Climate Change Adaptation Strategies for Coastal Resilience: A Stakeholder Surveys

Abstract

We studied the significance of stakeholder engagement in climate change adaptation within the context of coastal resilience. Our approach aimed to enhance collaboration in environmental planning processes by leveraging modeling tools to facilitate learning about the complexity of the socioecological system. A comprehensive questionnaire survey was conducted using Google Forms. The questionnaire included clear instructions and structured response formats, aiming to gather stakeholder perspectives on adaptation measures and define action thresholds in response to climate uncertainties. A total of 47 responses were received and included consulting firm professionals, freelance engineers, local authority professionals, port authority professionals, researchers, and university professors in the field of coastal management. The survey data were analyzed using statistical methods in SPSS to identify key insights and patterns. The survey findings offer valuable insights into the effectiveness of adaptation measures, threshold perceptions for initiating adaptation actions, and the dynamics of stakeholder perspectives. Therefore, the importance of incorporating diverse perspectives in climate change adaptation efforts is highlighted. As answers tend to vary for different stakeholder occupations, the urge for collaboration in future decision-making procedures is highlighted. By bridging the gap between stakeholder input and climate change adaptation measures, this study demonstrates the potential of participatory approaches in enhancing resilience and fostering sustainable development in coastal regions vulnerable to climate change.

1. Introduction

Climate change mitigation and adaptation policies feature high levels of uncertainty and risk [1]. The sustainable management of ecosystems, along with the decision-making process it entails, typically necessitates the examination of ecological, social, and economic data [2]. The importance of stakeholder engagement in climate change adaptation is underscored by the literature advocating participatory approaches to enhance resilience and foster sustainable development [3]. The assessment of climate change impacts and the formulation of adaptation and mitigation strategies within the realm of climate economics have traditionally relied on the use of integrated assessment models (IAMs). Some notable examples include [4,5]. Furthermore, various adaptation measures for climate change in coastal areas have been explored in the literature, including coastal defense [6,7,8], coastal management [9,10], and water management [11,12,13,14]. The literature emphasizes the importance of context-specific approaches to coastal adaptation [15] and provides valuable guidance for policymakers and practitioners.

Stakeholder engagement is a widely debated topic in academic literature, with considerable variation observed in the actors involved [16]. Effectively addressing systematic stakeholder mapping and engagement presents challenges, especially within the context of integrated urban planning. The identification and promotion of innovative urban resilience strategies, with a focus on environmental sustainability, require collaborative efforts involving public authorities, universities, businesses, and communities, serving as essential elements in this endeavor [17].

In scenarios where information on inputs is incomplete, analysts may assign broad or conservative subjective ranges to gain initial insights into model behavior. Field experts may suggest relevant parameter ranges for complex assessment models attempting to replicate real-world phenomena. However, the variety of approaches underscores the potentially infinite domain of procedures, with certain domains being tractable for parameters but intractable for procedures [18]. From a scientific standpoint, IAMs tend to overlook certain types of uncertainty and risks. This omission can greatly influence model outcomes, as well as raise difficulties for their implementation in real-life problems [19,20]. However, it can be addressed by incorporating experts’ insights in a structured manner to identify overlooked factors or bridge knowledge gaps effectively [21]. Romsdahl [22] and Sanderson et al. [23] highlight the need for the creation of structured and coordinated networks and web portals between stakeholders, researchers, and governments, which could provide opportunities for climate-related decision support systems. Shiau and Liu [24] developed an indicator system for local government to evaluate sustainability strategies for transport projects, while Soma et al. [25] have a similar approach for transitions towards urban sustainability. Meliadou et al. [26] used fuzzy cognitive mapping to promote the role of stakeholders in integrated coastal zone management. Pinto et al. [2] analyzed the trade-offs between relevant types of services by estuarine ecosystems and stakeholders. Mallampalli et al. [27] outlined the respective roles of stakeholders in analyzing scenarios of land use change.

Berkes [28] promotes integrating local knowledge and community-based approaches in climate adaptation, emphasizing bottom-up perspectives in effective policy interventions. Furthermore, the assignment of values within a model is inherently linked to its structure, with constraints binding certain elements together and limiting the magnitude or possibility of individual changes [29]. In some cases, disentangling individual effects by varying each input separately may prove challenging due to structural constraints, impacting the design of meaningful sensitivity analyses. Additionally, Leitch et al. [30] developed CoastAdapt, a decision support framework (DSF) for effective decision making in coastal adaptation to climate change, involving stakeholders in the development process. Smith et al. [31] emphasize the value of stakeholder engagement in co-designing adaptation strategies, stressing inclusive decision-making processes to tackle environmental challenges. Karamaneas et al. [32] highlighted the added value of stakeholder aspirations in the energy sector in the field of climate change. Elkady et al. [33] characterized interactions among community stakeholders as disaster buffers on the way to building community resilience. Palla et al. [17] adopted a participatory approach to planning urban resilience to climate change in three case studies in Italy. Stamou et al. [34] used stakeholder and expert aspirations for risk assessment during vulnerability analysis of water infrastructures in the Mediterranean Region.

