The Application of Multi-Criteria Analysis to Coastal Zone Management Decision-Making

Abstract

Various activities, whether economic, social, or environmental, exert pressure on a coastal area. The extent of economic activities taking place in coastal regions is continuously increasing, particularly in tourism, maritime transport, port operations, and fisheries and aquaculture. Therefore, the decision to establish activities in a coastal area is complex and requires careful consideration by all stakeholders who use this space, which is potentially one of the most important natural resources for the development of any coastal country. This research is focused on assessing the justification for establishing economic activities in a coastal area, taking into account the interconnection of spatial, safety, environmental, and social factors. Therefore, three possible scenarios have been proposed: the location of the communal port, the location of the nautical port-marina, and the location of the marine entertainment and recreation centre. The goal was to develop a model that would enable the objective assessment and selection of the most suitable activity that would simultaneously benefit society and have the least harmful impact on the environment. Therefore, a multi-criteria analysis was conducted using the AHP (Analytic Hierarchy Process) method. The decision-making process was based on the expert validation of criteria, sub-criteria, and alternatives. An analytical tool called Expert Choice was used to synthesise the results and select the optimal activity. The sensitivity analysis confirmed the stability and reliability of the obtained results, with the AHP method proving to be an effective tool in structuring the decision-making process regarding the establishment of activities in the coastal area. Based on the results of the multi-criteria assessment, planning the establishment of activities is an important precondition for the long-term and sustainable development of coastal activities in an area.

1. Introduction

Coastal zones underpin a variety of economically important activities characterised by specific location and sector demands. The lack of, and/or overuse of, areas is becoming a significant issue for certain sectors [1]. (Post) modern industrialisation, urbanisation, and globalisation amplify the impact of natural and anthropogenic changes on spatial dynamics [2].

When discussing the occupation of coastal zones, it should be considered that space is shared among multiple users. Three-dimensional spatial planning is essential, given that the marine space includes the sea surface, the water column, and the seabed. The sea, the coastline, and islands hold particular significance for coastal states. However, these valuable resources are strained by the economic activities occurring within them.

The spatial requirements of economic activities vary with their scope. While activities like fisheries and aquaculture and maritime transport occupy extensive marine areas, others, such as shipbuilding, limit public access to these waters. Tourism is a vital economic engine and a catalyst for future growth in most coastal states, largely because of its substantial multiplier effects [3]. Depending on their particular type, tourism facilities occupy a significant amount of coastal and marine space.

Certain areas hold greater significance than others, whether from an economic, ecological, or social perspective; specific events occur only in particular locations and at designated times [4]. A certain marine area can attract a variety of activities [5,6,7]. Marine spatial use patterns show daily, monthly, and seasonal changes [8,9,10]. The tourism sector, for example, exhibits a marked seasonal character.

Establishing an activity in a coastal zone is a complex process that requires reviewing several conflicting factors. The complexity of decision-making is twofold. The first pertains to the difficulty in organising various factors for a more precise understanding and analysis of the decision-making process, while the second concerns the nature of those factors. The factors can be quantitative and qualitative. Decision-making involves many criteria and sub-criteria that are used to rank possible decisions [11,12]. When employing any decision-making method that requires the numerical analysis of alternatives, three steps are required:

• Add numerical measures to the relative importance of the criteria and the impact of the alternatives on these criteria;
• Process the numerical values to determine the ranking of each alternative [13].

A larger number of interconnected and established criteria requires multi-criteria decision-making. In multi-criteria decision-making, several of the following methods are employed for decision-making: the Simple Additive Weighting (SAW) method, Data Envelopment Analysis (DEA), DEMATEL (DEcision MAking Trial and Evaluation Laboratory), TOPSIS (Technique for Order Performance by Similarity to Ideal Solution), a set of methods ELECTRE (Elimination and Choice Expressing the Reality), a set of methods, PROMETHEE (Preference Ranking Organisation Method for Enrichment of Evaluation), the Analytical Hierarchy Process (AHP), and the Analytic Network Process (ANP) method.

