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. 2020 Nov 10;94:102754. doi: 10.1016/j.ijhm.2020.102754

Will we have the same employees in hospitality after all? The impact of COVID-19 on employees’ work attitudes and turnover intentions

Dunja Demirović Bajrami a,b,*, Aleksandra Terzić a, Marko D Petrović a,b, Milan Radovanović a,b, Tatiana N Tretiakova b, Abosa Hadoud c
PMCID: PMC8586792  PMID: 34785836

Abstract

A crisis caused by COVID-19 pandemic affected the whole world leaving long-lasting effects on almost every aspect of human lives. The aim of this study was to test how different effects of COVID-19, expressed through job insecurity, employees' health complaints occurred during isolation, risk-taking behavior at workplace and changes in the organization, may impact work-related attitudes (job motivation and job satisfaction) and turnover intentions of the employees in hospitality industry. Based on the data collected from 624 hospitality workers from Serbia, the results indicated that job insecurity and changes in the organization were predictors of all outcomes, in a negative direction, while risk-taking behavior acted as a predictor of job satisfaction only, also in a negative direction. The significance of demographic characteristics, as control variables, showed that age and marital status had significant impact on job motivation and turnover intentions. The theoretical and practical implications were discussed.

Keywords: Hospitality industry, COVID-19, Employees, Work related attitudes, Turnover intentions

1. Introduction

COVID-19 disease caused by SARS-CoV-2 virus has changed the whole world in just a few months, leaving long-lasting effects on the global economy and each individual. The first cases were reported in Wuhan, China, in December 2019, and on 15 June 2020, more than 3.6 million people were marked as active cases with infection (with over 450,000 deaths) in over 200 countries (Worldometer, 2020). Job insecurity, unemployment and health risks were marked as the most serious consequences on the global level (Godinic et al., 2020).

After the pandemic was declared globally, over 90% of the world population had to face with a lot of restrictions, including international and domestic travel bans. In just a few weeks, something unimaginable happened – destinations dealing with overtourism became destinations without tourists, empty city centers, beaches, museums, etc. Cancelled flights, events and travel arrangements had a negative impact on direct service providers, but other organizations that were indirectly involved in the supply chain felt the consequences, too. The socio-economic implications of COVID-19 pandemic outlined the fact that the hospitality industry has been sector that was hit the hardest by the outbreak of COVID-19, with impacts on both supply and demand side, and workers in this sector were faced with potentially devastating hardships (Martins et al., 2020). As a direct consequence of COVID-19, the World Travel and Tourism Council warned that 50 million jobs in the global hospitality industry may be at risk (Nicola et al., 2020).

The greatest decline in staff numbers was reported in hospitality sector – hotels and restaurants, while even at the beginning of the pandemic about 65% of tourism businesses reported difficulties in paying invoices and reported liquidity problems. As a result of the crisis, millions of people in hospitality sector have already lost their jobs, and have been thrown into the poverty abyss (Jones, Comfort, 2020) while others were experiencing extremely high levels of job insecurity and physical and psychological risks associated with it.

The aim of the study was to analyze how different effects of COVID-19, expressed through job insecurity, employees' health complaints occurred during isolation, risk-taking behavior at workplace and changes in the organization, may impact work-related attitudes (job motivation and job satisfaction) and turnover intentions of the employees in hospitality industry. The theoretical model presented in Fig. 1 illustrates relationship between the proposed variables.

Fig. 1.

Fig. 1

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The theoretical model of the research.

These four effects of COVID-19 have not been analyzed in previous research related to hospitality, while the investigation of the impact of some effects was mostly represented among healthcare workers.

2. Theoretical framework

2.1. Impact of job insecurity on work-related attitudes and turnover intentions

Perceived job insecurity was marked as one of the most stressful moments in the career of every employee (Reisel et al., 2010). Employees’ subjective perception of a possibility to lose their job was recognized in the literature as quantitative job insecurity (De Witte et al., 2015).

Previous research showed that job insecurity was negatively associated with job satisfaction and motivation leading to undesirable employees’ behavior and responses (Reisel et al., 2010). In hospitality, Vujičić et al. (2014) confirmed that high level of job insecurity negatively influenced job satisfaction among hotel employees. Job insecurity accelerated and encouraged development of turnover intentions since employees saw it as one of the effective ways to deal with the stress caused by not knowing whether they would keep their job (Artz, Kaya, 2014). Job insecurity and turnover intentions were positively related, showing that the more employees felt insecure about keeping their current job, the more they would think about leaving the organization (Lee, Jeong, 2017). Shropshire and Kadlec (2012) and Akgunduz and Eryilmaz (2018) highlighted that job insecurity and burnout were the strongest factors that caused the development of turnover intentions in IT and hospitality sectors and even made employees think about changing careers.

