34Original Scientific Paper UDC: 338.488.2:640.432(497.11)
159.942.53-057.67 005.332:[616.98:578.834 doi: 10.5937/menhottur2201067G
The impact of fear of COVID-19 infection on consumers' intention to visit restaurants
Tamara Gajic1*, Mirjana Penic2, Dragan Vukolic3
1 Geographical Institute "Jovan Cvijic", SASA, Belgrade, Serbia; South Ural State University, Institute of Sports, Tourism and Service, Chelyabinsk, Russia
2 University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Novi Sad, Serbia
3 University of Business Studies, Faculty of Tourism and Hotel Management, Banja Luka, Bosnia and Herzegovina
Abstract: The problem of excessive tourism has overnight become an ideology and a part of the past. With the appearance of the COVID-19 pandemic, the flow of tourist movements was abruptly interrupted, and thus the visits to restaurants. The aim of the research was to determine whether the fear of the users of the pandemic infection affects the intention to visit restaurants. The total number of respondents was 508, in 27 restaurants in the Republic of Serbia. The authors used exploratory factor analysis (EFA) and multiple regression analysis with mediation for data processing. The research concluded that the perceived fears of the respondents may influence the decision to visit restaurants. The importance of research is reflected in the application of results in theory and practice, in order to facilitate business during the pandemic.
Keywords: restaurants, consumers, the Republic of Serbia, COVID-19 JEL classification: I12, J28, L83
Uticaj straha od infekcije COVID-19 na nameru korisnika da posete restorane
Sazetak: Problem prekomernog turizma preko noci postao je ideologija i deo proslosti. Pojavom pandemije COVID-19, naglo je prekinut tok turistickih kretanja, a samim tim i posete restoranima. Cilj istrazivanja bio je utvrditi da li strah korisnika od pandemijske infekcije utice na nameru da posete restorane. Ukupan broj ispitanika iznosio je 508, u 27 restorana u Republici Srbiji. Autori su za obradu podataka koristili eksplorativnu faktorsku analizu (exploratory factor analysis - EFA) i visestruku regresionu analizu sa medijacijom. Istrazivanjem se doslo do zakljucka da percipirani strahovi ispitanika mogu da uticu na odluku o poseti restoranima. Znacaj istrazivanja se ogleda u primeni rezultata u teoriji i praksi, kako bi se olaksalo poslovanje tokom pandemije.
Kljucne reci: restorani, korisnici, Republika Srbija, COVID-19 JEL klasifikacija: I12, J28, L83
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ^http ://creativecommons.org/licenses/by/4. 0/)_
1. Introduction
The pandemic COVID-19, which has lasted for more than two years, has completely disrupted all sectors of the economy, including the tourism and hospitality sector. Overnight, rigorous measures were adopted, which referred to the complete closure of facilities, up to limited working hours. In one period, protection measures included staying in restaurants until 8 pm, after which it was not possible to stay if the consumer does not have a COVID-19 certificate of vaccination. Such a system of work has completely destabilized the work of catering companies, so most of them closed their facilities and entered the market with a different way of doing business. That way was simple, with less cost, less labor, but the only way to survive in the market. Since the beginning of the pandemic in Serbia, the purchase of food over the internet has increased by 200%, clothing by 100%, and technical devices and computer equipment by 50% (Ministry of Trade, Tourism and Telecommunications, 2022). World companies in the field of tourism and hospitality, and even airlines, are facing major problems. These problems are mainly related to job losses, increased costs, and even company closures. A pandemic, as well as other crisis situations, creates certain fears among consumers. What is the perception in the minds of consumers is very difficult to determine, because consumers must be observed through the prism of different psychological groups. Everyone reacts differently to the type of fear, and everyone has a different duration of fear. According to similar research, the authors aimed to discover the strength of the pandemic fears among consumers of restaurant services, and whether and to what extent there is a correlation between them, and the impact on visits to restaurants during the pandemic. The factor analysis of the issues is divided into four factors, two of which relate to fear of the pandemic (F1) and fear of staying in restaurants (F2), while the other two relate to protection and security measures implemented in restaurants (F3) and the intention to visit restaurants during the pandemic (F4). With the help of multiple regression analysis with mediation, they determined the existence of a significant impact on the intention of users to visit restaurants during the pandemic. It turned out to be a partial mediation, because by introducing the variable Protection and Security Measure, the significance of the first fear decreases, while the value of the second type of fear remains the same.
