The Degree of Environmental Risk and Attractiveness as a Criterion for Visiting a Tourist Destination

Abstract

In recent years, more and more attention has been paid to the behavior of tourists and their intention to choose a destination based on various factors. The goal of this research was to determine to what extent environmental risks and the attractiveness of the destination influence the choice of destination and the behavior of tourists. Furthermore, the goal was to determine the influence of psychological groups of tourists on their decision to choose a tourist destination using three psychographic techniques: BFI-10 (Big Five Inventories), AIO (Activities, Interests, and Opinions), and VALS 2 (Values and Lifestyle), and a freely determined six-level scale of risk and tourist attractiveness of imagined destinations. Analyzing the results obtained through the structural modeling-path analysis model, it was determined that tourists grouped in almost all psychographic orientations, resulting from lifestyles, negatively perceive destinations with a high degree of risk and attractiveness, while, with the VALS 2 technique, only members of the action orientation tend to accept ecologically risky destinations. Despite the fact that many studies have looked at how tourists perceive various risks and behave, it is still uncommon to use an integrated approach that considers the simultaneous application of several psychological tests and a unique method of gathering responses from travelers by presenting them with descriptively imagined destinations that differ in their levels of environmental risk and tourist appeal. As a result, this study can provide a conceptual framework for theoretical and practical implications for improved risk management strategies in a specific travel destination and in areas vulnerable to environmental hazards, as well as for completing knowledge about traveler behavior in risky destinations.

1. Introduction

Environmental dangers come in a variety of shapes and sizes, beginning with climatic disturbances like pollution, radiation, noise, land use patterns, or climate change [1]. The EU 7th Environment Action Program included an integrated approach to risk management, recording them all in scientific and technical data for the purpose of planning strategic activities to prevent or reduce the strongest forms of these risks [2]. The European Commission is constantly working to identify new forms of environmental and social risk. The destruction of cities, alteration in the climate, and destruction of everything that man has created are just a few of the negative effects that some environmental risks have on the planet. However, they also have a significant impact on people’s awareness of their future behavior, both in daily life and in making decisions. Determining the actual impact of risk on the behavior of tourists and on their intention to choose a destination and travel is an increasing topic of research around the world. The perception of the safety of the visitors to the destination has an increasingly intense influence on their behavior. The same is indicated by the negative trends of visits to tourist destinations where terrorist attacks and crime have occurred, natural disasters have been caused by climate change, those where the consequences of the migrant crisis are obvious, destinations that record an increase in local crime, etc. Safety during the stay at the destination is in the subconscious of tourists, especially if one looks at the recent negative consequences that the pandemic has left on tourists and destination attendance. Environmental risks have a large share in the formation of tourists’ behavior models, and regardless of whether the risk was constant at the time of the trip, it is virtually embedded in human consciousness [3] because the perception of risk is such an image among tourists that they create the probability that something negative will also happen, caused, if nothing else, at least by environmental consequences during the trip [4]. Also, apart from environmental risks, it was determined that international attitude, risk of terrorism, level of risk perception, and income directly affect the choice of destination for an international vacation [5]. The perception of the impact of environmental risks on tourists’ decisions is very often established on the basis of various factors, such as lifestyle, personality traits, demographic factors, experience, etc.

Precisely, the goal of this research was to determine how personality traits, lifestyles, and psychographic orientations of tourists can be a defense or a response to environmental risks in their future behavior and in the survival of destinations that may suffer some of the potential consequences of natural or social disasters. The results that we reached undoubtedly show that the majority of tourists, of almost all psychographic orientations, do not accept challenges such as traveling to high-risk destinations. Also, it is only shown that the members of the action-oriented psychological group are ready for this kind of challenge.

This study has broad theoretical and practical implications, chiefly serving as a foundation for new information and research on the subject of how environmental dangers affect travelers’ choices and intentions. However, the importance of the application is primarily seen in how the results are used to update the documentation that is already in place. This is dependent on strategic actions that have an impact on how the destination’s and the company’s management of tourism development is handled during or after catastrophes. Additionally, by comprehending how people behave in unsafe circumstances, it is feasible to affect tourists’ knowledge of these conditions and their choices regarding where to travel. It has been demonstrated that studying how lifestyles and personality factors affect consumption habits and how different types of marketing communication are processed in the field of marketing communication has been successful. The approach to conducting the respondents’ interviews is another novel aspect of the work. In order to convey to respondents the level of risk and allure without bringing to mind well-known locations after reading the description, hypothetical locations with fictitious names were offered.

