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Article

The Effects of Workaholism on Employee Burnout and Turnover Intent at Deluxe Hotels during the COVID-19 Pandemic: Evidence across Generations

Center for Converging Humanities, Kyung Hee University, Seoul 02447, Republic of Korea
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Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5227; https://doi.org/10.3390/su15065227
Submission received: 17 February 2023 / Revised: 3 March 2023 / Accepted: 13 March 2023 / Published: 15 March 2023

Abstract

:
The coronavirus has caused unprecedented damage to the hospitality industry that cannot be compared to those caused by previous global crises. This study hypothesized that employee burnout and turnover intent can vary depending on their perceptions of workaholism, with the assumption that workaholism’s negative impact differs across generations. This study demonstrated that workaholism among hotel employees tends to increase their burnout and turnover intent. The examination of the intergenerational moderating role in the relationship between the influence of workaholism on burnout and turnover intent revealed that compared to Generations X and Y, Generation Z has a stronger negative relationship with workaholism.

1. Introduction

For the past three years, the coronavirus has caused unprecedented damage to the hospitality industry incomparable to previous global crises [1]. Many employees have been advised to take leaves of absence, whereas those who remain are frequently subjected to excessive work hours, leading to job insecurity and job shocks [2]. Thus, workaholic tendencies are promoted or aggravated by long work hours, meritocracy, blurred work–life boundaries, and job instability in the competition-oriented hotel industry. Although they are limited in number, studies on workaholism have consistently reported similar findings, implying that it is reasonable to regard workaholism as a poor investment in excessive work [3,4,5,6]. In a situation in which prolonged economic shocks from the COVID-19 outbreak are increasing fear of unemployment and employment instability, workaholism can become more severe. Thus, workaholism is likely to become more widespread among employees during the current era of the COVID-19 pandemic, in which quantitative job insecurity due to issues such as employee reductions is prevalent. Moreover, affective event theory (AET) emphasizes that emotional conditions at the workplace play an important role in employees’ emotional behaviors and attitudes [7]. This suggests that even seemingly trivial emotions and the events that create these emotions within the organization should not be overlooked, and a work environment related to prevalent workaholism may influence employees’ burnout, behaviors, and emotional responses.
Additionally, because hotel employees are characterized by chronic exhaustion and excessive physical labor through interpersonal services, given the nature of their duties, research on workaholism involving hotel employees can be applied more effectively than other studies. Moreover, many hotel companies currently reduce labor costs by encouraging their employees to take unpaid leave to cope with the current COVID-19 pandemic, which may expose hotel employees to more excessive work than before. Therefore, it is very timely to examine the negative impacts of this situation. However, studies on this topic are rare. At this point, investigating the degree and negative behavioral impacts of workaholism perceived by employees at five-star hotels can be important in determining how the hotel industry will recover and how the rapidly changing industry will be able to sustain itself in the future.
Concurrent with the coronavirus pandemic, from the perspective of generation theory, the hospitality industry is experiencing a demographic shift in its workforce [8]. Members of Generation Z are expected to become the largest group of hotel workers in the near future [9]. This is because intergenerational conflicts occurring in the workplace stem from differences in the way older and younger generations feel about changes in the organizational climate. Generation Zers, in particular, are overwhelmingly dissatisfied with the low wages, long working hours, and physical labor associated with the hotel industry [10]. In addition to this tendency, this generation exhibits different organizational values from those of other generations [11], and the work values resulting from these generational differences will have different influences on the outcome variables caused by workaholism. In this context, this study hypothesized that employee burnout and turnover intent can vary depending on individuals’ perceptions of workaholism, with the assumption that workaholism’s negative impact differs across generations. This study thus aimed to determine whether workaholism perceived by hotel employees has a significant effect on their burnout and turnover intent and moderates generation-specific characteristics (Figure 1).

2. Literature Review and Conceptual Model

2.1. Workaholism in the Hotel Industry

Work is a central component of life that satisfies basic human needs [12]. Job loss, in contrast, causes people to experience extreme psychological problems [13], so some individuals spend significantly more time at work than expected to counteract this prospect. This group of people is defined as workaholics [14]. Workaholism, first coined by Oates [15], refers to a compulsive or uncontrollable desire to work incessantly. It is a tendency to work much harder than a job requires and put in more effort than coworkers expect. In general, this tendency is driven by internal compulsion, personal needs, and impulses rather than by external factors, such as financial rewards, career perspectives, or organizational culture [16]. Although some researchers have suggested that workaholism has positive aspects [17], many more interpret workaholism as an excessive and persistent behavior that leads to detrimental consequences for an organization, indicating that workaholism should not be considered a positive job condition [18,19]. Workaholics tend to lack autonomy because of their obsession with work and inability to enjoy the process of working [20]. They often devote considerable time to work activities and give up family or personal activities, think about work during nonwork hours, and exert excessive effort beyond their responsibilities [21]. Similar to these conditions, the hotel industry is regarded as negatively affecting employees through long working hours, high job demands, and a high level of work–life conflict caused by unsocial working hours (night work, weekend work, holiday work, etc.; [22,23]). To overcome the challenging situation under the prolonged COVID-19 crisis, the hotel industry is also proposing various business strategies for survival with active solutions such as unpaid leave, replacement with low-wage temporary workers, and outsourcing except for key areas [2]. Consequently, hotel employees’ job anxiety continues, and it may be safely said that this leads them to overly commit themselves to their jobs and perform excessive tasks [24]. In a study on the hotel industry, Pan [25] reported that hotel managers are cognitively committed to their work in addition to the considerable time they spend in the workplace, and it is important to prevent hotels from becoming a breeding ground for overwork given that superiors’ workaholism negatively affects their subordinates’ performance. Shin and Shin [24] stated that hotel employees’ workaholism contributes to work–family conflict, so hotels should develop a strategy to minimize employee workloads. In a study targeting managers in the hospitality industry, Gordon and Shi [21] noted that workaholism plays a mediating role between the experience of recovery and job satisfaction and that workaholism should be neither vaguely guarded against nor encouraged. As shown thus far, studies on the hotel industry are very rare, and this subject has drawn attention from scholars in the field of hotel business due to the lack of sufficient academic research on workaholism in the hotel industry. Therefore, this study is likely to contribute to reducing the negative impacts of workaholism in the hotel industry.

