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Article

Risks in the Role of Co-Creating the Future of Tourism in “Stigmatized” Destinations

by
Tamara Gajić
1,2,3,*,
Dragan Vukolić
3,
Marko D. Petrović
1,2,
Ivana Blešić
2,4,
Miloš Zrnić
5,
Drago Cvijanović
3,
Dejan Sekulić
3,
Ana Spasojević
6,
Maja Obradović
7,
Ana Obradović
7,
Ilija Savić
7,
Jasmina M. Jovanović
8,
Mirjana Gajić
8,
Dobrila Lukić
9 and
Željko Anđelković
10
1
Geographical Institute “Jovan Cvijić” SASA, Đure Jakšića 9, 11000 Belgrade, Serbia
2
Institute of Sports, Tourism and Service, South Ural State University, Lenjina76, 454080 Chelyabinsk, Russia
3
Faculty of Hotel Management and Tourism, University of Kragujevac, Vojvođanska 5a, 36210 Vrnjačka Banja, Serbia
4
Department of Geography, Tourism and Hotel Management, Faculty of Sciences, University of Novi Sad, 21000 Novi Sad, Serbia
5
Academy of Applied Studies—The College of Hotel Management, Kneza Višeslava 70, 11000 Belgrade, Serbia
6
Faculty of Economics, University of Kragujevac, Đure Pucara Starog 3, 34000 Kragujevac, Serbia
7
Faculty of Business Economics, Singidunum University, Danijelova 6, 11000 Belgrade, Serbia
8
Faculty of Geography, University of Belgrade, 3/III Studentski Trg, 11000 Belgrade, Serbia
9
Eighth Belgrade Grammar School, 71 Grčića Milenka, 11000 Belgrade, Serbia
10
National Museum Niš, 14 Generala Milojka Lešjanina, 18105 Niš, Serbia
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(23), 15530; https://doi.org/10.3390/su142315530
Submission received: 15 October 2022 / Revised: 8 November 2022 / Accepted: 14 November 2022 / Published: 22 November 2022
(This article belongs to the Special Issue Current Trends in Tourism under COVID-19 and Future Implications)
Browse Figures
Review Reports Versions Notes

Abstract

:
The primary goal of this paper was to investigate the strength of the influence of different types of risk on the travelers’ intention to visit destinations in future, that are, prejudiced due to COVID-19, marked as “stigmatized”, “isolated”, or “risky destinations”. Field interview research was conducted at the “Belgrade Nikola Tesla Airport” (Serbia). The results obtained by multiple regression analysis showed that all types of risks influenced the intention of travelers, with financial risk showing a more significant impact. Canonical discriminant analysis indicated that men were most afraid of human induced risk, service quality risk, natural disaster and COVID-19 risk, and they chose safer destinations. Among the women, the biggest fear was financial risk, socio-psychological risk, and food safety risk. Older respondents and those under the influence of external factors decided on safer destinations, while financial status did not play a significant role in predicting the choice of destination. The selection of the destination according to the degree of security was determined by the ordinal regression methodology. The entire research presents a certain novelty, because so far in the numerous studies on the topic of the negative consequences of COVID-19 on tourism, there has been no discussion of stigmatized or risky destinations that received that epithet, and were therefore negatively and unfairly marked in the minds of tourists for future visits.

1. Introduction

From the beginning of the COVID-19 pandemic until today, some countries have been put on the very edge, and marked as “isolated” or “stigmatized” by creating prejudices among travelers [1]. These are countries such as China and Italy as well as some other countries that had the largest number of victims during the pandemic, where the future of tourism is still questionable [2,3]. Safety measures in some countries still exist, although they are in a minimal form such as wearing masks in public and maintaining a distance [4,5]. It has become a habit for all residents, but a new way of life [6]. In May 2022, the Chinese authorities introduced controlled movements and departures abroad, with extensive controls on the reason for departure, and certificates of receipt of all doses of vaccines, with the obligation of 14 days of quarantine, and the obligation to perform a PCR test upon entering the country [7]. There has been a small number of people who have decided to visit China as tourists, but mostly for business reasons or to visit family [2]. When looking at the situation in Serbia, it can be seen that tourism is slowly recovering. In May 2022, compared to May 2021, the number of visits increased by 88.4%, while the number of overnight stays increased by 56.1% [1]. Passenger traffic in the first quarter of 2022 increased three times compared to the same period in 2021 to 46.1% less than the level of 2019 (40.8% less in March) [1].
Figure 1 illustrates the spread of the coronavirus around the world and the countries that had the highest percentage of deaths (2020).
There are no accurate data or research that have confirmed that the media or a negative experience is the main reason for creating prejudices and fears among travelers when making their decisions about future trips [1]. In some studies, it was only considered that the experience, together with the media presentation of the destination, is the way to create subjective feelings that will influence the decision-making of consumers [8]. The pandemic is not just a medical phenomenon, in any case, it has great implications for people’s mental health and the fear of travel, especially to countries that have been under a lot of media attention due to the number of deaths [3,9]. Despite the modern age, health risks can be limiting factors during travel and threaten the safety of travelers [10,11]. Risk perception is generally a subjective assessment of possible situations during the trip, and it is individually created by different profiles of visitors [12,13]. The influence of risk on decisions about future trips, especially to countries marked as risk destinations, depends on the personal experience of travelers and their awareness of the crisis situation and negative consequences [14,15].
Based on existing research and available literature, the authors conducted a field interview research at the largest and busiest international airport in Serbia—Belgrade Nikola Tesla Airport (BEG). The survey was short and very precisely explained. It partly relied on similar research conducted by Gajić et al. [1], which also related to fears of a pandemic and financial risk in different personality profiles.
Although there are many types of risks, the emphasis was placed on the consequences of the pandemic as a current issue related to the enemy of the civilized living of the 21st century. The importance of the research is reflected primarily in the examination of risk perception by travelers when making a decision to go to countries that are on the very margin in terms of visiting, after the pandemic. The goal was to determine how much the fear of the pandemic left negative awareness among travelers in the following period. Based on the results, it will be possible to determine the influence of internal and external factors (experience and media) on the creation of subjective fears in people during travel, predict their directions of movement, and predict future tourist flows should a new unforeseen crisis arise. The study provides insight into data that can be helpful in creating research and theories of tourist behavior in the post-COVID period.