2. Literature Review

2.1. Perception of Risks as (Co)creators of Tourist Movements

The psychological state of travelers and tourists when they are on vacation is frequently examined using risk perception techniques [6]. The term “tourist risk perception” was established by proponents of cognitive psychology [7,8] and describes how conditions and situations are observed from the perspective of the negative effects of environmental dangers while also influencing the choices and expectations of visitors [9]. Even though there may be a real risk, Cater [10] argues that the subjective impression of risk is considerably more prominent, and tourist behavior is also influenced by the level of risk [11,12,13]. The way that tourists perceive risk affects their behavior significantly, and the way that information about risk is conveyed is frequently subjective to the point where the risk becomes a catastrophe [14], which has a further negative impact on the decision to forego taking the trip altogether [15,16,17]. However, other authors point out that risk perception is still a quantitative estimate of safety, even when tourists are very sensitive to particular dangers while traveling and while visiting a site [17]. Furthermore, the same authors claim that tourists should have prior knowledge about a destination and the possible types of risks associated with it. Sharifpour et al. [18] came to similar conclusions, contending that various dimensions and levels of information influence judgments regarding the kind and degree of danger associated with travel or the place itself. Travelers are known to constantly see bad scenarios that have been staged by the media or other travelers’ comparable experiences, and, based on this preconceived notion, they form an impression of the security situation [19,20,21,22,23]. The best examples of decisive factors are unplanned occurrences and natural disasters since they have a deep impact on people and society and can, therefore, have a negative impact on tourism flows [24,25,26,27]. Individual risks, including earthquakes, powerful storms, floods, and droughts, as well as biophysical and technological processes, have different effects on tourists’ awareness but can also provide certain difficulties [28]. The results of a study conducted in Taiwan in 1999, where tourism did not recover even a year after the earthquake [29], further support Mazzochi’s [30] assertion that there was a significant decline in tourist traffic after the huge earthquake that struck Italy in September 1997.

Sonmez et al. [31] point out that environmental risks do not allow for a quick recovery of the destination, while, on the other hand, tourists’ awareness of the negative effects and fears also slow down the recovery of tourism, and the negative impact of environmental disasters creates indirect consequences for travel in other nearby destinations [32]. After 30 years of research, Neumayer and Barthel [33] showed that the effects of climate disasters on tourism growth trends are long-lasting, that the tourism trend slowed down long after the risk, and that a stronger growth trend of disaster aversion can be seen. Environmental risks’ consequences have dramatically worsened in recent years, in part because of the intensifying effects of climate change but also because socio-ecological systems are becoming more complex in a highly interconnected and globalized world [34,35]. Numerous authors [36,37,38,39,40,41,42,43] discussed terrorist risks and their impact on destination adoption and choice, as well as risks from hazards. Using data from his research in Nepal, Ghmire [44] asserts that no place is safe from crises like earthquakes, wars, floods, and other natural and societal disasters, and that the reason for visitor anxiety in some places is that they cannot be swiftly evacuated.

2.2. Risk Perception Factors Determined through Various Psychographic Techniques

Ankomah et al. [45] point out that, under normal circumstances, the relationship between tourist attributes and destination characteristics determines the choice of destination, but, in situations where there is a certain amount of danger, travelers make their decisions based on their individual views [46]. According to certain studies, the impression of the riskiness of a trip shifts over time depending on the home country [47], the position of the destination within a larger geographic area [16,48], or the distinction between domestic and foreign destinations [20]. Numerous writers have studied how visitors from other cultures perceive cultural dangers, and it has been found that these perceptions of risk, travel safety, anxiety, and travel goals range significantly. Tourists from the United States, Hong Kong, and Australia perceived higher travel risk, felt less safe, and were more anxious and reluctant to travel than tourists from the United Kingdom, Canada, and Greece [49]. Cultural differences are shown to be an important demographic segment in tourist behavior and risk awareness [50]. The same authors looked at the preferences of Asians and non-Asians for green hotels and the perception of reducing carbon dioxide emissions in traffic, and they discovered that travelers from 11 different countries feel safer in places that provide this kind of environmental protection. Recurring visits also lessen concerns about environmental threats [51]. Numerous researchers have examined the effects of environmental dangers on tourists’ perceptions and plans in relation to sociodemographic parameters [16,52,53,54,55], with some authors emphasizing the issue of age [56,57,58] before moving on to the component of tourists’ psychological capacity for risk-taking [59]. According to the same authors, there are seven factors that are related to both psychological and material preparedness for both men and women: knowledge of psychological preparedness, prior emergency training or experience, exposure to natural hazards in the past, higher awareness scores, higher active engagement coping style scores, low stress scores, and low depression scores. Tourists tend to focus on two categories of risk indicators: subjective risk factors [11,16,60,61,62] and objective risk factors [63,64]. Blešić et al. [62] examine the relationship between subjective risk factors and objectively perceived risks and claim that more educated people perceive all the dangers of environmental risks as well as more subjective risk perceptions. Subjective risk factors include demographic variables and individual cognitive abilities (temperament, personality, emotions, views, values, cognitive, and meta-cognitive) [65], while objective factors include psychological risk, financial risk, performance risk, health risk, and social risk [66]. Physical characteristics and psychological processes (such as attention, perception, representation effect, memory, thinking, and language abilities) of tourists have a significant influence on how they perceive the danger associated with travel [65].

