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1. Introduction
COVID-19 has introduced profound changes in the hotel industry. On the one hand, some studies highlight that COVID-19 was a catalyst for digital transformation in the hospitality industry, leading to efficiency gains in hotel operations (Antonio, 2020). On the other hand, the pandemic and the comprehensive precautions against it instantly brought the tourism industry to a complete halt, from which it will not easily recover (Gössling, Scott & Hall, 2021). So far during the 21st century, several infectious diseases, such as SARS, MERS, Swine Flu, Avian Flu, and Ebola, have gravely threatened the tourism and hospitality industry as well as the global economy and human life (Hall, 2019; Min, 2005; Nhamo, Dube & Chikodzi, 2020; Pine & McKercher, 2004). However, the destructive effects of the COVID-19 outbreak were of unprecedented severity with regard to the global tourism industry in comparison with any other outbreak (Jian, Yang & Zeng, 2020; Škare, Soriano & Porada-Rochoń, 2021; Zenker & Kock, 2020; Zheng, Luo & Ritchie, 2021). The pandemic also has created serious risks for hotel employees. Above all, they are at high risk for COVID-19 infection due to working in a high-contact environment (WHO, 2020a; Vo-Thanh et al., 2021a; Liu, Shen & Hong, 2021).
Research shows that as the risk of contracting an infectious disease in the working environment increases, the employees' mental health is negatively affected (Khalid, Khalid, Qabajah, Barnard & Qushmaq, 2016). Especially the feeling of fear experienced during pandemics causes stress (Cheng, 2004; Liu et al., 2012; Wu et al., 2009). The fear of infection is mostly experienced together with the fear of job loss. Due to COVID-19, tourism employees have been dismissed in most countries, often with little or no compensation. For example, Disney shut down all Walt Disney World resort hotels, while Wynn and MGM Resorts announced the same for their Las Vegas hotels (Khan, Bibi, Lyu, Latif & Lorenzo, 2021). At the pandemic's peak, nine hotels out of ten in the USA had to dismiss their employees, while 7.5 million employees in the hospitality industry lost their jobs (AHLA, 2020). Similarly, on average, occupancies for China’s hotels declined by 90% (Duarte-Alonso et al., 2020). Much like other countries, Turkey has also been challenged by the COVID-19 pandemic. In 2019, it was the world’s sixth most popular destination, with 51.2 million visitors. However, tourist numbers fell by 71.3% in the first nine months of 2020, while occupancies were 21.5% (T.R. Minister of Culture and Tourism, 2020). Although dismissals were prohibited during the pandemic in Turkey, there were reports in the press that some employees were dismissed after being diagnosed with COVID-19 (Atas, 2020). In the face of such news, employees try to protect their jobs while trying to protect themselves from the risk of infection. Those trying to cope with the fear of COVID-19 take responsibility not only for themselves but also for their family members and dependents. As a result, the fear of contracting the COVID-19 virus may increase the perception of job insecurity among employees.
According to Hamouche (2020), the lack of job security is also an important antecedent of stress among employees. Stress is deemed an outcome of a threat or the loss of a resource (Walter et al., 2008). According to the conservation of resources theory (COR), personal health, the health of loved ones, and employment are the main resources (Hobfoll, 2001). Loss of personal resources, such as income or employment, makes it much more difficult to cope with stress (Baranik, Cheung, Sinclair & Lance, 2019). Therefore, fear of COVID-19 may make employees concerned about their health and job security, leading to negative psychological outcomes like stress (Baum & Hai, 2020; Vo-Thanh Vu, Nguyen, Nguyen, Zaman & Chi, 2021b). For example, a study conducted in China found that the stress levels of people who were forced to stop working due to COVID-19 increased (Zhang, Wang, Rauch & Wei, 2020).
It is known that COVID-19 affects different people in different ways. The authorities point out that age is an important factor (Boehmer et al., 2020; ECDC, 2020), and it has been reported that the rates of hospitalisation with the diagnosis of COVID-19 increase with age (Verity et al., 2020). So, the level of COVID-19 fear and the perception of job insecurity may differ according to the age factor. Another important factor that strongly affects the psychological outcomes of COVID-19 is the financial situation (Arampatzi, Burger & Veenhoven, 2015). Research shows that financial situation may increase employee stress as it is closely related to basic living standards (Rasdi, Zaremohzzabieh & Ahrari, 2021).
Tourism literature studies concerning the pandemic largely focused on tourists’ travel behaviours, tourism demand, and economic outcomes (Yang, Zhang & Chen, 2020; Zheng et al., 2021). Only a few studies have considered how infectious diseases affect hotel employees despite their key contribution to their organisations (Jung, Jung & Yoon, 2021; Vo-Thanh et al., 2021b). More studies are needed to discuss the grave threat and uncertainty posed by the COVID-19 pandemic for hotel employees.
The fact that this situation of tourism employees was not adequately mentioned in the press nor in scientific studies led to criticism (Baum & Hai, 2020). We believe that research studies can guide hotels during crises by showing which types of management can ameliorate the psychological states of their employees and maintain their job performance (Vo-Thanh et al., 2021b). Empirical research can be of great use to the industry by suggesting practical strategies as well as improving understanding of theoretical structures (Duarte-Alonso et al., 2020). So, this study aims to understand how the employees of five-star hotels are affected by COVID-19 by proposing a model to connect COVID-19 fear, job insecurity, stress, age, and financial situation. First, a review of the literature and the hypotheses are discussed. Then, we present the research sample, the data collection instruments, and the research model. Lastly, we discuss the results of the data analysis and suggest theoretical and practical implications accordingly.