Our approach aims to enhance collaboration in environmental planning processes by leveraging modeling tools to facilitate learning about socioecological system complexity. Ultimately, this endeavor seeks to promote policy innovation in response to the challenges posed by climate change and ecosystem management. Addressing these uncertainties, especially regarding human behavior and decision making, requires a critical understanding of stakeholder perspectives and their implications for modeling outcomes. Stakeholder engagement, therefore, becomes a crucial component in adaptation frameworks, improving their predictive capacity.

This paper focuses on the pivotal role of stakeholder-driven insights in enhancing climate change adaptation models, with a specific emphasis on coastal resilience. Through a comprehensive questionnaire survey, stakeholders are invited to contribute their perspectives on adaptation measures and define action thresholds in the face of climate uncertainties. The survey findings are analyzed using statistical methods in SPSS, and the results will be used as input in an agent-based model (ABM) currently under development, which is based on the work of Roukounis et al. [35,36]. The aim of this questionnaire survey is to quantify the impact of adaptation measures as well as decide on adaptation action thresholds. Also, it is important to examine possible variance in the answers of stakeholders from different sectors, which might lead to conflicts in future decision-making procedures. Therefore, by identifying the patterns of behavior among the stakeholders in advance, it would be easier to select the synthesis of the stakeholder group that will address a real-world problem. By incorporating diverse stakeholder perspectives, the study aims to improve the accuracy and robustness of regular coastal resilience modeling, thereby offering valuable insights for decision makers, urban planners, and policymakers tasked with safeguarding coastal communities against climate-induced hazards.

2. Survey Design and Objectives

2.1. Study Area

The study area is the greater area of Vouliagmeni, located in the southern region of Athens in Attica, Greece (Figure 1). It is renowned for its unique geological features and coastal environment. The decision to focus the current application within the area of Vouliagmeni is driven by several pragmatic and methodological considerations. This area was selected because it was highlighted in previous research [35] as vulnerable to the impacts of coastal flooding. Moreover, a smaller, more contained area allows for a more focused analysis of local resilience factors. Lessons learned in this focused setting can guide adjustments and enhancements when scaling to larger regions. Encompassing urban, suburban, and rural zones, alongside both natural and artificial coastlines, this area forms part of the continuous Athens Urban Area, the financial capital of Greece. The area is characterized by a high density of pine trees and a very high level of tourist activity. The study area, due to its orientation and the morphology of the wider area, is mainly affected by wind waves originating from the southwest, south, southeast, east, northeast, and north directions; the prevailing winds are northerly. The average range of sea level variation in the study area is small, and generally, the influence of tides on the movement of sea masses is not significant.

The following formations can be present in the area: artificial embankments, marine deposits (bottom sediments), marls, crock bedrock, limestones of flattened structure, or calcareous flats. The selected area is shown in Figure 1.

2.2. Scenarios

Climate change poses significant challenges to coastal communities worldwide. Rising sea levels, an increased frequency of extreme weather events, and coastal erosion threaten the region’s socio-economic and environmental well-being [37]. To address these challenges, informed decision making and proactive adaptation strategies are essential. The primary objective of the survey is to gather insights from stakeholders representing diverse sectors and perspectives on climate change adaptation strategies.

Adapting the Sixth Assessment Report (AR6) of the United Nations (UN) Intergovernmental Panel on Climate Change (IPCC) [38] to the Greek context involves refining the assumptions of the shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) to accurately mirror the unique socio-economic, environmental, and cultural landscapes of Greece. The GR-SSP2-RCP4.5 (“Symphony of Disintegration”) and GR-SSP5-RCP8.5 (“For whom the storm tolls”) scenarios, as a result, diverge significantly from their global counterparts in numerous crucial aspects.

2.2.1. Scenario 1 (GR-SSP2-RCP4.5)—“Symphony of Disintegration”

In this scenario, Greece’s economy, which is heavily reliant on tourism and services, is anticipated to follow a moderate development path. This trajectory suggests a slower transition to renewable energy compared to more industrialized economies, consequently affecting the pace of emission reductions. The cultural and policy responses in Greek society to climate change could be characterized by moderate adaptation and mitigation measures, possibly including gradual shifts in urban planning like moderate investments in sustainable infrastructure or coastal defenses. Governments, meanwhile, might implement moderate policy changes, reflecting a balanced approach to fostering economic growth alongside environmental sustainability.

