Risk and Resilience in Tourism: How Political Instability and Social Conditions Influence Destination Choices

Abstract

In an era of increasing global uncertainty, tourism destinations face significant challenges due to political instability and social unrest, which shape travelers’ perceptions and decision making. This study examines the relationship between perceived risk, resilience, and destination choice, focusing on the extent to which political and social conditions influence travel intentions. Using the social amplification of risk framework (SARF) and a quantitative survey, this research identifies key determinants of tourism resilience and risk perception management. Our findings indicate that political instability, safety concerns, and negative media coverage deter travelers, while effective crisis communication, strong governance, and high-quality public services can enhance a destination’s appeal. Based on these findings, the study recommends that destination marketers and tourism policymakers invest in targeted safety communication, service quality improvements, and strategies that address the specific concerns of more risk-sensitive demographics, such as women. The study offers strategic insights for destination marketers, tourism policymakers, and hospitality stakeholders on how to mitigate perceived risks and foster resilience in tourism-dependent economies. Future research could explore cross-cultural traveler behavior and incorporate perspectives from tourism professionals to further inform resilience strategies. By addressing these challenges, destinations can develop sustainable strategies to navigate crises and maintain competitiveness in an unpredictable global landscape.

1. Introduction

The tourism industry has exerted, and continues to exert, a substantial impact on the global economy, fostering the development of every nation (Milne & Ateljevic, 2001). It serves as a key driver of economic growth, employment generation, and cultural exchange, particularly in destinations where service-based industries dominate due to declining competitiveness in manufacturing and goods-processing sectors (McKinsey Global Institute, 2019). Tourism’s contribution to global economic activity is vast (IBIS World, 2021), influencing multiple sectors, including accommodation, transportation, entertainment, and local economies (Smeral, 1998). However, tourism is highly susceptible to external disruptions, with various factors, such as political instability, social unrest, and economic crises, influencing traveler perceptions, destination choices, and the long-term resilience of the industry (Wibowo & Hariadi, 2022; Sui et al., 2022).

According to the United Nations World Tourism Organization (UNWTO, 2022) tourism has expanded rapidly in developed nations, generating employment and economic benefits across multiple sectors. However, a destination’s attractiveness is not solely determined by infrastructure and service quality; rather, it is significantly affected by safety perceptions, stability, and sociopolitical factors. Destinations facing geopolitical instability, terrorism threats, or social unrest often experience declining visitor numbers, economic downturns, and reputational damage that weaken tourism resilience (Sönmez et al., 1999; Rittichainuwat & Chakraborty, 2009; Lagos, 2018). External factors, such as political unrest, global health emergencies, economic instability, and media framing, significantly influence destination attractiveness, often beyond the control of tourism stakeholders. The recent literature emphasizes that these uncontrollable events can rapidly alter travel intentions, create long-lasting reputational damage, and challenge even well-managed destinations (Brouder, 2020; Nguyen Viet et al., 2020). Incorporating these dimensions is essential to understanding how resilience strategies must adapt to an increasingly volatile global environment.

It is well-known that Greece’s tourism industry was significantly affected by the recent global health crisis and the resulting social disruptions, particularly during the first year of the pandemic (Medová et al., 2021; Ushakov & Andreeva, 2021). According to data from the Bank of Greece and the Hellenic Statistical Authority, international arrivals in 2020 dropped by over 76%, while travel receipts fell by approximately 78% compared to 2019. Although the sector began to recover in 2022, official figures from 2023 indicate that the recovery was still uneven, with fluctuations in inbound travel and persistent cost pressures challenging overall performance (Bank of Greece, 2023; Hellenic Statistical Authority, 2023). Similarly, the pandemic disrupted business-oriented tourism, which shifted toward digital and hybrid models. However, despite recognizing the benefits of digital events, participants continue to show a strong preference for physical events, underscoring the enduring importance of in-person interactions in business tourism (Kostopoulou et al., 2022).

Since 2022, the global tourism industry has demonstrated significant recovery. According to the UNWTO (2024), international tourist arrivals reached 98% of pre-pandemic levels in the first nine months of 2024, with many destinations surpassing 2019 figures. This resurgence is attributed to increased demand, improved air connectivity, and the easing of travel restrictions. Nevertheless, the recovery remains uneven. Regions continue to face challenges, such as labor shortages, inflation, and geopolitical tensions (OECD, 2024). Moreover, travelers’ expectations are evolving, with a greater emphasis being placed on sustainability, digital experiences, and personalized service (McKinsey & Company, 2024). These developments reinforce the importance of continuously reassessing how political and social conditions influence risk perception and destination choice in a rapidly changing tourism landscape.

Additionally, social and cultural conditions, such as public service quality, environmental concerns, and local attitudes toward tourism, influence both tourist satisfaction and long-term destination loyalty. These elements influence not only how satisfied visitors feel during their stay but also affect their willingness to return in the future and recommend the destination to others (Guo & Liu, 2024; Casado-Aranda et al., 2021; Kourkouridis et al., 2024).

As the global tourism industry operates in an increasingly volatile environment, understanding how risk perception influences travel decision making has become a critical research priority. Various external shocks—such as the COVID-19 pandemic (Medová et al., 2021; Ushakov & Andreeva, 2021), political crises (Angelou et al., 2022), terrorism threats (Theocharous, 2010; Sönmez & Graefe, 1998), and economic downturns (Chew & Jahari, 2014)—have demonstrated the extent to which crisis events disrupt tourism demand and reshape travelers’ attitudes toward certain destinations (Badoc-Gonzales et al., 2022; Braje et al., 2022).