2. Literature review and hypotheses
2.1 Relationship of COVID-19 fear with job ınsecurity and stress
Fear can be defined as a negative emotion triggered by potential danger and causing psychological and physiological reactions (Beck, Emery & Greenberg, 2005). Diseases like COVID-19 instil fear and panic (Ahorsu et al., 2020; Lee, Kang, Cho, Kim & Park, 2018; Strong, 1990). Fear of COVID-19 mainly arises from the worry of being infected by the disease, much like the fear of other infectious diseases (Lin, 2020). Especially in sectors such as hospitality that provide a direct service, COVID-19 predictably generates fear among employees. Fear is an emotion that causes anxiety and feelings of threat and insecurity regarding the future (Dobson, 1985). Job security is defined as the expectation of employees that they will not lose their jobs (Davy, Kinicki & Scheck, 1997; Lu, Du, Xu & Zhang, 2017); conversely, job insecurity is the fear of losing one’s job (Hartley, Jacobson, Klandermans & Van Vuuren, 1990; Heaney, Israel & House., 1994; Sverke Hellgren & Näswall, 2002; Witte, 1999). Job insecurity reduces the psychological well-being of employees (Inoue, Kawakami, Eguchi, & Tsutsumi, 2018; Nella, Panagopoulou, Galanis, Montgomery & Benos, 2015; Schaufeli, 2016). According to COR theory, losing resources of health and job security, which individuals consider valuable, can increase stress (Hobfoll, 2001). Thus, COVID-19 is a stress factor because it threatens valuable individual resources.
Even before COVID-19, many studies had shown that job insecurity is a significant issue for employees due to economic volatility and global changes (Niesen, Hootegem, Handaja, Battistelli & Witte, 2018; Pienaar, Witte, Hellgren & Sverke, 2013). Job insecurity is particularly important in the tourism and hospitality sector because temporary work and uncertainty are common (Ozturk & Karatepe, 2019; Unguren & Arslan, 2021). Because of very high job insecurity in Turkey’s tourism sector, its employees constantly fear losing their jobs at any moment (Etehadi & Karatepe, 2019). Thus, perceived job insecurity for tourism employees is likely to have become severe during the COVID-19 pandemic. As with any public health crisis, COVID-19 has damaged the economy (Mastroianni, 2009), which in turn has severely impacted the psychological well-being of employees. COVID-19 has increased job insecurity (Jung et al., 2021). And similar to the fear caused by other global crises, the fear of COVID-19 has disrupted employees’ plans for their futures and their careers (Mahmud, Talukder & Rahman, 2020; Tsai, Hsu & Hsu, 2017). Pacheco et al. (2020) found that employees in Canada have experienced perceived job insecurity and stress during the COVID-19 pandemic, which has harmed their well-being. Similarly, Agarwal (2021) reported that those experiencing COVID-19 fear in India also experience intense job insecurity. Therefore, the following hypothesis is posited:
Hypothesis 1. COVID-19 fear increases job insecurity among hotel employees.
During disease outbreaks, stress increases (Cheng, 2004; Liu et al., 2012; Wu et al., 2009). Currently, this constant fear of being infected with SARS-CoV-2 affects employees in different sectors physically and mentally. Various disciplines have demonstrated a link between COVID-19 fear and stress. The fear of infection and illness or losing loved ones can lead to stress, insomnia and even depression (Islam, Bodrud-Doza, Khan, Haque & Mamun, 2020; WHO, 2020b). Many frontline employees, including those in the hospitality sector, providing face-to-face services to guests are at higher risk of COVID-19 infection and suffering associated stress (Radic, Lück, Ariza-Montes & Han, 2020; Sim, 2020). And the stress becomes more severe for hotel employees when the management fails to promote employee well-being (Agarwal, 2021; Ariza-Montes, Hernández-Perlines, Han & Law, 2019). Overall, these research findings suggest the following hypothesis:
Hypothesis 2. Fear of COVID-19 increases stress among hotel employees.
2.2 Relationship between job ınsecurity and stress
Stranks (2005) argues that stress is a disturbance in the natural balance in one’s life and the related effects. Certain environmental changes cause individuals to utilise their bodily resources, generating a response to these environmental changes. Therefore, stress can also be defined as the psychological reaction to cope with problems. According to Selye (1976), stress can be either beneficial or harmful. The former type facilitates adaptation to situations, events and changes, whereas the latter, which is the focus of this study, reduces efficiency and damages health or even causes it to collapse under extreme pressure. Psychological and social workplace stresses are significant risk factors for mental and physical health problems (Karasek & Theorell, 1990). According to COR theory, job insecurity causes stress because it seriously threatens the employee’s resources. One’s job immediately affects other valuable resources like stable employment, financial stability, success and self-esteem (Hobfoll, 2001). Heaney et al. (1994) found that job insecurity for automotive workers leads to chronic stress and even severe long-term health problems. Similarly, Sverke et al. (2002) conducted a meta-analysis showing that job insecurity is a significant stress factor for employees. Due to its concern with high guest satisfaction and flexible and active work, stress is rather high in the hospitality sector (Kokt & Ramarumo, 2015; Zhao & Ghiselli, 2016; Unguren & Arslan, 2021). The feeling of uncertainty due to job insecurity is another significant source of stress for hospitality employees (Gilboa, Shirom, Fried & Cooper, 2008; Green, 2020; Kuhnert & Vance, 1992). Work environments characterised by job insecurity, as is the case during the COVID-19 pandemic, can cause stress (Pacheco et al., 2020). Duarte-Alonso et al. (2020) found that unemployment is a serious source of stress during COVID-19 for hotel employees. Therefore, the following hypothesis is posited:
Hypothesis 3. Job insecurity increases stress among hotel employees.