Research done before and throughout the crisis like Great Recession showed that job insecurity was significantly increased, while job satisfaction was reduced and this situation lasted for as many as several years after the recession had been finished (Margalit, 2013). The global crisis caused by COVID-19 inevitably changed the perception of usual job insecurity and placed it to the extreme levels due to the inability to predict the duration and strength of the crisis. In this study, it is expected that quantitative job insecurity will have negative relationship with job motivation and job satisfaction, while it will be positively related with turnover intentions.

2.2. Impact of employees' risk-taking behavior at workplace on work-related attitudes and turnover intentions

Risk-taking behavior was marked as employees' exposure to dangerous materials, equipment or other inadequate working conditions at their workplaces (DeJoy et al., 2004) and perceived risks at the workplace predicted changes in job motivation and job satisfaction (Bjorklund, 2007). If employees were concerned about the negative effects of the possible dangerous working conditions and if they questioned the justification for exposing themselves to such risks, it decreased their motivation and satisfaction with the job. On the other side, feeling unsafe at the workplace was a significant predictor of high turnover intentions. Unsafe workplace and exposure to dangerous working conditions was one of the most common reasons for thinking about leaving a job among healthcare workers (Wen et al., 2018), truck drivers and grocery workers (Smith, 2018). Storseth (2006) revealed that when employees found themselves in an unpredictable situation, they ignored some safety instructions or implemented them inadequately, in order to prove that they are useful to the organization and to keep their positions.

During the COVID-19 pandemic, after the healthcare practitioners, the next high-risk occupation was a variety of job positions in tourism and hospitality sector, marked as particularly vulnerable to the risk of contracting the disease (Chinazzi et al., 2020). The state of global panic that was caused by the threat of the disease spreading, was accompanied by the introduction of strict safety measures, causing anxiety and frustration (Mao et al., 2020), especially among the workers in the service-providing sector. Therefore, it is expected that increased risk-taking behavior at workplace during pandemic will decrease job motivation and job satisfaction among hospitality workers, while it will increase their turnover intentions.

2.3. Impact of employees’ health complaints which occurred during isolation on work-related attitudes and turnover intentions

Recent research on the impact of COVID-19 highlighted that isolation contributed to the feelings of loneliness, pessimism, anger and confusion resulting in higher blood pressure (O’Neil et al., 2020), reduced life satisfaction (Li et al., 2020), or even caused mental deterioration (Godinic et al., 2020). The research focused on employees returning to work after the illness showed that they were most concerned whether they would be as productive as before (Soeker et al., 2008). Tan et al. (2020) revealed that employees who returned to work during the pandemic of COVID-19 did not show signs of increased anxiety and stress although these symptoms were present during the isolation. So far, such research mostly focused on examining how different conditions impact employees' mental and physical health or how those conditions reflect on employees' performance and productivity (Ozcelik, Barsade, 2018), but not on how they impact work-related attitudes and turnover intentions. Going back to work after the justified absence (due to an illness or some other problem) was mostly seen as a way to increase employees' quality of life and as some type of therapy (Steiner et al., 2004), and the workplace gave employees the sense of normality upon return (Peteet, 2000). Thus, it is expected that health problems occurred during isolation caused by COVID-19 will not reflect negatively on job motivation and job satisfaction, nor encourage employees to consider leaving the organization.

2.4. Impact of organizational changes on work-related attitudes and turnover intentions

The perception of implemented or planned organizational changes reflects employees’ evaluation of the fairness of changes carried out by the management (Elias, 2009). Herscovitch and Meyer (2002) expressed an opinion that organizational changes caused fear among employees because they were not sure how these changes would affect them. Organizational changes reduced the level of job satisfaction and job motivation of those who remained at work, especially if those changes were perceived as unfair and reflected carelessness of the management (Schouteten, Van Der Vleuten, 2013). Although most previous studies showed strong compatibility in findings that organizational changes had negative impact on job motivation and job satisfaction, this was not the case when considering its effects on turnover intentions. Some research revealed that sudden organizational changes caused stronger turnover intentions (Kim, 2015; Lu et al., 2017), while others indicated that turnover intentions were not so strong among employees who stayed in the organization since they felt that they were more valued (Ngirande et al., 2014). As Folkman (1984) pointed out, events that employees have not encountered before, but might be perceived as threatening (as in this case COVID-19), can cause different reactions on workplace and require a longer period of adjustment.