Numerous authors have examined the relationship between lifestyle and personality characteristics and how tourists behave in specific circumstances [67,68,69,70]. They noted that lifestyle is a concept that captures the core values and interests of an individual [71,72] and that the perception of risky situations is also influenced by specific psychographic characteristics [73,74]. The level of self-confidence and cognitive abilities of tourists rises along with their lifestyle, personality features, and experience, which results in a decreased level of perceived danger [16,20,75,76]. Cohen [77] emphasizes the influence of lifestyle by which individuals frame the concept and stylize their lives around the choice of travel, while some authors claim that personality traits and lifestyles, family problems, various types of failures, and crises connect travel with an escape from everyday life [78]. Individuals who seek sensation and adventure are more prone to taking risks and going to risky destinations [20,48,75,76,79].

Contrary to all assertions that environmental risks have a negative impact, some authors’ research has led them to the conclusion that, for some tourist types, the presence of a particular kind of risk is what draws them to a particular location [80], and that controlled risk, when viewed as a challenge, adds to the overall enjoyment of the risky experience [81]. Additionally, the assertion made by Brida et al. [82] is supported. They contend that even in risky circumstances—in their study, the COVID-19 pandemic—the desire to travel persists. In addition to their assertion, the same authors note that tourists’ sociodemographic and psychological traits had a significant impact. According to Hamilton et al. [83], environmental risk modifications in general can even positively affect how tourists perceive them and turn them into an attraction.

2.3. Aim of the Present Study and Conceptual Framework

The purpose of this study was to ascertain the impact of personality characteristics, way of life, and psychographic orientations on the selection of hypothetical tourist sites with varying levels of environmental risk and tourist appeal.

The Big Five Inventory model of personality traits (BFI-10), which distinguishes between extroversion, agreeableness, conscientiousness, neuroticism, and openness as personality types, is used in the majority of research on the impact of personality traits on the choice of a tourist destination in relation to the degree of potential risk [73,84,85,86,87,88,89,90]. According to several studies [91,92,93,94,95], risk perception is presented using the psychographic technique VALS 2 (values and lifestyles). The four personality types that the same authors highlight are traditional idealists, modern idealists, traditional materialists, and modern materialists. The psychographic technique AIO (Activities, Interests, Opinions) was originally used to study the tourist business by Darden and Perreault [96], as well as Blackwell, Miniard, and Engel [97]. Chen et al. [98] also examined the perception of risk using the AIO technique, highlighting five psychographic dimensions: relaxation, outdoor recreation, first class, family orientation, and social orientation, which were also used for the purposes of this research.

The authors came up with the basic hypotheses, which are depicted in Figure 1 along with the suggested model.

H 1.

The relationship between psychographic lifestyle orientations (AIO lifestyle technique) and personality traits (BFI-10) is positive.

H 1a.

The relationship between psychographic lifestyle orientations (VALS 2 lifestyle technique) and personality traits (BFI-10) is positive.

H 2.

According to the level of environmental risk and tourist attraction, psychographic orientations and the AIO lifestyle method have a positive impact on the choice of destinations.

H 3.

According to the level of environmental risk and tourist attraction, psychographic orientations and the VALS 2 lifestyle method have a positive impact on the choice of destinations.

3. Methodology

To collect more comprehensive, genuine, trustworthy, and objective data, the combined research strategy included both quantitative and qualitative methodologies. A flowchart of the research method is shown in Figure 2.

3.1. Procedure and Participants

For the purposes of the research, a volunteer survey of tourists was carried out in seven hotels in Novi Sad (the second largest city in Serbia—a total of 218 respondents) and Belgrade (the capital of Serbia—a total of 322 respondents) in the period from January to June 2023. Out of a total of 800 questionnaires distributed, 540 with complete answers were taken into analysis, and the time period of the research was determined by the researchers, by statistical determination of a possible representative sample. A random sampling technique was used because the probability of being included in the sample is the same for each individual. The required sample size was calculated using G*power test. Taking into account that there was a total of 8 predictors and 6 criteria, the required effect size was set to η2 = 0.15, with a statistical power of 0.95, and it was calculated that a sample size of 138 respondents may be appropriate for this research. The researchers had the task of surveying exclusively adult visitors to the hotel.

Table 1. Sociodemographic description of tourists.

Gender		Frequency of Traveling
Male	39.9%	I travel abroad once a year			34.7%
Female	60.1%	I travel abroad once a month			18.8%
		I travel abroad several times a year			46.5%
Education		Earning
High school degree	24%	Low (≤300 *)			0.7%
Faculty degree	67.7%	Average (300–1000 *)			24.5%
MSc, PhD	8.3%	High (>1000 *)			74.8%
Age		Country of Residence
18–30	26.2%	Bosnia	31.1%	Hungary	3.6%
31–55	30%	Croatia	18.4%	Italy	2.3%
>56	43.8%	Slovenia	9.6%	Montenegro	29%
		Austria	4.9%	Germany	1.1%

* monthly salary in euros.

provides an insight into the demographic characteristics of tourists. It can be seen that the largest percentage of visitors are women, at about 60%, with men a little less than 39.9%, aged over 56, have a university degree (67.7%), and have an average salary (74.8%).

When examining the data on travel frequency, it becomes clear that 46.5% of the visitors surveyed belong to the category of people who travel frequently (several times a year) and that they are primarily from the nearby nations of Bosnia and Herzegovina (31.1%), Croatia (18.4%), and Montenegro (29%).