Previous studies have explored perceived risks associated with political instability (Rittichainuwat & Chakraborty, 2009; Richter, 1992), economic crises (Floyd et al., 2004), and natural disasters (Faulkner & Vikulov, 2001). However, there is limited empirical research on the intersection of political instability, social conditions, and tourism resilience. Additionally, most studies have analyzed macroeconomic trends rather than individual traveler perceptions and behavioral adaptations (Alvarez & Korzay, 2008; Shoemaker, 1994). Research also suggests that psychological factors, such as media influence and past travel experiences, significantly shape perceived risk in tourism (Cherian & Natarajamurthy, 2024; Kapuscinski & Richards, 2016; Pritchard & Morgan, 2001; Yang et al., 2016).

This study seeks to address this gap by examining how political instability and social conditions influence tourists’ risk perceptions and destination choices. It employs the social amplification of risk framework (SARF) (Kasperson et al., 1988) to explore how perceived risk is shaped by governance responses, media portrayals, and destination attributes. Given that the media plays a pivotal role in amplifying or mitigating risk perceptions (Kapuscinski & Richards, 2016; Beirman, 2003; Avraham & Ketter, 2008, 2016; Angelou et al., 2024; Angelou & Veglis, 2024), this research explores how travelers perceive risk-related information and examines, through a national-level survey, the implications for destination resilience strategies.

To address the research objective, the study poses the following questions:

• To what extent do political instability and social conditions influence travelers’ destination choices?
• How do risk perceptions vary across different traveler demographics (e.g., age, gender, travel experience) when evaluating politically and socially unstable destinations?
• What role does media coverage play in shaping tourists’ risk perceptions and influencing destination selection?
• How can destination managers, tourism policymakers, and hospitality businesses mitigate negative risk perceptions and enhance tourism resilience in politically and socially unstable regions?

All four research questions are derived from a single overarching research objective, namely to examine how political instability and social conditions influence risk perception and destination choice among travelers. Each question explores a different dimension of this objective, including demographic patterns, media influence, and strategic responses.

This study employs a quantitative survey approach, analyzing data from 280 respondents, to assess the key determinants of risk perception in destination decision making. The findings offer practical implications for destination managers, tourism marketers, and hospitality businesses, highlighting effective strategies for mitigating perceived risks, enhancing destination branding, and improving crisis communication.

Specifically, the study provides strategic recommendations for tourism stakeholders to develop resilience-building initiatives in politically and socially unstable environments. By exploring how travelers perceive and respond to risks, the study contributes to the broader discourse on crisis management, destination marketing, and tourism recovery strategies. Furthermore, by aligning the findings with theoretical frameworks, such as SARF and tourism crisis management models (Ritchie et al., 2004; Faulkner & Vikulov, 2001), the research offers insights into how destinations can proactively manage risk and maintain long-term competitiveness despite external uncertainties.

2. Theoretical Framework

2.1. Tourism and Perceived Risk

Pearce (1995) defines tourism as a phenomenon primarily involving leisure travel, categorizing tourists into types, such as business, health, and educational travelers. Tourism encompasses a wide range of activities and services arising from the interactions between tourists, industries, local governments, and communities (Goeldner & Ritchie, 2011; Cooper et al., 2008). It is viewed as a service-based industry with intangible products, making it vulnerable to sociopolitical instability, natural disasters, and health crises—factors that can adversely affect the image of a destination and deter potential visitors (Sönmez et al., 1999).

Destination image and perceived risk are critical factors in travel decisions. With the rise of natural and political threats, destination safety has become a priority (Poon & Adams, 2000). Tourism-related risks are often seen as undesirable, including health threats, terrorism, and political instability, which necessitate strategic management to safeguard both tourists and staff. Factors influencing perceived risk include gender, age, travel experience, and various sociocultural elements. Recent studies have examined how perceived risks influence destination choice, particularly in politically unstable or post-pandemic contexts (Blešić et al., 2022; Bae & Chang, 2021; Teng et al., 2023). These works emphasize the role of risk communication, governance, and psychological factors in shaping tourist behavior. However, there remains a lack of country-specific analysis focusing on Greece, particularly in relation to social conditions, media influence, and political trust. Given Greece’s heavy reliance on tourism and its exposure to economic, political, and health-related disruptions, this gap highlights the need for localized, empirical research.

Tourists are typically classified as either “psychocentric”, preferring safe, familiar destinations and avoiding risk, or “allocentric”, seeking unusual places and cultural engagement. In reality, these categories blend, making clear distinctions challenging. Additionally, tourists are significantly influenced by the media, especially regarding terrorism, as information shapes their perception of risk regardless of the event’s factual basis (Kapuscinski & Richards, 2016). Despite the recognized importance of destination image, limited studies explore the effects of perceived risk on its formation (Becken et al., 2017).

Destination safety is a significant factor since perceived risk directly impacts tourists’ choice of destination (Sönmez & Graefe, 1998). More recent studies confirm that safety remains a central concern for tourists, especially in the wake of global crises, such as the COVID-19 pandemic and the ongoing geopolitical instability. Recent findings suggest that safety perceptions now encompass not only crime or terrorism risks but also health infrastructure, emergency preparedness, and public trust in governance (Blešić et al., 2022; Bae & Chang, 2021; Teng et al., 2023). Travelers increasingly seek destinations that demonstrate both effective crisis management and transparent communication, reinforcing the need for resilience-oriented tourism strategies.

Risk is defined as potential loss, manifesting in various forms, such as physical, psychological, economic, or health-related risks, stemming from events, like natural disasters, terrorism, and political instability (Rittichainuwat & Chakraborty, 2009; Richter, 1992). Actual risk perception may vary due to media influence, which amplifies or dampens fears according to the social amplification of risk framework (SARF). SARF explains how perceptions of risk are socially constructed and intensified (Kasperson et al., 1988). It is important to distinguish between perceived risk and actual risk. Actual risk refers to the measurable probability or severity of a harmful event, based on objective data and expert assessments. In contrast, perceived risk is a subjective evaluation influenced by psychological, social, cultural, and informational factors. In tourism, travelers often respond more strongly to perceived risk, which may not align with real or statistically calculated threats (Blešić et al., 2022; Teng et al., 2023).