2.2.2. Scenario 2 (GR-SSP5-RCP8.5)—“For whom the storm tolls”

In contrast, the GR-SSP5-RCP8.5 scenario envisions a high-emission development path for Greece, akin to a ‘business-as-usual’ trajectory, potentially leading to significant economic growth fueled predominantly by fossil fuels. This path could result in higher emissions, thus increasing Greece’s vulnerability to severe climate impacts. Rapid development, particularly in coastal regions, might amplify vulnerability to sea-level rise and extreme weather events, potentially exacerbated by increased construction in flood-prone areas due to tourism and real estate pressures. In this scenario, households might lean towards prioritizing short-term economic gains, potentially underestimating long-term sustainability and climate risks. Governments, conversely, might concentrate on economic growth, possibly at the expense of stringent climate policies, which could result in delayed or insufficient adaptation and mitigation measures.

The evaluation criteria for the adaptation measures were established on a scale ranging from 1 to 7, where a score of 1 signifies minimal effectiveness in reducing risks related to SLR and coastal flooding, and a score of 7 indicates a high level of effectiveness. The cumulative outcomes of this survey were then aggregated to derive a comprehensive understanding of the efficacy of each adaptation measure. The adaptation measures selected for review for the purpose of the research are:

• Community information and participation: This category of adaptation measures includes building public awareness and community engagement about the impacts of climate change, using strategies such as the provision of information on news and social media, the participation of residents in co-creative workshops, living labs, etc.
• Individual anti-flood measures (property flood-proofing): Individual anti-flood measures involve homeowners taking direct action to protect their properties from the impacts of rising sea levels and associated flood risks. These actions include elevating new structures above flood levels, property flood-proofing, and building barriers. Homeowners take into consideration the cost in relation to the expected results on their property.
• Property insurance: This category includes individual property insurance for natural hazards as well as the implementation of mandatory insurance by the public authorities as an adaptation strategy for climate change. Insurance provides a financial safety net, ensuring that homeowners can recover and rebuild more quickly after a flood event.
• Nature-based protection measures (living shorelines): Nature-based solutions include methods like wetland restoration, beach nourishment, and the creation of living shorelines. They can enhance ecosystem services, habitat quality, and sustainability with lower construction and maintenance costs.
• Hard protection measures: Hard coastal protection measures, often employed to guard against erosion and sea-level rise, include structures like seawalls, breakwaters, and groynes. They offer immediate effectiveness, a high level of protection, and durability. Meanwhile, they have significant environmental impacts, higher construction costs, and possible aesthetic degradation.
• Managed retreat, realignment, and setbacks: Managed retreat, or managed realignment, is a coastal management method that entails controlled inundation of low-lying coastal zones and the strategic relocation of communities and infrastructure, allowing the natural inward movement of shorelines. Creating these setback zones offers long-term sustainability, community resilience through relocation to safer locations, and ecological benefits by allowing natural processes to occur.

The survey’s goal was to contribute to the understanding and enhancement of coastal resilience amidst the challenges posed by climate change. Recognizing the urgent need for proactive adaptation measures, the questionnaire aimed to gather data that would inform the development of robust strategies to mitigate risks associated with sea-level rise and coastal flooding. By aligning survey objectives with broader climate change adaptation goals, the questionnaire sought to bridge the gap between research and policy implementation, facilitating evidence-based decision making in the face of climate uncertainty. More specifically, the survey aims to:

• Evaluate the effectiveness of various adaptation measures, including community engagement, property flood-proofing, insurance, nature-based solutions, hard protection measures, and managed retreat.
• Estimate thresholds for initiating adaptation actions under different climate scenarios, focusing on sea-level rise and coastal flooding.
• Identify key challenges and opportunities in setting realistic thresholds for governmental action in coastal resilience models.

2.3. Methodology

The survey employs a mixed-methods approach, combining closed-ended and open-ended questions to capture both quantitative and qualitative data. The qualitative component introduces a degree of subjectivity due to stakeholder involvement. Stakeholders are identified through a comprehensive analysis of relevant organizations and networks, including government agencies, academic institutions, non-governmental organizations, industry associations, and community groups. To maximize participation rates and ensure diverse representation, the survey was disseminated through multiple channels, including email invitations and professional networks. Personalized invitations were sent to key stakeholders, highlighting the relevance of their expertise and experience to the survey objectives. Additionally, efforts were made to accommodate stakeholder scheduling constraints by offering flexible response deadlines and opportunities for follow-up discussions.

The inclusion of policymakers provided insights into the regulatory and policy frameworks necessary to support adaptation efforts, while researchers contributed scientific expertise and methodological insights. Practitioners shared practical experiences and implementation challenges encountered in the field, offering valuable insights into the feasibility and effectiveness of different adaptation measures. By engaging diverse stakeholders, the survey aimed to generate actionable insights that could inform decision-making and policy development processes. Stakeholder perspectives were integral to identifying adaptation priorities, evaluating the effectiveness of existing measures, and anticipating future challenges and opportunities. Policymakers could leverage survey findings to design evidence-based policies and programs that address the needs and concerns of local communities, while practitioners could benefit from peer insights and best practices shared by fellow stakeholders. Ultimately, the inclusion of diverse stakeholders enhanced the credibility, relevance, and applicability of the survey findings, ensuring that adaptation strategies were grounded in a holistic understanding of coastal resilience dynamics.