3.2. Measures

The standard BFI-10 scale (Big Five Inventory Model), which consists of 10 items and measures personality traits of the Big Five dimensions of extraversion, agreeableness, conscientiousness, neuroticism, and openness [98,99], was utilized for the objectives of this study. AIO (attitude, interest, and opinion) and VALS 2 (values and lifestyle), which are typically used to measure lifestyle and are tailored to the objective and practical limitations of field research, were also used. Additionally, in a paper titled Vacation Life Style and Travel Behaviors, the authors modified the AIO questionnaire slightly in order to identify the activities, interests, and attitudes of customers (16 items) [100]. All elements from the AIO questionnaire are divided into five categories: relaxation, outdoor recreation, first class, family orientation, and social orientation. The VALS 2 questionnaire (values, attitudes, and lifestyles) was changed by the authors by adding 39 items, which were created by Maričić [101], Mitchell and Olson [102], and Mitchell [103]. The social orientations, action orientations, and principal orientations are the three psychographic orientations into which all the VALS 2 technique items are divided. The visitors’ attitudes were rated according to their severity on a seven-point Likert scale (1—not important al all, 2—not important, 3—slightly not important, 4—neutral, 5—slightly important, 6—important, 7—extremely important). Tourists could choose which destination they would visit more or less from the given description in six instances where the authors changed the riskiness and allure of the locations (description of locations in Appendix A). In order to prevent the respondents from responding in accordance with destinations they already know from experience or from the media, the writers utilized the names of hypothetical locations with fabricated names.

3.3. Methods of Analysis of the Obtained Data

The program software IBM SPSS AMOS version 26.00 was used to process the data when they were obtained. All of the dimensions’ values, which are displayed in

Table 2. Descriptive dimension values and reliability level.

Dimensions	m *	sd *	α *
BIF-10—Neuroticism	2.27	1.238	0.956
BIF-10—Extroversion	3.19	1.252	0.922
BIF-10—Conscientiousness	3.49	1.827	0.811
BIF-10—Agreeableness	3.34	1.275	0.725
BIF-10—Openness	2.11	1.130	0.858
AIO—Relaxation	2.56	1.000	0.828
AIO—Outdoor recreations	2.13	1.084	0.737
AIO—First class	3.21	0.910	0.797
AIO—Family orientation	3.41	1.891	0.897
AIO—Social orientation	3.50	1.813	0.903
VALS 2—Status orientation	3.01	0.677	0.852
VALS 2—Action orientation	3.35	0.773	0.849
VALS 2—Principal orientation	3.13	0.767	0.749
Destination selection percentage values
Destination level risk 1		53.6%
Destination level risk 2		46.1%
Destination level risk 3		35.5%
Destination level risk 4		31%
Destination level risk 5		25.25%
Destination level risk 6		20.9%

* m—arithmetic mean; sd—standard deviation; α—reliability.

, were determined to be reliable with the use of Cronbach’s alpha. Path analysis was utilized as a form of extension of regression analysis, which is carried out in the aforementioned program, to analyze previously proven effects or associations. The dependent variable destinations were measured on a binary scale. A total of 10 questions were collected from the AIO lifestyle dimension, 39 from the VALS 2 lifestyle dimension, and 10 from the BFI-10 personality traits dimension (questions are provided in the attachment). Adequacy or model fit conditions were met with the following values: X2 = 3066.431, df = 28, p = 0.00, CMIN/df = 2.820, TLI = 0.901, CFI = 0.932, NFI = 0.962, IFI = 0.939, RMSEA = 0.041, AIC = 305,830, and BIC = 306,777.

4. Results and Discussion

According to the chosen level of risk and tourist appeal, Table 2 displays the findings of the average ratings for the dimensions that will be used to assess their influences on the choice of six hypothetical tourist locations.

The AIO lifestyle group has the highest average score (m = 3.59) for the social orientation dimension. The action orientation dimension from the VALS 2 psychographic technique group has the greatest average rating (m = 3.35), and the conscientiousness dimension from the BFI-10 personality traits group has the highest average value of the arithmetic mean (m = 3.49). The highest percentage of travelers (53.6%) chose the destination D1, which falls into the category of high attractiveness and low risk, while the lowest percentage of travelers (20.9%) selected D6, which is in the category of high attractiveness and high risk for the environment.

4.1. Results of Assessing How Personality Traits Affect Psychographic Orientations

Five personality traits (BFI-10) were analyzed using path analysis to see how they affected lifestyle aspects (AIO and VALS 2), which were categorized into psychographic orientations. Figure 3 displays the effect values, while

Table A2. Values of significance of the influence of BFI-10 dimensions on psychographic orientations.