The importance of research will leave effects in the social, economic and scientific spheres, when observing consumer behavior and their impact on the business of certain industries. In this case, the results will significantly contribute to broader research, where it will be possible to predict consumer behavior in crisis situations, and accordingly take strategic measures to prevent large economic losses and continue working in these circumstances. After the COVID-19 pandemic, consumers will also, in a way, be prepared and already familiar with behavior if a new crisis period arises. Empirical results can contribute to the development of security measures in tourism services and the design of effective actions for the renewal of tourism and hospitality.
2. Literature review
2.1. Some of the negative effects of the pandemic on the economy
In times of crisis, there are structural changes in all economic sectors, including the behavior of consumers of services. The COVID-19 pandemic had the strongest impact on business, but also on the psyche and behavior of consumers (Assaf et al., 2021; Bozovic et al., 2021). Most schools and higher education institutions worked remotely, cafes, bars, pubs and shopping malls were closed. Only pharmacies, food stores, and pumps operated (Gajic et al., 2021a). Statistics show that 40% of hotels in Barcelona are closed, and that instead of the average 60.000 guests a day, only 13.000 tourists stayed in city hotels at the beginning of the pandemic,
and that the hotel industry has lost 2.7 trillion euros since the epidemic (Gajic et al., 2021b). One of the draconian epidemiological measures against the spread of COVID-19, was introduced in early November 2020 and most hotels are officially defined as quarantine hotels. Global revenue from international tourism in 2019 amounted to 1.47 trillion dollars, and in the following, pandemic year, it dropped by 63 percent (Kock et al., 2020).
In the Republic of Serbia, when the pandemic began, there were no recorded reservations in hotels, the level of health procedures increased, public spaces were closed, demand was disrupted and reduced, operating costs increased, and borders were closed (Bradic-Martinovic & Kovacevic, 2020). Considering the number of employees, Republic of Serbia felt the impact through the production of durable goods. About 19 percent of Serbia's workforce is employed in the production of durable goods (Radic et al., 2021). The crisis caused by COVID-19 affected the Serbian economy primarily through the processing industry. In the Republic of Serbia, service activities and smaller companies have experienced very severe consequences (Blesic et al., 2021). Some sectors, such as the hospitality industry, immediately felt the negative consequences of dismissing employees or sending them on forced leave. Tourist traffic in Serbia in June 2020 is only half lower compared to the same month in June 2019. There is still a huge decline, but it is much better than in May with a turnover of only 17% compared to the same period last year (Ministry of Trade, Tourism and Telecommunications, 2022). This increase in traffic is primarily a consequence of domestic tourists, not foreign ones, which is understandable given the existing travel restrictions. The number of realized nights of foreign tourists is only 15% of the level from 2018, and the number of nights spent by domestic visitors is 82% (Ministry of Trade, Tourism and Telecommunications, 2022).
The cities of Belgrade and Novi Sad are the most affected, which means an increase in traffic in the mountains and spas. The number of tourist nights in Belgrade is 21% of the level from June last year, in Novi Sad 27%, while in mountainous places 78%, and in spas 80%. Vranjska Banja, Palic and Stara planina even show a significant increase in the number of tourist nights compared to 2018 (Ministry of Trade, Tourism and Telecommunications, 2022). Estimates of many organizations show that the emergence and spread of the pandemic will result in a drop in international tourist arrivals by 20-30% this year, which is a loss of between 30 and 50 billion dollars (27.5 to 46 billion euros). In Europe, for example, due to the pandemic, airlines will make a loss of 76 billion dollars (70 billion euros) annually (OECD, 2022). The survival of some 75 million tourism-related jobs worldwide is in question (Gajic et al., 2021b).