2.3 Moderating effect of age and financial situation
Mortality rates from COVID-19 increase with age (Goldstein & Lee, 2020; Sudharsanan, Didzun, Bärnighausen & Geldsetzer, 2020). The global median age of COVID-19 cases has declined in recent months, although it remains at 37 years in the United States and at least 39 in Europe (Boehmer et al., 2020; ECDC, 2020). While younger people are not safe from danger, they mostly spread the disease to higher-risk groups. Although Ahorsu et al. (2020) found that COVID-19 fear does not vary with age; age-related mortality differences indicate that COVID-19 research should not ignore this variable. For example, Hossain et al. (2020) reported that COVID-19 fear is higher in older people. Age also significantly increases job insecurity (Fullerton & Wallace, 2007; Keim, Landis, Pierce & Earnest, 2014; Kinnunen & Nätti, 1994). For example, the proportion of U.K. employees reporting job insecurity rises from 16.5% for 16-24 year-olds to 24.5% for 45-54 year-olds (Meltzer et al., 2010). Näswall and De Witte (2003) also reported an increase in job insecurity with age in Europe. Overall, these research findings suggest the following hypothesis:
Hypothesis 4. The effect of COVID-19 fear on job insecurity is moderated by age.
Financial situation refers to an employee’s income and assets, such as home, automobile or belongings, or the products and services available to them (Fergusson, Horwood & Beautrais, 1981). The financial situation is a predictor of employee well-being (Joo, 2008), as an undesirable financial situation may significantly increase stress (Peirce, Frone, Russell & Cooper, 1994). Financial issues that increase stress particularly relate to health, family or employment (APA, 2015). Similarly, Saunders (1998) and Wilkinson (1992) argue that low income and a poor financial situation lead to stress, low self-esteem and various psychological problems in employees. Within the COR framework, the financial situation refers to the ownership of resources, the absence of which can lead to stress (Halbesleben, Wheeler & Paustian-Underdahl, 2013). Arampatzi et al. (2015) found that financial situation moderates the extent to which employees in Europe are psychologically affected by a crisis. During the COVID-19 pandemic, greater financial concern leads to higher stress and anxiety (Wilson et al., 2020). In addition, the indirect effect of job insecurity on anxiety is moderated by financial concern. Shoss (2017) also argues that economic vulnerability, which results from the financial situation, increases job insecurity and stress, among other negative effects. Conversely, Berglund, Furåker & Vulkan (2014) found that income security reduces the stress caused by job insecurity. These research findings suggest the following hypothesis:
3. Methodology
3.1 Sampling
The effect of the COVID-19 pandemic was heavily felt in the hospitality industry as human resources in hotels were cut or the businesses had to shut down temporarily or permanently. In Turkey, the Ministry of Tourism obliged all accommodation facilities with a capacity of 30 rooms or more to acquire a “Safe Tourism Certificate”, starting in June 2020. Fieldwork for the present study was conducted between August and October 2020 with employees of five-star hotels in Alanya, which is one of Turkey’s most important tourist destinations. Of the city’s 84 five-star hotels, 72 had the Safe Tourism Certificate at the time of the study. In other words, 72 five-star hotels were operating in the region during the research process. During the research period, the occupancy rate of hotels in the region was 63% (ALTID, 2020). Given health, time and cost limitations due to the pandemic, non-probabilistic purposive sampling was preferred. Personal interviews and the drop-and-pick method were used for data collection. In July 2020, a meeting was held with the human resources managers of 36 five-star hotels operating in the Alanya region. The preliminary interviews gave information about the research aim and method. After being informed about the research, permission was requested to conduct research. After the interviews, ten businesses stated that they could not contribute to the research due to the pandemic, and no response could be obtained from four hotel businesses. The survey forms were delivered by the researchers to the human resources managers that agreed to participate in the research, and two weeks later, the hotels were visited, and the survey forms were collected. The final sample included hotel employees from 22 different five-star hotels in Alanya. Respondents were informed about the study objectives, the voluntary nature of their participation, the possibility of withdrawing from the study and the confidentiality of the collected data. A total of 800 questionnaires were distributed. Three trap questions were included to identify those who did not pay careful attention to the questionnaire items (Liu & Wronski, 2018). Before analysing the data, the 684 completed questionnaires were evaluated. This eliminated 53 questionnaires: 14 questionnaires with inaccurate responses to trap questions and 39 questionnaires with missing responses or straight-lining. One of the main components of reliability is to have a representative sample size. G*Power was used to determine the minimum sample size for this study, with the settings determined between the values suggested by Cohen (1988) and Hair, Hult, Ringle & Sarstedt (2017) (power = 0.95, f2 = 0.15, alpha = 0.05, highest number of predictors = 3). While these values indicate that the minimum sample size was 74, Ringle, Wende & Becker (2015) argue that a research model is more reliable if the number of respondents required is tripled. So, it was decided that 631 respondents were more than adequate. More than half of the respondents (61%) were male, while the marital status was balanced (51.2% married and 48.8% single). Regarding education, 29.6% of respondents were primary school graduates, 48.2% high school graduates and 22.2% university graduates. Regarding their departments, 30.1% worked in the restaurant, 18.1% in housekeeping, 16.5% in the kitchen, 14.4% in the bar, 12.2% at the front desk and 8.7% in accounting and purchasing.