			Estimate	S.E.	C.R.	p
Relaxation		Neuroticism	−0.115	0.047	−2.429	0.015
Outdoor recreation		Neuroticism	−0.068	0.054	−1.253	0.210
First class		Neuroticism	−0.093	0.044	−2.144	0.032
Family orientation		Neuroticism	−0.083	0.081	−1.033	0.302
Social orientation		Neuroticism	−0.190	0.069	−2.754	0.006
Status orientation		Neuroticism	0.097	0.033	2.966	0.003
Action orientation		Neuroticism	0.034	0.039	0.867	0.386
Principal orientation		Neuroticism	0.133	0.036	3.679	***
Relaxation		Extroversion	0.055	0.040	1.384	0.166
Outdoor recreation		Extroversion	0.039	0.045	0.864	0.387
First class		Extroversion	0.057	0.037	1.570	0.116
Family orientation		Extroversion	0.051	0.068	0.746	0.455
Social orientation		Extroversion	0.024	0.058	0.413	0.679
Status orientation		Extroversion	0.078	0.028	2.827	0.005
Action orientation		Extroversion	0.135	0.033	4.081	***
Principal orientation		Extroversion	0.088	0.030	2.881	0.004
Relaxation		Conscientiousness	0.140	0.025	5.531	***
Outdoor recreation		Conscientiousness	0.122	0.029	4.247	***
First class		Conscientiousness	0.137	0.023	5.941	***
Family orientation		Conscientiousness	0.512	0.043	11.928	***
Social orientation		Conscientiousness	0.561	0.037	15.300	***
Status orientation		Conscientiousness	−0.014	0.017	−0.778	0.437
Action orientation		Conscientiousness	0.000	0.021	−0.002	0.999
Principal orientation		Conscientiousness	−0.032	0.019	−1.649	0.099
Relaxation		Agreeableness	0.145	0.037	3.871	***
Outdoor recreation		Agreeableness	0.096	0.042	2.253	0.024
First class		Agreeableness	0.094	0.034	2.738	0.006
Family orientation		Agreeableness	0.184	0.064	2.900	0.004
Social orientation		Agreeableness	0.291	0.054	5.350	***
Status orientation		Agreeableness	0.044	0.026	1.706	0.088
Action orientation		Agreeableness	−0.022	0.031	−0.712	0.477
Principal orientation		Agreeableness	0.059	0.028	2.077	0.038
Relaxation		Openness	0.057	0.050	1.152	0.249
Outdoor recreation		Openness	0.065	0.057	1.149	0.251
First class		Openness	0.058	0.046	1.280	0.201
Family orientation		Openness	0.093	0.085	1.103	0.270
Social orientation		Openness	0.084	0.072	1.153	0.249
Status orientation		Openness	0.063	0.034	1.830	0.067
Action orientation		Openness	0.001	0.041	0.032	0.975
Principal orientation		Openness	0.090	0.038	2.373	0.018

*** p = 0.00.

(Appendix B) lists the value estimates, standard error, critical ratio, and statistical significance (p).

The following psychographic lifestyle orientations were found to be statistically affected by the neuroticism dimension: relaxation (AIO) (p = 0.15, ß = −0.141), first class (AIO) (p = 0.32, ß = −0.125), social orientation (AIO) (p = 0.06, ß = −0.190), status orientation (VALS 2) (p = 0.03, ß = 0.097), and principal orientation (VALS 2) (p = 0.00, ß = 0.133). With the exception of the VALS 2 lifestyle, where it has a positive effect, it is true that those who are more neurotic tend to view the status and principal orientation dimensions less favorably than those who are less neurotic.

Only three VALS 2 relationships in the positive effect—status orientation (p = 0.05, ß = 0.146), action orientation (p = 0.00, ß = 0.218), and principal orientation (p = 0.04, ß = 0.145)—led to statistical significance in the extroversion dimension. The conscientiousness dimension has a significant and positive effect on the AIO lifestyle aspects of relaxation (p = 0.00, ß = 0.262), outdoor orientation (p = 0.00, ß = 0.208), first class (p = 0.00, ß = 0.283), family orientation (p = 0.00, ß = 0.511), and social orientation (p = 0.00, ß = 0.591). Furthermore, a very strong effect of this dimension was found for family orientation and social orientation.

Agreeableness shows a statistically significant effect on the dimensions of the psychographic orientation of AIO: relaxation (p = 0.00, ß = 0.190), outdoor recreation (p = 0.024, ß = 0.114), first class (p = 0.06, ß = 0.135), family orientation (p =0.04, ß = 0.128), and status orientation (p = 0.00, ß = 0.084), and on only one dimension of VALS 2, which is principal orientation, with values p = 0.038 and lower correlation ß= 0.100.

In relation to the two VALS 2 dimensions of status orientation (p = 0.067, ß = 0.107) and principal orientation (p = 0.018, ß = 0.135), the openness dimension has statistical significance. The findings corroborate the initial hypotheses (H1 and H1a), which claimed that personality traits had a strong effect on psychographic lifestyle orientations (AIO and VALS 2).

4.2. Examining the Effect of Psychographic Orientations on Travelers’ Preferences for a Particular Location

Table A3. Values of the direct influence of psychographic orientations on the choice of a tourist destination.

