME matrix, priority strategies were identified that are aligned with the SDGs most relevant to the port context.

Table 7. Priority strategies and their alignment with the SDGs.

Strategy	Related SDGs	Justification
S4-O4	SDG 4, SDG 9, SDG 17	Training in advanced technologies and public–private collaboration to optimize port processes.
S1-O3	SDG 8, SDG 9, SDG 12	Development of digital platforms and services in the Metaverse to improve efficiency and innovation.
W2-O4	SDG 9, SDG 17	Strategic alliances to overcome financial constraints and adopt emerging technologies.
W4-O3	SDG 4, SDG 8, SDG 9	Modernization of port processes through technological tools and continuous training.
S1-T1	SDG 9, SDG 13	Use of advanced technological infrastructure to mitigate global risks and improve competitiveness.
F3-A2	SDG 12, SDG 17	Pilot projects to comply with European regulations and strengthen public–private partnerships.
W2-T1	SDG 9, SDG 16	Design of solutions to mitigate cybersecurity risks and overcome financial constraints.
W3-T4	SDG 4, SDG 8, SDG 9	Technical training to reduce supplier dependency and optimize internal management.

presents the correspondence between the proposed strategies and the SDGs, highlighting how each initiative contributes to global commitments on sustainability, innovation, operational efficiency, and safety.

The strategic analysis shows that port modernization not only boosts operational efficiency but also contributes to the fulfillment of the SDGs in multiple dimensions.

The transformation of the port sector within the framework of the Sustainable Development Goals (SDGs) is closely linked to education, technological innovation, and sustainability.

In the context of SDG 4—quality education, training staff in advanced technologies and digital skills is a key factor. The implementation of strategies such as F4-O4 and D3-A4 promotes training programs in automation, digitalization, and cybersecurity, ensuring that human talent can adapt to the new demands of the port market.

For its part, SDG 8—decent work and economic growth highlights the role of technological innovation and logistics optimization in generating new job opportunities. Strategies such as F1-O3 and D4-O3 favor the creation of digital platforms, improving operational efficiency and promoting the generation of highly qualified jobs in the digital and sustainable field.

SDG 9—industry, innovation, and infrastructure is a cross-cutting axis in the modernization of the port sector, promoting digitalization, automation, and the integration of emerging technologies. Strategies such as W2-O4, S1-T1, and W3-T4 promote the adoption of technological innovations, allowing organizations to overcome financial barriers and strengthen strategic alliances with technology companies and public agencies.

In terms of sustainability, SDG 12—responsible production and consumption highlights the importance of sustainable digital solutions to optimize logistics processes and reduce environmental impact. Strategies such as S1-O3 and S3-T2 prioritize the implementation of digital tools to improve energy efficiency and minimize the ecological footprint of the sector.

Likewise, SDG 13—climate action highlights how port digitalization contributes to reducing carbon emissions and mitigating negative effects on the environment. Strategies such as S1-T1 focus on the use of advanced technological infrastructures for better climate risk management and a transition to more sustainable operations.

From the perspective of cybersecurity and operational stability, SDG 16—peace, justice, and strong institutions emphasizes the need to strengthen digital resilience in an increasingly interconnected environment exposed to cyber threats. Strategies such as W2-T1 address these challenges by developing digital solutions that ensure the integrity of port systems.

Finally, SDG 17—partnerships to achieve the goals underlines the importance of cooperation between companies, governments, and international organizations to ensure the sustainability of the port sector. Strategies such as W2-O4 and S3-T2 promote public–private collaboration, facilitating access to finance, knowledge sharing, and the joint development of innovative solutions.

This study provides a novel contribution by diagnosing the current state of digitalization in Spanish ports, an area with limited prior research. While previous studies have examined isolated technologies such as digital twins [9], no structured framework has been developed to assess the digital readiness of ports and establish strategic pathways for sustainable transformation. This research fills this gap by applying SWOT-CAME to evaluate how AI, blockchain, and immersive digital environments can be leveraged for port sustainability and efficiency.

Together, these approaches reinforce the vision of a more efficient, innovative port sector committed to sustainable development, ensuring its competitiveness in the future.