2. Literature Review

The pandemic is changing the economy, tourism, and awareness in society [16,17,18,19]. COVID-19 has created great fears and anxiety among people [20,21], but only the short-term effects of the pandemic are visible, while the long-term effects related to consumer behavior in the future have not yet been fully observed [22,23]. Due to the fact that the impact of different types of risk on people’s awareness has not been fully explored, Zaman et al. [10] developed a risk scale or construct that measured the intrapersonal anxiety of travelers, based on which it will be possible to predict future behavior if a pandemic or similar crisis situation occurs. All tourist decisions related to travel are determined by the perception of safety and security [24], and the perception of safety itself is a subjective attitude of an individual that implies understanding and knowledge of the type of risk [25,26,27,28]. In addition to the risk of infection, the same authors listed several other types of perceived risks that were no less important than the risk of a pandemic [16]. Some of these were: human induced risk (caused by human action), service quality risk (lack of quality service), natural disaster (nature hazards), financial risk (financial losses; unstable economy), socio-psychological risk (negative influence on the cultural factors of the people), and food safety risk (the risk of non-compliance with safety measures when preparing food) [16]. It is believed that in the post-COVID period, intact tourism will have a great impact, more precisely, destinations that did not feel the attack of the pandemic will gain a high position in the attendance market [29]. The pandemic has definitely created new domestic consumers who are turning to nature [30]. Certain studies have established five levels of risk associated with the intention to travel: psychological risk (the impact of purchases and decisions on the attitude towards oneself and on the level of self-esteem), social risk (how the impact of shopping on the attitude of others about us), physical risk (the impact of shopping on the physical state of financial risk (fear of money shortages), and time risk (costs related to planning and opportunity time costs) [31,32,33]. In the research on risk perception, this relationship with the pandemic and the intentions of tourists lacks a clear conceptualization and measurement [34]. A study conducted in Uruguay, where the sample was collected using a convenience sampling method, indicates that most travelers still had a high perception of the risk of COVID-19, but that there was interest in travelling to Uruguay. They obtained two groups of visitors who behaved differently under the influence of the fear of the pandemic: groups who were more willing to travel domestically and abroad during the pandemic, and groups who were more moderate and cautious about the risk of travel [35]. Some studies have indicated a strong influence of geopolitical risk on the movement of tourists [36]. However, there is significant evidence presented by Blešić et al. [13], where based on the types of tourists, they indicated the existence of differences in the objective and subjective perception of the risk of natural disasters.
Destinations that have suffered crisis situations, and the intention of tourists to visit the same destinations in the future have been the subject of research by many theoreticians in the field of tourism development [37,38,39], but very few studies have been carried out on consumer behavior after the COVID-19 crisis, and their decision to visit “isolated” or “stigmatized” destinations [12]. In many cases, the perceived risk of COVID-19 was not a significant predictor in making a travel decision, but the negative impacts of the pandemic on tourism were certainly noted [40]. Pappas and Farmaki [37] proved with their results that respondents took the risk of contracting COVID-19 seriously, and that some respondents still did not feel comfortable on domestic trips, but wanted to believe in the hygiene measures taken at each location in the close future [41,42]. Qi et al. [39] used the theory of protection motivation to explain the intention and decision-making to travel during a crisis and determine their relationship. Their theory relies on the theory of expected values and explains the relationship between risk perception and “cognitive appraisal processes” and their influence on changes in intentions or attitudes.
The risk and fear of infection has influenced the great reluctance of visitors to restaurants and catering establishments in the future period [43,44]. Research has shown that the majority of travelers are more likely to change their travel plans to a destination that has an increased risk, while a minority of them indicate that they are less likely [45]. Serbian tourists are largely afraid of traveling abroad during the COVID-19 pandemic [8,46], but also the fear of the lack of funds or financial risk that may follow in the post-COVID period [14]. At the very beginning of the pandemic, an interesting survey was conducted in the Dach region of Germany on a sample of 1156 respondents, and an increase in the fear of COVID-19, travel risk perception, and travel behavior during a short stay in the destination was found [47]. The passenger’s risk perception is their search for information about a certain risk, and the subjective assessment of the severity of the risk affects their decisions regarding future travel [48]. Subjective prejudice as a consequence of something happening, and later subjective assessment of the chance of it happening again in the future, is a heuristic approach in personality psychology [14].
The influence of personality traits on the intention to travel during crises is known [49], where certain groups of personalities do not react to any prejudices about destinations after crisis situations, especially those that are exposed in the media and presented in people’s minds as isolated [8]. For certain personality types such as extroverts, the fear of risk has no influence on the decision to travel to a destination where the risk may be created again [14]. Alkieer et al. [46], in their research, claimed that the perception of travel risk and health-psychological risk was higher, in both periods, during and after the pandemic. Uncertainty, worry, fear, and anxiety were closely related to risk perception in the travel decision [50,51,52,53]. However, some research indicates that there are multiple vague theories about subjective risk perception on the travel decision in the future [52,54]. Ashikul et al. [2] arrived at the result that the COVID-19 pandemic affected the consciousness of people in the world toward the direction that they were even afraid to