			Estimate	S.E.	C.R.	p
D1		Relaxation	0.096	0.084	1.145	0.052
D2		Relaxation	0.093	0.097	0.963	0.335
D3		Relaxation	0.135	0.107	1.270	0.004
D4		Relaxation	0.166	0.095	1.750	0.080
D5		Relaxation	−0.112	0.095	−1.179	0.038
D6		Relaxation	−0.009	0.084	−0.112	0.010
D1		Outdoor recreation	−0.032	0.072	−0.449	0.654
D2		Outdoor recreation	−0.096	0.083	−1.160	0.246
D3		Outdoor recreation	−0.134	0.091	−1.469	0.142
D4		Outdoor recreation	−0.087	0.082	−1.063	0.088
D5		Outdoor recreation	−0.053	0.082	−0.655	0.013
D6		Outdoor recreation	−0.123	0.072	−1.712	0.057
D1		First class	0.039	0.079	0.491	0.623
D2		First class	−0.018	0.091	−0.194	0.846
D3		First class	−0.057	0.101	−0.571	0.568
D4		First class	−0.076	0.090	−0.850	0.395
D5		First class	−0.214	0.090	−2.386	0.017
D6		First class	−0.112	0.079	−1.412	0.058
D1		Family orientation	−0.047	0.048	−0.972	0.331
D2		Family orientation	0.056	0.055	1.018	0.309
D3		Family orientation	0.131	0.061	2.139	0.032
D4		Family orientation	0.012	0.055	0.219	0.027
D5		Family orientation	−0.005	0.055	−0.099	0.021
D6		Family orientation	−0.033	0.048	−0.684	0.004
D1		Social orientation	−0.005	0.046	−0.110	0.913
D2		Social orientation	−0.057	0.053	−1.066	0.287
D3		Social orientation	−0.042	0.059	−0.725	0.068
D4		Social orientation	−0.053	0.052	−1.011	0.012
D5		Social orientation	−0.030	0.052	−0.579	0.013
D6		Social orientation	−0.064	0.046	−1.382	0.047
D1		Status orientation	−0.326	0.139	−2.341	0.019
D2		Status orientation	0.023	0.161	0.146	0.884
D3		Status orientation	−0.206	0.177	−1.163	0.245
D4		Status orientation	−0.540	0.158	−3.420	***
D5		Status orientation	−0.476	0.158	−3.015	0.003
D6		Status orientation	−0.453	0.140	−3.243	0.001
D1		Action orientation	0.158	0.100	1.576	0.115
D2		Action orientation	0.106	0.115	0.918	0.358
D3		Action orientation	0.317	0.127	2.497	0.013
D4		Action orientation	0.267	0.113	2.354	0.019
D5		Action orientation	0.362	0.113	3.189	0.001
D6		Action orientation	0.062	0.100	0.623	0.033
D1		Principal orientation	0.128	0.115	1.116	0.265
D2		Principal orientation	−0.057	0.132	−0.431	0.026
D3		Principal orientation	0.006	0.146	0.040	0.968
D4		Principal orientation	0.075	0.130	0.579	0.562
D5		Principal orientation	0.020	0.130	0.151	0.055
D6		Principal orientation	0.120	0.115	1.043	0.297

*** p = 0.00.

(Appendix C) provides the values of the direct effects of psychographic orientations on the selection of a travel place, and Figure 2 shows the effects. The lifestyle group AIO’s psychological orientation toward relaxation has a substantial effect on the low-risk destination D1 (p = 0.052, ß = 0.065), and with values of p = 0.04 and ß = 0.072, has an effect on destination D3. Also, it has a significant and positive effect on destination D4 (p = 0.080, ß = 0.098), while on the last two destinations D5 and D6, with high attractiveness and a high degree of risk, it has a significant and negative influence (D5: p = 0.038, ß= −0.066; D6: p = 0.010, ß = −0.346). Fewer tourists prefer high-risk areas as they identify more with this psychographic subgroup of the AIO lifestyle.

The selection of only high-risk locations D5 and D6 was significantly affected by the outdoor recreation component (p = 0.013, ß = −0.234 and p = 0.057, ß = −0.291). The effect is negative; thus, the more attracted they are to this psychographic group, the more carefully they select locations with high levels of both attraction and environmental risk.

Only the high-risk destinations D5 (p = 0.017, ß = −0.115), and D6 (p = 0.058, ß = −0.069) are significantly affected by the first class dimension from the AIO lifestyle group. This finding suggests that people with this psychographic orientation are less likely to choose high-risk locations. It was shown that members of the family orientation dimension have a significant effect on the choice of the following destinations: D3 (p = 0.032, ß = 0.131), D4 (p= 0.027, ß = 0.013), D5 (p = 0.021, ß= −0.406), and D6 (p = 0.04, ß= −0.542). Members of this lifestyle group are less likely to choose the most risky destination, while they are more determined for those with low environmental risk. The last AIO dimension of social orientation has a significant effect on the choice of the following destinations: D4 (p = 0.012, ß= −0.055), D5 (p = 0.013, ß= −0.032), and D6 (p = 0.047, ß= −0.076). The effects are negative and low, which confirms that members of this psychographic orientation also evaluate risky destinations negatively and choose them less often.