Attitudes towards organizational changes made during COVID-19 pandemic were noted as affective and cognitive responses (Yousef, 2017) reflecting employees' judgment on actual changes and their personal estimation if those changes were necessary, fair, or caused a concern about their position in the organization. It is assumed that if the changes were perceived as unfair, they would have negative relationship with job satisfaction and job motivation, while having a positive relationship with turnover intentions.

2.5. Relationship between work-related attitudes and turnover intentions

Identification of the factors which can cause turnover intentions has been present in research for decades, making impact of work motivation and job satisfaction as the most significant ones (Zeffane, Bani Melhem, 2017).

According to Kim (2015; 2018), job motivation had strong negative relationship with turnover intentions. The research showed that turnover intentions were not so pronounced among employees who were motivated to do their work and who recognized their job as a source of learning and progress (Cimbaljević et al., 2020; Mijatov et al., 2018). On the contrary, employees were more prone to developing turnover intentions if they couldn’t develop their careers, if they performed the same and monotonous tasks, or had limited opportunities for learning new things. Dysvik and Kuvaas (2010) concluded that motivation had the strongest negative relationship with turnover intentions, compared to other analyzed variables, and it was proven that intrinsic motivation helped people in dealing better with challenging situations (Ryan, Deci, 2000). In this research, intrinsic motivation was taken into consideration when analyzing impact on turnover intentions, assuming that these two constructs will have a strong negative direct relationship.

Extant research has examined the relationship among job satisfaction and employees' turnover intentions (Zeffane, Bani Melhem, 2017; Liu, Lo, 2017; Huang et al., 2017), pointing out that employees who were satisfied with their job were less prone to consider leaving the organization and that job satisfaction can be consider as one of the most consistent predictors for turnover intentions. Various studies highlighted that job satisfaction was negatively associated with turnover intention, but such relationship remained unconfirmed in research of Tongchaiprasit and Ariyabuddhiphongs (2016) conducted among chefs in hotels. In this particular study, job satisfaction had one dimension as recommended in previous research connected with turnover intentions (Huang et al., 2017), including employees’ attitudes towards work conditions, available opportunities and expected outcomes. It is expected that job satisfaction will have a direct and negative effect on turnover intentions.

2.6. Control variables

Researchers provided evidence that demographic variables like gender, age and marital status were significant for the variables marked as dependent in this research.

Age and gender positively related to job satisfaction and job motivation, while with turnover intentions, findings were inconsistent. Kipkebut (2013) found out that older employees at the university were more satisfied with their jobs and did not have so pronounced turnover intentions compared to their younger colleagues explaining it with the fact that older employees invested more effort and time and that opportunities for finding a new job were limited, while Du Plooy and Roodt (2013) determined that older employees who thought more carefully about leaving the job were employees who were 50 years and older. While Tanova and Holtom (2008) proposed that younger employees were more likely to take risks and have turnover intentions (as part of career advancing and exploration), Akova et al. (2015) found that younger employees in hotel industry showed higher organizational commitment that affected turnover intention in the reverse direction (due to being relatively inexperienced and with fewer job opportunities). The same authors indicated that female voluntary turnover rates may be lower compared to males, while larger-scale research showed that women's turnover rates were slightly higher compared with their male counterparts (Chen et al., 2018).

Regarding the marital status, research revealed that married employees were less likely to develop turnover intentions compared to unmarried employees since married employees had more responsibilities toward their family members, including financial responsibility (Cetin, 2006; Kipkebut, 2013; Du Plooy, Roodt, 2013). Also, married employees seem to be more satisfied with their jobs (Azim et al., 2013). Chen (2006) indicated that marital status was one of the main factors which contributed to the occurrence of turnover intentions among flight attendants, explaining that flight attendants who were single expressed higher intentions to leave their job, while Lu et al. (2002) found negative relationship between marital status and turnover intentions since unmarried hospital workers had greater intention to leave compared to their married colleagues.

Based on all of this, the significance of gender, age and marital status was taken into consideration when analyzing the effects of COVID-19 on work-related attitudes and turnover intentions.