mix with the Chinese population. The strong influence of the media in presenting China as an isolated destination had consequences for Chinese tourism, according to the same research. Of course, other types of risk also affect the decision of travelers, and among them, both the risk of violence and socio-psychological risk had a significant negative impact on the participants’ intention to visit China [43]. Travel risk and management perceptions had a significant relationship with risk management, service provision, transport patterns, distribution channels, avoiding overcrowded destinations, and hygiene and safety [55,56,57]. One interesting study conducted in Macau found that high perceived travel risk during COVID-19 increased negative emotions and decreased travel intentions [58]. Research on risk perception in the COVID-19 period can contribute to the subsequent observation of consumers and the prediction of their behavior [59]. Any perceived risk worsens the mental state of tourists by creating anxiety [60], and negatively affects the decision-making to go to a given destination [61,62].
The media can influence people’s consciousness to create extreme fears and prejudices [63]. Certain theoreticians have previously investigated the strong influence of the media on the awareness of tourists [64], creating prejudices among travelers during the decision-making process regarding travel [12]. As much as the media create a panic situation, to another extent, they can restore the brand of the destination and create a positive image for people [57,65]. There are even opposing views that the media do not have such a strong influence on personal experience, decisions, and risk perception [66]. Media and social networks have a strong influence on tourists, but theories related to this are very limited [67,68]. The results revealed that past experience of traveling to certain regions simultaneously increases the intention to travel there again and decreases the intention to avoid areas, especially risky areas [69].
According to Carballo et al. [65], it was shown that women were more afraid of going to risky destinations than men, while men reported a bad experience regarding a risky destination to a greater extent than women did. Men were more risk tolerant and created weaker risk perceptions than women [70,71]. In people’s minds, risk manifests itself differently in decision-making in relation to gender differences [72], which certainly creates an essential basis for further risk management and the understanding of tourists [73]. Risk is defined in different dimensions depending on personality traits, gender, culture, and previous experience [74]. The type of risk that creates the greatest fears for women when making travel decisions is physical violence or sexual harassment [75]. Furthermore, women are more afraid than men to make decisions to travel abroad because it seems an unsafe destination to them [76]. However, with the advent of the COVID-19 pandemic, women rated the image of China as a tourist destination higher than men [77].
Some earlier research pointed to different attitudes about the impact of the fear of infection on travelers, but also the lack of theories related to proving the impact of different types of risk on travel and the purchase of tourist products by travelers [78]. However, apart from the risk of a pandemic, along with the same power of influence on the travelers’ awareness, there was also a financial risk [14], where the perception of that kind of risk and the attitude of customers did not show effects on satisfaction, but had a significant impact on intention behavior [12,79], and proved to be the most important factor in consumption [80].
The biggest criticism of the majority of research thus far is that almost no studies have highlighted the issue of the movement of visitors to destinations that have been marked as risky by the media, even after the pandemic has passed [1]. The awareness that dictates the movement pattern of the visitors is connected to the image of the situation that remains imprinted in the consciousness for a long period of time [56]. The question is what happens to their desire to visit such destinations in the future and how long it would take for those countries to regain their positive image from before the pandemic.
The fact is that there is no official evidence obtained through research of whether these destinations are still threatened, apart from media reports, about the influx of tourists. Of all the destinations that have been cited most in the media as risky, China is still under attack [46]. The data show that a strategy called the “zero covid” strategy was introduced in China. This means that there are still measures to limit movement, regardless of the elimination of all cases of infection in the country [81]. However, all the states that suffered the strongest impact of the pandemic are also facing other difficulties such as an economy that is slow to recover, climate change, the loss of technological giants in China, and the strained economic relations between China and the U.S. [82]. These are all factors that have a negative impact on the promotion of the tourist market, but the pandemic made a strong and crushing impact on these countries, and the aim of this research was to highlight the extent to which risk awareness is still represented among visitors in these countries [83]. Hypotheses are proposed on the basis of the mentioned similar literature and research problems (Figure 2):
H1: 
People are most afraid of COVID-19.
H2: 
All types of risks have a significant impact on the intention to travel, without the influence of external factors (media, experiences).
H3a: 
Media, as a mediator, significantly changes the strength of the influence of different types of risk on the intention to travel to “stigmatized” destinations.
H3b: 
Experience, as a mediator, significantly changes the strength of the influence of different types of risk on the intention to travel to “stigmatized” destinations.
H4a: 
Women are more afraid of COVID-19.
H4b: 
Men are more afraid of COVID-19.
H5a: 
Women are more determined to go to “stigmatized” destinations.
H5b: 
Men are more determined to go to “stigmatized” destinations.
H6a: 
The elderly are more determined to go to “stigmatized” destinations.
H6b: 
Younger people are more determined to go to “stigmatized” destinations.
H7a: 
The rich are more determined to go to “stigmatized” destinations.
H7b: 
The poor are more determined to go to “stigmatized” destinations.
H8a: 
The media have a significant influence on the choice of destination according to the proposed level of safety.
H8b: 
Experience has a significant influence on choosing a destination according tothe proposed level of safety.