Unlike previous studies that focus solely on the theoretical potential of port digitalization, this research provides a structured decision-making framework for evaluating and prioritizing digital transformation strategies in real-world port environments. The use of SWOT-CAME, combined with expert validation, enables a systematic approach to assessing technological adoption pathways, cybersecurity risks, and workforce adaptation. This study’s findings offer actionable insights for policymakers, port authorities, and logistics operators, aligning digitalization efforts with sustainability objectives. Future research should expand on the scalability of AI-driven logistics solutions and their economic viability in port operations.

This study represents a step forward in port digitalization research by addressing a critical gap: the lack of a structured assessment of digital maturity in ports. While previous research has examined individual technological innovations, such as digital twins [9] or automation strategies [5], these studies do not provide a holistic analysis of the readiness of port infrastructures to embrace emerging technologies. The findings of this research establish a baseline for future technological adoption strategies, offering port authorities and policymakers a structured framework to guide sustainable digital transformation. Furthermore, the integration of SWOT-CAME with expert validation via the Delphi Panel enhances the strategic robustness of the proposed pathways, ensuring that recommendations are both theoretically sound and practically viable.

A key contribution of this study is its structured approach to defining digitalization strategies for ports. Unlike previous studies that provide broad recommendations, this research ensures that strategic priorities are not arbitrarily selected but rather emerge from an expert-driven validation process. The combination of SWOT-CAME with the Delphi methodology enhances the reliability of strategic planning by incorporating expert opinions in a statistically validated manner. The findings establish a roadmap for port authorities and policymakers to make data-driven decisions about technological adoption and sustainability investments.

Despite its contributions, this study has some limitations. First, the SWOT-CAME methodology relies on expert input, which, while valuable, introduces a degree of subjectivity. Although the Delphi Panel approach mitigates this by ensuring consensus among professionals, future research could enhance robustness by incorporating quantitative modeling techniques for scenario forecasting. Second, this study focuses exclusively on Spanish ports, meaning that findings may not be fully generalizable to other regional contexts with different regulatory and technological landscapes. Comparative studies with ports in other countries would be beneficial to validate the applicability of the proposed strategic framework on a broader scale. Lastly, while this research identifies key areas for digital transformation, it does not evaluate the economic feasibility of implementing these strategies, which should be explored in future work.

The findings of this study align with previous research that highlights the role of digitalization in optimizing port operations [5,9]. However, this study advances the discussion by offering a structured framework for assessing digitalization readiness, an aspect that has not been systematically addressed in port studies. From a theoretical perspective, this research contributes to the strategic management literature by demonstrating how SWOT-CAME can be effectively applied to digital transformation planning. In practical terms, the results provide actionable insights for port authorities, enabling them to prioritize investment in digital infrastructure, workforce training, and cybersecurity measures. Moreover, from a policy standpoint, this study underscores the need for regulatory frameworks that support the integration of emerging technologies in port operations, ensuring alignment with international sustainability objectives such as the European Green Deal and the IMO’s digitalization agenda.

5. Conclusions

This study has shown that the integration of emerging technologies, in particular the Metaverse and the SWOT-CAME strategic methodology, can significantly contribute to the sustainability and digitalization of port logistics. Through the strategic analysis carried out, key strengths and opportunities were identified that can enhance operational efficiency and reduce environmental impact in ports.

This study provides a structured assessment of digitalization readiness in Spanish ports, filling a critical gap in the literature by combining SWOT-CAME with expert validation. The results highlight the importance of strategic planning in port digitalization, emphasizing the need for investment prioritization, workforce training, and regulatory adaptation. This study contributes both theoretically and practically by offering a replicable framework that can be adapted to different port contexts. Future research should further explore the economic implications of digital transformation strategies, ensuring that sustainability and operational efficiency goals align with financial feasibility and policy development.

The main findings highlight that port digitalization, through the implementation of solutions such as digital twins, artificial intelligence, and blockchain, allows for optimization of resource management and a significant reduction in carbon emissions. In particular, the use of the Metaverse is presented as an innovative tool with the potential to improve staff training, port operations simulation, and strategic decision making based on real-time data.