3. Methodology

3.1. Sample and data collection procedure

The data used in this study were collected among employees in the hospitality industry in Serbia. The sampling procedure was done in March and April 2020, a time during which most of the countries, including Serbia, were affected by the pandemic caused by COVID-19. An email was sent to managers of different tourism businesses located in 10 most visited destinations in Serbia, inviting them to take part in the research by sending a link to the survey to all of their employees. All the responses were collected via a web-based survey. Most of the managers (75%) reported that their organizations had undergone some organizational changes due to pandemic. These changes included reduced employees' salaries, employees were sent to an unpaid annual leave, some departments were merged, part-time employees lost their jobs, and some branches were closed. The managers sent a link to the survey only to those who were still employed during the research period. A total of 624 questionnaires were received. The respondents came from a wide range of organizations (accommodation sector 36%, travel agencies 28%, restaurants 19%, transportation 9%, and agencies for events and conferences organization 8%), while 79% of the respondents were frontline employees. Demographic information indicated that 39% of the respondents were between ages of 31 and 40 or between 41 and 50 (36%). In terms of gender, 56% of the respondents were female. With regard to education, 71% had a university degree, while the rest (29%) had a high school degree. Approximately, 61% were married (51% had children) and 34% were single.

3.2. Research instrument

The measures of several constructs were derived from existing scales and studies. Effects of COVID-19 were defined as independent variables, while the second group of independent variables was control variables. Employees’ perceived job insecurity was measured with 10 items based on scales developed by De Witte (1999) and Storseth (2006), showing uncertainty and worry about whether respondents will keep the present employment due to the impact of COVID-19. Respondents expressed their agreement/disagreement with the statements ranged from 1 (strongly disagree) to 5 (strongly agree) for the items such as: “COVID-19 is a risk for the company's closedown” and “I’m concerned regarding the continuance of my work”. Around 67% of the respondents agreed or totally agreed that people in their organization may lose jobs due to COVID-19, 61% felt unsecure regarding the future of their work, while 37% of the respondents believe that COVID-19 can cause company's closedown if not permanently, then temporarily.

Employees' health was measured by 13 items which represented the presence of negative symptoms (mental and physical health complaints) developed by Eriksen et al. (1999) through so-called “Subjective Health Complaints Inventory”. Participants were asked to rate on a 5-point scale (1= never, 5 = always) to which extent they experienced different symptoms during isolation like sleep problems, sadness/depression, tiredness, headache, neck pain, and migraine. The respondents reported that sometimes or often during isolation they had problems with sleeping (52%), tiredness (46%), sadness/depression (38%), or they had headaches (41%), or felt neck and back pain (52%).

The scale of risk-taking behavior at workplace, developed by Storseth (2006) and Rundmo and Iversen (2007), was slightly modified. For example, statement “I take risks to get the job done” was divided into two statements: “I will take health risks at my job by having contact with clients” and “I will take health risks at my job by having contact with my colleagues”, while the statement “I violate regulations and safety instructions because they are too difficult to follow” was phrased as: “Safety instructions due to COVID-19 will be too difficult to follow at my workplace”. In total, the scale had 7 items. The items expressed respondents concerns regarding following safety instructions in order to perform the expected tasks and the impact on their health when they return to their workplace, rated on a 5-point scale (1 = strongly disagree to 5 = strongly agree). Around 43% of the respondents agreed that it would be too difficult to follow safety instructions at their workplaces (mostly those who work in accommodation and transportation sectors and in restaurants) or that they will not have enough time to implement all safety instructions (31%). Furthermore, 30% of the respondents agreed or strongly agreed that having contact with clients after they return to work can expose them to health risks.

Ito and Brotheridge (2007) scale was used to measure if employees perceive changes made in the organization during the pandemic as fair. The scale had four items, such as: “The steps that company took during the pandemic (e.g. salary reduction) were fair to me. Respondents expressed their opinion on a 5-point scale (1 = strongly disagree to 5 = strongly agree). Only 29% of the respondents agreed that changes in the organization occurred as a result of the pandemic were fair.

Three variables were marked as possible outcomes and dependent variables – job motivation, job satisfaction and turnover intentions (final dependent variable). Work motivation was measured by six selected items from scale developed by Warr et al. (1979) and Sjoberg and Lind (1994) in order to express the extent to which respondents will be personally stimulated/motivated to work at the present job after the pandemic (e.g. “I look forward to going back to work after the pandemic”, “My work will be still motivating”). Responses were measured on a 5-point scale (1 = strongly disagree to 5 = strongly agree). The results showed that 42% of the respondents look forward to going back to work and they will still find their work challenging (35%), but they are not sure if they will be still motivated to do their job (37%).