The AHP method was chosen for this research because it effectively addresses the study’s goals while integrating various stakeholder perspectives in a multi-criteria decision-making framework. This procedure was chosen because it simplifies complex decisions by breaking them into smaller, more manageable parts compared to other methods. The AHP method establishes a linear hierarchical structure that allows for ranking alternatives while effectively managing the procedure’s consistency. It is important to note that the AHP method is one of the most commonly used multi-criteria decision-making methods in the analytical decision-making approach [14,15,16,17,18,19].

The AHP method, within the context of multi-criteria decision-making, assists the decision-maker in structuring the problem by comparing criteria in pairs and considering the opinions of experts. This method is used to solve complex decision-making problems by breaking them down into smaller components: goals, criteria (sub-criteria), and alternatives. These components are subsequently connected to a hierarchical structure [20]. AHP provides a methodological framework for assessing quantitative and qualitative performance indicators [16]. A key benefit of this methodology is its capacity for regulating consistency, a feature lacking in other methods, such as TOPSIS, ELECTRE I, and ELECTRE II [21]. Within strategic management, AHP offers a suitable methodology for evaluating far-reaching decisions, where decision-makers prioritise a dependable approach for analysing options and determining their alignment with predefined objectives [22]. The AHP method produces a ranking of alternatives, similar to the TOPSIS, ELECTRE I, ELECTRE II, and ELECTRE III methods [21].

The Analytical Hierarchy Process (AHP) is a method that structures and integrates both quantitative and qualitative factors into a unified framework. It comprises two phases:

• The hierarchy tree definition;
• The numerical evaluation of the tree [23].

The Analytic Hierarchy Process (AHP) can organise the pertinent elements of a problem into a framework that is comprehensible to humans [24]. It is a multi-criteria decision-making process studied through measurement theory in a hierarchical structure [25]. AHP is a multi-criteria decision-making tool used in almost all applications related to decision-making [16]. This method is based on statistical data on the criteria describing the compared objects (alternatives) A j (j = 1, 2, …, n), or expert estimates and the criteria weights (statistically significant) ωi (i = 1, 2, …, m), where m is the number of criteria and n is the number of the objects (alternatives) compared [26]. In cases lacking a scale to confirm results, the pairwise comparison method offers advantages; its simplicity surpasses the initial complexity of other methods [27]. The comparisons are based on real measurements or a scale reflecting the relative preference scores [28]. Applying the AHP method starts with each stakeholder providing input on the relative importance of each criterion within a specific set of criteria [29].

While simple and flexible, the Analytical Hierarchy Process presents some challenges in its practical application [24]. The AHP method involves breaking down the decision-making problem into pairwise comparisons. A major downside is the rapidly increasing number of pairwise comparisons, potentially reaching n(n − 1)/2 [30]. This method’s significant drawback is that the preparation phase demands far more comparisons, depending on the number of criteria and alternatives. This process is often time-consuming, expensive, and demanding [31]. Saaty’s scale of relative importance is used to compare elements in pairs. A nine-level scale compares pairs of elements to determine their weights [32].

In certain cases, a scale may not convey the varying levels of importance among individual criteria and alternatives. A significant evaluation challenge arises when, for instance, alternative A is five times more important than B, which is five times more important than alternative C. The AHP method cannot cope with alternative A being 25 times more important than alternative C [30]. Furthermore, when determining the weights of criteria and sub-criteria, it is necessary to answer the questions: How many times more does option A contribute to the goal compared to option B, or how many times more does option B contribute to the goal compared to option A? Anomalies may appear if the questions asked to obtain the weights are not expressed correctly [30]. Sensitivity analysis explores how variations in decision-making criteria influence the outcome of selecting an alternative [22]. According to [33], the model is correctly specified if a 5% change in input data across all combinations does not alter the ranking of the alternatives.