2.2. The SARF Model

News coverage of risks is considered essential for shaping the public’s perception of risk, especially among people connected to specific tourist destinations. While this is vital for the global tourism industry, the relationship between risk portrayal and public perception is rarely studied in depth. Research by Kapuscinski and Richards (2016) found that the media can either intensify or mitigate risk perceptions by using framing that enhances or diminishes the perceived danger, with tourists’ psychographic characteristics affecting how they interpret this information.

The media serve as crucial tools in crisis management for tourism, as suggested by Mansfeld (2006) and Ritchie et al. (2004), who emphasize the importance of maintaining a proactive relationship with media outlets to reduce negative perceptions. Similarly, Avraham and Ketter (2008, 2016) and Beirman (2003) highlight the use of strategic communication to influence public perception through tourism stakeholders.

The SARF model (social amplification of risk framework), introduced by Kasperson et al. (1988), describes how risk-related events interact with social and psychological processes, either increasing or decreasing risk perceptions and leading to broader social and economic impacts. These impacts may require further action or, when risks are downplayed, potentially hinder necessary protective measures.

SARF is a theoretical tool examining how risks are perceived and amplified or attenuated through communication. Messages convey data, values, and symbolic elements that shape public attention. Research suggests that symbols and information from credible sources, such as a renowned scientist or an award-winning organization, receive greater acceptance (Sundar & Nass, 2001).

Among the available risk theories, SARF is particularly well suited for this research because it explicitly focuses on how communication channels—such as media outlets, institutions, and social interactions—shape public risk perception. Since this study investigates how travelers interpret risks related to political and social instability, as well as how these interpretations are influenced by media and governance responses, SARF offers a comprehensive framework that links risk perception with behavioral outcomes in a tourism context.

Additionally, the repetition of data across various sources strengthens public trust. The concept of social amplification of risk demonstrates how institutional structures, group behaviors, and individual reactions contribute to society’s collective experience of risk (Kasperson et al., 1988). For instance, certain events, such as social unrest or terrorism, interact with social processes, influencing people’s responses and the way they experience these events (Shahrabani et al., 2019; Shakeela & Becken, 2015).

2.3. Determinants of Tourism Demand

The World Economic Forum’s “Travel and Tourism Competitiveness Report” serves as a strategic tool for strengthening the tourism sector, providing data and forecasts on tourism development, policies, risks, and an assessment system with 4 main categories and 90 sub-indicators (World Economic Forum, 2019). According to Lagos (2018), factors determining tourism demand include economic, social, psychological, sociological, political, external, cultural, institutional, demographic, and technological aspects.

Social factors encompass lifestyle changes, such as smaller family sizes, higher education levels, the employment of both spouses, urban living, and increased travel experience, all of which contribute to stronger tourism demand (Lagos, 2018). In this context, destination loyalty is shaped by a combination of visitor satisfaction, trust, and overall perception of the destination, as these elements influence the likelihood of repeat visits and positive recommendations (Kourkouridis et al., 2024). Moreover, sociological factors are closely linked to social pressures and norms that promote tourism as an expression of modern values. In addition, evolving travel trends, such as the pursuit of new experiences, changing fashion influences, and the growing popularity of sports activities, further contribute to shaping travel behavior (Lagos, 2018).

Political factors include military conflicts, political relationships, political instability, and economic development. External factors, such as terrorism and health issues, significantly impact tourism, while other factors, like distance, cost, and crime, reduce demand for destinations perceived as unsafe or difficult to access (Lagos, 2018).

2.4. Tourism and Social Factors

Social factors, such as culture, family, and social class, significantly shape individual behavior as they influence how each person interacts within society (Beldona et al., 2009; Fitzsimons & Morwitz, 1996). Culture encompasses traditions, taboos, values, and the core attitudes of a society (University of Minnesota, 2016). It forms a framework within which people develop and lead their lives, with cultural norms acting as behavioral guidelines.

In the context of tourism development, social factors in a broad sense bring substantial benefits, including the creation of demands in the tourism market, the exchange of cultural elements, and the promotion of international relationships. Tourism, as one of the world’s largest service industries, contributes significantly by generating employment, strengthening ties with other sectors, fostering progress in various fields, and improving the socioeconomic status and quality of life within local communities (Ngoc & Trinh, 2015).

Tourism development also aids in reducing social issues by creating job opportunities, fostering mutual understanding and respect among different cultures, and enhancing the quality of life for both residents and visitors (Tuan & Rajagopal, 2019). Recent studies emphasize the role of social equity, accessibility, and inclusion in shaping travel experiences and perceptions of hospitality (Guo & Liu, 2024; Zhu et al., 2017). In particular, the perceived fairness of public services, quality of urban infrastructure, and attitudes of local communities toward tourism are increasingly seen as key contributors to destination image and loyalty.

Given the interconnectedness between social and political factors (Kim, 2005), it is essential for countries to carefully develop policies that effectively and sustainably harness tourism’s potential. Recognizing that society and politics are inseparable and considering that political factors will be explored in the next section, this study now examines how political influences may impact visitor inflow to a destination.

2.5. Tourism and Political Factors

Political risks, such as terrorism, are often considered more dangerous than natural disasters due to their emotional impact. Theocharous (2010) defines perceived political risk as a condition influenced by internal or external changes, like terrorism, which conveys messages through violence and impacts the sense of security in a destination. Although terrorism does not always deter tourists (Rittichainuwat & Chakraborty, 2009), demand often decreases significantly in cases of such risks (Floyd et al., 2004). Media coverage amplifies fear and influences travel decisions, frequently leading to cancellations (Sönmez et al., 1999).