Job satisfaction was assessed by a 6-item scale developed by Rundmo and Iversen (2007). The scale was designed to measure how much employees will be satisfied with different aspects of their job when they return to work. Items like job content, degree of responsibility, and recognition for good performances were assessed on a 5-point scale (1 = very dissatisfied, 5 = very satisfied). The respondents think they will be the least satisfied with job content (28%), degree of the variation in the job (36%), and recognition for good performances (37%). Significant percentage of the respondents (27%) expressed neutral attitude, showing that they are not sure what their job will be like after the pandemic.

The measure of employees' turnover intentions included six items. Two items came from Fried et al. (1996) scale, but one was divided into two – “I am planning to look for a new job during the next 12 months” to “I am planning to look for a new job during the next 12 months in tourism industry” and “I am planning to look for a new job during the next 12 months in some other industry, rather than tourism”. Next two items were derived from Meyer and Allen (1984) research (e.g. “It would be hard to find employment outside my organization”), while one item was added (“After the pandemic, I do not find working in tourism attractive anymore”). Respondents expressed their tendency to leave the organization on a 5-point scale (1 = strongly disagree, 5 = strongly agree). The results showed that the respondents agreed that they will look for a new job (44% within the tourism industry), but 62% agreed or strongly agreed that finding a new job won't be easy.

3.3. Data analysis

The data analysis was done by using the statistical software package SPSS 22. A confirmatory factor analysis (CFA) was used to assess the validity and reliability of the measurements used in the study. The CFA results suggested that the model had a good fit of the measurement (χ2/df = 2.014, p < 0.001, goodness of fit index (GFI) = 0.925, confirmatory fit index (CFI) = 0.980; incremental fit index (IFI) = 0.973; root mean square error of approximation (RMSEA) = 0.053). Internal consistency among the measures was supported with values of the Cronbach’s α coefficients (values ranged from 0.734 to 0.892). After checking the validity and reliability of each construct, structural equation modeling (SEM) was used to assess the overall fitness of the model proposed in Fig. 1. The SEM was used to test how effects of COVID-19 predict changes in job motivation, job satisfaction and turnover intentions. The main and interactive effects of job insecurity, employee's health complaints which occurred during isolation, risk-taking behavior at workplace, and fairness of organizational changes were tested by using hierarchical multiple regression analysis. The means of all the variables were standardized (z-scores) and then multiplied so they could form the interaction term. Hierarchical multiple regression analyses were used to examine contribution, direct and indirect impact of different effects of COVID-19 on job satisfaction, job motivation and turnover intentions. The casual order of the variables was reflected by different steps that were used to enter variables.

Table 1 shows the means, standard deviations and correlations between the ten constructs and the greatest correlation between the constructs was lower that all of the square roots of an average variance extracted. Job insecurity, risk-taking behavior, and fairness of organizational changes correlated negatively with job motivation, job satisfaction and turnover intentions, while employees' health during isolation was negatively correlated only with job motivation. Both of the components of the work attitudes (job motivation and job satisfaction) were related with turnover intentions, in a negative direction. Finally, controls (age, gender and marital) showed that gender did not have negative correlation with any of the proposed variables, while marital status and age created negative correlations with job insecurity and turnover intentions, plus age was correlated with risk-taking behavior in a negative direction, too.

Table 1.

Descriptive statistics, scale reliability, and correlations among the variables.

M SD 1 2 3 4 5 6 7 8 9 10
  • 1.

    Gender

 1.50 0.50
  • 2.

    Marital status

 2.05 1.12 .07
  • 3.

    Age

 3.64 0.89 −.01 .04
  • 4.

    Job insecurity

 4.20 3.10 .04 −.29* −.22* (.76)
  • 5.

    Employee's health

 3.43 2.18 .09 .09 .19 −.15 (.66)
  • 6.

    Risk-taking behavior

 3.98 2.01 .09 −.14 −.18* −.09 .04 (.83)
  • 7.

    Fairness of organizational changes

 4.01 1.29 .06 .05 −.14 −.14 .08 0.11 (.74)
  • 8.

    Job motivation

 3.18 0.88 .03 .17 −.13* −.13* −.03* −.33** −.35* (.81)
  • 9.