2.2. Model Development and Hypotheses

2.2.1. Relationship between Workaholism and Burnout

Workaholic tendencies are a major cause of burnout [26], and Moyer et al. [27] reported that burnout is the main outcome measure of workaholism. Burnout refers to a feeling of excessive emotional and physical resource exhaustion [28]. Wen et al. [29] stated that long working hours are associated with various psychological risks to hotel employees, including sleep problems. Sonnentag and Zijlstra [30] outlined that workaholism generally refers to a tendency to work excessively hard. They argued that because workaholics have such a strong desire to accomplish things, they cannot control their compulsive desire to work and thus expend considerable energy on work without sufficient recovery. Additionally, Schaufeli et al. [16] indicated that workaholism tends to increase employee distress and psychosomatic complaints and that employees consume many resources in their obsession with work, often leading them to feel burned out [31]. Graves et al. [32] suggested that workaholics are more engrossed in work than non-workaholics because they have high work compulsiveness, which increases stress and ultimately leads to emotional exhaustion. Likewise, Innanen et al. [33] found that workers who experience mainly negative emotions at work tend to experience burnout and workaholism simultaneously. These results and observations suggest that burnout has a very strong correlation with workaholism; notably, high fatigue and cynicism are common in people with high workaholic tendencies. This result suggests that increased time and effort spent on work leads to greater exhaustion. Moreover, Clark et al. [14] stated that workaholism and emotional fatigue also have a very strong correlation because workaholics invest excessive time and energy in work, which reduces their ability to disconnect from work. According to Moyer et al. [27], workaholism has a positive relationship with exhaustion, as well as close relationships with all three subdomains of burnout. Therefore, they pointed out the need for employers to recognize that it is undesirable for organizational members to engage in excessive labor and thus maintain a culture that discourages it. Eventually, despite the existence of various strategies to protect employees from burnout, establishing a culture that discourages workaholism is also highly important. From a similar point of view, Cheung et al. [34] said that workaholics experience greater burnout than non-workaholics because they continue to invest their cognitive, emotional, and physical resources in their work. This idea indicates that workaholism can increase employee burnout. Additionally, Choi [35] stated that employees’ workaholism not only has a serious impact on their health but also poses significant harm in terms of burnout, and that workaholism leads to burnout and long hours of work eventually increases tension, thereby elevating the level of burnout. Based on previous research on workaholism perceived by employees, this study proposes the following hypothesis with the assumption that employees’ workaholic tendencies have a positive effect on their burnout:
Hypothesis 1. 
Employee workaholism positively influences burnout.

2.2.2. Relationship between Workaholism and Turnover Intent

As a predictor of employees’ tendency to leave their jobs [36], turnover intent refers to the intentions of an organization’s members to give up their qualifications and leave their current job [37]. Burke and MacDermid [38] found that employees who work excessively and are obsessed with work are more likely to have strong intentions to quit. Killinger [39] argued that workaholics work too hard to avoid negative feelings that they experience when they are not engaged in work, such as irritability, anxiety, and guilt, and that they consequently come to develop negative thoughts about their organization. Concentration on work can become an excuse not to participate in social work functions, thus lowering life satisfaction [40] and relationship quality [41]. These findings suggest that addiction to work can negatively affect organizations. Ng et al. [42] indicated that high levels of workaholic tendencies—which refer to an overcommitment to work and excessive time spent on it—in employees lead to stronger intentions to leave their organizations. The authors noted that turnover intention demonstrates clear causality as an outcome variable of workaholism. Schaufeli et al. [16] suggested that employees’ workaholism increases their self-sustaining commitment and suggested that even this commitment to remain at their organizations in terms of exchanges is not reduced through workaholism. Additionally, Shimazu and Schaufeli [43] stated that overall job performance has a negative relationship with workaholism but not with the intent to leave. Beek et al. [3] similarly reported that workaholism has a negative correlation with job satisfaction and work commitment and a positive relationship with turnover intent, suggesting that policy-level management is required to prevent employees from becoming workaholics at the corporate level. In a similar context, De Beer et al. [44] pointed out that compulsive overworking could negatively influence organizational commitment, thereby increasing employee turnover intention. Kim and Cha [45] stated that workaholism induces strong turnover intent. Kim et al. [46] found from a slightly different point of view that workaholic bosses may cause emotional exhaustion in junior employees, thus increasing their turnover intent. Sánchez-Medina et al. [47] specified that the driving force, which constitutes one aspect of workaholism, has a positive effect on turnover intent. Given these findings, a second hypothesis was proposed:
Hypothesis 2. 
Employee workaholism positively influences turnover intent.

2.2.3. Relationship between Burnout and Turnover Intent

The positive relationship between employee burnout and turnover intent has been empirically supported in various business settings [48,49]. Hughes [50] argued that even if employees experience burnout at work, they may remain at work for a variety of personal reasons, but this is ultimately detrimental to the organization because such employees tend to only work enough to maintain their employment. Leither et al. [51] also stated that employee burnout is very strongly associated with employees’ withdrawal from work. Business-wise, Kang et al. [52] found that burnout costs organizations substantial amounts of money and may lead to detrimental consequences in terms of performance. Han et al. [53] suggested that employees are more likely to save their own resources in response to exhaustion experienced in an organization, which can lead to stronger turnover intent. Hsiao et al. [54] reported that the more burnout is experienced in an organization, the stronger the intention to change jobs becomes. Many recent studies have also shown that burnout perceived by employees has a significant effect on turnover intent [1,55,56]. Given these findings, a third hypothesis was developed:
Hypothesis 3. 
Employee burnout positively influences turnover intent.