While safety is essential for tourists, repeat visitors often disregard certain risks, influenced by their personal connection to a destination (Shoemaker, 1994). For example, tourists continued to visit areas affected by a tsunami, as their familiarity with the location lessened the perceived risk (Sönmez & Graefe, 1998). Research by Alvarez and Korzay (2008) found that, despite negative media portrayals of Turkey, Spanish tourists continue to choose it as a destination, highlighting the distinction between a country’s general image and its image as a tourist destination.

Research confirms that political instability continues to have a significant negative impact on tourism development and destination image. Tomczewska-Popowycz and Quirini-Popławski (2021) demonstrate how instability in Ukraine led to a sharp decline in international arrivals and tourism revenue. Meanwhile, Farhangi and Alipour (2021) highlight the role of digital communication and social media in managing the image of destinations affected by political tension, offering tools to help rebuild trust among potential travelers. These studies emphasize the importance of managing both perception and communication in politically sensitive contexts.

2.6. Hypotheses Discussion

2.6.1. Economic Crises, Political Instability, and Terrorism

The hypothesis that an increased perceived importance of economic crises, political instability, and terrorism reduces the likelihood of choosing destinations affected by these issues is based on findings linking political and economic risks to tourism demand. Chew and Jahari (2014) emphasize that perceived risks can shape a destination’s image, influencing the attitudes of repeat tourists toward locations deemed dangerous. When sociopsychological and economic risks coexist, travelers tend to reconsider their intention to visit destinations impacted by such crises, particularly after disasters or significant negative events, like the 2004 tsunami and the 2010 Arab Spring. This analysis is supported by studies by Floyd et al. (2004) and Sönmez et al. (1999), who argue that frequent media reports on terrorist attacks or political unrest intensify risk perception, increasing travelers’ fear and anxiety (Angelou et al., 2022), which in turn leads to booking cancellations and changes in travel plans.

2.6.2. Recreation, Safety, Municipal Facilities, and Services

The remaining hypotheses suggest that residents who are satisfied with the services and facilities in their chosen area place a higher value on these attributes when choosing a tourist destination. Ramkissoon and Nunkoo (2011) point out that social characteristics and destination infrastructure play a crucial role in the level of local community support for tourism development. Quality municipal services, a sense of security, and recreational opportunities enhance a city’s image, making it more attractive to both visitors and residents. Research indicates that residents satisfied with the services they receive in their home area are more likely to seek similar quality in tourist destinations, thus reinforcing their interest in destinations that promote wellbeing and safety. Such preferences reflect the broader role of infrastructure and service quality in shaping perceptions of destination appeal, particularly among individuals who associate safety and comfort with reliable public amenities and recreational opportunities.

2.6.3. Gender and Perception of Tourism Risks

The hypothesis that gender plays a role in the perception of tourism risks is based on the tendency of women to perceive greater risks in issues of personal safety, as highlighted in studies by Pritchard and Morgan (2001) and Yang et al. (2016). Female tourists appear to be more sensitive to risks related to violence or physical security, especially in locations with a history of sexual assaults or in societies where women may be viewed as more vulnerable. Conversely, male tourists are generally more likely to take risks, particularly in adventure tourism, where risk perception is tied to a social culture of risk-taking. Chiu and Lin (2011) also note that risk perception is influenced by such factors as travel experience, cultural background, and the type of trip. Therefore, female tourists who feel more vulnerable to certain risks may avoid destinations deemed unsafe, while males may assess the same destinations with different criteria, being less influenced by such factors. Gender-based differences in risk tolerance thus emerge as important variables in travel behavior, shaped by social norms, personal safety concerns, and varying responses to perceived threats.

3. Materials and Methods

The study was conducted in Greece, a country heavily dependent on tourism and simultaneously affected by significant economic and social challenges in recent years. Data were collected in July 2022 through a structured questionnaire distributed online to individuals residing in Greece. The sample included men and women aged 18 and over, regardless of educational level, marital status, or employment status. A total of 280 valid responses were collected using a non-probability convenience sampling method, whereby participants were recruited based on their accessibility and willingness to respond to the online questionnaire.

The aim of this study is to explore how political instability and social conditions influence perceived risk and destination choice among potential travelers.

To achieve this, the study sets out the following research objectives:

• To measure the influence of social factors on visitors’ travel intentions and risk perception;
• To assess the impact of political instability on visitors’ travel intentions and risk perception;
• To determine the role of gender and other demographic characteristics in shaping travel intentions related to these factors.
• To explore how media coverage influences risk perception and destination choice.

The hypotheses tested in this study were derived directly from the research questions introduced in the Introduction. Each hypothesis corresponds to one of the study’s stated objectives and was formulated to allow for empirical testing of the conceptual framework. This structure ensures alignment between the study’s purpose, theoretical assumptions, and analytical design.

The primary research question examined in this study is whether political instability and social conditions at a destination affect the travel preferences of potential visitors. Specifically, the research aims to assess the extent to which social and political factors influence risk perception and travelers’ destination choices.

The research methodology employed in this study follows a quantitative approach. The quantitative method was selected as the most appropriate, as it provides numerical data and aims to depict causal relationships between such variables as perceived risk, political instability, social conditions, and destination choice. The method is based on a structured questionnaire consisting of 27 closed-ended questions, organized into 5 main sections. The data collection process was carried out via the following steps:

• The research questions were formulated to align with the research aim;
• The study sample was defined based on the number of participants;
• The research tool (questionnaire) was structured to assess demographic factors, travel behavior, political factors, social conditions, and risk perception;
• The questionnaire was distributed electronically to the participants;
• Responses were entered into SPSS for statistical analysis;
• The necessary statistical analyses were conducted, and the resulting data were interpreted.