3. Methodology

3.1. Sample and Procedure

The research was carried out from January to July 2022 at the Belgrade Nikola Tesla Airport in the Serbian capital of Belgrade. The total sample was 522 respondents. The required sample size was calculated using the G*power test [84]. Considering that there was a total of nine predictors (seven independent in the first step, and two inserted in the second step of the applied analysis) and one criterion, the required effect size was set at η2 = 0.15, with a statistical power of 0.95, and it was calculated that a sample size of 166 respondents could be appropriate for this research. The authors of the paper, together with 45 students of the School of Tourism and Hotel Management in Vrnjačka Banja, collected the sample by interviewing passengers while they were waiting to check in for their flight. Two main research questions (R.Q.1–2) were appointed:
R.Q.1: 
Which of the mentioned fears is the most represented when making a decision about traveling in the future to the “stigmatized” destinations?
R.Q.2: 
Do some of the demographic and external factors (media and experience) influence the choice of destination in terms of its proposed level of safety?
The sample was not large due to limited flights in this period, and due to the non-cooperation of passengers with the research team. The research was of a voluntary nature, carried out in the context of a pilot study, and it was assumed that this number of respondents could be representative because the research was carried out at the airport in reduced working conditions. Each question was asked very clearly and briefly verbally, in order to obtain a quick answer from the passengers, without causing them to refuse. Of the total number of respondents, 25.4% belonged to the age group of 18 to 30 years, followed by 41.9% over 50 years, and 32.7% from 31 to 50 years. When looking at the demographic structure of the respondents, there was not a big difference regarding the gender structure as 49.4% of men and 50.6% of women were interviewed. Looking at the educational structure, it can be seen from the results that 63.8% had a university degree, and 36.2% had lower education, which means high school. Other groups had no share.

3.2. Measures

The authors used the existing risk scale from Zaman et al. [10]. These authors established a seven-point risk scale using multiple data collection methods including interviews, focus groups, and survey questionnaires. In addition, the authors of this research followed up on the research they conducted in 2021 on the topic of perceived fear of the pandemic and financial risk in relation to the psychological typology of personality [1]. The adopted scale contains the following types of risk: human induced risk (total of three items: political instability α = 0.822, terrorism α = 0.753, crime α = 0.630); financial risk (total of three items: additional costs α = 0.797, higher prices than expected α = 0.761, influence of the financial situation in the destination α = 0.699); service quality risk (total of three items: quality of accommodation and food, hospitality α = 0.785, durability of tourist infrastructure α = 0.892); socio psychological risk (total of three items: influence of friends on the decision α = 0.803, influence of family α = 0.992, self-assessment α = 0.942); natural disaster risk (total of two items: natural disasters α = 0.789, traffic accidents α = 0.810); food safety risk (total of two items: quality of food α = 0.786, quantity of food α = 0.709); and COVID-19 risk (total of three items: fear of infection α = 0.805, fear of dying α = 0.929, fear of associated diseases α = 0.860). The values for two mediators were also obtained: media (total of two items: the media influence the choice of a tourist destination α = 0.760, the media influence the perception of fear when traveling α= 0.846) and experience (total of two items: experience influences the choice of destination α = 0.870, the experience affects the creation of fear when traveling in a crisis period α = 0.690). Only one criterion variable was called intention to travel (I intend to travel α = 0.600, I do not intend to travel α = 0.721). Cronbach’s alpha values are given in parentheses, more precisely, the coefficient used to measure the reliability of each item or scale is given. It can be seen that the reliability of each item in this research is of high value. In addition, the authors, studying the literature related to the research of the development of the destination during crisis situations, divided or ranked the destinations according to the proposed degree of security. The first rank was made up of domestic destinations because it considered that they were the safest to travel and stay in during a crisis period; the second rank was foreign destinations that were not marked with a negative image; and the third rank was destinations that were marked as isolated or risky, and even “stigmatized” destinations.

3.3. Data Analysis

Statistical processing of the collected data was carried out using the statistical program SPSS, version 26.00. According to Tabacnick and Fidell [85], all variables were normally distributed (Sk and Ku are in the range −1.5–1.5), and parametric statistical analysis was used. Descriptive statistical analysis was used to process the obtained data to determine the average score for each of the items as well as the standard deviation. In this way, each type of risk was assessed. A five-point Likert scale was used, and in some questions, only coded yes and no answers were used. For the answers to the question about the safety of the destination, the respondents had three answers on offer, more precisely, three coded ranks of destinations, listed in the section above. Exploratory factor analysis includes the reduction and condensation of a set of manifest variables into a smaller number of latent variables [86]. Then, with the help of Horn’s parallel method, the exact number of components that should be retained, which were obtained by exploratory factor analysis, was determined [87]. In this case, the exact number of seven factors to be retained was confirmed. A hierarchical regression analysis with mediation was performed in order to determine whether any of the predictors, in this case, risk types, can have a statistically significant impact on the decision to visit destinations that were considered high risk during the pandemic. More precisely, hierarchical analysis served as a statistical test of the effect of the mediator variables [88]. Experience and the media were taken as mediators, to see whether they significantly influenced the decision to travel to once very risky destinations due to the pandemic. In addition, the authors aimed to determine the differences in the perception of risk types in relation to the gender structure by means of a discriminative canonical analysis [89]. Canonical discrimination analysis procedures are primarily intended to examine the existence of differences between groups (i.e., of two or more experimental or real populations on a set of quantitative traits, and analyzing the nature of the structure or composition of those traits underlying the existing differences). These procedures basically boil down to transforming quantitative multivariate data in order to more economically and clearly see the differences between populations defined by the categories of some qualitative feature [90]. The authors used ordinal logistic regression analysis [56], coding the destinations according to the level of safety in three ranks or categories. Demographic factors and external factors (media and experience) were used as predictors in this type of regression. A graphical scheme of the research method can be seen in Figure 3.