2.2.4. Moderating Role of Employee Generation Characteristics

A generation can be defined as a group of people who are close in age and share important social events [57]. Because each generation has lived in different environments, the social problems and perceptions each generation experiences inevitably differ as well [58]. Conversely, the similarities among members of a generation tend to be evident, even in the way they live their lives, including their participation in the workforce [59]. Therefore, making efforts to understand the characteristics of each generation within an organization is essential to understanding organizational behavior [60]. Specifically, research on the value of labor for each generation has revealed that the value of labor is affected by generational experiences more than by age and maturity [61]. Goh and Okumus [9] stated that it is inevitable for differences to arise between generations in terms of understanding the work process and its outcomes, so a new method and approach are needed to solve this potential problem due to intergenerational differences. To elucidate intergenerational differences in workaholism’s negative effects in this study, I divided and investigated the following generations: Generation X (born 1965–1979), which was the major generation of the past, and Generations Y (born 1980–1998) and Z (born after 1999), which are the modern major generations [62,63]. In the workplace, Generation X is characterized by tendencies to place great importance on career goals, growth opportunities, and a sense of belonging or teamwork in an organization [64,65]. Generation Y pursues work autonomy, has excellent adaptability to new technologies from network experience, and values transparency in communication [55]. A number of studies have found that Generations X and Y have similar job values and share a tendency to seek challenging jobs that provide opportunities for growth, continuous skill development, and active participation in the decision-making process [66,67]. In contrast, Generation Z considers well-being the most important organizational element and places the highest value on job flexibility, values, and universality [68]. One study showed that Generation Zers who work in the hospitality industry recognize that the hospitality industry itself is an interesting sector because there are several opportunities to be in contact with diverse people, but they find it considerably difficult to experience various events that occur because of people [10]. Goh and Okumus [9] also argued that equal opportunity, equality, and fairness are the most important values that organizations must pursue for Generation Zers and that to promote this generation’s enthusiasm for the job, organizations should engage in sustainable practices. Ozkan and Solmaz [69] reported that Generation Zers seek independence at work and prefer to find joy while working. Self et al. [70] also described how Generation Zers are highly adaptable to social media, hate being interfered with regarding minor details, and want to receive feedback on their work. However, according to Robins et al. [71], young talents applying to the hospitality industry are often disenchanted with the field after their initial work or internship. Therefore, workaholism’s negative effect may be greater in the younger generation. However, despite the fact that Generation Zers play a pivotal role in the workplace, research on their general workplace attitudes has been remarkably limited. Therefore, this study hypothesizes that the degree of workaholism’s positive influence on burnout and turnover intent perceived by employees differs depending on the generation. In particular, the degree of workaholism’s negative influence would be stronger among Generation Z than among Generations X and Y.
Hypothesis 4. 
Employee generation moderates workaholism’s effects on burnout and turnover intent.
Hypothesis 4a. 
A younger generation’s workaholism will have a greater influence on their burnout.
Hypothesis 4b. 
A younger generation’s workaholism will have a greater influence on their turnover intentions.

3. Research Methodology

3.1. Sample and Data Collection

This study’s samples included full-time employees working at five-star hotels in Seoul that had at least 200 bedrooms and provided comprehensive hospitality services. In this study, five-star hotels were named deluxe hotels. Based on the assumptions (a) that there were 22 five-star hotels in Seoul, (b) that each hotel’s food and beverage department had an average of 500 employees, and (c) that approximately 11,000 employees worked at five-star hotels in Seoul, we calculated the number of subjects as 400 at an error level of 5%. To this end, we contacted all 22 hotels in Seoul and, after obtaining permission from the manager of each hotel’s human resource management department, provided a voluntary survey form for employees to fill out. A self-reported convenience sampling method was employed because it was impossible to obtain consent from every respondent. The survey began in a separately prepared place during a break at work after the study’s purpose was explained to the subjects and their consent to participate was obtained. To increase the response rate, a ballpoint pen worth USD 3 was presented to employees who responded to the survey. After their distribution, the completed questionnaires were sealed in an envelope to protect the employees’ anonymity and collected by the researcher one week later. A total of 500 questionnaires were distributed, with 50 questionnaires sent to each hotel, and then 408 of them were collected and 350 of the collected questionnaires were used for the final analysis (70.0%). All questionnaires with incorrect or unclear markings were removed. The response rates for each hotel are as follows: hotel A, 35/50, 70.0%; hotel B, 31/50, 62.0%; hotel C, 32/50, 64.0%; hotel D, 41/50, 82.0%; hotel E, 39/50, 78.0%; hotel F, 29/50, 58.0%; hotel G, 38/50, 76.0%; hotel H, 33/50, 66.0%; hotel I, 36/50, 72.0%; and hotel J, 36/50, 72.0%. Additionally, the samples from the results of a preliminary survey were not collated in this survey.