    Job satisfaction

 3.88 1.14 .05 .16 .16 −.17** .10 −.28** −.24* .57* (.77)
  • 10.

    Turnover intentions

 4.19 1.10 .14 −.41** −.29* −.23** .19 −.16 −.29* −.55* −.59** (.85)
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Note. Scale reliability estimates are on the diagonal, in parentheses.

*

p < .05.

**

p < .01.

4. Results

Table 2 shows that two effects of COVID-19 were direct predictors of job motivation when the significance of age was accounted in Step 2. Although the amount of the explained variance for the effects of marital status on job motivation decreased in Step 2, the impact was still significant (β = .11, p < .05), suggesting that married people, people with families were more motivated for the job than those who were single. On the other side, the amount of the explained variance in job motivation was increased by introducing effects of COVID-19 (ΔR2 = .27, p < .001), but not all the four effects had the same effect. Only job insecurity and fairness of organizational changes showed to predict job motivation significantly, both in negative direction, while risk-taking behavior did not have a significant impact. This indicated that insecure job in tourism caused by COVID-19 will have a negative impact on job motivation, while changes, that were undertaken as a response to the pandemic, will decrease job motivation. On the other side, risk taking behavior will not have a significant impact on job motivation, probably because employees believe that these measures are only temporary. The results on employees' health showed that mental and physical health complaints that occurred during isolation will not have impact on job motivation, suggesting that those complaints were caused mostly by the restrictions on movement, impossibility to see friends and family members or to go to work. Overall, as much as 31% of the variance in job motivation was significantly accounted, F(5, 065) = 15.24, p < .001.

Table 2.

Hierarchical regression analysis: predictors of job motivation.

Job motivation
β (t)
Step 1		 β (t)
Step 2
Step 1: Control variables
Age .06
(0.71)		 .05*
(0.69)
Marital status .14*
(1.78)		 .11*
(1.62)
Step 2: Effects of COVID-19
Job insecurity −.12**
(−1.54)
Employees' health
Risk-taking behavior −.11
(−1.25)
Fairness of organizational changes −.09**
(−0.88)
R2 .07 .29
Adjusted R2 .06 .31
F 7.03*** 15.24***
ΔR2 .27
ΔF 19.88***
Dfs 2213 5065
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*

p < .05.

**

p < .01.

***

p < .001.

As shown in Table 3 , job insecurity, risk-taking behavior, and fairness of organizational changes showed to predict job satisfaction significantly, in a negative direction. This suggested that the perceived insecure continuance of work, threat that company can be closed temporary or even permanently because of COVID-19, changes made in the organization during the pandemic or the expected changes after the pandemic can negatively affect job satisfaction. Although risk taking behavior did not have a significant impact on job motivation, the results revealed that the proposed safety instructions and perceived health risks after the employees return to work can be an important predictor of job satisfaction. However, none of the control variables were found to act as significant predictors when it comes to job satisfaction. As in the previous analysis, employees' health complaints did not have any significant impact. Taken together, the model variables explained 24% of the variance in job satisfaction, F(3,103) = 7.43, p < .001.

Table 3.

Hierarchical regression analysis: predictors of job satisfaction.

Job satisfaction
β (t)
Step 1		 β (t)
Step 2
Step 1: Control variables
Age −.05
(−0.44)		 −.04
(−0.46)
Marital status .04
(0.38)		 .03
(0.27)
Step 2: Effects of COVID-19
Job insecurity −.16**
(−1.72)
Employees' health
Risk-taking behavior −.14**
(−1.55)
Fairness of organizational changes −.13**
(−1.65)
R2 .09 .21
Adjusted R2 .08 .24
F 7.16*** 7.43***
ΔR2 .06
ΔF 7.37***
Dfs 2099 3103
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* p < .05.

**

p < .01.

***

p < .001.

Table 4 shows that, in the second step, the regression model of turnover intentions marked the two effects of COVID-19, job insecurity and fairness of organizational changes, as predictors when the significance of age and marital status was accounted for. Step 3 revealed that work attitude variables can be predictive when it comes to turnover intentions, since when they were added, job motivation (β = −.15, p < .01) and job satisfaction (β = −.38, p < .001) had significant effect, while the explained variance increased ΔR2 = .33, p < .001. The effect of age and marital status, although slightly decreased, still remained significant showing that older employees and those who have families were less willing to leave their employer. Overall, as much as 47% of the variance in turnover intentions was significantly explained, F(6,586) = 26.42, p < .001.