Figure 1 provides an insight into the strength of the pandemic impact on local expenditures, by areas of the economy. The volume of travel in Europe is still far from the period before the pandemic, which is not expected to be surpassed by 2024. It has caused significant damage to economies around the world. Demand was reduced by restrictions on movement, and supply-side shocks were due to labor supply constraints and difficulties in procuring material inputs.
Figure 1: COVID-19 pressure on subnational expenditures, by area
Social services
Social benefits
Support for SMEs and the self-employed
Public health expenditure
Education (e.g. school closures,
remote teaching) nformatlon and communication technologies
Adapting local public transport Adapting administrative services Public order and safety
100%
■ High pressure ■ Moderate pressure ■ Mo pressure Don't know or no answer
Source: OECD (2022)
Figure 2 shows revenue in European hotels during the pandemic. A drastic drop in the capacity of the rooms from March 2020 is shown.
Figure 2: European Hotels - Rooms Revenue (2019-2020)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Source: Statista - Statistic Portal for Market Data (2022)
Figure 3 provides insight into the assessment of the evolution of the hotel value range in Europe, for the period 2019-2025. Three scenarios are presented, with a starting point in 2019. The hotel industry is among the hardest hit. Catering will also see subtle and significant changes in the post-pandemic era. Some are already apparent today (Yoo, 2020). Tourism is completely devastated, and is known as an activity that depends on human labor (Roxas et al., 2022).
Figure 3: The range of economic realization of hotels (2019-2025) - — - Base Line Best Case Most Likely — Worst Case
€330,000
€310,000 ___________
E €290,000 f---------
o €270,000 V ------
| €250,000 >\
2 €230,000 \ V^ y/
> €210,000 €190,000 €170,000
2019 2020 2021 2022 2023 2024 2025 Source: Statista - Statistic Portal for Market Data (2022)
2.2. Behavior of tourists during the pandemic
Godovykh and Tasci (2020), explored how loyal visitors will remain as before the pandemic, and how the emotional experience affects loyalty. The perceived risk has implications for the intention to travel and visit catering facilities in the context of the COVID-19 pandemic (Sánchez-Cañizares et al., 2021). The main factors that affect the creation of an image of health risk during travel are divided into: affective, cognitive, individual, and contextual. The influence of these factors on the tourist's decision to travel is pronounced (Godovykh et al., 2021; Krejic & Milicevic, 2021). Agag et al. (2020), investigate the willingness of consumers to pay more for green destinations in some specific crisis periods. However, despite everything, no factor has shown that it has an impact on the willingness of consumers to pay more during the pandemic. Bae and Chang (2020) examine the effect of COVID-19 risk perception on tourism behavior intent. They came to the conclusion that attitude influences the relationship between the affective vision of risk and consumer intention in making a decision, and that the relationship between cognitive vision and consumer intention is determined by subjective factors. Chew and Jahari (2014), examined the effects of perceived risks on the image of the destination. They found that affective and cognitive perceptions of a particular journey are affected by two risks: socio-psychological and financial. Consumer loyalty was affected by perceived physical risk. Perceived and possible risks during the pandemic negatively affect the attitude of consumers towards food and repair in catering facilities, and the perceived benefits positively affect the attitude (Choi et al., 2013). Floyd et al. (2004), examined the effect of the crisis situation on travel decisions after 11 September 2001. The study revealed that people were really scared in the next year, when they wanted to travel. They feared for security, then financial resources. If there is a dose of ignorance about the existing and potential health risk, dangerous consequences can occur when combined with low perceived risk (Hartjes et al., 2009). Kim (2020), investigated an individual's perception of the danger and uncertainty of the COVID-19 virus in the Jordan area. Fear has been found to have a major impact on tourist movements and visits to accommodation and food facilities. Fotiadis et al. (2021), claim that the decline in tourist arrivals and visits to catering facilities can range between 30.8% and 76.3%. Tourism is particularly vulnerable to pandemic measures due to limited mobility and social distancing (Gossling et al., 2020). COVID-19 pandemic, as well
71
as isolations, have a great impact on the socio-economic, but also on the mental health of people and their decision-making (Poudel & Subedi, 2020). Polas et al. (2019), indicate the lack of a link between tourism health risk and tourism decision-making. It has been noticed that the capacities and ability to manage tourism and hotel and restaurant facilities in resolving complex and critical situations are limited (Santana, 2003). In the wake of the spread of the pandemic news, consumer fears and influence on decision-making begin (Ugur & Akbiyik, 2020). Zhang et al. (2020, p. 1), show that tourists have a strong negative emotional reaction to unfavorable prices related to tourism and hospitality in response to the high (compared to low) threat of infectious diseases. Moreover, risk aversion acts as a basic mechanism that triggers this effect: tourists are afraid of being hit, which further influences negative travel decisions. Alan et al. (2006), highlight the negative impact of SARS pandemic on restaurant visits in Hong Kong, and the very difficult recovery and return of consumer confidence. Bali et al. (2016), argue in their research entitled Long Shadow of Fear in an Epidemic: The Pheronomic Effects of Ebola on the Private Sector in Nigeria, that no business has been immune to the effects of a pandemic. Based on the analysis of the problem and the given literature, the following hypotheses were set:
H1: Fear of a pandemic affects on intention to visit restaurants during the pandemic. H2: There is a correlation between factors offear of the pandemic.