Observing the psychographic dimensions of the VALS 2 category, it is observed that the status orientation dimension significantly affects the choice of next destinations: D1 (p = 0.19, ß = −0.152), then D4 (p = 0.00, ß = −0.218), D5 (p = 0.003, ß = −0.192), and D6 (p = 0.01, ß = −0.208). The effects are negative and quite low. The effect of the action orientation dimension on destination choice has the following values: it shows a significant effect on destination D3 (p = 0.013, ß = 0.135), destination D4 (p = 0.019, ß = 0.125), destination D5 (p = 0.01, ß= 0.169), and destination D6 (p = 0.033, ß = 0.233). Members of the action psychographic orientation are more willing to take their own risks and choose destinations with a higher degree of environmental risk. The principal orientation dimension shows a significant effect with very low values on destinations D2 (p = 0.026, ß = −0.026) and D5 (p = 0.055, ß = 0.009). Hypotheses H2 and H3 confirmed that the psychographic orientations of AIO and VALS 2 lifestyle techniques have positive effects on the choice of a tourist destination in relation to the degree of environmental risk and tourist attractiveness.

According to Woodsidem and Pitts [104], personality traits (BFI-10) affect how travelers perceive risk in addition to demographic factors. They focus on two types of behavior related to personality traits: one in the place of residence and the other in the tourist destination. Similar research demonstrates that personality factors play a significant role in predicting how tourists will behave when selecting a travel destination, particularly when it comes to locations with a history of risk. According to research, those who exhibit strong extraversion and conscientiousness traits make critical judgments more quickly and easily, both at work and in high-risk scenarios [79], whereas those who exhibit strong openness pick particular services [105,106]. Due to danger and uncertainty, a high amount of novelty seeking might either attract novelty seekers or deter those seeking familiarity from certain locations [20]. Certain locations with possible hazards may appeal to sensationalists, explorers, extroverts, and members of the openness group who are aware of the repercussions [37,75]. Maričić et al. [101] indicate that personality types according to lifestyle and style are completely diametrically different in tourist behavior: materialists and status-oriented people may prefer fun and idealists and action-oriented people may be interested in news and learning and choose such destinations accordingly, in contrast to those who are principally oriented, who are less likely to choose challenges and deviation from established principles. Chen et al. [98] also indicate that social orientation, relaxation, and family orientation groups of people are more dedicated to fun, socializing, and traveling, where they would achieve social interaction in contrast to outdoor recreation, which aims to get to know something new and is more ready for challenges.

5. Conclusions

The way that people live, work, travel, interact, and spend their spare time is changing as a result of technological and digital advancements, yet the lines between the digital, social, physical, and environmental settings are becoming more and more blurred [107]. Environmental dangers have the potential to influence not just the social environment but also the natural environment by affecting how tourists behave and select their travel destinations. Additionally, tourism as a sector of the economy is sensitive to a variety of dangers, particularly those related to the environment, and it has the potential to discourage travelers [79,108,109]. In addition to natural reasons, the rising population and all of its activities may also be the source of the increase in environmental dangers [110,111]. Visitation to the afflicted area may decline as a result of disasters and other crises (such as epidemics, conflicts, and pollution) [57,62,109]. The perception of tourist risk comprises knowledge of the social and environmental conditions in popular tourist areas as well as the security circumstances surrounding “food, housing, transportation, travel, shopping, and entertainment” during the journey process [112]. Researching how people perceive environmental risk is an essential part of developing any region as a tourist destination, whether it be in unstable or threatened areas or, on the other side, in developed tourist destinations [18,113,114], and it is especially vital for luring visitors after significant disasters [54]. The environment’s ecosystem is thought to be harmed by the overdevelopment of tourism, nevertheless. Many of the world’s natural places could be threatened by unrestrained conventional tourism. It can put a lot of strain on a region and have negative effects, including soil erosion, increased pollution, discharges to the sea, habitat loss, greater pressure on endangered species, and increased susceptibility to wildfires.

This manuscript examines advancements in the evaluation of risk perception in tourism in relation to the psychological traits of tourists, drawing on literature reviews of domestic and international scientists who deal with systemic risk perception in tourism from the perspective of concepts, factors, and evaluation of tourist risk perception. This paper summarizes the basic idea, general methodology, and conclusions of risk perception of travel to attractive and risky destinations. The authors wanted to know how much personality traits and lifestyle psychographic orientations influenced people’s decisions about where to travel in relation to risk and attractiveness. The BFI-10, AIO, and VALS 2 scales were used to gauge how visitors perceived risk. In Figure 3, the estimated model’s diagram, the relationship between recognized psychographic qualities and the choice of locations with various levels of danger and tourist allure is explored. It has been demonstrated that personality characteristics derived from a scale with ten predetermined questions have a significant influence on lifestyles and form psychographic orientations, which further influence the choice of destinations and the behavior of tourists in relation to various risk and attractiveness levels. According to the findings of the psychographic orientation of the AIO lifestyle, tourists’ choice of attractive and risky places has a negative statistical link, and they tend to choose them less frequently. Members of the action orientation are more likely to take personal risks and select locations with higher levels of environmental danger according to the VALS 2 lifestyle dimension.