2.4. Survey Design

The questionnaire itself was designed to be accessible and user-friendly, using Google Forms, with clear instructions and structured response formats. Closed-ended questions allowed for quantitative analysis of stakeholder preferences and perceptions, while open-ended questions encouraged respondents to provide qualitative insights and elaborate on their responses. By incorporating a mix of quantitative and qualitative data collection methods, the survey aimed to capture a comprehensive range of stakeholder perspectives on climate adaptation. The questionnaire consisted of three main parts (A, B, and C). The questionnaire survey is provided in full in the Supplementary Materials file accompanying this paper:

i.

Survey dissemination and respondent personal information

ii.

Part A—Evaluation of adaptation measures: Stakeholders rate the effectiveness of six categories of adaptation measures on a scale from 1 to 7, focusing on community engagement, property flood-proofing, insurance, nature-based solutions, hard protection measures, and managed retreat (Supplementary Materials, Questions M.1–M.7). Afterwards, the participants were asked to select the criteria based on which they made their evaluation in a multiple-choice question.

iii.

Part B—Estimation of adaptation thresholds: Stakeholders estimate thresholds for initiating adaptation actions under two climate scenarios, GR-SSP2-RCP4.5 (Supplementary Materials, Questions Q1.1–1.7) and GR-SSP5-RCP8.5 (Supplementary Materials, Questions Q2.1–Q2.6), focusing on indicators such as climate change awareness, insurance coverage, sea-level rise, and the Coastal Resilience Index (CResI).

iv.

Part C—Open questions: Stakeholders provide qualitative insights on recommended approaches for updating thresholds, additional indicators for setting thresholds, and key challenges in governmental action on coastal resilience (Supplementary Materials, Questions O.Q.1–O.Q.3).

A key strength of the survey design was its inclusivity, which facilitated the capture of diverse viewpoints and expertise areas. Stakeholders representing various sectors, including government agencies, academia, non-governmental organizations, industry, and local communities, were invited to participate. This diversity ensured that the survey findings reflected a broad spectrum of perspectives, priorities, and concerns related to coastal resilience and climate adaptation.

3. Data Collection and Analysis

Overall, 47 answers were taken into consideration from different fields (academia, research institutions, port and marina management, central and local authorities, and relevant consultancies). The response rate was around 65% of total invitations. The distribution of responders’ occupations is shown in Figure 2.

Invitations for the questionnaire survey were sent, distributed equally in the academic sector (universities and research institutions), engineering firms (consultancies, freelancer engineers, and employees in port/marina authorities), members of local/central government, and NGOs. Questionnaires were not addressed to residents, as they do not have the expertise to analyze the data and propose actions and thresholds at this level of decision making. However, their aspirations need to be taken into consideration in the next steps of the research. Furthermore, a similar set of stakeholders has been used in other case studies in the literature [39,40]. As the survey is addressed to experts in the field and not to the general public, the final number of 47 responses is enough to extract useful conclusions. Members of the academic community had the highest response rate, while local/central government and NGOs had the lowest. Out of the 47 responders, twenty-one (21) were members of the academic community, including professors, post-doc researchers, and PhD candidates; four (4) were members of a research institution; twelve (12) were employed in consulting firms in relevant fields (coastal, marine, hydraulic or environmental engineering); five (5) were freelancer engineers; three (3) were occupied in the port or marina management field; and two (2) were employed in local authorities. Statistical analysis was performed using the SPSS software (Version 29.0.1.0). In this study, both descriptive statistics and MANOVA (multivariate analysis of variance) were employed to analyze the data and address the research objectives effectively. Measures of the central tendency (e.g., means) and variability (e.g., standard deviations) of the data have been calculated in descriptive statistics. Particularly, frequencies were utilized to provide a comprehensive overview of the dataset, offering insights into the distribution and the response patterns for the variables under investigation.

The next step included the use of descriptive statistics and multivariate analysis of variance (MANOVA). In order to look into some key characteristics of the data, we calculated frequencies, measures of central tendency, and variability in order to reveal response patterns. With MANOVA, we were able to investigate the existing relationships among multiple dependent variables, such as effectiveness, simplicity, and sustainability, in relation to one or more of the independent variables, such as the occupation or the demographic characteristics of the sample.

4. Results

Descriptive statistics are shown in

Table 1. Descriptive statistics of the questionnaire survey.