3. Methodology
The research was conducted in the period from June to December 2021, on a total sample of 508 participants in the research, in 27 restaurants in the Republic of Serbia. Of the total number of respondents, 62.4% are men, while 37.6% are women. When looking at the age structure, the situation is as follows: 24.9% of people aged 20 to 35, then 48.1% aged 36 to 55, and 27% of respondents over 56. The highest percentage is 56.7% with a university degree, followed by 32% with a high school diploma and only 11.3% with a lower secondary school education. A total of 45% have incomes of 200 to 500 euros, followed by 32.1% of 500 to 1,000 euros and 22.9% with a personal income of over 1,000 euros. The obtained data were processed by software SPSS 26.00, and AMOS SPSS version 21. Exploratory factor analysis (EFA) was used for data processing to determine the number of factors or group all items into the appropriate number of factors and confirmed the reliability of the questionnaire. All these items are grouped into four factors. The following factors are named F1- fear of a pandemic, F2 - fear of staying in restaurants during pandemic, F3 - security and protection measures in restaurants, F4 - intention to visit restaurants during pandemic. Issues belonging to the factor F1: I'm afraid of the Covid-19 pandemic, The information in the media upsets me, I'm afraid of transmitting the virus through food and drink, The tought of getting sick from COVID-19 is terrible, Generally have a hard time being sick, I'm afraid to be in a space where the distance is less than 2 meters. The following variables belonged to the F2 factor: I am afraid to stay in restaurants during the pandemic, I'm afraid of spreading the virus with other visitors, I'm afraid of infection generally in restaurants, Fear of staying in the open part of the restaurant. The F3 factor consists of the following variables: Inventory and equipment are disinfected, Masks are used as protection, The distance between the visitors is applied, Disinfection is carried out regularly, Long stay pollutes the space and spreads the virus, Safety standards are complete. Criterion variable or Factor 4 includes questions: I intend to visit restaurants during the pandemic, I intend to visit restaurants with a vaccination certificate, I intend to visit open areas of the restaurant, I intend to visit restaurants with limited time. A measure of the reliability of the scale was also determined with the help of Cronbach's alpha. The value of Cronbach's alpha (a) for the first two factors F1 and F2 is a = 0.854, while for F3 and F4 a = 0.858. A high level of reliability of the questionnaire is noticed, which is a condition for approaching each analysis. Multiple regression analysis was used to determine the influence of factors or
predictors on restaurant visits during a pandemic. The mediator variable Security and protection measures has been introduced, in order to see whether fears significantly influence the intention to visit restaurants through the mediator variable. The task of multiple linear regression is to detect as many factors (independent variables) as possible that affect the dependent variable. Based on the magnitude of the regression coefficients, we can conclude what is the relative impact or importance of each independent variable. Mediation proves how and why, ie by what mechanisms a certain relationship is realized (Baron & Kennz, 1986).