3.2 Instruments
This study aims to understand the relationship between COVID-19 fear, job insecurity and stress of hotel employees during the COVID-19 pandemic whose work requires physical contact with guests and also the moderator effects of age and financial situation. The data were collected through a questionnaire. COVID-19 fear was measured with a scale consisting of seven propositions and one dimension developed by Ahorsu et al. (2020). The scale was adapted into Turkish by Satici, Gocet-Tekin, Deniz & Satici (2020). The scale is to measure the fear that arises in individuals due to COVID-19. Higher scores indicate higher levels of COVID-19 fear. There is no reverse-scored item on the scale. Employees' perceived job insecurity due to the COVID-19 scale was designed by Witte (1999), and a short version of it was developed by Pienaar et al. (2013). The scale consists of 8 propositions, and a high score indicates that people feel a high level of job insecurity due to the COVID-19 outbreak. Employee financial situation was measured by the three-item financial well-being scale developed by Castro-González, Fernández-López, Rey-Ares & Rodeiro-Pazos (2020). In all the scales, respondents rated the items on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The study's dependent variable, the employees' perceived stress, was measured by the 14-item Perceived Stress Scale (PSS-14) developed by Cohen, Kamarck & Mermelstein (1983). Participants responded to each item on a 5-point Likert scale ranging from 1 (never) to 5 (very often). In the last part of the questionnaire form, questions to determine the demographic characteristics of the participants, such as age, gender, and education, were included.
3.3 Data analysis
This study was designed to test the moderated mediation research model. Figure 1 presents a model of the integrated effect of COVID-19 fear, age, financial situation and job insecurity on perceived stress. Moderated mediation combines the effects of moderation and mediation. In this study, the mediation moderation effect was used to determine in what conditions the indirect effects between two variables change. The model of effect, designating the instances (W and Z), when the indirect effect of COVID-19 fear (X) on the dependent variable perceived stress (Y) through the mediating variable (M) job insecurity changes, can be described as mediation moderation (Gürbüz, 2019; Muller, Judd & Yzerbyt, 2005). Prior to the multi-variable statistical analyses, we tested the suitability of the data. First, no missing values were found, and there were no data losses. Second, the Mahalanobis distance indicated that there were no outliers. Third, the skewness and kurtosis values indicated that normal distribution assumptions were met. Confirmatory factor analysis (CFA) was used to confirm the validity of the measurement model. The goodness of fit indices were used to test the structural validity and reliability of the scales and calculate their convergent validity and discriminant validity values. A correlation analysis was conducted to investigate the relationships between the variables in the research. Moderator, mediation and moderated mediation relationships were tested with the SPSS macro PROCESS developed by Hayes (2018). The indirect, direct and total effect values were tested with bootstrap confidence intervals (CI) to determine their statistical significance. Following Preacher and Kelley (2011), K2 (Kappa-squared) was calculated to determine the mediation effect.
4. Analysis results
4.1 Measurement model
Table 1 displays the results of the confirmatory factor analysis (CFA) conducted to assess the distinctiveness of each variable used in the study. Data from the measurement model, including all structures, is shown in Table 2 in terms of maximum likelihood estimation. The standardised factor load values were over 0.70 for all scale items, which also had high t values and loaded onto the relevant implicit variable in a statistically significant way (p < 0.05). The goodness of fit statistics for the model (x2 = 458,892, df = 458, x2/df=2,153, p < 0.001, RMSEA = 0.043, CFI = 0.977, GFI = 0.908, IFI = 0.977, NFI = 0.957, RFI = 0.954) indicated that the measurement model was acceptable (Schermelleh-Engel, Moosbrugger & Müller, 2003). Skewness and kurtosis values for the scale items confirmed that the data met multi-variable normality assumptions (Kline, 2011).
The measurement model, convergent validity, discriminant validity and construct reliability were examined to assess construct validity. Composite reliability (C.R.) was used to assess the internal consistency of the factors. As shown in Table 2, all the dimensions of R of the constructs exceeded the recommended threshold of 0.70. The procedure suggested by Fornell and Larcker (1981) was used to determine convergent validity and discriminant validity. This determined that the AVE (average variance extracted) values of all dimensions were over 0.50 while their C.R. values exceeded the AVE values (Table 2) to confirm that the variables possessed convergent validity (Fornell & Larcker, 1981). To assess discriminant validity, MSV (maximum shared variance) and ASV (average shared variance) values were examined with cross-loading values. As the MSV and ASV values of all variables were lower than the AVE values while the AVE square root values were higher than the correlation values of the relevant variables, the discriminant validity of the scales was confirmed (Fornell & Larcker, 1981). Cronbach Alpha values were calculated to assess scale reliabilities. These ranged between 0.96 and 0.97 (Table 2), indicating an acceptable level of reliability (Hair, Babin, Babin, Anderson & Tatham, 2013). Overall, the results indicate that the research model was reliable and possessed convergent and discriminant validity. The correlation analysis revealed several significant positive relationships. Job insecurity correlated strongly with perceived stress (r = 0.78, p < 0.01) and slightly with COVID-19 fear (r = 0.29, p < 0.01) while COVID-19 fear correlated moderately with perceived stress (r = 0.45, p < 0.01). There is a strong and negative relationship between financial situation and perceived stress (r = -0.59, p < 0.01). On the other hand, financial situation has a negative and partially weak relationship with COVID-19 fear (r = -0.33, p < 0.01) and job insecurity (r = -0.23, p < 0.01).