4. Results and Discussion

Taking into account the goal of the research, and in order to obtain answers to key questions and confirm hypotheses, a combined method of qualitative and quantitative analyses was used. Combined research involves the use of primary and secondary data, in order to observe existing relationships between variables.

4.1. Perceived Types of Risk and Their Impact on the Intention to Travel to Risky or Stigmatized Destinations

Table 1 gives the values of the arithmetic means for each type of risk as well as the values of the standard deviation. It can be seen that the highest average rating was given to financial risk, with a rating of m = 2.99, and socio-psychological risk of m = 2.67. The lowest value of the arithmetic mean was carried by the human induced risk m = 1.98. Then, the service quality risk was assessed with an average score of m = 2.19. The natural disaster risk was assessed with an average score of m = 2.17, while the food safety risk was assessed with m = 2.13. Regarding the COVID-19 risk, it had an average score of 2.06. Table 1 also shows the results of the exploratory factor analysis, which was confirmed by the mathematical Horn’s parallel method. It was observed that a total of exactly seven factors were obtained from all the variables in the research. The total percentage of explained variance was 44,5%, while the first factor had the highest saturation in the value of 9.92%. The first factor in the largest percentage explains the common variance of the set of manifest variables, while the other factors have a lower percentage saturation.
Of the total number of respondents, 36.5% said that they would choose a domestic destination, 35.1% a foreign destination, while 28.4% said that they would like to travel to a stigmatized destination. Table 1 provides data that negate the initial hypothesis H1, that people are most afraid of COVID-19. In this research, the results show that it was insignificant, but still noticeable, that the majority of people perceived the fear of financial risk and socio-psychological risks more strongly than the fear of COVID-19. In this table, it can be seen as a partial answer to research question R.Q.1, which of the fears had the greatest influence on the decision to travel to stigmatized destinations.

4.2. The Degree of Influence of Different Types of Risk on the Intention to Travel

Table 2 provides an insight into the results of the multiple hierarchical regression analysis, which shows the procedure before the introduction of the mediator (Step 1), and the procedure and results after the introduction of the mediator (Step 2). The results of the regression analysis show that a large percentage of the variance can be explained by all seven predictors, in both steps of the analysis, before and after the introduction of mediator variables, where unchanged statistical significance was observed (Step 1: R2 = 0.0954, F= 1502.143, sig = 0.00; Step 2: R2 = 0.956, F = 19.671, p = 0.00).
The R2 coefficient indicates how much percent of the variance can be explained. These results indicate that the model fits the data. The contribution of all seven predictors in predicting the criteria was significant, more precisely, each type of risk showed a statistical significance in predicting the decision to visit the destinations that were most affected by the pandemic. Table 2 shows the partial contribution data for each of the risks (b) as well as the correlation of how much they are related to the predictor (ß). The largest partial contribution was shown by the food safety risk (b = 0.155) and financial risk (b = 0.148), followed immediately by the natural disaster risk (b = 0.139) and COVID-19 risk (b = 0.149). It was shown that the risk of a pandemic from the given risk scale did not show the greatest contribution in influencing the predictor. However, adding mediators that were considered to be able to influence the perception of risk among travelers increased the partial contribution of pandemic risk (b = 0.146), and food safety risk (b = 0.153) was again in first place. In this case, experience and the media increased the people’s fear of going to certain destinations, more than financial fear. Given that the changes were insignificant or very small, and that each predictor had a partial contribution, which was partial mediation. Both mediators (experience and media) had statistical significance, but did not provide full mediation, because even before their introduction, all predictors significantly influenced the criterion variable.
After the obtained results of the multiple hierarchical analysis, hypothesis H2, that all types of risks have a significant impact on the intention to travel (without the influence of external factors), was confirmed. However, H3a and H3b were rejected, because the media and experience (although significant in predicting the intention to travel) did not significantly change the strength of the influence of all types of risks on the intention to travel to stigmatized destinations. It was determined that it was a partial mediation, not a full mediation. Table 2 also shows the complete answer to research question R.Q.1, where it can be seen that each of the fears had an impact on the decision to travel to stigmatized destinations.

4.3. The Influence of Sociodemographic Factors (Gender) on the Intention to Travel during a Crisis Situation

Table 3 gives the results of the discriminant canonical analysis. The authors aimed to determine the existence of differences between groups (i.e., two populations on a set of quantitative characteristics). The value of Wilks’ Lambda was 0.943, which shows the statistical significance and that there were differences in relation to the composition. The canonical correlation value was 0.238, which means that 8.41% of the variance can be explained by this model, which is a very good value.
Table 4 shows that men had the greatest fear of human induced risk (−0.250), service quality risk (−0.209), natural disaster risk (−0.161), and COVID-19 risk (−0.135) while women were afraid of socio psychological risk (0.674), financial risk (0.514), and food safety risk (0.030).
The probability that the respondent would belong to a group was 56.5%. The exact classification is shown in Table 4, where it can be seen that 58.5% of men and 41.5% of women belonged to these groups. How accurate the classification is can be shown by the fact that there was a 56.5% chance or probability that the respondent would belong to one of the given groups. Hypothesis H4a, that women are more afraid of COVID-19, was rejected, while hypothesis H4b, that fear of the pandemic is more pronounced in men, was confirmed. There were statistically significant differences in relation to composition, more precisely, there was a difference between the groups, that is, two populations on a set of quantitative characteristics. Simply put, there is a difference in the perception of types of risk in relation to the gender structure of the respondents.