Before the main data collection, a pilot survey was conducted with 15 participants to test the clarity, structure, and relevance of the questionnaire items. Based on their feedback, minor modifications were made to improve wording and ensure alignment with the study objectives. To ensure the reliability of the questionnaire, Cronbach’s alpha test was conducted. The internal consistency scores for the individual sections and the overall questionnaire were high (α > 0.7). Specifically, the internal consistency scores were as follows: (a) for the “Political factors” variable, the score was 0.814, (b) for “Social factors related to place of residence”, the score was 0.838, (c) for “Social factors related to destination choice”, the score was 0.904, and (d) for the entire questionnaire, the score was 0.890.

4. Results

This section presents the analysis of the survey results, which were derived from questionnaire responses and analyzed using SPSS software V.26.0. First, the demographic profile of the respondents and their tourism habits are outlined. Subsequently, the responses related to political and social factors are examined in detail. Finally, the research hypotheses are tested and analyzed.

4.1. Descriptive Statistics

4.1.1. Demographic Data

The study included a sample of 280 participants, comprising 50.7% women and 49.3% men. In terms of age distribution, 6.4% were in the “18–25 years” group, 27.1% were in the “26–35 years” group, 43.2% were in the “36–45 years” group, 18.2% were in the “46–60 years” group, and 5.0% were in the “61 and over” group, as shown in

Table 1. Demographic characteristics of participants.

Variables		Frequency	Percentage
Gender	Male	138	49.3%
	Female	142	50.7%
Age	18–25	18	6.4%
	26–35	76	27.1%
	36–45	121	43.2%
	46–60	51	18.2%
	61 and over	14	5.0%
Marital status	Single	103	36.8%
	Married	156	55.7%
	Divorced/Widowed	21	7.5%
Educational level	Primary Education	4	1.4%
	Secondary Education	29	10.4%
	Higher Education	123	43.9%
	Postgraduate Education (MSc, Ph.D.)	124	44.3%
Employment Status	Student	12	4.3%
	Public Sector Employees	22	7.9%
	Private Sector Employees	210	75.0%
	Self-Employed/Business Owners	17	6.1%
	Unemployed	8	2.9%
	Homemakers	3	1.1%
	Retired	8	2.9%

.

Regarding marital status, 36.8% of respondents were “Single”, 55.7% were “Married”, and 7.5% were “Divorced/Widowed”. In terms of education level, 1.4% had completed only “Primary Education”, 10.4% had completed “Secondary Education”, 43.9% held a “Higher Education” degree, and 44.3% had attained “Postgraduate Education (MSc, Ph.D.)”.

Finally, employment status showed a diverse distribution, as 4.3% were “Students”, 7.9% were “Public Sector Employees”, 75.0% were “Private Sector Employees”, 6.1% were “Self-Employed/Business Owners”, 2.9% were “Unemployed”, 1.1% were “Homemakers”, and the remaining 2.9% were “Retired”.

4.1.2. Tourist Habits

Regarding tourist habits, as shown in

Table 2. Tourist habits of participants.

Variables		Frequency	Percentage
How many trips abroad have you made in the last 5 years?	None	58	20.7%
	1–2	103	36.8%
	3–5	71	25.4%
	6+	48	17.1%
Who do you usually travel with?	Alone	26	9.3%
	With partner/spouse	103	36.8%
	With friends	70	25.0%
	With family	77	27.5%
	In organized tours (group)	4	1.4%
What type of accommodation do you usually stay in?	Hotel	203	72.5%
	Rented accommodation (Airbnb)	45	16.1%
	Shared rooms (hostel)	9	3.2%
	With relatives or friends	23	8.2%

, for the question “How many trips abroad have you taken in the last five years?”, 20.7% of respondents answered “None”, 36.8% answered “1–2”, 25.4% answered “3–5”, and 17.1% answered “6 or more”. Additionally, for the question “Who do you usually travel with?”, 9.3% of respondents answered “Alone”, 36.8% answered “With a partner/spouse”, 25.0% answered “With friends”, 27.5% answered “With family”, and only 1.4% answered “In organized tours (groups)”. Furthermore, in response to “What type of accommodation do you typically stay in?” the majority, 72.5%, answered “Hotel”, while 16.1% answered “Rented accommodation (Airbnb)”, 3.2% answered “Shared rooms (hostel)”, and 8.2% answered “With relatives or friends”.

Additionally, regarding the question “What is the main reason you usually travel?”, Figure 1 shows that 36.5% of respondents indicated “Leisure”, 35.8% stated “Entertainment”, 20.3% cited “Business obligations”, 3.8% cited “Family obligations”, 2.6% said that they traveled for “Sports/Music events”, and 1.0% (five respondents) cited “Ecotourism”. Lastly, concerning the question “What is the most important criterion for choosing a tourist destination?” (Figure 2), 132 respondents (26.56%) stated “Seeking new experiences”, 128 (25.75%) mentioned “Safe destination”, 88 (17.71%) chose “Low cost”, 76 (15.29%) based their choice on “Good reviews”, and 73 (14.69%) cited “Ease of access”.

4.1.3. Political and Social Factors

Regarding political influencing factors, as shown in

Table 3. Means and standard deviations for questions in the “Political Factors” section.