Table 1 Result of measurement model
| Mean | SFL | t-value | Skewness | Kurtosis | |
|---|---|---|---|---|---|
| COVID-19 Fear | |||||
| My heart races or palpitates when I think about getting coronavirus-19 | 3.18 | 0.93 | Fixed | -0.03 | -0.76 |
| I cannot sleep because I’m worrying about getting coronavirus-19 | 3.25 | 0.91 | 40.65*** | -0.08 | -0.54 |
| When watching news and stories about coronavirus-19 on social media I become nervous or anxious | 3.19 | 0.89 | 38.32*** | 0.05 | -0.78 |
| I am afraid of losing my life because of coronavirus-19 | 3.16 | 0.87 | 35.36*** | 0.09 | -0.72 |
| My hands become clammy when I think about coronavirus-19 | 3.22 | 0.89 | 38.43*** | 0.11 | -0.86 |
| It makes me uncomfortable to think about coronavirus-19 | 3.16 | 0.86 | 33.97*** | 0.08 | -0.84 |
| I am most afraid of coronavirus-19 | 3.19 | 0.91 | 40.44*** | 0.23 | -0.92 |
| Job Insecurity (Due to COVID-19 outbreak) | |||||
| I think that I will be able to continue working here | 3.68 | 0.93 | Fixed | -0.32 | -0.94 |
| There is only a small chance that I will become unemployed | 3.58 | 0.91 | 41.06*** | -0.52 | -0.52 |
| I am certain/sure of my job environment | 3.70 | 0.88 | 37.33*** | -0.30 | -1.12 |
| I am very sure that I will be able to keep my job | 3.65 | 0.89 | 37.49*** | -0.36 | -0.71 |
| I feel uncertain about the future of my job | 3.69 | 0.86 | 35.01*** | -0.30 | -1.07 |
| I worry about the continuation of my career | 3.66 | 0.91 | 40.52*** | -0.35 | -0.80 |
| I fear that I might lose my job | 3.69 | 0.82 | 31.29*** | -0.29 | -1.10 |
| I fear that I might get fired | 3.68 | 0.92 | 42.34*** | -0.26 | -1.22 |
| Financial Situation | |||||
| I tend to worry about paying my normal living expenses | 3.02 | 0.94 | Fixed | -0.10 | -0.55 |
| I have too much debt right now (R) | 2.98 | 0.83 | 28.54*** | -0.31 | -0.75 |
| I pay my bills on time | 2.90 | 0.80 | 26.71*** | -0.18 | -0.69 |
| Perceived Stress | |||||
| In the last month, I have been upset because of something that happened unexpectedly | 3.64 | 0.88 | Fixed | 0.01 | -0.90 |
| In the last month, I have felt that I were unable to control the important things in my life | 3.68 | 0.88 | 32.95*** | -0.15 | -0.76 |
| In the last month, I have felt nervous and stressed | 3.71 | 0.85 | 30.36*** | -0.13 | -0.88 |
| In the last month, I have dealt successfully with irritating life hassles (R) | 3.68 | 0.83 | 28.84*** | -0.24 | -0.41 |
| In the last month, I have felt that I were effectively coping with important changes that were occurring in my life (R) | 3.70 | 0.87 | 31.86*** | -0.09 | -0.71 |
| In the last month, I have felt confident about my ability to handle my personal problems (R) | 3.67 | 0.84 | 29.69*** | -0.14 | -0.66 |
| In the last month, I have felt that things were going my way (R) | 3.66 | 0.83 | 28.46*** | -0.11 | -0.65 |
| In the last month, I have found that I could not cope with all the things that I had to do | 3.69 | 0.83 | 28.76*** | -0.16 | -0.63 |
| In the last month, I have been able to control irritation in my life (R) | 3.65 | 0.85 | 29.89*** | -0.19 | -0.74 |
| In the last month, I have felt that I were on top of things (R) | 3.65 | 0.82 | 27.89*** | -0.08 | -0.87 |
| In the last month, I have been angered because of things that happened that were outside of my control | 3.67 | 0.81 | 27.60*** | -0.15 | -0.69 |
| In the last month, I have found myself thinking about things that I have to accomplish | 3.66 | 0.87 | 31.77*** | -0.14 | -0.62 |
| In the last month, I have been able to control the way I spend my time (R) | 3.63 | 0.82 | 28.08*** | -0.06 | -0.91 |
| In the last month, I have felt difficulties were piling up so high that I could not overcome them. | 3.67 | 0.83 | 29.02*** | 0.00 | -0.81 |
Note: SFL= Standardized Factor Loadings, *** p < .001
Table 2 Correlations, discriminant validity, convergent validity and internal consistency
| 1 | 2 | 3 | 4 | Mean | α | CR | AVE | MSV | ASV | |
| (1) COVID | [0.98]a | 3.19 | 0.96 | 0.96 | 0.80 | 0.21 | 0.13 | |||
| (2) JOPINS | 0.29** | [0.98] a | 3.66 | 0.96 | 0.97 | 0.79 | 0.61 | 0.25 | ||
| (3) STRS | 0.45** | 0.78** | [0.98] a | 3.67 | 0.97 | 0.97 | 0.71 | 0.61 | 0.39 | |
| (4) FINSTN | -0.33** | -0.23** | -0.59** | [0.88] a | 2.96 | 0.88 | 0.78 | 0.74 | 0.35 | 0.17 |
Note: COVID= COVID-19 Fear, JOPINS = Job Insecurity, STRS = Perceived Stress, FINSTN = Financial Situation, ** p < 0.01 level (2-tailed), a = Squared correlation [Root of AVE value], SD= Standard Deviation, α= Cronbach’s alpha, CR= Composite reliability, AVE= Average Variance Extracted, MSV= Maximum Shared Variance, ASV=Average Shared Squared Variance.