	Descriptive Statistics
	Questions *	N	Minimum	Maximum	Mean	Std. Deviation
Adaptation Measures Evaluation	M.1	47	1	7	4.83	1.60
	M.2	47	1	7	4.21	1.65
	M.3	47	1	7	4.09	1.85
	M.4	47	1	7	5.21	1.50
	M.5	47	2	7	5.49	1.16
	M.6	47	1	7	5.43	1.58
Criteria	Effectiveness	47	0	1	0.72	0.45
	Simplicity	47	0	1	0.13	0.34
	Sustainability	47	0	1	0.57	0.50
	Aesthetic_Degradation	47	0	1	0.19	0.40
	Action_Cost	47	0	1	0.23	0.43
	Financial_Impacts	47	0	1	0.28	0.45
	Other	47	0	1	0.09	0.28
Scenario 1: GR-SSP2xRCP4.5 Thresholds	Q.1.1	46	20%	100%	55.39%	19.53%
	Q.1.2	47	10%	90%	45.74%	21.74%
	Q.1.3	46	0.00	0.50	0.22	0.12
	Q.1.4	46	0.00	0.50	0.25	0.12
	Q.1.5	45	1.0	4.0	2.80	0.64
	Q.1.6	45	0.0	16.0	6.38	5.10
	Q.1.7	43	0	16	8.40	5.19
Scenario 2: GR-SSP5xRCP8.5 Thresholds	Q.2.1	46	20%	100%	50.72%	24.04%
	Q.2.2	46	5%	100%	47.50%	24.49%
	Q.2.3	46	0.00	0.50	0.24	0.12
	Q.2.4	45	0.00	0.50	0.26	0.12
	Q.2.5	45	0.3	5.0	2.99	0.98
	Q.2.6	44	0.0	16.0	7.48	4.88
	Valid N (listwise)	42

Note: * The questions of the survey are presented in the Supplementary Materials accompanying this paper.

. In the first part of the questionnaire, the effectiveness of various adaptation measures related to sea-level rise (SLR) and coastal flooding is explored.

Notably, “Local Authorities” and “University” exhibited high mean assessments across multiple measures, emphasizing community engagement, individual flood protection measures, and property insurance. In contrast, “Freelancers” demonstrated lower mean scores, potentially indicating a lower priority given to these aspects. The effectiveness of nature-based protection measures varied, with “Freelancers” and “Port Authorities” showing the highest mean scores. Diverse perspectives emerged on hard protection measures, with “University” displaying the lowest mean and “Local Authorities” the highest, indicating varied approaches. Similarly, opinions on managed retreat, realignment, and setbacks varied, with “Freelancers” expressing the highest mean score and “University” the lowest (see

Table 2. Frequencies based on the “Occupation” variable.

Occupation			M.1 *	M.2 *	M.3 *	M.4 *	M.5 *	M.6 *
Local Authorities	N	Valid	2	2	2	2	2	2
		Missing	0	0	0	0	0	0
	Mean		5.00	5.50	3.00	4.00	7.00	4.50
	Std. Deviation		0.00	0.70	0.00	2.83	0.00	3.53
	Minimum		5	5	3	2	7	2
	Maximum		5	6	3	6	7	7
Port/Marina Authorities	N	Valid	3	3	3	3	3	3
		Missing	0	0	0	0	0	0
	Mean		5.00	4.33	6.33	6.00	5.33	6.00
	Std. Deviation		0.00	0.58	1.15	1.00	0.57	0.00
	Minimum		5	4	5	5	5	6
	Maximum		5	5	7	7	6	6
University	N	Valid	19	19	19	19	19	19
		Missing	0	0	0	0	0	0
	Mean		5.21	4.63	4.37	5.11	5.74	5.32
	Std. Deviation		1.78	1.83	1.86	1.45	1.04	1.83
	Minimum		2	1	2	1	3	1
	Maximum		7	7	7	7	7	7
Research institution	N	Valid	4	4	4	4	4	4
		Missing	0	0	0	0	0	0
	Mean		3.50	4.00	3.50	5.50	5.00	6.50
	Std. Deviation		2.08	2.31	2.64	1.73	0.81	0.58
	Minimum		1	2	1	4	4	6
	Maximum		6	6	7	7	6	7
Consultancy	N	Valid	12	12	12	12	12	12
		Missing	0	0	0	0	0	0
	Mean		4.92	3.67	3.42	5.42	5.00	5.25
	Std. Deviation		1.44	1.61	1.67	1.31	1.47	1.29
	Minimum		2	2	1	2	2	3
	Maximum		7	7	7	7	7	7
Freelancer	N	Valid	5	5	5	5	5	5
		Missing	0	0	0	0	0	0
	Mean		3.80	3.40	4.20	4.40	5.80	5.20
	Std. Deviation		1.48	1.14	1.79	1.95	1.09	1.79
	Minimum		2	2	3	2	4	3
	Maximum		6	5	7	7	7	7

Note: * The questions of the survey are defined in the Supplementary Materials accompanying this paper.

).

Local authorities emphasize the effectiveness and financial aspects of measures, underscoring the importance of cost implications. Port authorities share a concern for effectiveness, with a specific interest in the economic impacts of actions. Professionals affiliated with universities prioritize effectiveness, sustainability, and consider additional aspects beyond the predefined choices. Respondents from research institutions highlight the significance of simplicity in measures. Consultancy professionals underscore the importance of sustainability and economic considerations. Freelancers express a preference for simple measures and a concern for action costs.