Graphical feedback methods show greater efficacy than those relying only on numerical output [34]. The AHP method utilises the Expert Choice 11 software application. When faced with a small, homogenous set of options (not exceeding six), the AHP method, in combination with the Expert Choice software, proves appropriate [35,36]. This program provides various approaches to structuring the problem and uses pairwise comparisons of alternatives and criteria. Every comparison highlights the relationship between two elements, regardless of whether it uses numbers, graphs, or words. The Expert Choice method employs pairwise comparisons to establish a unique prioritisation of criteria and alternatives. In hierarchical problem frameworks, decision-makers select a prioritised alternative [37,38]. The AHP method uses Saaty’s scale of relative importance for pairwise comparison. The relative values range from one to nine and are implemented within the Expert Choice program tool [39]. The ability to control consistency is a significant advantage in using the program, as it identifies possible errors and inconsistencies in the assessment.

The AHP method is suitable for problem-solving because it can structure and combine quantitative and qualitative criteria and sub-criteria into a common framework. The linear hierarchical structure of the AHP method enables the visualisation of conflicting interests and results in the ranking of different alternatives while constantly managing the procedure’s consistency.

The decision on the choice of activity that will occupy the coastal zone is demanding, since once the space used for one activity becomes difficult to access for other activities, the decision-maker faces the challenge of selecting from several alternative solutions. Establishing a new activity causes interventions in the environment, resulting in either permanent or temporary changes that vary in intensity. Given the growing demand for space, it is crucial to choose activities that reduce pressure and increase economic and social benefits.

Coastal zone economic planning compares activities, prioritising those with positive economic and social impacts while ensuring environmental sustainability, safety, and public health. To identify these activities, we must consider those common in coastal zones: fisheries and aquaculture, tourism, shipbuilding, maritime transport, energy production and transmission, sports, recreation, and port operations.

2. Materials and Methods

The methodology for implementing the AHP method consists of four basic steps. The model developed in the first step is hierarchically structured (Figure 1).

The goal occupies the highest position in the hierarchical structure, followed by the criteria at the first level and the sub-criteria at the subsequent level. Alternatives are at the bottom level of the model’s hierarchical structure. The second step involves a pairwise comparison of elements at each hierarchical level. This shows the relative significance of the first criterion compared with the second.

2.1. The AHP Method’s Implementation

Considering the research topic’s complexity and the lack of statistical data for assessing the criteria and sub-criteria that justify activities in the coastal zone, it is crucial to utilise the knowledge of experts in relevant fields. This method guarantees that the research findings are more impartial and, as a result, widely acceptable and applicable. Considering that the results rely on the quality of expert judgement [40], it is essential that the expert assessment is conducted by at least two to three experts from each field addressed by the model. One reason is that multiple opinions are necessary to address complex problems with various dimensions [41], each requiring specific expertise [42]. Another reason is that decisions affect different stakeholders, necessitating varied perspectives in the decision-making process [43].

Expertise includes theoretical, contextual, and procedural knowledge, practical and empirical skills, positive attitudes, and relational or cognitive behaviours [44]. While expert knowledge is being used more frequently [45], a problem can emerge because of the subjective nature of expertise in assessment [46]. The AHP method utilises expert knowledge and experience from various domains to evaluate criteria and alternatives, ensuring objectivity in the decision-making process. This objectivity establishes AHP as a mathematical framework that incorporates the personal preferences of individuals or groups, making it a structured approach to rational and transparent decision-making [47].

Expert validation was conducted to assess the criteria and sub-criteria for selecting the location of an economic activity in the area. The research involved experts from diverse sectors, including state institutions (such as ministries, agencies, and administrative departments), port authorities, universities, business professionals, and representatives from the local community engaged in shaping local policies. The selected experts possess professional expertise in spatial planning, coastal area management (administrative procedures), marine environment protection (sea and coastline), maritime transport (vessels and coastal areas), potential economic activities, and public services (community representatives). The opinions of 20 experts were examined; eleven of them were females and nine were males. Six experts were representatives from the local community, and three of them were engaged in shaping local policies. Research participation was voluntary and anonymous.