3.2. Instrument Development

This study used measurement items whose reliability and validity had been confirmed through previous studies. According to Brislin’s [72] suggestion, the questionnaire, originally written in English, was translated into Korean through the reverse translation method. It was then translated back into English, at which point two experts confirmed whether the original meaning was retained. To check the completed questionnaire’s reliability, a pilot test was conducted with 50 hotel employees, and some terms that were not translated smoothly were modified. In addition, in-depth interviews were conducted with 10 managers who had been in the field for more than 15 years to investigate whether there were any confusing questions and if the sentences’ context was correct. The survey questions were confirmed through this process, and the questionnaire was organized as follows: The parameters were grouped into five categories (workaholism, burnout, turnover intent, work engagement, and demographic characteristics), with a seven-point Likert scale used to measure the hotel employees’ tendencies toward the first four. To measure the employees’ perceptions of workaholism, eight items were adapted from Aziz et al. [73], in which respondents were asked to answer to how often they feel a specific way. Burnout was measured using three subcomponents suggested by Maslach et al. [74] and Maslach and Jackson [28]: emotional exhaustion (three items), depersonalization (three items), and personal accomplishment (three items). In addition, as a dependent variable, turnover intention was measured using four items with questions derived from Seashore et al. [75]. To measure work engagement, which was defined as a positive state of mind characterized by vigor, dedication, and immersion [76] and used as the marker variable in this study, three items from Schaufeli et al. [76,77] were used. Finally, the questionnaire included questions regarding the respondents’ demographic information (age, gender, and education level) and occupation-related details (tenure and position).

3.3. Analysis Methods

In this study, the two-step approach proposed by Anderson and Gerbing [78] was used to test the proposed hypotheses. All measurement items (including the marker variable) were tested for validity and reliability through second-order factor analysis. A structural equation modeling (SEM) analysis was performed to verify the proposed measurement model and determine the significance of the hypotheses. A multigroup analysis was performed as well to determine the differential influences among generations. In addition, to assess whether there was any common method bias, a marker variable (work engagement) was used to reduce errors in self-reported data [79].

4. Results

4.1. Sample Profile

Table 1 shows the profiles of the study sample. By gender, 74.1% of the respondents were male, and 28.6% were female. Generation Z accounted for 28.3% of the sample, whereas Generations Y and X constituted 50.3% and 21.4%, respectively. As for education level, four-year college graduates, at 62.6%, accounted for most of the sample. In terms of tenure, those with 6–9 years of employment were in the majority at 35.7%. Regarding department affiliation, front-of-house employees accounted for 38.9%, back-of-house employees accounted for 43.1%, and others accounted for 18.0%.

4.2. Measurement Model

According to Podsakoff et al. [80], this study applied a technique called common method bias (CMB) before the data collection process because participation in a study should be entirely optional. In addition, a marker variable was used to solve the common method bias problem that may occur when samples are collected at the same time to perform a survey [81,82]. As shown in Table 2, there was no significant difference in the correlation between the exogenous and endogenous variables when compared with the case where work engagement was the marker variable. Therefore, CMB was determined not to be a major problem in this study. Based on these findings, the validity and reliability of the measurement variables were verified. In this study, the validity of the factor structure for the measurement parameters was determined through confirmatory factor analysis (CFA) using the two-step approach suggested by Anderson and Gerbing [78]. A second CFA was performed to find the factor structure of the three subcomponents of burnout (emotional exhaustion, depersonalization, and personal accomplishment; [83]), and the fit of the model was found to be excellent (χ2 = 498.602; df = 315; χ2/df = 1.583; GFI = 0.906; NFI = 0.960; TLI = 0.983; CFI = 0.985; IFI = 0.985; RMSEA = 0.083). Table 3 shows the results obtained from the analysis of the measurement model for the parameters included in the research model (workaholism, the secondary components of burnout, and turnover intent) and the marker variable (work engagement). The standardized estimates of all items were 0.70 or higher, and their t-values were also higher than 8.0 (p < 0.001). The synthetic reliability estimates (0.839–0.953) and Cronbach’s alpha values (0.887–0.976) of each factorized result value exceeded the general minimum requirement of 0.70, and the AVE value was also higher than 0.50, which confirmed the presence of internal consistency and one-dimensionality [84,85]. Table 2 presents the relationships between the measurement items. The analysis revealed a significant and positive relationship among all measurement items, confirming that the hypothesis and direction were in accordance.

4.3. Structural Equation Modeling

SEM analysis was used to test the hypotheses. The fit of the model was found to be adequate (χ2 = 391.554; df = 246; p < 0.001; χ2/df = 1.592; GFI = 0.914; NFI = 0.964; CFI = 0.986; RMSEA = 0.041). Table 4 shows the standardized path coefficients, t-values, and p-values for the relationships between the proposed hypotheses. Hypothesis 1 predicted that a greater perception of workaholism in a hotel employee would correlate with higher burnout tendencies, and this hypothesis was supported (β = 0.697; t = 12.894). This finding indicates that employees with strong workaholic tendencies are particularly likely to experience job-related burnout. Next, Hypothesis 2 proposed that stronger observed workaholism would be associated with higher turnover intent in employees, and this hypothesis was also supported (β = 0.378; t = 10.017). This finding indicates that when people perceive their jobs as the most important thing and focus only on work, they are more likely to think about job turnover. Hypothesis 3 also predicted that burnout perceived by hotel employees would increase their turnover intent, and the path estimate, as expected, indicated a strong positive causal relationship. Therefore, Hypothesis 3 was supported (β = 0.555; t = 7.744). Finally, Hypothesis 4 predicted that workaholism’s influence on employee burnout and turnover intent would be strongest in Generation Z. The presence of any distributional differences among the variables (workaholism, burnout, and turnover intention) measured along with the variable of generation was identified before the moderating effect of generation was verified. According to the results of a chi-square test, the generation had no statistically significant distributional differences from any of the other variables. In addition, generation-related measurement invariance was investigated with the results presented in Table 5. The differences in the invariant model were not statistically significant, with 38 to 40.810 degrees of freedom at an alpha level of 0.05, which means that the metric invariance was satisfied. This confirms that the measurement invariance of the three moderating variables used in this study was not a problem [54]. Table 6 shows the results of the analysis, which verified the moderating role of each employee’s generation in these causal relationships using the difference in the degrees of freedom between the unconstrained and constrained models. Considering that the difference in the degrees of freedom between the models is 2, if the difference in the chi-square value was greater than 5.99, it would be interpreted as having a significant moderating effect. The analysis revealed that the influence of workaholism awareness on burnout was greater in Generation Z than in Generations X and Y, meaning that Hypothesis 4a was accepted. In contrast, Hypothesis 4b was rejected because there was no intergenerational difference in the influence of workaholic awareness on turnover intention. Therefore, Hypothesis 4 was only partially accepted. These results suggest that members of Generation Z, the youngest generation surveyed in this study, are more likely to experience burnout through their workaholic tendencies; therefore, workaholism’s negative influence on members of Generation Z, to whom autonomy and creativity are central values, is stronger than that on other generations. Various assumptions can be made about the reason for no differences in workaholism’s influence on turnover intentions depending on the generation. However, given that workaholism has a greater influence on burnout than turnover intention, it may be assumed that turnover intentions were lowered due to the uncertainty related to COVID-19, and thus workaholism’s negative influence on turnover intentions had little difference across the generations.