4.2 Hypothesis test
The hypotheses concerning the mediation and moderated mediation relationships were tested by regression analysis based on the bootstrap method using the Process Macro developed by Hayes (2018). The bootstrap technique used 5,000 resampling. The 95% confidence interval (CI) values from the analysis had to exclude the value zero (0) to support the hypotheses (Gürbüz, 2019; MacKinnon, Lockwood & Williams, 2004). The first hypothesis concerned the mediation relationship. The first hypothesis tested concerned the mediation relationship (Table 3 Model 1). The independent variable COVID-19 fear (β = 0.21, 95% CI [0.16; 0.24], t=10.26, p < 0.01) and the mediating variable job insecurity concern (β = 0.57 95% CI [0.53; 0.61], t= 29.26, p < 0.01) had a significant positive effect on perceived stress (R2= 0.66, p < 0.01). At the same time, COVID-19 fear (β =0.30 95% CI [0.22; 0.38], t = 7.65, p < 0.01) had a significant positive effect on job insecurity (R2 = 0.29, p < 0.01), which in turn was a mediating variable. In the model without mediating variables COVID-19 fear had a significant and positive effect on perceived stress (Y) (β = 0.38 95% CI [2.27; 2.66], t = 12.79, p < 0.01). These results show that COVID-19 fear has a significant indirect effect on perceived stress; that is, job insecurity mediates the relationship between COVID-19 fear and perceived stress (β = 0.17, 95% BCA CI [0.12; 0.22]). The point estimate of K2 was 0.206 [95% CI (0.15; 0.26)], which indicates that the mediating effect of COVID-19 fear on perceived stress via job insecurity is high.
A second regression model was set up to test the second hypothesis. To test the moderating effect of age, respondents were first divided into two groups based on their age using two-step cluster analysis. Groups were divided into 26 age (n = 386) and 44 age (n= 245). The results in Table 3 Model 2 show that COVID-19 fear (a1 path), age (a2 path) and interaction (a3 path) all significantly affected job insecurity (M) (R2= 0.23, p < 0.01). Moreover, fear of COVID-19 (β = 0.17, p< 0.01) and age (β = 0.62, p< 0.01) had significant positive effects on job insecurity. There was also a significant interaction effect (X × W) [β = 0.44, p< 0.01, CI (0.27; 0.61)], which indicated that age was moderating the relationship between COVID-19 fear and job insecurity.
Table 3 Results for testing hypotheses (n =631)
COVID = COVID-19 Fear, JOBINS = Job Insecurity, FINS = Financial Status, Bootstrap sample size = 5,000, LL=Low limit, CI=confidence interval, UL= Upper limit, **p < 0.01.
Figure 2 shows how the effect size of COVID-19 fear on job insecurity differed across age groups (26 age and 44 age). These results show that COVID-19 fear did not significantly increase job insecurity in 26 age five-star hotel employees [β = 0.007, 95% CI (-0.08; 0.10), t = 0.16, p > 0.05] whereas the relationship was significant and positive for 38 age and over group [β = 0.45, 95% CI (0.30; 0.59), t = 6.16, p < 0.01]. That is, the effect of COVID-19 fear on job insecurity increases with age for these employees.
Table 3 Model 3 shows the results of the regression analysis to test the third hypothesis. These show that job insecurity (M = b1 path), financial situation (Z = b2 path) and interaction (b3 path) all had quite strong significant effects on perceived stress (Y) (R2 = 0.82, p < 0.01) while perceived stress was positively affected by job insecurity (β = 0.52, p<. 01) but negatively by financial situation (β = -0.53, p < 0.01). The interactive effect (M × Y) was significant [β = -0.09, p < 0.01, CI (-0.13; -0.05)], which indicates that financial situation moderated the relationship between job insecurity and perceived stress. Figure 3 provides further details of the moderating effect of the employees’ financial situation on the relationship between job insecurity and perceived stress. Financial situations had a significant positive moderating effect at all two levels: low (β = 0.61, p < 0.01), and high (β = 0.43, p < 0.01). That is, the effect of job insecurity on perceived stress becomes stronger as the employees’ financial situation deteriorates.