From a strategic point of view, the conversion of SWOT to CAME made it possible to structure offensive, defensive, adaptive, and corrective strategies aligned with the Sustainable Development Goals (SDGs). Four fundamental strategic axes were identified:

• Technological leadership and digitalization: The implementation of the Metaverse and advanced digitalization can position ports as benchmarks in sustainability and innovation.
• Strengthening cybersecurity: Increasing digitalization exposes port systems to vulnerabilities, so it is essential to strengthen security through artificial intelligence and blockchain.
• Reducing external dependency: Public–private collaboration and investment in proprietary technologies can mitigate risks associated with dependence on external suppliers.
• Organizational change management: Resistance to the adoption of new technologies remains a major barrier, requiring training and awareness-raising programs aimed at port staff.

The results obtained in this research provide valuable information for port managers and planners by offering a clear and data-driven roadmap for the digital transformation of the sector. This study contributes to optimizing decision making by applying the SWOT-CAME methodology, which allows planners to identify in a structured manner the critical factors that influence port sustainability and to prioritize strategies with the highest impact. Additionally, the findings support the design of policies and investment strategies, enabling managers to allocate resources efficiently towards digital infrastructures and technologies with greater potential for economic and environmental returns. Another key contribution is the planning of staff training programs, as port digitalization requires new professional profiles and specific skills. By highlighting the importance of continuous training, this study emphasizes the need to reduce resistance to change and accelerate the adoption of new technologies. Furthermore, the use of Metaverse-based models and artificial intelligence can facilitate the implementation of simulation and risk management tools, allowing for the evaluation of different operational scenarios before their application in real environments, minimizing risks, and optimizing port processes. Finally, the methodology presented enables port managers to assess how each strategy contributes to the achievement of the Sustainable Development Goals (SDGs), ensuring that port operations align with regulatory frameworks and global sustainability trends.

The results indicate that the adoption of strategies based on emerging technologies can accelerate the transition to more sustainable and resilient ports. However, there are still challenges to be addressed, such as the initial investment in digital infrastructure, the need for standardized regulations, and the integration of new technologies into the daily operations of ports.

The results of this study are significant because they establish a baseline for understanding the digital transformation readiness of Spanish ports, an area previously unexplored in the literature. The strategic pathways identified in the SWOT-CAME analysis demonstrate that digitalization must be approached holistically, considering not only technological feasibility but also human capital development and regulatory adaptation. This research contributes to the field by integrating expert-driven validation techniques into digitalization assessments, ensuring that proposed strategies align with real-world industry needs. Furthermore, by prioritizing digital training and cybersecurity as key enablers, this study highlights essential factors that must be addressed to ensure a smooth transition towards smart, sustainable ports.

The analysis of alignment with the SDGs shows that port modernization goes beyond simple digital transformation, consolidating itself as a model of sustainability, inclusion, and global competitiveness. By integrating training, digitalization, energy efficiency, and cybersecurity, prioritized strategies ensure balanced growth that responds to the sector’s environmental, economic, and technological challenges.

The adoption of emerging technologies such as the Metaverse, artificial intelligence, and blockchain, together with the consolidation of strategic alliances, provides a solid foundation for Spanish ports to lead the transition towards a smarter, more resilient, and sustainable model.

Finally, it is recommended that future research delve into the economic viability of the implementation of the Metaverse in port environments as well as the development of standardized metrics to assess the real impact of digitalization on port sustainability. In addition, it is crucial to continue exploring the role of automation, artificial intelligence, and the circular economy in transforming the sector.

The combination of technological innovation and sustainable management strategies represents a unique opportunity for ports to become key players in the global transition towards greener, more efficient, and resilient maritime trade.

The theoretical implications of this study lie in its methodological approach. By applying a structured SWOT-CAME framework in a port digitalization context, this research provides a replicable model for evaluating digital transformation readiness in other industries. The integration of Delphi Panel validation further strengthens its reliability, offering a strategic assessment method applicable beyond the maritime sector. On a practical level, this study offers a decision-making tool for port authorities and policymakers, helping them to prioritize investments in digitalization based on empirical data rather than speculation. The insights derived from the analysis can guide policy formulation, infrastructure planning, and funding allocation to accelerate the transition towards smart and sustainable ports.