5. Discussion and Conclusions

5.1. Conclusions

The purpose of this study was to investigate workaholism’s effects on burnout and turnover intent among hotel employees and thereafter identify the moderating roles of employees’ generations in these causal relationships. This study revealed that workaholism among hotel employees tends to increase their burnout and turnover intent. This result is consistent with the work of Schaufeli et al. [31] and Clark et al. [14], who investigated the relationship between workaholism and burnout, and that of Burke and MacDermid [38] and Beek et al. [3], who examined the positive relationship between workaholism and turnover intention. Additionally, the present study verified a significant causal relationship between burnout and turnover intent, which is consistent with previous studies indicating that burnout increases turnover intent [1,51,53]. The examination of the intergenerational moderating role in the relationship between the influence of workaholism on burnout and turnover intent revealed that, compared to Generations X and Y, Generation Z has a stronger negative relationship with workaholism. These results are consistent with those of Ozkan and Solmaz [69] and Robins et al. [71], who reported that workaholism’s negative impact is greater in members of Generation Z, who place great importance on adequate work–life balance while seeking independence.

5.2. Theoretical Implications

Most studies on this topic have mainly investigated workaholism in general, with very few studies specifically targeting hotel workers. Especially considering that workaholism becomes aggravated in situations that elevate internal anxiety, such as job instability, this study has produced meaningful findings on workaholism’s ripple effect as perceived by hotel employees. This study is particularly meaningful in that it targeted deluxe hotels, which suffered the most during the pandemic. Hotel employees highly depend on human resources, and these resources’ effectiveness ultimately determines organizational performance, which also indicates this study’s importance. This empirical study may therefore be the first to investigate workaholism’s negative effects on burnout and turnover intent in the hospitality industry during the unprecedented coronavirus pandemic, and its results are expected to greatly contribute to the hospitality literature. Consequently, this study has provided a step forward in terms of integrating studies on workaholism, burnout, and turnover intentions in the context of the hospitality industry. This study contributes to a wide range of literature on workaholism by showing that workaholism can increase employee burnout and turnover intentions. The findings of this study indicate that workaholic tendencies in the workplace can become an important factor that can increase employee burnout and turnover intentions. Therefore, this study provides a theoretical basis for future studies by signifying that special attention should be paid to workers who experience high levels of workaholism. Furthermore, this study not only theoretically emphasizes the dangers of workaholism and explores the justification of its negative influences but also provides an academic contribution to future research. The study introduced a unique moderating variable, generation, which distinguished this study from other studies that have focused only on simple causal relationships and emphasized the need to expand current theory. This study also lays the foundation for additional workaholism research to empirically identify implicit assumptions about workaholism’s negative impacts.

5.3. Practical Implications

This study’s results suggest important practical implications regarding workaholism. Considering that workaholism can increase employee burnout and turnover intent, these results highlight the necessity of devising practical measures to reduce workaholism. They also provide empirical evidence that measures are required to lower the negative effects of workaholism at the organizational level. This, in turn, can mitigate employee burnout and prevent the loss of human resources. Because the hotel industry in particular is characterized by unsocial and relatively long work hours, the work environment is accustomed to excessive work, which can increase employee exhaustion and anxiety. The coronavirus era’s instability may especially have made workers more prone to workaholism. Therefore, it is necessary for hotel managers to devise constructive measures to minimize workaholism’s negative impacts. Specifically, it is important to establish a horizontal and stable work environment so that employees feel that overworking is not a means of expressing loyalty to the organization. It is also essential for managers themselves to realize that excessive immersion in work does not improve organizational performance, as well as to create conditions to reduce employees’ psychological concerns and prevent turnover. Furthermore, it is necessary to create a culture in which employees can freely communicate through positive social interactions and create systematic devices at the hotel level so that employees feel less pressure related to performing their duties and can more easily adapt to the organization. Additionally, training programs can inform hotel employees of workaholism as a detriment to organizational performance. This can help prevent workaholism, as can implementing sabbatical years and giving employees time to reimmerse themselves in the organization after sufficient burnout recovery. Furthermore, it is necessary to clarify job roles through clear guidelines or coaching and to provide employees with counselors, mentor/mentee programs, or seminars to help them find meaning in their jobs. Companies must also eliminate existing behaviors that encourage workaholism and develop institutional devices such as educational programs on how to work wisely. Creating an environment that imposes penalties to prevent excessive working hours or showing the management’s will to do so will also significantly reduce workaholism’s negative impact. Consequently, employee turnover, which can occur as a ripple effect of workaholism, not only causes short-term costs and losses to the organization but also influences other organizational members’ turnover in the long term. For this reason, employee turnover is a highly important factor contributing to organizational performance. Therefore, this study’s results indicate the importance of changing organizational culture as it relates to workaholism to prevent employee turnover. Finally, the finding that workaholism’s negative influence is greater in Generation Z employees, who will play a major role in the hotel industry in the future, than in Generations X and Y suggests new implications at the organizational level. Specifically, organizations must create an environment that encourages rest so that Generation Z can flexibly adapt, and they must provide situational conditions that allow these employees to rest sufficiently by encouraging an adequate work–life balance. It is likely most important to understand the psychological state that Generation Z can experience while performing excessive tasks; provide them with various learning opportunities; and create an organizational culture and atmosphere that supports psychological counseling, rest, and leisure activities exclusively for this generation. It is necessary to create an atmosphere in which Generation Z is trained and supported with positive psychology without feeling job pressure. Organizations should also lead this generation to expect to build close ties with other employees through devices such as mentoring systems and to view their duties from a positive perspective through special lectures on humor and counseling services.