4. Results and discussion
In the beginning, an exploratory factor analysis was performed, which is shown in Table 1 and Table 2. The first table refers to determining the percentage of variance of items on F1 and F2. Specifically, the first two items have significant saturation on factors, while the others have a characteristic root lower than 1, and were not grouped into factors. The first factor showed the highest saturation of about 43.8%, while the second factor had a saturation of 12.8%. The total percentage of explained advances was 56.7%.
Table 1: Total variance explained for Factor 1 and Factor 2
Component Initial eigenvalues Extraction sums loadin of squared gs Rotation sums of squared loadingsa
Total % of Variance Cumulative % Total % of Variance Cumulative % Total
1 4.387 43.867 43.867 4.387 43.867 43.867 3.959
2 1.285 12.850 56.716 1.285 12.850 56.716 3.278
3 0.874 8.744 65.460
4 0.678 6.784 72.243
5 0.666 6.662 78.905
6 0.567 5.665 84.570
7 0.508 5.083 89.653
8 0.443 4.426 94.079
9 0.322 3.224 97.303
10 0.270 2.697 100.000
Extraction method: Principal component analysis
a. When components are correlated, sums of squared loadings cannot be added to obtain a total variance Source: Author's research
Table 2 indicates the percentage of saturation of items on factors F3 and F4. These results suggest that the questionnaire is based on only two factors and that the identification of a number of factors would result in highly related scales of insufficient discriminatory validity.
Table 2: Total variance explained for Factor 3 and Factor 4
Component Initial eigenvalues Extraction sums loadin of squared gs Rotation sums of squared loadingsa
Total % of Variance Cumulative % Total % of Variance Cumulative % Total
1 5.039 50.391 50.391 5.039 50.391 50.391 4.460
2 1.243 12.426 62.818 1.243 12.426 62.818 4.074
3 0.859 8.592 71.410
4 0.614 6.139 77.549
5 0.589 5.891 83.440
6 0.493 4.932 88.372
7 0.383 3.830 92.202
8 0.329 3.292 95.494
9 0.270 2.698 98.192
10 0.181 1.808 100.000
Extraction method: Principal component analysis
a. When components are correlated, sums of squared loadings cannot be added to obtain a total variance Source: Author's research
Table 3 shows the percentage of explanation of variance. It can be noticed that in the first step of the multiple regression analysis, the percentage of explanation of the aviation was 42.2%, while after the introduction of the mediator or F3, the percentage increased to 50.2%.
Table 3 : Percentage of ex
planation of variance
Model R R square R2 Std. Error R Change Statistics F Change df1 df2 Sig.
1 0.652a 0.425 0.422 1.1662 0.425 189.238 2 513 0.000
2 0.710b 0.504 0.502 1.0832 0.080 82.601 1 512 0.000
a. Predictors: (Constant), F1 and F2
b. Predictors: (Constant), F1, F2, F3 (mediator) Source: Author's research
Table 4 provides an insight into the partial contribution of each predictor, when predicting the score on criterion variable F4. In the first step, before the introduction of the F3 mediator, it is observed that each of these fears has a statistically significant effect on F4 prediction. Fear of pandemic (F1) has the following contribution to determining the score on F4: B = 0.253, B = 0.161 and p = 0.55. Regarding the fear of staying in restaurants (F2), the partial contribution is as follows: B = 0.639, B = 0.500 and p = 0.000.
Table 4: Partial contribution of predictors
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 0.802 0.149 5.378 0.000
F1 0.253 0.137 0.161 1.851 0.055
F2 0.639 0.111 0.500 5.759 0.000
2 (Constant) 0.239 0.152 1.575 0.116
F1 0.144 0.128 0.092 1.131 0.259
F2 0.412 0.106 0.323 3.885 0.000
F3 0.424 0.047 0.373 9.089 0.000
a. Dependent variable: F4 (Intention) Source: Author's research
With the introduction of the F3 mediator, the value of F1 changes significantly, which means that there is no longer a partial contribution or statistically significant impact on F4. In this case, it is a matter of partial mediation. The value of F2 remains unchanged. Both types of fears significantly influence the decision to visit restaurants during a pandemic. Security measures were not necessarily a condition for users to change their attitude about visiting restaurants.
Table 5 shows the values of the significant correlation between the two factors related to the two types of fear (F1 and F2). There is a positive and high correlation between the two factors.