4.4. Choosing a Destination According to the Rank of Security, in Relation to Sociodemographic and External Factors (Media and Experience)

Table 5 provides insight into the results obtained by ordinal regression analysis, which was used to determine the choice of destination, with the fact that at the very beginning, the destinations were coded into three categories according to the level of safety. Socio-demographic factors that served as predictors for the possible selection of one of the three coded destinations were gender, age, and financial status, while the media and experience were used as external factors for the analysis.
The general indicators of model fit showed that it fit well with the data, where the following values were obtained: Chi-square- 30.148, p = 0.00; GOF (goodness-of-fit) with values 0.762, then Pseudo R2: Naglekerke 0.87. Destination categories were coded according to the level of security: (1) domestic destinations, (2) foreign destinations (destinations without a negative image), and (3) stigmatized destinations. The results showed that the media and experience had a statistical significance in the selection of the three coded destinations. Respondents who were influenced by the media and experience were more decisive in choosing the domestic destination as a safer type of vacation (media E = −0.619; experience E = −0.466). These results confirmed hypotheses H8a and H8b. Considering the data obtained by ordinal logistic regression analysis, men chose safer destinations coded under category 1, while women showed the opposite (H5a was confirmed and H5b rejected). Regarding age, it was observed that as a predictor, it plays an important role in choosing a destination, therefore, it was observed that all categories were more susceptible to choosing safer destinations. The older they were, the more likely they were to choose a safer destination (H6a rejected). Except for the category from 18 to 30 years old (E = 0.857), where the choice of destination was the opposite, more precisely in that category, they were ready to go to isolated or less safe destinations (H6 was confirmed). Material status was not a statistically significant predictor, so the hypotheses H7a and H7b were rejected. These data provide an answer to the second research question (R.Q.2) of which of the demographic factors influence the choice of destination according to the proposed level of safety.

5. Discussion

Many studies that have been conducted have provided different results regarding the types of risks and their strength in the intention to travel. Rittichainuwat and Chakraborty [87] emphasized the stronger impact of health risks than the impact of terrorism. Law [88] also highlighted the stronger impact of human risks compared to all of the other perceived types of risk. Some studies have highlighted the strong influence of geopolitical risk on the tourism sector [91]. However, all of the research that has been conducted thus far only talks about the types of risks and their impact on the visitors’ decisions [92,93]. Some of them have highlighted risky destinations that have been marked with that label for many years due to economic instability or socio-political disharmony [94]. There has been almost no research focusing on decisions to travel to risky destinations after severe and unforeseen sudden crises or pandemics, especially after COVID-19 [95]. The main goal of this research was to determine which types of risk have the greatest influence on the visitors’ intentions to go to countries that are somehow marked as risky after the pandemic. The results of the research show that financial and socio-psychological risk have a stronger influence on visitors’ decisions than the risk of a pandemic.
Additionally, the research obtained data that indicate that each of the mentioned types of risk has an impact on making a decision about traveling to stigmatized destinations. It has been shown that the risk of a pandemic is not the only one and does not have the strongest negative effect on the number of consumers. By introducing factors that influence decision-making such as the media and experience, the situation remained unchanged. They did not have a decisive influence, nor did they increase the effect of the risk, nor did they reduce it. Similar investigations were conducted by Fuchs and Reichel [89], and Koji pointed out in their research on the territory of Israel, following the statistics of visits, that experience as well as psychological factors had the greatest influence on the intention to travel. Lepp and Gibson [45] claimed that experience was the main indicator for decision-making during some crisis situations. Giusti and Raya [90] believed that the strongest perception was human risks, which include terrorism and crime. Reisinger and Mavondo [56], based on research, believed that risks such as health, terrorism, criminality, and political instability were the strongest in their influence on the intention to travel. Chew and Jahari [92], in their research on the value of different types of risk, emphasized health as the most influential.
The influence of sociodemographic factors on risk perception was investigated by Sebra et al. [28]. Their results indicate the existence of heterogeneity in the tourist population in terms of risk perception and intention to travel. Previous research has shown that women are more afraid of traveling to destinations that are marked as risky, and showed more anxiety than men, and they feared for their safety from terrorism and socio-cultural risks [76]. In this research, the results indicated that men were most afraid of the risks caused by the human factor, the risk of not being satisfied with the required quality of services, the risk caused by natural disasters, and the risk of COVID-19. In contrast to the results obtained by male respondents, it was found that the greatest fear of financial risk, socio-psychological risk, and food safety risk was represented among women.
Yang et al. [96] investigated the tourists’ risk perception toward Malaysia as a risky destination. They examined the effects of travel experience, prior risk experience, travel motivation, newspaper preference, gender, age, and nationality on the tourists’ risk perception. They showed that age, gender, and nationality significantly influenced the choice of a safer destination. Kvítková et al. [93] indicated that domestic tourism is one of the safest types of travel. Similar results were obtained in this research, where it was found that men as well as the older category of pollution chose safer destinations according to the predetermined level of safety. Material status did not prove to be a significant factor in choosing a destination according to the degree of security.