5.4. Limitations and Future Research

Despite its informative results, this study has several limitations. First, because the study is cross-sectional and only included one-time measurements, similar longitudinal studies are still required. Second, because the study’s sample was limited to hotel employees as part of the hospitality industry, it is difficult to generalize the results to all hotels. This necessitates an analysis of hotels and other organizations in the hospitality industry in a follow-up study. Third, this study did not investigate workaholism’s antecedent variables, such as organizational culture and climate, which can affect employees’ workaholic tendencies; thus, future studies should expand to include these variables. Fourth, although the study featured the negative performance variable of turnover intent, the correlation of performance with positive work aspects, such as job satisfaction, organizational citizenship behavior, and performance, should be considered in future research. Additionally, although this study analyzed burnout using a single construct through a secondary factor analysis, it will also be meaningful to conduct future research aimed at identifying organic causal relations between workaholism and burnout’s subfactors. Fifth, although this study identified the moderating role of generation, general characteristic variables that affect workaholism’s influence within an organization should be considered. If these limitations are supplemented in the future, more substantial study results would be obtained. Sixth, since various demographic characteristic variables may have been involved in the causality of the model, perfect control of these parts will be needed in future studies. Finally, South Korea’s collectivist culture may have contributed to workaholism’s negative influence. In Triandis et al. [86], collectivism was characterized by a tendency to place greater meaning on the group’s goals and on accepting them, even if one is uncomfortable with them. In this respect, it would be meaningful to conduct a comparative analysis involving other cultures in future research.