Table 5: Correlations among F1 and F2
F1 F2
F1 Pearson Correlation 1 0.923**
and Sig. (2-tailed) 0.000
F2 N 516 516
** Correlation is significant at the 0.01 level (2-tailed)
Source: Author's research
The research confirmed the initial hypotheses. Hypothesis H1 has been confirmed: both factors related to the fear of a pandemic, have influence on intention to visit restaurants during pandemic. Also, it has been proven that there is a correlation between factors F1 and F2, more precisely that there is a correlation between two types of fear (H2- confirmed).
5. Conclusion
Tourism and hospitality present one of the most important economic sectors in the world, employing one in ten people on Earth and providing livelihoods for hundreds of millions of people. Tourism and hospitality enable the progress of every country (Delic et al., 2021). The COVID-19 virus has shut down many businesses and jobs, and nearly destroyed economies that rely on tourism and services. The first measures were the introduction of strict epidemiological measures to combat the spread of the infection, which meant either complete closure or restriction of population movements and restrictions on the work of service activities, primarily catering facilities - cafes and restaurants. Among those that have maintained but also increased revenues are companies for online trade, sale of equipment and chemical means for protection against infection, pharmacies, computer stores. The pandemic is a great challenge for everyone, and tourism workers have faced severe consequences, which are slowly destroying the world economy. Maintaining mental health is possible by following the instructions and advice of the World Health Organization and local authorities. Everyday disorders caused by the fear of viruses and death, also cause anxiety, and because of that, mental health can be impaired. Consumers are afraid of staying in catering facilities, and when making decisions for tourist travel. Many psychologists face the problem of predicting consumer behavior in the future. The appearance of the COVID-19 virus has given a completely new shape, but also space for work on some internal processes. To begin with, it is important to state that one of the most common mistakes in thinking is catastrophizing and predicting negative scenarios in the future. Fear is a natural reaction and allows us to be careful to protect our health and life. To determine exactly what the real state of consumers might be, we would have to study all psychological groups, and then assess their answer to the question of whether or not they would be afraid of future travel and restaurant visits after the pandemic. The authors of the paper conducted a survey in 27 restaurants in Serbia, on a total sample of 508 respondents. The aim was to determine whether any of the factors of fear have an effect on intention to visit restaurants. The exploratory factor analysis yielded four factors (F1 and F2 related to the fear of a pandemic), and F3 and F4 (related to security measures and
protections and intention to visit restaurants during pandemic), and with the help of multiple regression analysis, it was found that both types of fear affect on intention to visit restaurants. A significant correlation was also found between the first two factors F1 and F2. Thus, the initial hypotheses were confirmed: fears of pandemic have significant influence on intention to visit restaurants during pandemic (H1), and that there is a correlation between factors of fear (H2).
The importance of research can play a major role in future research of wider significance. The results can be implemented in all economic areas and sectors of society, and observe the behavior of consumers in crisis situations. Based on the results on the perception of fear in consumers and the impact of fear on future restaurant visits, it will be possible to have a ready business response to a similar scenario, if a similar crisis situation occurs again. Identifying the key business problems during the pandemic, a realistic picture of consumer and employer behavior will be created, and measures will be taken to continue the business with as little loss as possible and without a restaurant closure system.