The importance of evaluation criteria is expressed by the Saaty scale. The Saaty scale allows for an assessment of the importance ratio of two criteria when their values are expressed quantitatively, qualitatively, and in different units of measurement. A consistency analysis is conducted at each level. The consistency should be below 0.1 and 10% for the model to be valid. Inconsistency can result from misunderstanding the hierarchy, lack of information, incorrect thinking, or a writing error [48]. In the third step, a mathematical model is employed to calculate the local priorities (weights) of the criteria, sub-criteria, and alternatives. These priorities are then combined to obtain the total priorities of the alternatives [49]. The fourth step involves conducting a sensitivity analysis to assess how changes in the model’s input data impact the priority alternatives. Sensitivity analysis aims to determine the impact of input data variations on the model variables, irrespective of their connection to the data used in constructing the model or the significance of critical parameters and independent variables in the model. Sensitivity analysis assesses the effects of changes but does not demonstrate the probability of these changes occurring [50]. The utilisation of sensitivity analysis increases the reliability of the model. Sensitivity analysis is used to examine the effects of variations in judgements on the stability of the outcome [40]. If the rankings do not change, the results are stable; otherwise, they are sensitive.

2.2. Assessment Criteria for Coastal Zone Activities

The assessment criteria for coastal zone activities are grounded in scientific and professional insights, expert consultations, and the experiences of various states in implementing practices in coastal zone management and marine spatial planning. Figure 2 illustrates the proposed assessment criteria for coastal zone activities.

A structured model has been developed to help select suitable activities for the coastal zone, considering its inherent characteristics, distinctive features, and spatiotemporal potential. Figure 3 illustrates the hierarchical model for introducing activities in coastal areas.

The criteria are qualitative and quantitative. Multiple criteria affect the decision, making it a multi-criteria decision-making process. Assigning importance to the criteria enables the final ranking of activities and results in selecting the most acceptable one. The impact of an intervention on a coastal area is directly related to the quality of the chosen activity. A hierarchical model is used to analyse and determine the optimal activity for the coastal zone. The criteria comprise both qualitative and quantitative aspects. Since various criteria influence the decision-making process, it can be classified as multi-criteria decision-making. Assigning importance to the criteria enables the final ranking of activities, resulting in the selection of the most suitable one. The importance of choosing a quality activity is reflected in the impact of such an intervention on the coastal area where the activity occurs. A hierarchical model is used to analyse and determine the optimal coastal zone activity during the analysis and decision-making process. The goal is placed at the top of the hierarchical structure and is not compared to any other element. By evaluating the options (like fisheries and aquaculture, shipbuilding, etc.), the set limitations or criteria (spatial, security, environmental, and social) are decided, allowing for the selection of the most suitable solution. A definitive solution is reached through a pairwise comparison using expert evaluation.

3. Results

This study will analyse ranked scenarios of coastal zone economic activities to address the research problem, purpose, and objectives, using these scenarios as its primary data source. A validation application of the hierarchical model is presented below, implemented within the Žurkovo Bay area of the Kostrena municipality. The chosen scenarios are consistent with the pre-existing coastal zone spatial development plan.

3.1. A Framework for the Selection of Activities in Coastal Zones

Three coastal activity scenarios were proposed to assess the validity of the activity selection model:

• Scenario 1—the location of a communal port;
• Scenario 2—the location of a nautical port—marina;
• Scenario 3—the location of a marine entertainment and recreation centre.

Consequently, the locations of a communal port (Scenario 1), a nautical port-marina (Scenario 2), and a marine entertainment and recreation centre (Scenario 3) represent the components of the coastal activities: port operations, tourism, and sports and recreation.