6. Concluding Remarks

Many scientific papers have already been written and a lot of research has been conducted on the topic of the negative impact of COVID-19 on all sectors of the economy including tourism. The pandemic caused the most damage to tourism, but not only directly but also in indirect ways, creating fear or prejudice among travelers regarding the destinations where it had the strongest impact and left the biggest consequences. There was even a study in which the authors found out that at the beginning of the pandemic, tourists were even afraid of socializing and having close encounters with Chinese residents [97,98], but women rated the image of China better than men [62]. However, there is little research on the topic of the fear of going to so-called “stigmatized” destinations, which are marked either by bad experiences or through social networks and the media. Under that term, isolated destinations can be counted primarily as the countries of China and Italy, which are synonymous with COVID-19. Their influence on the perception of fear and risk among travelers has not yet been investigated, especially whether the psychological aspect of the division of personality typology is also included. Of course, the perception of risk when making travel decisions is a subjective feeling, but the literature on it is very scarce. It is certain that China, as the country with the most tragic consequences of the pandemic, is facing other problems related to tourism, but also the entire economy. Some of them are the decline in the economy, the departure of large technological giants, the fall in the Chinese currency, social instability and poverty, climate change, etc. Many other countries that were also under strong attack by the invisible enemy of COVID-19 experienced the same fate, but according to media reports, their return to the tourist market is observed every day. The data provided in the manuscript indicate that China is still facing restrictive measures even after the pandemic, regardless of the fact that the epidemic is declining and the number of infected people is decreasing. It is not officially recorded anywhere that these countries are called “stigmatized” or “risky”, but somehow in society, this term has inevitably been imposed. The goal of the research was to determine the extent to which the risk of a pandemic continues to act as a brake in the mind of visitors in making decisions to travel to these countries. According to the available literature, the authors have tried to reach appropriate results related to the perception of different types of risk among passengers through a pilot study. The results indicated that the risk of a pandemic was not the strongest factor in making decisions for traveling to marked destinations. Additionally, it was found that men were more afraid of human induced risk, service quality risk, natural disasters, and COVID-19 risk, and they chose safer destinations. In the case of women, it turned out that they had a pronounced fear of financial risk, socio-psychological risk, and food safety risk. Regarding the demographic age structure, older respondents and those under the influence of external factors decided on safer destinations, while financial status did not play a significant role in predicting the choice of destination.
The innovativeness of this research was primarily reflected in the accentuation of research on visiting destinations that are unfairly marked by the tragedy of the invisible enemy of COVID-19. There are destinations that fall into the category of risky for tourists, but so far the topic of visiting destinations marked by the COVID-19 pandemic as high risk has not been addressed, even after the pandemic has passed. Additionally, the specificity of the research was reflected in the obtained results, where it might have been expected that there would be different results and that, as usual, women would be more afraid of the pandemic than men. Furthermore, it has been proven that material status did not play a role in determining the strength and type of fear among tourist consumers. In some normal circumstances and environment, material status has a significant contribution in consumer decision-making. COVID-19 certainly brought different and more serious consequences to the society of the 21st century, but also in the domain of access to research and areas of research.

Limitations and Suggestions for Future Research

There were difficulties primarily due to the problems faced by airlines in the post-COVID period, namely the lack of manpower, flight cancellations, long waits for check-in, nervousness, and non-cooperation with investigators. The passengers were quite reluctant to cooperate with the researchers due to the reasons given, which caused nervousness, impatience, and even panic reactions. Limiting circumstances include the travelers’ fears of giving answers because the post-COVID period is still a taboo topic. The respondents did not even want to talk about the topic of the pandemic in either a positive or negative context, and especially not about what the consequences will be in the future. The older population in the research stands out as a group that refuses to cooperate on this issue.
The negative effects of the pandemic will only be fully realized in the coming period [83]; if there are no new waves of infection, the consequences of the pandemic on tourism will only be revealed [84]. The more information is available to travelers through social media and the media, the more subjective fear and prejudice will be created among travelers [85,86,99]. The importance of the research is reflected in the fact that, although only the pilot research, the results reached by the authors will be able to be used for larger and more significant research, theory development as well as application in practice, not only in the region but also wider. There is a lack of literature related to the implications of the pandemic on the travelers’ decisions to visit destinations that were the hardest hit by the pandemic. These are destinations that can be said to be marked as isolated or stigmatized by the media or personal experience and subjective perception of the travelers.
Furthermore, these data can be the starting point to indicate a very interesting direction of research, which is preconceptions about destinations after the pandemic and general unforeseen crisis situations in tourism. For now, it is a topic that does not have enough research, so this research is a good basis for further investigation in the future. Additionally, based on this sample, it will be possible to predict or at least know the possible direction of research into personality types and their reactions to different types of risk. The passengers’ risk perception can answer many questions regarding passenger behavior in the future if a similar crisis situation occurs. With the help of such and similar research, in the future, it will be possible to predict or assume the behavior of travelers, in the sense of whether certain destinations will make a quick return to the tourist market or will be marked in the future as undesirable to visit.