Conflict of interest
The authors declare no conflict of interest. References
1. Agag, G., Brown, A., Hassanein, A., & Shaalan, A. (2020). Decoding travelers' willingness to pay more for green travel products: Closing the intention-behaviour gap. Journal of Sustainable Tourism, 28(10), 1551-1575. https://doi.org/10.1080/09669582.2020.1745215
2. Alan, C. B., So, S., & Sin, L. (2006). Crisis management and recovery: How restaurants in Hong Kong responded on SARS. International Journal of Hospitality Management, 25(1), 3-11. http://doi.org/10.1016/j.ijhm.2004.12.001
3. Assaf, A. G., Kock, F., & Tsionas M. (2021). Tourism during and after COVID-19: An expert-informed agenda for future research. Journal of Travel Research, 59,1140-1146. https://doi.org/10.1177/00472875211017237
4. Bae, S. Y., & Chang, P. J. (2020). The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards 'untact' tourism in South Korea during the first wave of the pandemic. Current Issues in Tourism. https://doi.org/10.1080/13683500.2020.1754354
5. Bali S., Stewart K. A., & Pate, M. A. (2016). Long shadow of fear in an epidemic: Fearonomic effects of Ebola on the private sector in Nigeria. BMJ Global Health. http://dx.doi.org/10.1136/bmjgh-2016-000111
6. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173-1182. https://doi.org/10.1037/0022-3514.51.6.1173
7. Blesic, I., Petrovic, M., Gajic, T., Tretiakova, T., Vujicic, M., & Syromiatnikova, J. (2021). Application of the analytic hierarchy process in the selection of traditional food criteria in Vojvodina (Serbia). Journal of Ethnic Foods, https://doi.org/10.1186/s42779-021-00096-2
8. Bozovic, T., Blesic, I., Nedeljkovic Knezevic, M., Deri, L., & Pivac, T. (2021). Resilience of tourism employees to changes caused by COVID-19 pandemic. Journal of the Geographical Institute "Jovan Cvijic" SASA, 71(2), 181-194. https://doi.org/10.2298/IJGI2102181B
9. Bradic-Martinovic, A., & Kovacevic, I. (2020). Poslovanje hotela tokom pandemije [Hotel operations during the COVID-19 pandemic]. In Bradic-Martinovic et al. (Eds), Poslovanje u periodu pandemije - izazovi i sanse [Doing business during the pandemic -challenges and opportunities] (pp. 72-90). Beograd: Institut ekonomskih nauka Beograd.
10. Chew, E. Y. T., & Jahari, S. A. (2014). Destination image as a mediator between perceived risks and revisit intention: A case of post-disaster Japan. Tourism Management, 40, 382-393. https://doi.org/10.1016/j.tourman.2013.07.008
11. Choi, J., Lee, A., & Ok, C. (2013). The effects of consumers' perceived risk and benefit on attitude and behavioral intention: A study of street food. Journal of Travel & Tourism Marketing, 30(3), 222-237. https://doi.org/10.1080/10548408.2013.774916
12. Delic, M., Gajic, T., & Kozic, B. (2021). Agriculture in the function of rural development - Case study from Republic of Serbia and Republic of Srpska. Economics of Agriculture, Belgrade, 68(2), 463-476. https://doi.org/10.5937/ekoPolj2102463D
13. Floyd, M. F., Gibson, H., Pennington-Gray, L., & Thapa, B. (2004). The effect of risk perceptions on intentions to travel in the aftermath of September 11, 2001. Journal of Travel & Tourism Marketing, 15(2-3), 19-38. https://doi.org/10.1300/J073v15n02_02
14. Fotiadis, A., Polyzos, S., Cheng, T., & Huan, T.C. (2021). The good, the bad and the ugly on COVID-19 tourism recovery. Annals of Tourism Research, 87, 103117. https://doi.org/10.1016/j.annals.2020.103117
15. Gajic, T., Raljic Popov, J., Aleksic, M., Blesic , I., Vukolic, D., Petrovic, M. D. ... Sikimic, V. (2021a). Creating opportunities for the development of craft beer tourism in serbia as a new form of sustainable tourism. Sustainability, 13(16), 1-22, 8730. https://doi.org/10.3390/su13168730
16. Gajic, T., Petrovic, D. M., Blesic, I., Radovanovic, M., & Syromjatnikowa, J. (2021b). The power of fears in the travel decisions: COVID-19 vs. lack of money. Journal of Tourism Futures, 1-22. https://doi.org/10.1108/JTF-03-2021-0064
17. Godovykh, M., & Tasci, A. D. (2020). The influence of post-visit emotions on destination loyalty. Tourism Review, 76, 277-288. https://doi.org/10.1108/TR-01-2020-0025
18. Godovykh, M., Pizam, A., & Bahja, F. (2021). Antecedents and outcomes of health risk perceptions in tourism, following the COVID-19 pandemic. Tourism Review, 76, 737748. https://doi.org/10.1108/TR-06-2020-0257
19. Gossling, S., Scott, D., & Hall, C. M. (2020). Pandemics, tourism and global change: A rapid assessment of COVID-19. Journal of Sustainable Tourism, 1-20. https://doi.org/10.1080/09669582.2020.1758708
20. Hartjes, L. B., Baumann, L. C., & Henriques, J. B. (2009). Travel health risk perceptions and prevention behaviors of US study abroad students. Journal of Travel Medicine, 16(5), 338-343. https://doi.org/10.1111/j.1708-8305.2009.00322.x.