The selection of experts responsible for determining the most appropriate activity within the observed area depends on their knowledge, expertise, and experience. The selected experts possess professional expertise in spatial planning, coastal area management (administrative procedures), marine environment protection (sea and coastline), maritime transport (vessels and coastal areas), potential economic activities, and public services (community representatives).

The research involved experts from diverse sectors, including state institutions (such as ministries, agencies, and administrative departments), port authorities, universities, business professionals, and representatives from the local community engaged in shaping local policies. The selected experts filled out a designed form, “Expert Assessment of the Criteria for Selection of Activities in the Coastal Zone”, in which they compared pairs of criteria in the first step, pairs of sub-criteria in the second step, and pairs of alternatives in the last step. The comparison was conducted using the Saaty scale of relative importance, which determines the significance of one alternative over another based on a specific level on the scale.

The study employed the Expert Choice software, which determines priorities and consistency and provides various sensitivity analysis options. Following group discussion, individual results can be analysed, interpreted, and then synthesised into a collective outcome. Figure 4 shows the hierarchy tree along with the weighting coefficients for the criteria and sub-criteria.

The environmental criterion has been recognised as the most important. This criterion’s importance stems from the recognition that environmental protection is a paramount contemporary challenge. The marine environment is subject to contamination by diverse pollutants, impacting water quality, climate, marine life, food safety, and human health. In acknowledging the problems of overexploitation and habitat degradation through pollution, the goal is to establish an equilibrium between the utilisation of marine resources and the interests of all stakeholders. Environmental awareness has increased across all sectors of society, and initiatives in coastal areas should focus on preserving both the quantity and quality of marine resources while protecting biological and landscape diversity, thereby ensuring the ecosystem’s overall health.

The criterion of social justification has been recognised as the second most crucial component, encompassing sub-criteria related to development potential in the area and the ability to generate income for the local community. The implementation of this initiative is expected to enhance the overall development of the area, improve the standard of living for the population, increase employment opportunities, and elevate the quality of life for both local and regional communities. The income derived from concessions and utility fees is of significant importance to the local government budget, as these funds are essential for meeting the local community’s needs. In this process, one should not overlook the increase in the value of the surrounding land and real estate.

The security criterion has been recognised as the third most important criterion. Implementing activities within a security and health protection system helps minimise risks and prevent potential hazards, enhancing workplace security. In situations where security is compromised, the consequences for employees, residents, facilities, and the environment can vary from minimal to severe and catastrophic. Although the immediate impacts might seem minor, they could lead to severe consequences for the workplace and the ecosystem. Concentrating on measures that avert harmful incidents, occupational illnesses, and workplace injuries lowers the chances of accidents. Security ensures the smooth operation of the activities.

The spatial criterion has been given the least importance, which is understandable. Each location has its own specific characteristics that must be respected. The design should prioritise functionality and align with the space’s intended use.

The Analytic Hierarchy Process (AHP) produces a prioritised ranking of alternatives in relation to the established objective following the completion of pairwise comparisons of all criteria, sub-criteria, and alternatives (see Figure 5).

Experts generally agree that a marina is the best option for the area. Alternatively, a communal port location is the second most acceptable scenario. A recreation centre in that location is the least favourable option. The inconsistency for the evaluation is 0.01, which makes this decision valid.

3.2. Sensitivity Analysis

In performing a sensitivity analysis, the variables that are subject to alteration are:

• Input parameters within the hierarchical model;
• Values of the criteria feature in the hierarchical model;
• Other values that define or limit the choice of activity.