5.1. Theoretical Implications

Some authors continue to argue that there is not enough study on the subject of the perception of environmental risk in the choice of a tourist destination, despite the number of comparable studies on the influence of environmental risks on tourist behavior that have been published). It may be claimed that there is relatively little literature on this subject, especially when we consider the number of studies coming from the Republic of Serbia. In this situation, it is even more crucial to consider the study’s findings in order to close the gap left by a lack of literature. The majority of studies discuss how environmental risks affect travel and the effects that they have on the destination, but hardly any of them look at how visitors from this region behave when confronted with the destination’s level of risk and its allure. The truth is that there are places with a high risk of harm that are also quite appealing. In this regard, it is critical to identify which tourist profile, knowing in advance in connection to the level of attraction given, is prepared to accept the risk and which tourist profile is not in order to determine which is unprepared for such an endeavor. The findings will undoubtedly provide a useful foundation for extending the literature on the study of tourist profiles and behavior, but they achieve this in the context of two crucial factors in destination selection: risk and appeal.

As a result, knowledge in many economic sectors would be strengthened in the area of theoretical research. The data could be used for further research on this subject in a wide range of scientific fields, including economics, management, and spatial planning, among others. A thorough examination of risk management techniques, criteria for the selection of measures, and evaluation of the efficacy of these measures should be related to further research on this issue and the study of the obtained results because these factors can affect how tourists behave when selecting high-risk tourist destinations. The data can undoubtedly complete the idea regarding psychology and different tourist profiles. The results can more precisely corroborate the behavior of specified tourist profiles in specific scenarios—in this case, when picking a dangerous and alluring trip—because two models of lifestyle and personality attributes were combined. By keeping an eye on these profiles, it is feasible to anticipate visitor responses in advance and make an offer in response to their desires. This type of research employed the model of presenting respondents with hypothetical locations for the first time. In order to better understand respondents’ responses to the level of environmental risk and appeal, it is advised that future research involve conducting semi-experiments in which respondents are digitally presented with potential destinations.

5.2. Practical Implications

Personality and lifestyle traits are significant consumer attributes for marketing and management objectives. Personality characteristics are enduring, firmly ingrained, and indicate dependable reaction patterns that have been formed from childhood. Consumers’ activities, interests, and opinions serve as a means of expressing their lifestyle. When establishing business plans for tourism and other industries, the findings can be used as methodological support and useful advice, keeping in mind how environmental risks affect customer behavior. Studying the extent to which environmental concerns have an impact on tourist behavior is a difficult and complex endeavor that calls for the cooperation of the resources and knowledge of numerous stakeholders, including governments, corporations, and community organizations. Organizations that oversee the growth of the tourist destination can make use of the data collected to efficiently identify and assess potential hazards, put prevention and mitigation measures in place, and respond to and recover from issues as they arise. It is well established that environmental dangers can come from a variety of sources and that their effects can be very diverse and challenging to assess. Given this, data collected directly from the field are required in order to improve resource allocation and the prioritization of risk management measures. Environmental risks have a wider impact on society and the economy, and, by enhancing destination management based on study findings, local people can survive less negatively. It may be difficult for the tourism industry and the economy to recover from these repercussions, which have the potential to have long-lasting implications for communities and economies.

5.3. Limitations

The field study by these authors has legitimate constraints, just like any other kind of research. In order to gather empirical data on how perceived environmental threats affect tourists’ behavior in the Republic of Serbia, this study conducted a comprehensive survey. Tourists’ reluctance to collaborate with researchers and complete surveys is one limiting factor. It is also noteworthy that the majority of respondents did not comprehend the sort of risk, necessitating the researcher’s requirement for a further explanation in addition to the written descriptions of each of the six locations. The pandemic in the foreground is the kind of risk that still affects travelers, whereas other risks are largely ignored by travelers. It is interesting to note that because the majority of respondents have not personally experienced any of the key environmental concerns, their ability to assess risk is actually rather constrained. The tourists who took part in the poll are from a region without any significant environmental disasters, and they were primarily recommended by the media. As a result, the respondents do not have a realistic perception of the risks and effects on the destination, and since they lack firsthand experience, they forget the effects on the destination that they wish to visit. We employed the BFI-10 model with ten questions, whereas the BF model with all 44 questions of authors who dealt with the theory of personality traits can be included. Limitations are also related to the number of variables, and it is advised that future studies include more factors. We dare to assert that the results would be more reliable through experimentation or observation, and that we would obtain more reliable results if we screened destination-specific films and thus observed on-site how tourists reacted to their perceptions of the location in relation to the visual depiction of its level of risk and allure. We solely take into account how lifestyles and personality qualities affect destination choice; we ignore socio-demographic factors (gender, age, income, and education), informational trust, and prior experience. Family size, employment level, site of living (rural/urban), and various cultural backgrounds can all be thought of as potential predictors. Furthermore, it is believed that the inclusion of such categorical factors will produce significant findings. Also, given that the mentioned variables were excluded, it is recommended that they be included in future research (because differences in the gender structure were observed). Since tourists come from different countries, the study should be extended to those countries, which would increase the regional significance of the research. Additionally, the study’s data analysis model can be seen as a weakness and replaced with the econometric analysis model, which is increasingly used in the majority of recent studies in this field.