21. Kim, H. (2020). The endless battle against COVID-19. Everything has changed in South Korea. Segye Daily.
22. Kock, F., Norfelt, A., Josiassen, A., Assaf, A. G., & Tsionas, M. G. (2020). Understanding the COVID-19 tourist psyche: The evolutionary tourism paradigm. Annals of Tourism Research. https://doi.org/10.1016Zj.annals.2020.103053
23. Krejic, Z., & Milicevic, S. (2021). Research on tourists' satisfaction with the gastro offer of Novi Sad. Anali Ekonomskog fakulteta u Subotici, 57(45), 41-50. https://doi.org/10.5937/AnEkSub2145041K
24. Ministry of Trade, Tourism and Telecommunications (2022). Retrieved on February 3, 2022 from https://mtt.gov.rs/
25. Novelli, M., Burgess, L. B., Jones, A., & Ritchie, B. W. (2018). No Ebola... still doomed'-The Ebola-induced tourism crisis. Annals of Tourism Research, 70, 76-87. https://doi.org/10.1016/j.annals.2018.03.006
26. Organisation for Economic Co-operation and Development (OECD) (2022). Retrieved on February 3, 2022 from https://www.oecd.org/_
27. Polas, R. H., Imtiaz, M., Mahbub, A., & Khan, A. M. (2019). Antecedent and consequences of risk perception on tourist decision making towards the sustainable medical tourism development in Bangladesh. Journal of Tourism Management Research, 6(1), 93-108.
28. Poudel, K., & Subedi, P. (2020). Impact of COVID-19 pandemic on socioeconomic and mental health aspects in Nepal. The International Journal of Social Psychiatry, 66(8), 748-755. https://doi.org/10.1177/0020764020942247
29. Radic, N., Radic, V., & Grujic, I. (2021). Economic impact of the coronavirus pandemic on air traffic. Ekonomika, 67(2), 59-68. https://doi.org/10.5937/ekonomika2102059R
30. Roxas, F. M. Y., Rivera, J. P. R., & Gutierrez, E. L. M. (2022). Bootstrapping tourism post-COVID-19: A systems thinking approach. Tourism and Hospitality Research, 22(1), 86-101. https://doi.org/10.1177/14673584211038859
31. Sánchez-Cañizares, S. M., Cabeza-Ramírez, L. J., Muñoz-Fernández, G., & Fuentes-García, F. J. (2021). Impact of the perceived risk from COVID-19 on intention to travel. Current Issues Tourism, 24, 970-984. https://doi.org/10.1080/13683500.2020.1829571
32. Santana, G. (2003). Crisis management and tourism. Journal of Travel and Tourism Marketing, 15(4), 299-321. https://doi.org/10.14505/jemt.11.6(46).20
33. Statista - Statistic Portal for Market Data (2022). Retrieved February 3, 2022 from https://www.statista.com/HVS.com
34. Ugur, N. G, Akbiyik, A. (2020). Impacts of COVID-19 on global tourism industry: A cross-regional comparison. Tourism Management Perspectives, 36: 100744. https://doi.org/10.1016/j.tmp.2020.100744
35. Yoo, S. (2020). Take personal amenities with you when you visit hotels. Code ofconduct for traveling in the era of Corona.
36. Zhang, K., Hou, Z., & Li, J. (2020). Threat of infectious disease during an outbreak: Influence on tourists' emotional responses to disadvantaged price inequality. Annals of Tourism Research, 84, 102993. https://doi.org/10.1016/j.annals.2020.102993
Received: 9 March 2022; Sent for revision: 14 March 2022; Accepted: 18 April 2022