To continue, the responders were asked to provide thresholds for each one of the scenarios. For scenario GR-SSP3xRCP4.5 “Symphony of Disintegration”, the analysis of thresholds set by different occupational categories for key adaptation measures reveals nuanced patterns of divergence. Local authorities uniformly agree on lower sea-level rise thresholds and exhibit a cautious approach across various measures. Port authorities, while demonstrating diversity, generally hold a more conservative stance, particularly in managing retreat. Universities and research institutions present moderate diversity in their perspectives, with slightly varying thresholds reflecting their nuanced positions. Consultancy firms and freelance engineers exhibit more consistent and moderate stances, with lower thresholds for certain measures. These findings underscore the importance of considering diverse occupational perspectives in crafting adaptive strategies, providing valuable insights for policymakers and planners seeking effective and inclusive climate adaptation measures (see

Table 3. Adaptation thresholds for Scenario 1.

Occupation			Q.1.1 *	Q.1.2 *	Q.1.3 *	Q.1.4 *	Q.1.5 *	Q.1.6 *	Q.1.7 *
Local Authorities	N	Valid	2	2	2	2	2	2	2
		Missing	0	0	0	0	0	0	0
	Mean		62.50%	42.50%	0.17	0.18	3.00	4.50	7.50
	Std. Deviation		17.68%	45.96%	0.03	0.09	1.41	0.70	3.53
	Minimum		50%	10%	0.15	0.125	2.0	4.0	5
	Maximum		75%	75%	0.20	0.250	4.0	5.0	10
Port/Marina Authorities	N	Valid	3	3	3	3	3	3	3
		Missing	0	0	0	0	0	0	0
	Mean		56.67%	46.67%	0.20	0.23	2.83	11.00	9.33
	Std. Deviation		11.55%	25.66%	0.08	0.06	0.29	7.81	7.02
	Minimum		50%	25%	0.10	0.200	2.5	2.0	2
	Maximum		70%	75%	0.25	0.300	3.0	16.0	16
University	N	Valid	19	19	19	19	18	19	19
		Missing	0	0	0	0	1	0	0
	Mean		55.68%	44.21%	0.2026	0.22105	3.000	7.579	9.11
	Std. Deviation		21.91%	21.81%	0.11	0.11	0.62	5.48	5.23
	Minimum		30%	15%	0.00	0.000	2.0	2.0	2
	Maximum		100%	90%	0.50	0.500	4.0	16.0	16
Research institution	N	Valid	4	4	4	4	4	4	3
		Missing	0	0	0	0	0	0	1
	Mean		48.75%	57.50%	0.22	0.30	3.12	6.75	15.00
	Std. Deviation		24.62%	35.94%	0.19	0.18	0.63	6.70	1.732
	Minimum		20%	10%	0.05	0.100	2.5	0.0	13
	Maximum		80%	90%	0.50	0.500	4.0	16.0	16
Consultancy	N	Valid	11	12	11	11	11	10	10
		Missing	1	0	1	1	1	2	2
	Mean		60.00%	45.83%	0.2727	0.28455	2.409	3.750	6.00
	Std. Deviation		19.87%	17.23%	0.14	0.13	0.66	3.24	4.94
	Minimum		25%	10%	0.00	0.100	1.0	0.0	0
	Maximum		85%	80%	0.50	0.500	3.0	10.0	16
Freelancer	N	Valid	5	5	5	5	5	5	4
		Missing	0	0	0	0	0	0	1
	Mean		53.00%	52.00%	0.21	0.26	2.70	6.30	7.25
	Std. Deviation		14.83%	13.04%	0.11	0.09	0.45	3.56	4.85
	Minimum		40%	30%	0.10	0.150	2.0	0.5	1
	Maximum		75%	60%	0.40	0.400	3.0	10.0	12

Note: * The questions of the survey are defined in the Supplementary Materials accompanying this paper.

).

In this analysis of Scenario GR-SSP5xRCP8.5 threshold perceptions, distinct patterns emerge. Local authorities maintain conservative stances, particularly evident in their sea-level rise and flood-proof assistance program thresholds. Port authorities exhibit variability, while universities and research institutions demonstrate moderate diversity. Consultancy firms and freelancer engineers present consistent, moderate thresholds, aligning with their generally cautious approach. These findings underscore the importance of recognizing occupational nuances in crafting adaptive strategies, providing valuable insights for policymakers aiming at comprehensive and effective climate adaptation measures (see

Table 4. Adaptation thresholds for Scenario 2.