Sensitivity analysis can be conducted on any variable within the hierarchical model of the AHP method, whether it involves the weights of criteria, sub-criteria, or the assessment of the alternatives themselves. This analysis enables continuous assessment of how changes in individual elements of the model impact the final ranking and the priorities of the selected alternatives. Sensitivity analysis aims to identify to what extent the key factors, i.e., the most significant criteria and sub-criteria, affect the overall priorities of the alternatives. In other words, the stability and reliability of the model are analysed, i.e., whether the recommended alternatives change with slight variations in criteria weights, or whether the decision remains consistent and robust despite variations. Therefore, this analysis is extremely important since it enables the decision-makers to identify the key factors. Furthermore, the analysis contributes to a better understanding of decision-making sensitivity and enables reassessment of the initial assumption on the importance of the criteria.

Sensitivity analysis—Option Dynamic shows a dynamic overview of weight coefficients in percentages. This option demonstrates how changes in individual criterion weights affect the prioritisation of alternatives. By changing the weight of one criterion, the other weights change proportionally in relation to the initial criteria weights.

Figure 6 displays a ranking of the alternatives obtained from a multi-criteria evaluation.

The left-hand side of the graphic illustrates the impact of individual criteria on the prioritisation of alternatives. The alternatives are illustrated on the right side of the graphic.

Adjusting the weight of one criterion alters the weights of the other criteria in relation to the initial weights. As the percentages of the weighting coefficients change, so do the final results, which answer the question: What should be the weight of an individual criterion for a certain alternative to be preferred over another alternative?

Figure 7 depicts the increased influence of the spatial criterion and the decreased influence of the other three, resulting in a revised ranking of alternatives.

Increasing the weight of the spatial criterion has reordered the alternatives. If the percentage of the spatial criterion rises from 20.4% to 62.2%, the priority alternative becomes Scenario 1—the location of a communal port.

Changing the relative importance of the selection criteria by 5% has shown how the rankings of the alternatives changed. The importance of each criterion varies by 5%, as shown in Figure 8, Figure 9, Figure 10 and Figure 11.

The ranking of alternatives remained consistent despite a 5% variation in the weighting of all criteria; however, minor changes in the priorities of the alternatives occurred. The results show that with a 5% variation in the significance of the spatial criterion, the priorities of the alternatives for Scenario 1—the location of a communal port—decrease by 0.1%, whereas the priorities for the alternatives in Scenario 2—the location of the nautical port—marina, and Scenario 3—the location of the marine entertainment and recreation centre, increase by 0.1%. Despite a 5% change in the importance of the security criterion, the priorities for the alternatives, Scenario 1—the location of a communal port and Scenario 2—the location of the nautical port-marina, remained unchanged. For the alternative Scenario 3—the location of the marine entertainment and recreation centre, a decrease in priority of 0.1% was recorded. Adjusting the weight assigned to the environmental criterion by 5% has not affected the ranking of the alternative, Scenario 1: the location of a communal port. Scenarios 2 (nautical port/marina) and 3 (marine entertainment and recreation centre) have each experienced a 0.1% decrease in prioritised ranking. The alteration of the criterion of social justification by 5% caused a corresponding 0.3% decrease in the priority assigned to Scenario 1 (the location of a communal port), in contrast to the elevated priority observed in the remaining alternatives. The priority of the alternative Scenario 2, the location of the nautical port/marina, increased by 0.3%, compared to a 0.1% increase for alternative Scenario 3, the location of the marine entertainment and recreation centre.

Given that a 5% variation in the importance of all criteria did not result in any changes in the ranking of the alternatives, the stability of these rankings across the different criteria was established. As the stability of the results was confirmed during the sensitivity test, all evidence suggested that the method employed was suitable for the problem at hand.

Using the Option Dynamic method, a sensitivity analysis adjusted the criteria priorities at set intervals to assess their effect on alternative rankings. Despite adjustments to the weighting of individual criteria, Scenario 2, designating the location of the nautical port-marina, proved to be the optimal choice.

Figure 12 illustrates the sensitivity analysis conducted to determine the impact of changes in criterion weights on the ranking of alternatives.