Figure 3 Moderating effect of financial situation on the relationship between job insecurity and perceived stress
The multiple moderated mediation regression analysis results are shown in Table 3 Model 4. The indirect effect of COVID-19 fear (X) on perceived stress (Y) through job insecurity (M) was also tested to determine whether or not it depends on employee age (W) and financial situation (Z). The index of the multiple moderated mediation was significant (β = -0.040, 95% CI [-0.05; -0.01]), indicating that the indirect effect of COVID-19 fear on perceived stress via job insecurity depends on employees’ age and financial situation as moderating variables. Additionally, bootstrapping was used to test whether COVID-19 fear has a significant moderating effect on perceived stress via job insecurity, dependent on employee age and financial situation. The confidence interval values in Table Table 3 Model 4 show that the mediating effect of COVID-19 fear on perceived stress via job insecurity was stronger for 44 aged employees with worse financial situations [β = 0.26, 95% CI (0.20; 0.31)]. As employees get older, COVID-19 fear has a stronger mediating effect on perceived stress via job insecurity as their financial situation worsens. For the youngest group of employees with different financial situations, COVID-19 fear does not have a significant moderating effect on perceived stress via job insecurity. More specifically, COVID-19 fear does not have a significant indirect effect on perceived stress via job insecurity for 26 Age-Low Financial Situation [β = 0.004, 95% CI (-0.05, 0.06)], 26 Age -High Financial Situation [β = 0.003, 95% CI (-0.04; 0.05)].
5. Discussion and conclusion
COVID-19 is a very easily transmitted disease, and research on this subject reveals that people are worried about contracting COVID-19 due to the high transmission potential and mortality rate of COVID-19 (Ahorsu et al., 2020). Common routes of transmission of COVID-19 include direct transmission (through coughing, sneezing, and droplet inhalation) and contact with an infected surface (contact with the mucous membranes of the mouth, nose, and eyes) (Peng et al., 2020). In this context, hotel employees who come into direct and indirect contact with guests of different nationalities every day are at high risk of contracting the COVID-19 virus (Yu, Park & Hyun, 2021). The hotel industry, which is characterised by high levels of stress (Karatepe, Yavas, Babakus & Deitz, 2018), has become much more stressful with the COVID-19 outbreak (Jung et al., 2021). In this study, the relations between COVID-19 fear, job insecurity and stress, and the moderator role of age and financial status variables were examined.
In line with previous research (Agarwal, 2021; Islam et al., 2020; Jung et al., 2021; Pacheco et al., 2020; Wang, Mather & Seifert, 2018), our results show that COVID-19 fear increases both job insecurity and stress, and job insecurity also increased stress. COVID-19 is a serious life-threatening respiratory disease. This can create a fear of being infected, which negatively affects individuals' psychology (Mertens et al., 2020). Studies reveal that COVID-19 fear is predominantly associated with anxiety, depression and stress (Bakioğlu, Korkmaz & Ercan, 2020; Satici et al., 2020). Although dismissals were prohibited during the COVID-19 outbreak, there were reports in the press that some employees were dismissed after being diagnosed with COVID-19 (Atas, 2020). Fear of being infected and worrying about losing their job after being infected have devastating effects on employees (Agarwal, 2021). Gasparro et al. (2020), in their study on dentists in Italy, determined that COVID-19 fear played a moderator role in the relationship between perceived job insecurity and depression. In other words, the relationship between job insecurity and depressive symptoms in dentists with high fear of COVID-19 was found to be stronger than in those with low fear of COVID-19. Zhang et al. (2020) found that the psychological and physical health of people who were forced to stop working due to the COVID-19 outbreak were negatively affected. Labrague and Santos (2021), in their study on nurses in the Philippines, determined that fear of COVID-19 decreased job satisfaction and increased organisational and professional turnover intentions. Employees who show signs of being infected should be able to take leave without fear of losing their jobs, so the necessary inspections should be made for businesses to implement the laws.
Another important finding of the study was that the age variable played a moderator role in the relationship between COVID-19 fear and job insecurity. The effect of COVID-19 fear on job insecurity differs significantly according to the age of the employees. While COVID-19 fear does not have a significant effect on job insecurity in employees aged 37 and under, it has a significant effect on employees aged 38 and over. This result shows that as the age of the employees increases, the fear of losing their job may also increase, they may also be more financially insecure and worry more about their careers. Other studies indicate that serious conditions such as anxiety and depression are more common among older people and linked to economic hardship (Mistry et al., 2021). One study revealed that older people suffer higher levels of COVID-19 fear (Hossain et al., 2020).
Similarly, another study revealed that during the SARS epidemic, elderly individuals were more likely to take precautions against infection (Wu, Chan & Ma, 2005). The results obtained are important in terms of showing that the effect of pandemic diseases differs according to the age factor. Another important finding obtained in the study is that the relationship between job insecurity caused by the COVID-19 pandemic and stress differs according to the financial status of the employees. In other words, the employees' financial situation plays a moderator role in the relationship between job insecurity and stress. Basic living conditions are based on the management of personal financial resources (Rasdi et al., 2021), and this result shows that having financial well-being is an important factor in protecting an individual's mental health in the face of adverse events. The obtained findings also contribute to the COR theory (Hobfoll, 1989). According to the COR theory, resources such as job security offer a protective function against stress. When these resources are lost, if sufficient resources cannot be obtained to replace the losses, the stress levels of individuals increase (Hobfoll, 2001).