Political Factors	Mean	Std. Dev.
	3.61	0.78
Avoiding travel to countries with unstable economic conditions	3.03	1.09
Avoiding travel to destinations with potential health risks	4.32	0.90
Avoiding travel to destinations with political instability	3.80	1.10
Avoiding travel to destinations that experienced a terrorist attack in the current year	3.83	1.14
Avoiding travel to destinations with potential risks of earthquakes or other natural disasters	3.09	1.21
Given the opportunity to travel abroad	3.58	0.91
Avoiding destinations with travel advisories for safety concerns	3.96	1.14
Avoiding destinations with travel advisories for health risks (e.g., flu)	4.10	1.03
Avoiding destinations with travel advisories for potential natural disasters	3.68	1.20
Avoiding destinations that recently experienced a terrorist attack	3.60	1.24
Avoiding destinations with unstable economic conditions	2.85	1.16
Avoiding destinations with political instability	3.31	1.17
Intent to travel to specific destinations
Israel	2.71	1.33
Turkey	2.78	1.27
Mexico	3.20	1.38
Egypt	3.26	1.24
Russia	2.79	1.45
If you are unwilling to travel to a destination, please assess the importance of the following conditions	3.69	0.78
High likelihood of a terrorist attack	3.95	1.18
Health risks	4.12	1.04
High crime rate	4.08	0.98
Destination is quite expensive	3.55	1.09
Risk of earthquakes or other natural disasters	3.21	1.18
High likelihood of social unrest	3.57	1.07
Political instability	3.34	1.10
Overall	3.69	0.78

, which presents the means and standard deviations, participants “Agree” that they would avoid destinations with “unstable economic conditions, potential health risks, political instability, previous occurrences of terrorist attacks, and potential risk of earthquakes or other natural disasters” (mean = 3.61, SD = 0.78), (mean = 3.58, SD = 0.91). Additionally, in the section “Assess the significance of the following conditions for your trip to a destination”, participants rated the following as “Important”: “High likelihood of a terrorist attack” (mean = 3.95, SD = 1.18), “Health risks” (mean = 4.12, SD = 1.04), “High crime rate” (mean = 4.08, SD = 0.98), “Destination is quite expensive” (mean = 3.55, SD = 1.09), and “High likelihood of social unrest” (mean = 3.57, SD = 1.07). They rated as “Moderately Important” the “Risk of earthquakes or other natural disasters” (mean = 3.21, SD = 1.18) and “Political instability” (mean = 3.34, SD = 1.10). Lastly, regarding the “Participants’ intention to travel to certain destinations”, they expressed “Interest” in all listed destinations, including “Israel, Turkey, Mexico, Egypt, and Russia”.

In

Table 4. Mean scores and standard deviations for the sections “Social Factors Regarding Your Place of Residence” and “Social Factors Regarding the Choice of Tourist Destination”.

Please Evaluate the Following Factors Regarding Your Place of Residence	Mean	Std. Dev.
Quality of facilities	3.48	0.70
Adequate night lighting	3.75	0.93
Availability of public transportation	3.33	1.26
Good road network and sidewalks	3.29	1.17
Easy access to local services (e.g., police)	3.51	1.06
Green spaces	3.24	1.08
Cleanliness	3.69	1.03
Low air pollution	3.57	1.12
Entertainment	3.43	0.82
Tourist facilities (e.g., accommodations, restaurants)	3.62	1.08
Proximity to major cities	4.05	0.95
Nightlife	3.14	1.20
Children’s activity centers	2.91	1.33
Safety	3.96	0.80
Quietness	3.79	1.04
Security	4.22	0.88
Low crime rate	4.12	0.91
Reduced overcrowding	3.71	1.10
Provided Services	3.49	0.87
Sufficient bank branches—ATMs	3.52	1.14
Numerous retail shops	3.19	1.12
Adequate healthcare facilities	3.32	1.25
Supermarkets in convenient locations	3.91	0.99
Social Factors Regarding the Choice of Tourist Destination
Quality of facilities	3.79	0.68
Adequate night lighting	3.66	1.00
Availability of public transportation	4.03	0.95
Good road network and sidewalks	3.71	0.99
Easy access to local services (e.g., police)	3.61	1.03
Green spaces	3.74	0.95
Cleanliness	4.27	0.82
Low air pollution	3.52	0.99
Entertainment	3.29	0.76
Tourist facilities (e.g., accommodations, restaurants)	4.34	0.84
Proximity to major cities	3.68	1.04
Nightlife	2.91	1.10
Children’s activity centers	2.24	1.30
Safety	3.90	0.74
Quietness	3.49	1.08
Security	4.44	0.77
Low crime rate	4.29	0.89
Reduced overcrowding	3.36	1.07
Provided Services	3.49	0.83
Sufficient bank branches—ATMs	3.46	1.07
Numerous retail shops	3.29	1.00
Adequate healthcare facilities	3.81	0.99
Supermarkets in convenient locations	3.41	1.07
Tourism and Recreation	3.67	0.65
Historical monuments	4.03	0.92
Cultural heritage	4.06	0.94
Variety of restaurants and leisure centers	3.87	0.90
Sports (sports events)	2.68	1.14
Cultural activities (theaters, museums)	3.73	1.02

, the responses of participants in the sections “Social Factors Regarding Your Place of Residence” and “Social Factors Regarding the Choice of Tourist Destination” are presented.

In the section “Social Factors Regarding Your Place of Residence”, under the sub-category “Quality of Facilities”, participants on average responded with “Interested” (mean = 3.48, SD = 0.70). For the sub-category “Entertainment”, the average response was also “Interested” (mean = 3.43, SD = 0.82). In “Safety”, participants indicated “Very Interested” (mean = 3.96, SD = 0.80), and under “Provided Services”, the average response was “Interested” (mean = 3.49, SD = 0.87).