Table 4.

Hierarchical regression analysis: predictors of turnover intentions.

Turnover intentions
β (t)
Step 1		 β (t)
Step 2		 β (t)
Step 3
Step 1: Control variables
Age −.23**
(−3.18)		 −.21**
(−.3.03)		 −.19**
(−3.14)
Marital status −.35**
(−4.29)		 −.32**
(−4.06)		 −.29**
(−4.61)
Step 2: Effects of COVID-19
Job insecurity −.10**
(−.57)		 −.09**
(−0.71)
Employees' health −.06
(−.10)
Risk-taking behavior −.09
(−.1.03)		 −.07
(−0.66)
Fairness of organizational changes −.12**
(−1.50)		 −.08**
(−0.63)
Step 3: Work attitudes
Job motivation −.15**
(−1.67)
Job satisfaction −.38***
(−4.35)
R2 .14 .17 .52
Adjusted R2 .10 .12 .47
F 21.16*** 9.17*** 26.42***
ΔR2 .05 .33
ΔF 2.74 33.19**
Dfs 1258 3374 6586
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* p < .05.

**

p < .01.

***

p < .001.

5. Discussion and conclusion

Job insecurity perceived by the respondents proved to be a strong predictor of job motivation, job satisfaction and turnover intentions. The results indicated that job insecurity caused by some crisis can change the level of motivation which is in line with the previous research. During the world economic crisis in 2008/2009, a critical change in employees' motivation was recorded (Hitka, Sirotiakova, 2011), and job insecurity affected employees who worked before and after the crisis by drastically reducing their job motivation level (Mehri et al., 2011). A negative correlation between job insecurity and job satisfaction pointed to a fact that if the employees do not feel secure about the future of their job, it will cause a lower level of job satisfaction. Increased job insecurity caused by COVID-19 was a strong predictor of higher turnover intentions, since the respondents consider looking for a new job, despite being “survivors”. Although the origin of job insecurity can be marked as an external problem in times of crisis, changes in the organization perceived as less fair indicate that employees blame organization's internal problems for job insecurity, too (Van Hootegem et al., 2018). However, the respondents were aware that it would be hard to find new employment since almost every sector was hit by COVID-19. Research focused on labor market during crisis showed that opportunities for job selection were quite limited (Snorradottir et al., 2013) and that leaving the organization may not be the best way to deal with job insecurity (Kim et al., 2012). Creating more challenging tasks, respecting the effort invested in doing the job and giving support to the employees can increase their commitment to the organization and create desire to stay, even when the economy recovers. The good thing was that those who think of looking for a new job still think of looking for it within the tourism industry, showing that COVID-19 did not significantly reduce the attractiveness of tourism industry for employment.

Although the results of the research revealed that mental and physical health complaints occurred during isolation were not a significant predictor of work attitudes or turnover intentions, these complaints should not be neglected by employers. Employers need to make an effort and show their employees that their workplace is an environment where one can talk openly about all health complaints, especially mental health problems, without any prejudice. All of this can contribute to physically and mentally healthier staffand reduce economic and social costs in the long-term period.

Employees in tourism industry considered returning to work during the pandemic as a risk for their health. The results indicated that risk-taking behavior was a strong predictor of job satisfaction, i.e. working under new circumstances can negatively impact job satisfaction. Research on the impact of COVID-19 was mostly concentrated on healthcare professionals. According to Shanafelt et al. (2020), the lack of appropriate personal protective equipment and lack of access to up-to-date information and communication were sources of anxiety, while shift management, protective equipment, education, meetings and health measures had positive impact on job motivation and job satisfaction (Zhou et al., 2020). In order to protect employees and potential customers, employers need to provide clear information, instructions and supervision. Besides the global safety recommendations, an organization should create workplace health and safety policies (this can also be at the branch level – for example, joint policies for hotel industry). Supervisors can organize online trainings about COVID-19 transmission, what steps organization plan to implement in order to protect employees at their workplaces, what employees need to do in order to keep themselves and their colleagues safe, and which safety instructions the customers will follow. The respondents in this study expressed concerns that they will not have enough time to implement all the safety instructions and that it would be difficult to follow them when they start working with tourists. The concerns were much more expressed among hotel and restaurants' employees since the larger number of people is circulating in these facilities. With the aim to reduce those concerns and avoid that employees break some rules in order to get the job done, supervisors can schedule few breaks during work time to avoid gathering of larger groups, provide enough time between two shifts for regular cleaning of all high-touched tools and surfaces.