Author Contributions

Conceptualization, H.-H.Y.; Methodology, H.-S.J., Y.-S.J. and H.-H.Y.; Validation, H.-S.J.; Formal analysis, H.-S.J. and H.-H.Y.; Investigation, Y.-S.J.; Resources, H.-S.J. and H.-H.Y.; Data curation, H.-S.J. and Y.-S.J.; Writing—original draft, H.-S.J.; Writing—review & editing, H.-S.J.; Visualization, Y.-S.J.; Supervision, H.-H.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a grant from Kyung Hee University in 2022 (KHU-20220132).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the first author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chi, O.H.; Saldamli, A.; Gursoy, D. Impact of the COVID-19 pandemic on management-level hotel employees’ work behaviors: Moderating effects of working-from-home. Int. J. Hosp. Manag. 2021, 98, 103020. [Google Scholar] [CrossRef]
  2. Jung, H.S.; Jung, Y.S.; Yoon, H.H. COVID-19: The effects of job insecurity on the job engagement and turnover intent of deluxe hotel employees and the moderating role of generational characteristics. Int. J. Hosp. Manag. 2021, 92, 102703. [Google Scholar] [CrossRef] [PubMed]
  3. Beek, I.; Taris, T.W.; Schaufeli, W.B.; Brenninkmeijer, V. Heavy work investment: Its motivational make-up and outcomes. J. Manag. Psychol. 2014, 29, 46–62. [Google Scholar] [CrossRef] [Green Version]
  4. Bonebright, C.A.; Clay, D.L.; Ankenmann, R.D. The relationship of workaholism with work-life conflict, life satisfaction, and purpose in life. J. Couns. Psychol. 2000, 47, 469–477. [Google Scholar] [CrossRef]
  5. Burke, R.J. It’s not how hard you work but how you work hard: Evaluating workaholism components. Int. J. Stress Manag. 1999, 6, 225–239. [Google Scholar] [CrossRef]
  6. Burke, R.J. Workaholism in organizations: Psychological and physical well-being consequences. Stress Med. 2000, 16, 11–16. [Google Scholar] [CrossRef]
  7. Weiss, H.M.; Cropanzano, R. Affective Events Theory: A Theoretical Discussion of the Structure, Causes and Consequences of Affective Experiences at Work. In Research in Organizational Behavior: An Annual Series of Analytical Essays and Critical Reviews; Staw, B., Cummings, L., Eds.; JAI Press Inc.: Stamford, CT, USA, 1996; Volume 18, pp. 1–74. [Google Scholar]
  8. Shulga, L.V. Front-line employee self-determination in value Co-Creation: Generational profiles. Int. J. Hosp. Manag. 2021, 48, 479–491. [Google Scholar] [CrossRef]
  9. Goh, E.; Okumus, F. Avoiding the hospitality workforce bubble: Strategies to attract and retain generation Z talent in the hospitality workforce. Tour. Manag. Perspect. 2020, 33, 100603. [Google Scholar] [CrossRef]
  10. Goh, E.; Lee, C. A workforce to be reckoned with: The emerging pivotal Generation Z hospitality workforce. Int. J. Hosp. Manag. 2018, 73, 20–28. [Google Scholar] [CrossRef]
  11. Leung, X.Y.; Sun, J.; Zhang, H.; Dung, Y. How the hotel industry attracts generation Z employees: An application of social capital theory. J. Hosp. Tour. Manag. 2021, 49, 262–269. [Google Scholar] [CrossRef]
  12. Blustein, D.L. The role of work in psychological health and well-being: A conceptual, historical, and public policy perspective. Am. Psychol. 2008, 63, 228–240. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Lucas, R.E.; Clark, A.E.; Georgellis, Y.; Diener, E. Unemployment alters the set point for life satisfaction. Psychol. Sci. 2004, 15, 8–13. [Google Scholar] [CrossRef] [Green Version]
  14. Clark, M.A.; Michel, J.S.; Zhdanova, L.; Pui, S.Y.; Baltes, B.B. All work and no play? a meta-analytic examination of the correlates and outcomes of workaholism. J. Manag. 2016, 42, 1836–1873. [Google Scholar] [CrossRef]
  15. Oates, W. Confessions of a Workaholic: The Facts about Work Addiction. Psychology 1971, 6, 111–112. [Google Scholar]
  16. Schaufeli, W.B.; Taris, T.W.; Rhenen, W.V. Workaholism, burnout, and work engagement: Three of a kind or three different kinds of employee well-being. Appl. Psychol. Int. Rev. 2008, 57, 173–203. [Google Scholar] [CrossRef] [Green Version]
  17. Hu, Q.; Schaufeli, W.; Taris, T.W.; Hessen, D.J.; Hakanen, J.; Salanova, M. East is east and west is west and never the twain shall meet work engagement and workaholism across eastern and western cultures. Procedia 2014, 1, 6–24. [Google Scholar]
  18. Scott, K.S.; Moore, K.S.; Miceli, M.P. An exploration of the meaning and consequences of workaholism. Hum. Relat. 1997, 50, 287–314. [Google Scholar] [CrossRef]
  19. Spence, J.T.; Robbins, A.S. Workaholism: Definition, measurement, and preliminary results. J. Personal. Assess. 1992, 58, 160–178. [Google Scholar] [CrossRef]
  20. Snir, R.; Harpaz, I. Beyond workaholism: Towards a general model of heavy work investment. Hum. Resour. Manag. Rev. 2012, 22, 232–243. [Google Scholar] [CrossRef]
  21. Gordon, S.E.; Shi, X. The well-being and subjective career success of workaholics: An examination of hospitality managers’ recovery experience. Int. J. Hosp. Manag. 2021, 93, 102804. [Google Scholar] [CrossRef]
  22. Lee, G.; Magnini, V.P.; Kim, B.P. Employee satisfaction with schedule flexibility: Psychological antecedents and consequences within the workplace. Int. J. Hosp. Manag. 2011, 30, 22–30. [Google Scholar] [CrossRef]
  23. Wong, A.K.F.; Kim, S.; Kim, J.; Han, H. How the COVID-10 pandemic affected hotel employee stress: Employee perceptions of occupational stressors and their consequences. Int. J. Hosp. Manag. 2021, 93, 102798. [Google Scholar] [CrossRef]
  24. Shin, J.W.; Shin, H.C. Impact of job insecurity on hotel workers’ workaholism and work-family conflict in Korea. Int. J. Environ. Res. Public Health 2020, 17, 7783. [Google Scholar] [CrossRef]
  25. Pan, S.Y. Do workaholic hotel supervisors provide family supportive supervision? a role identity perspective. Int. J. Hosp. Manag. 2018, 68, 59–67. [Google Scholar] [CrossRef]
  26. Maslach, C. Stress, Burnout and Workaholism. In Professionals in Distress: Issues, Syndromes and Solutions in Psychology; Killberg, R.R., Nathan, P.E., Thoreson, R.W., Eds.; American Psychological Association: Washington, DC, USA, 1986; pp. 53–73. [Google Scholar]
  27. Moyer, F.; Aziz, S.; Wuensch, K. From workaholism to burn: Psychological capital as a mediator. Int. J. Workplace Health Manag. 2017, 10, 213–227. [Google Scholar] [CrossRef]
  28. Maslach, C.; Jackson, S.E. The measurement of experienced burnout. J. Organ. Behav. 1981, 2, 99–113. [Google Scholar] [CrossRef]