Simultaneously, in the section “Social Factors Regarding the Choice of Tourist Destination”, participants indicated “Very Interested” in the sub-category “Quality of Facilities” (mean = 3.79, SD = 0.68), “Interested” in “Entertainment” (mean = 3.29, SD = 0.76), and “Very Interested” in “Safety” (mean = 3.90, SD = 0.74). Additionally, they responded with “Interested” in “Provided Services” (mean = 3.49, SD = 0.83), and “Very Interested” in “Tourism and Leisure” (mean = 3.67, SD = 0.65).

Based on the results in

Table 5. Aggregate mean scores and standard deviations for sections.

Aggregate Mean Scores and Standard Deviations	Mean	Std. Dev.
Political Factors	3.63	0.74
Social Factors Related to Place of Residence	3.57	0.55
Social Factors Related to Choice of Tourist Destination	3.65	0.56

, it is observed that, on average, participants “Agree” that “Political factors influence the choice of travel destination” (mean = 3.63, SD = 0.74). Additionally, they consider “Social factors related to the place of residence” as “Important” (mean = 3.57, SD = 0.55), as well as “Social factors related to the choice of tourist destination” (mean = 3.65, SD = 0.56).

4.2. Inferential Statistics

In this section, inferential statistical techniques are used to examine the correlations between key variables in our study. Initially, the ANOVA test reveals a significant correlation between the variables “Social Factors in the Place of Residence” and “Social Factors in the Choice of Tourist Destination” (Sig. = 0.000 < 0.05). The Pearson r test indicates a strong positive correlation (Sig. < 0.01, Pearson r = 0.57), meaning that the better the “social factors in the place of residence”, the higher the expectations for “social factors” in the choice of destination.

Subsequently, the ANOVA test confirms a correlation between the variables “Quality of Facilities in the Place of Residence” and “Quality of Facilities at the Travel Destination” (Sig. = 0.000 < 0.05), with Pearson r showing a strong and positive relationship (Pearson r = 0.42), indicating that the higher the quality of facilities in the place of residence, the greater the demands for quality in the destination.

Similarly, a significant correlation is found between “Entertainment in the Place of Residence” and “Entertainment at the Travel Destination” (Sig. = 0.000 < 0.05), with Pearson r indicating a strong positive relationship (Pearson r = 0.34). This implies that the quality of entertainment in the place of residence positively influences expectations for entertainment at the destination.

Likewise, the ANOVA test shows a significant correlation between the variables “Safety in the Place of Residence” and “Safety at the Travel Destination” (Sig. = 0.000 < 0.05), with Pearson r confirming a strong positive correlation (Pearson r = 0.52).

Furthermore, a significant correlation is found between “Services Provided in the Place of Residence” and “Services Provided at the Travel Destination” (Sig. = 0.000 < 0.05, Pearson r = 0.42). This suggests that the better the services at the place of residence, the higher the demand for similar services at the destination.

The analysis reveals a significant positive correlation between the “Perceived Importance of Economic Crises” and the “Intention to Choose a Destination Affected by Economic Crisis” (Sig. = 0.001 < 0.05, Pearson r = 0.70). Similar strong correlations are observed between “Perceived Importance of Political Instability” and “Intention to Choose a Destination with Political Instability” (Sig. = 0.000 < 0.05, Pearson r = 0.66), as well as between “Perceived Importance of Terrorist Attacks” and “Intention to Choose a Destination at Risk of Terrorism” (Sig. = 0.000 < 0.05, Pearson r = 0.75).

Additionally, using the above tests, strong correlations are found between “Political Factors” and “Social Factors in the Place of Residence” (Sig. = 0.000 < 0.01, Pearson r = 0.39), as well as “Political Factors” and “Social Factors in the Choice of Tourist Destination” (Sig. = 0.000 < 0.01, Pearson r = 0.44). Moreover, “Social Factors in the Place of Residence” appear to influence destination choice based on “social factors” (Sig. = 0.000 < 0.01, Pearson r = 0.57).

Finally, using the t-test, it is determined that there is a correlation between the variable “Gender” and “Choice of Travel Destination Based on Risks” (Sig. = 0.004 < 0.05), with women being more affected by risks in the travel destination compared to men.

5. Discussion

Prior research has examined the influence of social and political factors on travel behavior, particularly in relation to destination selection and risk perception. The results of this study confirm that positive social factors significantly enhance a destination’s attractiveness, reinforcing the idea that social stability, public services, and local attitudes toward tourism are crucial in shaping tourist preferences (Beldona et al., 2009; Fitzsimons & Morwitz, 1996; Kim, 2005). However, this research adds new insights by specifically showing how political stability fosters a more favorable social environment, which enhances tourism demand. These findings support previous research demonstrating the complex relationship between political governance, public satisfaction, and tourism resilience (Goeldner & Ritchie, 2011; Cooper et al., 2008).

The role of safety and security in destination selection was further emphasized in the results. The study confirms that the risk of terrorist attacks and political unrest significantly decreases a country’s attractiveness as a travel destination, while a strong sense of safety increases the likelihood of a destination being chosen (Rittichainuwat & Chakraborty, 2009; Floyd et al., 2004; Sönmez & Graefe, 1998; Sönmez et al., 1999; Shahrabani et al., 2019; Rittichainuwat & Chakraborty, 2009). These findings align with previous research, which has shown that perceived political instability negatively impacts tourism demand and destination loyalty (Chew & Jahari, 2014). However, this study also adds to the literature by demonstrating that certain tourist segments remain less affected by safety concerns, as seen in previous studies, such as Shoemaker (1994) and Rittichainuwat and Chakraborty (2009).