When Scenario 1 (the location of a communal port) is the top-ranked alternative, the security and spatial criteria show the greatest sensitivity to changes in criteria weights. When examining the alternative Scenario 1, the proposed location for a communal port ranks highest in both the spatial criterion (0.39) and the security criterion (0.367). However, it shows a notable drop in the criterion of social justification, where it scores only 0.14.

The alternative Scenario 3—the location of a marine entertainment and recreation centre within the environmental criterion is ranked first with a weight of 0.349. However, considering the weights of the criteria of the other alternatives, the differences in the weights of the environmental criterion are not that significant. The alternative Scenario 3—the location of a marine entertainment and recreation centre would rank highest only if the environmental criterion were considered. When the alternative Scenario 2—the location of a nautical port-marina (0.323) and the alternative Scenario 1—the location of a communal port (0.328) is considered separately, there is a minor difference in weight within the environmental criterion.

Since alternative Scenario 1—the location of a communal port—has the highest values for the spatial and security criteria, an increase in their weighting is likely to change the ranking of the alternatives (Figure 13).

By increasing the weight of the spatial criterion by 0.21 and the security criterion by 0.18, Scenario 1 (the location of a communal port) becomes the highest-ranked alternative. Sensitivity analysis reconfirmed the suitability of Scenario 2—the location of a nautical port-marina.

4. Discussion

The spatial impact of establishing both a communal port and a marina is permanent; however, the transformation is less complex for a communal port. A contributing factor is the concession’s typical duration of 12 to 15 years. Marina investment makes up a capital outlay; concessions commonly span 20, 30, or 50 years, thus restricting the space availability. The water areas occupied by both activities are comparable in size. The marina, however, is larger in scale due to the requirement for extensive additional land-based facilities. Therefore, the selection of the communal port is justified, considering the heightened importance of spatial and security criteria alongside the absence of significant land superstructure requirements. Although both activities demand ongoing commitment, this is less apparent for communal ports because of limited onshore infrastructure. Operating only six months a year, the marine entertainment and recreation centre remains inactive for the other six months. The marine entertainment and recreation centre, having operated under concession for 10–12 years, is inactive for six years, which eliminates it from consideration as a top priority.

Prescribed procedures regulate vessel entry, berthing, mooring, transfer, anchoring, and launching in both communal ports and marinas. Regulation of the aforementioned actions is also mandated as a critical factor in ensuring human safety and security. Marina services are of superior quality, with on-site personnel ensuring port safety. Marina berths usually accommodate vessels of seven metres or more, resulting in a greater overall fuel storage capacity. It is crucial to remember that the electronic systems aboard marina vessels are a frequent fire source. Besides mooring, marinas offer various additional boater services, some of which (like catering) may pose safety risks. Therefore, communal ports present a lower risk of incidents. Occupational injuries and diseases are more common in complex work environments with numerous processes, such as shipbuilding, for example. Given the absence of work processes, it is reasonable to consider the communal port acceptable in terms of work injuries and occupational diseases.

Considering its intensive activities and significant user numbers, the marine entertainment and recreation centre presents the greatest safety concerns. Aside from noise pollution generated by its operations, the marine entertainment and recreation centre exhibits no other substantial environmental effects. Therefore, environmental protection makes it the optimal alternative (weight 0.349). A minimal, insignificant weight difference (0.005) exists between the marina and the communal port, irrelevant to activity choices or environmental concerns.

The communal port and the marina have similar environmental impacts. Ship-sourced water pollution is attributable to engine exhaust emissions and the direct discharge of fuel, lubricating agents, and waste products. Moreover, harmful environmental impacts encompass habitat fragmentation and loss, water quality and sediment alterations, and elevated surface and underwater noise levels.

Unlike other commercial activities, the siting of a marina provides the most direct and indirect economic benefits to the local community, boosting its development. Based on the criterion of social justification, it follows that the marina represents the optimal choice. Marina construction acts as a catalyst for wide-ranging development in economically underdeveloped areas. The addition of restaurants, shops, and boat services near the marina stimulates employment and elevates the overall standard of living for the local population. Notably, the local community generates substantial revenue from concessions and utility fees, which are to be allocated exclusively for the benefit of the community.