Author Contributions

Conceptualization, T.G., I.B. and M.D.P.; Methodology, T.G., I.B. and D.V.; Software, D.S.; Validation, D.C., M.Z. and D.S.; Formal analysis, A.S. and Ž.A.; Investigation, T.G., I.B., M.D.P. and D.V.; Resources, M.O. and A.O.; Data curation, I.S.; Writing—original draft preparation, T.G., M.D.P. and I.B.; Writing—review and editing, J.M.J.; Visualization, M.G.; Supervision, D.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The research will be part of the project “The impact of the pandemic caused by the COVID-19 virus on increasing income in rural tourism” (01.07.2022 to 30.05.2023), based on the Agreement on the Regulation of Personal Rights and Obligations Regarding the Use of Incentives for Improving the System of Creating and Transferring Knowledge through Development of technical-technological, applied, developmental and innovative projects in secondary agriculture and rural development in 2022, concluded between the Ministry of Agriculture, Forestry, and Water Management, the Administration for Agrarian Payments and the Faculty of Hotel Management and Tourism in Vrnjačka Banja, University of Kragujevac.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 15530 g001 550
Figure 1. The world map of countries with number of confirmed COVID-19 cases (2020). Source: (https://www.nationsonline.org/oneworld/map/New-Coronavirus-2019-nCoV-world-map.htm, accessed on 17 September 2022).
Figure 1. The world map of countries with number of confirmed COVID-19 cases (2020). Source: (https://www.nationsonline.org/oneworld/map/New-Coronavirus-2019-nCoV-world-map.htm, accessed on 17 September 2022).
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Figure 2. Proposed model of research with the defined hypotheses.
Figure 2. Proposed model of research with the defined hypotheses.
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Figure 3. A graphical scheme of the research flow.
Figure 3. A graphical scheme of the research flow.
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Table
Table 1. Results of descriptive and exploratory factor analysis.
Table 1. Results of descriptive and exploratory factor analysis.
FactorsmsdTotal% of VarianceCumulative %
Human induced risk1.981.1693.1889.9249.924
Financial risk2.991.4222.2186.93216.896
Service quality risk2.191.3392.1956.86023.756
Socio psychological risk2.671.4121.8065.64229.398
Natural disaster risk2.171.3431.7845.57634.974
Food safety risk2.131.3461.5594.87239.846
COVID-19 risk2.061.2911.5194.74844.594
Domestic destinationsForeign destinationsStigmatized destinations
36.5%35.1%28.4%
Note: m—arithmetic means, sd—standard deviation.
Table
Table 2. Impact of the perceived risks on travel intention (multiple hierarchical analysis with mediation).
Table 2. Impact of the perceived risks on travel intention (multiple hierarchical analysis with mediation).
STEP 1
BBetatp
Human induced risk0.1200.15414.7770.001
Financial risk0.1480.23416.9080.000
Service quality risk0.1200.17713.4570.000
Socio psychological risk0.1270.19814.6230.000
Natural disaster risk0.1390.20516.7620.000
Food safety risk0.1550.23017.0060.000
COVID-19 risk0.1490.21118.0200.000
R2 = 0.954, F = 1502.143, sig = 0.000
STEP 2
BBetatp
Human induced risk0.1210.15615.2220.000
Financial risk0.1390.21815.5990.000
Service quality risk0.1180.17413.4950.000
Socio psychological risk0.1200.18713.8500.000
Natural disaster risk0.1390.20416.9730.000
Food safety risk0.1530.22717.1040.000
COVID-19 risk0.1460.20818.0050.000
Media0.0340.0504.4350.000
Experience0.1430.2038.0050.000
R2 = 0.956, F = 19.671, p = 0.000
Note: Dependent variable: intention to travel to “isolated, stigmatized or marked”. destinations, mediators: media, experience.
Table
Table 3. General indicators of model fit with data.
Table 3. General indicators of model fit with data.
EigenvalueWilks’ LambdaChi-SquaredfSig.Canonical Correlation
0.0600.94330.22870.0000.238
Table
Table 4. Indicators of different perceptions of risk in relation to the gender structure of the respondents (canonical discriminant analysis).
Table 4. Indicators of different perceptions of risk in relation to the gender structure of the respondents (canonical discriminant analysis).
Standardized Canonical Discriminant Function CoefficientsFunction 1
Socio psychological risk0.674
Financial risk0.514
Human induced risk−0.250
Service quality risk−0.209
Natural disaster risk−0.161
COVID-19 risk−0.135
Food safety risk0.030
Functions at Group Centroids
Male −0.270 Female 0.223
Classification Results—Predicted Group Membership
Male 58.5% Female 41.5%
56.5% of the original grouped cases correctly classified
Table
Table 5. Results of ordinal logistic regression analysis.
Table 5. Results of ordinal logistic regression analysis.
EstimateStd. ErrorWalddfSig.
PredictorsMedia−0.6190.6091.03510.009
Experience−0.4660.6030.59710.040
GenderMale−0.4110.2452.81810.003
Female0 a 0
Age category18–300.8570.26710.30910.001
31–50−0.6000.2615.27410.022
51+−0.3890.4858.72310.000
Material status300–500−0.7350.6101.45410.228
500–1000 Euro0.7290.2906.33110.082
1000+0.1840.4434.34310.068
Link function: Logit. a. This parameter is set to zero because it is assumed to be the opposite of the first category. Destination types are coded into three categories according to the level of security: 1. Domestic destination 2. Foreign destination (without negative image). 3. Stigmatized destination.
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Gajić, T.; Vukolić, D.; Petrović, M.D.; Blešić, I.; Zrnić, M.; Cvijanović, D.; Sekulić, D.; Spasojević, A.; Obradović, M.; Obradović, A.; et al. Risks in the Role of Co-Creating the Future of Tourism in “Stigmatized” Destinations. Sustainability 2022, 14, 15530. https://doi.org/10.3390/su142315530

AMA Style

Gajić T, Vukolić D, Petrović MD, Blešić I, Zrnić M, Cvijanović D, Sekulić D, Spasojević A, Obradović M, Obradović A, et al. Risks in the Role of Co-Creating the Future of Tourism in “Stigmatized” Destinations. Sustainability. 2022; 14(23):15530. https://doi.org/10.3390/su142315530

Chicago/Turabian Style

Gajić, Tamara, Dragan Vukolić, Marko D. Petrović, Ivana Blešić, Miloš Zrnić, Drago Cvijanović, Dejan Sekulić, Ana Spasojević, Maja Obradović, Ana Obradović, and et al. 2022. "Risks in the Role of Co-Creating the Future of Tourism in “Stigmatized” Destinations" Sustainability 14, no. 23: 15530. https://doi.org/10.3390/su142315530

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