Additionally, the study highlights that female tourists tend to be more risk-averse than male travelers when evaluating potential travel destinations. This finding aligns with previous research showing that women are generally more sensitive to risks related to personal safety, health hazards, and crime, incorporating these concerns into their travel decisions (Pritchard & Morgan, 2001; Gustafson, 2006). Chiu and Lin (2011) further suggest that destination choice is influenced not only by gender but also by group composition, cultural background, and past travel experiences, indicating that perceived risk is a multi-dimensional construction shaped by both personal and external factors.

This results also confirm the strong interconnections between political stability, social conditions, and tourism demand. Political factors directly influence the social environment of a destination, which in turn shapes visitor perceptions of safety, service quality, and overall experience. Tourists place high value on the quality of public services, recreational facilities, safety, and entertainment options when selecting a travel destination. Furthermore, travelers who express satisfaction with social services and infrastructure in their place of residence tend to apply similar expectations when choosing a destination, reinforcing the importance of social stability and service quality in tourism decision making (Lagos, 2018; Kourkouridis et al., 2024; Guo & Liu, 2024; Casado-Aranda et al., 2021).

The role of media outlets in shaping tourism risk perception is particularly evident in the results. Previous research suggests that media coverage plays a crucial role in amplifying or mitigating risk perception, thereby influencing destination choice (Avraham & Ketter, 2008; Beirman, 2003). This study primarily focused on traditional media channels, such as news outlets and mainstream publications, due to their long-standing influence on public opinion and their significant role in shaping perceptions during crises. However, it is important to recognize that social media, blogs, and other online platforms are increasingly shaping travel decisions and risk perceptions, particularly among younger and more tech-savvy travelers. Previous studies also emphasize the significant influence of digital platforms on tourism decision making (Angelou et al., 2022; Kapuscinski & Richards, 2016; Badoc-Gonzales et al., 2022; Braje et al., 2022). Even minor crises, such as political protests, may lead to substantial decreases in tourism demand if media narratives emphasize instability rather than recovery efforts. Future research could explore the intersection of traditional and digital media to provide a more comprehensive understanding of how different communication channels influence tourism behaviors.

Given the impact of perceived instability on travel behavior, destinations that experience political or social challenges should prioritize strategic reputation management and risk mitigation measures. Governments and tourism authorities can counter negative perceptions by investing in social development projects, strengthening security measures, and promoting cultural and natural attractions. A strong crisis communication strategy—including positive media engagement, transparency in governance, and safety assurances to visitors—is essential for rebuilding trust and restoring destination attractiveness (Avraham & Ketter, 2016; Shoemaker, 1994).

Finally, the findings confirm that the social amplification of risk framework (SARF) is a valuable model for understanding how political and social instability influence tourist psychology and decision making. The results support the notion that risk perception is often shaped by external narratives rather than objective analysis, leading travelers to develop biases based on media portrayals and public discourse (Kasperson et al., 1988). Similar results have been reported in previous studies that highlight how uncertainties and instability shape perceived risk and influence destination choice (Shahrabani et al., 2019; Shakeela & Becken, 2015).

Recent studies in the post-pandemic era have focused increasingly on travelers’ behavioral adaptation to risk (e.g., Teng et al., 2023; Blešić et al., 2022; Bae & Chang, 2021). While these works have addressed evolving patterns of risk perception in global contexts, few have explored the specific interplay between political instability, social conditions, and tourism behavior within the Greek context. This study adds to the literature by combining a country-specific analysis with a broader theoretical framework, providing insights into how local social infrastructure and gender-specific perceptions shape destination decisions in politically uncertain environments.

Overall, the results of this study largely confirm the hypotheses derived from the literature review, reinforcing the strong relationship between political stability, social conditions, and tourism resilience. Destinations with stable social and political environments are more likely to attract visitors, while those experiencing unrest or uncertainty face greater challenges in maintaining their tourism appeal. These findings underscore the need for destination managers, policymakers, and tourism stakeholders to adopt proactive strategies to mitigate perceived risk and enhance the overall travel experience.

6. Conclusions

Considering the results, destination managers, tourism policymakers, and hospitality businesses should prioritize investments in visible safety measures and public services, particularly in regions perceived as politically unstable. This is especially relevant for female travelers, who were found to be more risk-averse in relation to safety concerns. Additionally, engaging local communities in promoting positive images of the destination and emphasizing the strength of local social infrastructure can help improve the destination’s appeal. Moreover, it is essential to improve crisis communication strategies that highlight recovery efforts and ensure transparency in governance, as these elements can counteract negative media narratives and mitigate the impact of political instability on tourism resilience.

However, this study has certain limitations. The use of a non-probability convenience sampling method may introduce self-selection bias, as participants were recruited based on their availability and willingness to respond. Although this approach is common in exploratory tourism research, it may affect the representativeness of the sample. Furthermore, findings related to political instability (RQ2) and media influence (RQ4) should be interpreted as indicative, given the limitations of the sample and the structure of the questionnaire. Additionally, the sample size limited the ability to conduct meaningful segmentation across multiple demographic groups. While gender-based differences in risk perception were observable, further distinctions based on age or travel experience could not be robustly analyzed. It should also be noted that a subset of respondents (n = 58) had not traveled in the past five years. While they were included in general perception analyses, their responses may have introduced bias into the descriptive findings related to travel behavior.

While the findings offer practical implications for resilience strategies in tourism, they should be interpreted within the context of a national-level study, considering the sample size and geographic focus. In light of these findings, several practical recommendations can be proposed. Destination marketers should tailor communication strategies to highlight safety, service quality, and social stability—particularly when addressing female travelers and other risk-sensitive groups. Policymakers and tourism planners are encouraged to invest in public infrastructure, visible safety measures, and inclusive services that enhance both actual and perceived destination security. Furthermore, collaboration with media outlets is essential to ensure responsible reporting during periods of instability, as this can significantly influence traveler confidence and destination image.