Occupation			Q2.1 *	Q.2.2 *	Q.2.3 *	Q.2.4 *	Q.2.5 *	Q.2.6 *
Local Authorities	N	Valid	2	2	2	2	2	2
		Missing	0	0	0	0	0	0
	Mean		47.50%	40.00%	0.2500	0.3250	3.750	1.000
	Std. Deviation		38.89%	49.50%	0.07	0.10	1.06	0.00
	Minimum		20%	5%	0.20	0.25	3.0	1.0
	Maximum		75%	75%	0.30	0.40	4.5	1.0
Port/Marina Authorities	N	Valid	3	3	3	3	3	3
		Missing	0	0	0	0	0	0
	Mean		56.67%	56.67%	0.23	0.26	3.33	10.000
	Std. Deviation		11.55%	32.14%	0.12	0.06	0.58	7.21
	Minimum		50%	20%	0.09	0.20	3.0	2.0
	Maximum		70%	80%	0.30	0.30	4.0	16.0
University	N	Valid	21	21	21	21	20	20
		Missing	0	0	0	0	1	1
	Mean		51.74%	46.05%	0.22	0.22	3.03	8.61
	Std. Deviation		27.36	26.24%	0.11	0.09	0.83	4.74
	Minimum		20%	15%	0.00	0.00	1.0	2.0
	Maximum		100%	100%	0.40	0.40	4.0	16.0
Research institution	N	Valid	4	4	4	4	4	4
		Missing	0	0	0	0	0	0
	Mean		50.00%	45.00%	0.21	0.25	3.37	6.75
	Std. Deviation		31.62%	23.80%	0.20	0.19	1.10	6.70
	Minimum		20%	10%	0.05	0.10	2.5	0.0
	Maximum		90%	60%	0.50	0.50	5.0	16.0
Consultancy	N	Valid	11	11	11	10	11	10
		Missing	1	1	1	2	1	2
	Mean		53.64%	56.82%	0.27	0.31	2.66	6.65
	Std. Deviation		22.37%	22.16%	0.12	0.15	1.30	4.59
	Minimum		25%	20%	0.06	0.01	0.3	0.5
	Maximum		90%	90%	0.50	0.50	4.0	16.0
Freelancer	N	Valid	5	5	5	5	5	5
		Missing	0	0	0	0	0	0
	Mean		47.00%	40.00%	0.3100	0.3700	2.700	7.800
	Std. Deviation		19.87%	15.81%	0.09	0.10	0.84	3.35
	Minimum		30%	20%	0.20	0.25	2.0	4.0
	Maximum		75%	60%	0.40	0.50	4.0	12.0

Note: * The questions of the survey are defined in the Supplementary Materials accompanying this paper.

).

Furthermore, the multivariate tests examine the overall significance of the intercept (baseline) and the effect of occupation on the dependent variables. The intercept effect is highly significant, indicating that there are significant differences in the dependent variables across groups or conditions represented by the intercept. However, the effect of occupation is not statistically significant according to three out of four multivariate test statistics (Pillai’s Trace, Wilks’ Lambda, and Hotelling’s Trace), suggesting that there is no overall significant difference in the dependent variables based on occupation. Interestingly, according to Roy’s Largest Root, there is a significant effect of occupation on the dependent variables. This discrepancy could be due to the sensitivity of different multivariate tests to the underlying assumptions and characteristics of the data (see

Table 5. Multivariate Tests ^a (MANOVA).

Effect		Value	F	Hypothesis df	Error df	Sig.
Intercept	Pillai’s Trace	0.99	36.65 b	26.000	11.000	<0.001
	Wilks’ Lambda	0.01	36.65 b	26.000	11.000	<0.001
	Hotelling’s Trace	86.62	36.65 b	26.000	11.000	<0.001
	Roy’s Largest Root	86.62	36.65 b	26.00	11.00	<0.001
Occupation	Pillai’s Trace	3.41	1.235	130.00	75.00	0.16
	Wilks’ Lambda	0.001	1.29	130.00	59.17	0.14
	Hotelling’s Trace	18.09	1.31	130.00	47.00	0.15
	Roy’s Largest Root	9.41	5.43 c	26.00	15.00	<0.001

Note: ^a Design: Intercept + Occupation, ^b Exact statistic, ^c The statistic is an upper bound on F that yields a lower bound on the significance level.

).

5. Discussion

The results of the questionnaire survey revealed that the effectiveness of adaptation measures varies among stakeholders. This diversity is logical, considering the unique experiences of each expert. For example, academics, particularly those involved in environmental research, are more likely to prioritize environmental-friendly approaches, while others lean towards strategies for economic efficiency. Those involved in local authorities and academia tended to rate community engagement, flood-proofing, and insurance measures higher than proactive risk reduction strategies. This perception, however, was not universally accepted by all groups. In contrast, freelancing engineers set higher scores in short-term economic efficiency than in long-term sustainability and climate risk mitigation. However, their interest in nature-based protection measures, alongside port authority stakeholders, shows the growing recognition of the value of ecosystem-based approaches in coastal resilience planning. Meanwhile, the perspectives on hard protection measures and managed retreat were diverse among stakeholders.