5.1 Theoretical implications
Past research indicates that responses to the pandemic vary widely among individuals. However, the factors determining these variations have not been clear (Killgore, Taylor, Cloonan & Dailey, 2020). Therefore, this study used a mediated moderation model to understand the impact of the COVID-19 pandemic on people in more detail. As a result of the research, it has been determined that the indirect effect of COVID-19 fear on stress through job insecurity varies according to the age of the employees (18-37 years and 38 years and above) and their financial status (good-weak). The effect of COVID-19 fear on job insecurity was stronger for 38 age and over employees, while the effect of job insecurity on stress was weaker for employees with better financial situations. So, various individual and conditional antecedents of stress during the COVID-19 pandemic are identified. We believe that these results make important contributions to the hospitality literature. They also carry important practical implications for hotel managers and hospitality professionals both in Turkey and worldwide.
The results contribute to a better understanding of the effects of COVID-19 on hotel employees. It is important to support research from a macro-perspective on the pandemic's sociological, economic and psychological consequences with studies of the psychological states and behaviours of those in the hospitality sector, which has been heavily affected by the pandemic. This study fills an important gap in the literature by providing empirical data on how hotel employees are psychologically and behaviorally affected by COVID-19 (Škare et al., 2021). A very limited number of empirical studies have been conducted on this matter. The study provides a theoretical framework to explain the stress experienced by employees during the pandemic. Thus, our findings may significantly contribute to the hospitality research literature. The study also shows how situational factors like age and financial status shape employee experience in special cases, such as the COVID-19 pandemic.
5.2 Practical implications
This study also has practical implications for hospitality managers and professionals. First, hotels must take serious precautions to protect employees because COVID-19 fear causes job insecurity and stress. Emphasising employee safety during the pandemic can help the hotels survive the crisis (Hu, Yan, Casey & Wu, 2021) and avoid damaging employees’ psychological well-being and performance. In short, it should not be forgotten that employee safety is just as crucial as guest safety. Second, given that job insecurity mediates the effect of COVID-19 fear on stress, this highlights the importance of building a stable and safe work environment to reduce job insecurity in hotels. Since the hospitality sector has experienced an unprecedented loss of work due to COVID-19 (Filimonau, Derqui & Matute, 2020), putting employees on unpaid leave as a cost-cutting measure merely exacerbates their problems. As well as coping with the fear and anxiety from the pandemic, they also must face an uncertain future and job insecurity. While imposing unpaid leave certainly has cost advantages for companies, it causes stress for employees, reduces their feelings of trust and fairness and weakens their psychological contract due to the uncertainty (Baranik et al., 2019). Thus, hotel administrators should review their unpaid leave policies and consider measures like rearranging working hours and redistributing duties instead of reducing the number of employees. If hotels must continue with their unpaid leave policies, these must be communicated openly and closely with employees to make them feel secure.
Moreover, hotels should openly share with the employees the significant problems caused by COVID-19 and include them in the decision-making process. Transparent communication has strategic importance in the hospitality industry for employee well-being and performance (Ariza-Montes et al., 2019). It appears particularly important for older employees who feel job insecurity more intensively.
Finally, there are important practical implications of our finding that job insecurity causes more stress for employees with poorer financial situations. According to Karakas (2020), the COVID-19 pandemic has had traumatic effects on lower-income groups in terms of lack of income or unemployment. Here, governments and hospitality representatives have as much responsibility as individual hotel administrators. Social and financial security measures must be developed to protect employees in the tourism and hotel industry from such sudden crises, while hotel administrations should develop policies to support employees financially as much as possible. For example, after closing two thirds of its hotels during the pandemic, Accor decided to allocate 25% of its dividend payments, 70 million Euros, to its employees (Nhamo et al., 2020). Without such approaches, the lack of supportive measures may make hospitality industry occupations less attractive in the long term (Baum & Hai, 2020) so that skilled workers gravitate towards other sectors (Mao, He, Morrison & Coca-Stefaniak, 2020). In sum, it is particularly important that this paper focused on hotel hospitality, which may be the most negatively affected industry by COVID-19. We believe that the results contribute noticeably to the hospitality literature and the industry.
5.3 Limitations and future recommendations
This study has several limitations to consider. First, many hotels in Alanya were reluctant to participate in the study because of the pandemic conditions. That’s why the researchers used non-probabilistic purposive sampling. Second, it was conducted with hotels in only one destination due to time, resource, and social distancing restrictions. Thus, the generalizability of the results is limited. Investigating job insecurity and stress among hotel employees in different contexts during COVID-19 times would significantly contribute to the literature. Third, this study used quantitative analyses to explore the causal relations between COVID-19 fear, job insecurity and stress, and the moderator effects of age and financial situation. Given the complexity of the theoretical model, future studies may use a mixed-methods approach or qualitative analysis to improve the model’s explanatory power. Fourth, the data relies on the subjective perceptions of employees. Especially in cases of job insecurity and poor financial situation, employees may have provided responses they deemed to be expected. Thus, future studies could apply qualitative data collection methods to gain more in-depth insights from the employees. Finally, the dependent variable was stress. However, future studies could investigate various other dependent variables to understand how stress caused by COVID-19 affects employee behaviour and organisational performance.