The marine entertainment and recreation centre is desirable for entertaining the local and broader population. Because of its seasonal operation, the centre’s contribution to the community is less than that of a marina, yet marginally more than that of a communal port.

The communal port is important for the local population as a choice, but it does not bring economic benefits to the local community. The most significant benefit is reflected only in the accommodation of vessels. It is important to note that communal ports serve a small percentage of the population.

Although the environmental criterion has been recognised as the most important one, the chosen alternative in the observed area was the location of the marina. The location of the marina brings certain environmental risks. However, when all key criteria and sub-criteria are considered, a marina emerges as a balanced and sustainable investment, provided that it is planned in accordance with spatial plans and adheres to environmental protection principles. It is important to emphasise that modern trends in marina planning and management are increasingly focused on ecological sustainability. By introducing environmental standards, wastewater treatment systems, low-emission energy solutions, and digital monitoring, negative environmental impacts can be significantly mitigated. In this way, the marina becomes not only an economic asset but also a spatial and ecological benefit. Therefore, the marina’s long-term economic and social contributions far outweigh the limitations arising from its spatial and environmental demands.

5. Conclusions

Research findings suggest that integrating all factors influencing coastal zone spatial function facilitates the development of a model for evaluating the economic viability of activities, enabling the selection of those that benefit both society and the environment. A careful assessment of activity impacts on the coastal zone is necessary to ensure that chosen activities enhance economic and social well-being, environmental protection, safety, and public health.

The selected methodology enabled the development of a model to assess the justification for establishing activities in the coastal area. In developing the model, a multi-criteria analysis approach was conducted using the AHP method. Expert assessment was used in the implementation of the AHP method for comparing and assessing the selected criteria, sub-criteria, and alternatives. The experts’ preferences were synthesised using the Expert Choice software, resulting in the identification of the most suitable economic activity. The sensitivity analysis confirms that the selected activity is appropriate. Therefore, it can be concluded that the application of multi-criteria assessment methods in the decision-making process for establishing activities in the coastal area enables decision-makers to choose the most suitable option. The use of the AHP method allows a structured approach to decision-making, thereby enhancing the consistency of the process.

The application of research results becomes possible only after establishing a designated use for the coastal area. The appropriateness of activities in the observed area needs careful consideration. Early designation of the purpose of coastal areas helps prevent inappropriate economic activities.

The selection of experts significantly affects the decision-making process. The experts assess the defined criteria, sub-criteria, and alternatives according to their preferences, educational background, professional domain, and other factors. Therefore, it is important to select experts based on their fields of influence and their adequate level of expertise. It is of utmost importance that expert assessments are carried out by at least two to three experts from each domain involved in the decision-making process. The knowledge required to solve the problem is distributed among multiple experts and synthesised using the AHP method. A fundamental limitation of this approach lies in the selection of experts needed to assess the impacts of activities, since it is challenging to assemble the required number of experts.

This approach can be adapted for various coastal zones by adjusting scenarios and selection criteria, especially in spatial planning. This can also function as a tool in the development of marine spatial plans to ensure the sustainable management of marine areas. These results offer a theoretical framework for future work exploring coastal zone scenarios, the criteria used to assess them, and the varying expert viewpoints on these criteria. Therefore, further theoretical research and practical application could benefit from evaluating the rationale behind coastal activities.

Within the context of clarifying the purpose of the area and evaluating the rationale for initiating an economic activity, the AHP method has demonstrated its efficacy as a valuable instrument for selecting a viable decision-making solution for suitable economic activities in the coastal zone. The AHP method’s greatest advantage in creating a decision-making model is in expert involvement, the clear process for establishing criteria, and the opportunity for ongoing model development. Applying other multi-criteria decision-making methods, especially in integration with the AHP method, can also assist future research.