On the other hand, similar variation among the different occupational groups was observed when setting the adaptation thresholds. It is worth mentioning that different groups of similar answers were identified when analyzing questions of A (adaptation measures evaluations) and part B (adaptation thresholds). More specifically, local and port authorities showed a similar yet cautious approach to risk management and infrastructure planning. Furthermore, members of academia and research faculties emphasized the importance of evidence-based decision making and interdisciplinary collaboration. Engineering consultants and freelancers, meanwhile, demonstrated more consistent and moderate thresholds, as their cost-effectiveness profiles suggested. All the above highlights the complexity of decision-making procedures and the urge for collaboration among different sectors, in order to achieve the optimal adaptation strategy.

The impact of stakeholder group dynamics on decision-making issues was assessed using multivariate tests (MANOVA). To be more specific, the variance of occupation was not statistically significant based on three out of four multivariate test statistics. However, as the intercept effect was highly significant, important differences in dependent variables across occupational groups are indicated. As shown in Table 5, Roy’s Largest Root test revealed a noteworthy effect of occupation on dependent variables, highlighting the sensitivity of different analytical approaches to the set of stakeholders.

The answers to the open questions were key to understanding the mindset of the respondents as well as the general process of climate change adaptation decision making. In Question 1, stakeholders emphasized the necessity of active monitoring, collaborative decision making, and the integration of new data and research findings. More specifically, the majority of stakeholders suggested a collaborative approach, incorporating inputs from scientific bodies and aligning updates with authoritative reports such as those from the Intergovernmental Panel on Climate Change (IPCC). Moreover, the uncertainty over climate projections is highlighted in adaptive decision making, especially when utilizing techniques such as decision making under deep uncertainty and resilience engineering. Furthermore, collaboration among diverse stakeholders is crucial, followed by recommendations for structured data collection, expert panel reviews, and continuous assessment and evaluation. Real-time monitoring using high-end observation technologies and long-term data analysis are proposed to inform the determination of action thresholds and enable timely responses to emerging risks. Additionally, risk assessment strategies, scenario-based planning, education, and community engagement actions are highlighted to raise awareness and promote proactive adaptation measures.

In Question 2, stakeholders suggested other environmental, social, and economic indicators deemed critical for setting thresholds in coastal modeling. Environmental indicators included biodiversity, ecosystem services, land use/cover, storm intensity, overland flooding, flood frequency, coastal dynamics, extreme temperatures, and the protection of natural habitats. Social indicators identified the percentage of coastal inhabitants affected, socioeconomic impact, cultural heritage preservation, community resilience, and public trust in governance. Moreover, to assess the economic impact, stakeholders suggest economic indicators such as the financial situation of citizens, the cost of actions, insurance affordability, and impacts on the real economy. Furthermore, and to agree with their responses in the previous part of the questionnaire, collaboration with the scientific community and the establishment of monitoring networks are suggested for tracking indicators such as shoreline erosion, habitat loss, and shifts in coastal occupation patterns.

For Question 3, stakeholders were asked to suggest potential challenges in setting realistic thresholds for governmental action in coastal resilience models, along with potential solutions. A critical challenge is to find the ideal balance among economic development, social justice, and environmental protection, highlighting the need for policies that take into account diverse stakeholder interests. In real-world situations, however, conflict of interests among stakeholders poses another significant obstacle that could be addressed using participatory approaches and the integration of fuzzy numbers in models. Moreover, in this era of continuous change, with the economy, legislation, and climate being highly dynamic, stakeholders highlighted that frequent updates to proposed thresholds are required to make sure they remain relevant and effective. According to the survey participants, challenges can also arise from data resolution issues and the lack of societal impact analysis when assigning relevant studies to institutions, emphasizing the need for non-centralized frameworks and local stakeholder involvement. Building trust among stakeholders and tailoring models to local scales are identified as potentially effective strategies for overcoming these challenges. Furthermore, the rise of economic growth over environmental protection in urban development requires innovative sustainable practices to ensure that spatial policies focus on sustainability. Challenges related to human factors, governmental coordination, budget availability, uncertainty in climate projections and models, and the incorporation of past data into resilience models are also mentioned. Nevertheless, it is worth mentioning that the stakeholders’ responses were rarely beyond their day-to-day field point of view, agreeing with the notes of researchers in similar cases [41,42].

6. Conclusions

In conclusion, this paper contributes to the existing, yet constantly evolving, literature on climate change adaptation strategies in coastal communities. Diverse stakeholder perspectives, threshold perceptions, and the dynamics of adaptation decision making are crucial to addressing the challenges of climate change-related hazards. As mentioned in previous research, the study area in Greece faces hazards from climate change. Therefore, socio-economic and environmental challenges need proactive adaptation strategies or perfectly timed reactive planning. Useful conclusions on climate change adaptation planning and decision-making procedures are highlighted, focusing on the GR-SSP2-RCP4.5 (“Symphony of Disintegration”) and GR-SSP5-RCP8.5 (“For whom the storm tolls”) scenarios. The survey found that stakeholders from different occupations have varied views on the effectiveness of adaptation measures. By examining differences in stakeholder responses across sectors, variations that could lead to conflicts in decision making are addressed. Early identification of common actions can help to form a united stakeholder group to address real-world issues.