The changes that occurred in organizations due to COVID-19 prove to be strong predictors of both work-related attitudes and turnover intentions. The majority of those who remained on their workplaces did not perceive organizational changes as fair and they felt that their status within the organization would change. All of this has caused that employees feel insecure about their future in the organization and they are not sure what role they will have in the organization. Perceiving changes in the organization as unfair may show that employees expected the management to react better, to make different decisions and to protect employees. It is proven that poor managerial decision-making can cause a feeling of job insecurity (Vahtera et al., 1997). During political crisis in Egypt in 2011, most of the workers in tourism industry expressed that they lost faith in their organizations, they were less motivated to work and their intention to leave the organization was increased because management did not know how to work in unstable conditions, nor were the decisions perceived as fair procedures (Elshaer, Saad, 2016). Negative impacts of the perceived changes due to COVID-19 were in line with some previous research. Markovits et al. (2014) highlighted that employees who remained in their jobs after crisis expressed lower motivation and job satisfaction because they sympathized with those who were fired and they were worried that something similar could happen to them, while Elshaer and Saad (2016) showed that changes like salary reduction or mandatory vacation can encourage the remaining workers (survivors) to leave the organization and find a new job. The results from this research pointed out that in uncertain and unpredictable situations (like a pandemic), competencies of the managers and knowledge of crisis management can be crucial in managing the business and keeping employees motivated to do their jobs. Supervisors or HR staff should try to provide sufficient amount of information on time to all employees and give them enough time to process the information and ask questions. When employees come back to work after a situation like a pandemic, supervisors should show that they understand how employees feel after all, give clear guidance on how to manage job duties or to appreciate the way someone is doing a job. The leadership style in situation like this should be based on informing employees, taking care of their health and well-being, and enabling them to actively participate in decision making to make it easier for everyone to get through the situation.

If the control variables were taken into consideration, age and marital status showed to have significant impact on job motivation and turnover intentions. The results indicated that older participants (40+) and employees with families do not have such a clear intention to leave the organization and were more motivated, compared to younger and single employees. Employees who have families probably feel more responsible because someone is depending on them and they cannot afford hasty decisions or being unemployed. This is in line with some previous research, where it was concluded that a family has a great impact on employee’s decisions to stay in the current organization due to financial responsibilities (Emiroğlu et al., 2015). Results showed that older employees will be more motivated to work after the pandemic is over. During the SARS outbreak in Taiwan, senior nurses were more willing to be in the first line of the defense and they were facing with a crisis much better because of their practical experience (Wu et al., 2012). This shows that managers, including tourism managers, should reconsider the role of senior employees in the organization, since they can act as mentors and leaders, especially in difficult and uncertain times. On the other side, younger employees can be motivated if they have more control in their workplaces, do challenging tasks, and are praised or rewarded for what they do well. Also, younger employees are more willing to adapt to changes. Supervisors should have in mind that older employees were more concerned about the impact of COVID-19 on their health when they return to work, and it can be reflected on their motivation. In the research about the clinical feature of COVID-19, it is shown that elderly people were more affected than younger people (Rothan, Byrareddy, 2020), compared to, for example, pandemic caused by H1N1 in 2009 when younger people (in their 20s) were more anxious about infection at work because they were more susceptible to infection (Matsuishi et al., 2012).

Since the data for this study were collected during the pandemic, the results have important implications for managers in hospitality industry since they can better understand possible changes in employees' attitudes when they return to work. Based on the results, managers can change or create new HR practices that will, in the first line, help employees to cope better with the effects of COVID-19 and then increase employees' motivation and satisfaction with job and decrease intention for looking for a new job.

Future research can bring more detailed results by analyzing the effects of COVID-19 between two or more countries, especially if those countries have similar cultural or economic circumstances. Also, future research can analyze if different organizational strategies, CSR initiatives or employees' commitment and trust in organization can have impact on work attitudes and turnover intentions and alleviate the negative consequences of the pandemic. Additional socio-demographic variables like household income, number of household members/children, occupation of spouse, and psychological characteristics – human values (ambition, risk aversion, family dedication, etc.) can be taken into consideration. In order to see if the attitudes of employees have changed in the same way in other industries, it would be useful to replicate this study on employees in other industries since there is no branch of industry that was not affected by the pandemic.

Declaration of Competing Interest

None.

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