  29. Wen, B.; Zhou, X.; Hu, Y.; Zhang, X. Role stress and turnover intention of front-line hotel employees: The roles of burnout and service climate. Front. Psychol. 2020, 11, 36. [Google Scholar] [CrossRef] [Green Version]
  30. Long working hours, safety, and health: Toward a national research agenda. Am. J. Ind. Med. 2006, 11, 930–942.
  31. Sonnentag, S.; Zijlstra, F.R.H. Job characteristics and off-job activities as predictors of need for recovery, well-being, and fatigue. J. Appl. Psychol. 2006, 91, 330–350. [Google Scholar] [CrossRef] [Green Version]
  32. Schaufeli, W.B.; Bakker, A.B.; van der Heijden, F.; Prins, J.T. Workaholism, burnout, and well-being among junior doctors: The mediating role of role conflict. Work. Stress 2009, 23, 155–172. [Google Scholar] [CrossRef]
  33. Graves, L.M.; Ruderman, M.N.; Ohlott, P.J.; Weber, T.J. Driven to work and enjoyment of work: Effects on managers’ outcomes. J. Manag. 2012, 38, 1655–1680. [Google Scholar] [CrossRef]
  34. Innanen, H.; Tolvanen, A.; Salmela-Aro, K. Burnout, work engagement and workaholism among highly educated employees: Profiles, antecedents and outcomes. Burn. Res. 2014, 1, 38–49. [Google Scholar] [CrossRef] [Green Version]
  35. Cheung, F.; Tang, C.S.K.; Lim, M.S.M.; Koh, J.M. Workaholism on job burnout: A comparison between American and Chinese employees. Front. Psychol. 2018, 11, 2546. [Google Scholar] [CrossRef] [PubMed]
  36. Choi, Y. The influence of bullying on burnout through workaholism and perceived organizational support. East Asian J. Bus. Manag. 2018, 8, 13–21. [Google Scholar] [CrossRef]
  37. Brown, S.; Peterson, P.A. Antecedents and consequences of salesperson job satisfaction meta-analysis and assessment of causal effects. J. Mark. Res. 1993, 30, 63–77. [Google Scholar] [CrossRef]
  38. Meyer, J.P.; Allen, N.J. Testing the side-bet theory of organizational commitment: Some methodological considerations. J. Appl. Psychol. 1984, 59, 372–378. [Google Scholar] [CrossRef]
  39. Burke, R.J.; MacDermid, G. Are workaholics job satisfied and successful in their careers? Career Dev. Int. 1999, 4, 277–282. [Google Scholar] [CrossRef]
  40. Killinger, B. The Workaholic Breakdown Syndrome. In Research Companion to Working Time and Work Addiction; Burke, R.J., Ed.; Edward Elgar Publishing Limited: Cheltenham, UK, 2006; pp. 61–88. [Google Scholar]
  41. Taris, V.W.; Schaufeli, W.B.; Verhoeven, L.C. Workaholism in the Netherlands: Measurement and implications for job strain and non-work conflict. J. Appl. Psychol. 2005, 54, 37–60. [Google Scholar] [CrossRef]
  42. Bakker, A.B.; Demerouti, E.; Burke, R. Workaholism and relationship quality: A spillover–crossover perspective. J. Occup. Health Psychol. 2009, 14, 23–33. [Google Scholar] [CrossRef] [Green Version]
  43. Ng, T.W.H.; Sorensen, K.L.; Feldman, D.C. Dimensions, antecedents, and consequences of workaholism: A conceptual integration and extension. J. Organ. Behav. 2007, 28, 111–136. [Google Scholar] [CrossRef]
  44. Shimazu, A.; Schaufeli, W.B. Is workaholism good or bad for employee well-being? the distinctiveness of workaholism and work engagement among Japanese employees. Ind. Health 2009, 47, 495–502. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. De Beer, L.T.; Horn, J.; Schaufeli, W.B. Construct and criterion validity of the Dutch workaholism scale (DUWAS) within the South African financial services context. SAGE Open 2022, 12, 1–11. [Google Scholar] [CrossRef]
  46. Kim, J.E.; Cha, O. The effects of workaholism on job satisfaction and turnover intention: Mediating effect of personal relationship impairment. Korean J. Manag. 2018, 26, 59–95. [Google Scholar] [CrossRef]
  47. Kim, N.; Kang, Y.J.; Choi, J.; Sohn, Y.W. The crossover effects of supervisors’ workaholism on subordinates’ turnover intention: The mediating role of two types of job demands and emotional exhaustion. Int. J. Environ. Res. Public Health 2020, 17, 7742. [Google Scholar] [CrossRef] [PubMed]
  48. Sánchez-Medina, A.J.; Arteaga-Ortiz, J.; Naumchik, R.M.; Pellejero, M. The intention to quit entrepreneurship in tourism SMEs: The effect of work addiction. Int. J. Hosp. Manag. 2020, 89, 102400. [Google Scholar] [CrossRef]
  49. Podsakoff, N.P.; LePine, J.A.; LePine, M.A. Differential challenge stressor-hindrance stressor relationships with job attitudes, turnover intentions, turnover, and withdrawal behavior: A meta-analysis. J. Appl. Psychol. 2007, 92, 438–454. [Google Scholar] [CrossRef]
  50. Tews, M.J.; Michel, J.W.; Stafford, K. Does fun pay? the impact of workplace fun on employee turnover and performance. Cornell Hosp. Q. 2013, 54, 370–382. [Google Scholar] [CrossRef]
  51. Hughes, E. Deciding to leave but staying: Teacher burnout, precursors and turnover. Int. J. Hum. Resour. Manag. 2001, 12, 288–298. [Google Scholar] [CrossRef]
  52. Leiter, M.P.; Jackson, N.J.; Shaughnessy, K. Contrasting burnout, turnover intention, control, value congruence and knowledge sharing between Baby Boomers and Generation X. J. Nurs. Manag. 2009, 17, 100–109. [Google Scholar] [CrossRef]
  53. Kang, B.; Twigg, N.W.; Hertzman, J. An examination of social support and social identity factors and their relationship to certified chefs’ burnout. Int. J. Hosp. Manag. 2010, 29, 168–176. [Google Scholar] [CrossRef]
  54. Han, S.J.; Bonn, M.A.; Cho, M.H. The relationship between customer incivility, restaurant frontline service employee burnout and turnover intent. Int. J. Hosp. Manag. 2016, 52, 97–106. [Google Scholar] [CrossRef]
  55. Hsiao, S.T.S.; Ma, S.C.; Guo, S.L.; Kao, C.C.; Tsai, J.C.; Chung, M.H.; Huang, H.C. The role of workplace bullying in the relationship between occupational burnout and turnover intentions of clinical nurses. Appl. Nurs. Res. 2021, 68, 151483. [Google Scholar]
  56. Park, J.; Gursoy, D. Generation effects on work engagement among US hotel employees. Int. J. Hosp. Manag. 2012, 31, 1195–1202. [Google Scholar] [CrossRef]
  57. Santhanam, N.; Srinivas, S. Modeling the impact of employee engagement and happiness on burnout and turnover intention among blue-collar workers at a manufacturing company. Benchmark. Int. J. 2020, 27, 499–516. [Google Scholar] [CrossRef]
  58. Kupperschmidt, B. Multigeneration employees: Strategies for effective management. Health Care Manag. 2000, 19, 65–76. [Google Scholar] [CrossRef] [PubMed]
  59. Eyerman, R.; Turner, B.S. Outline of a theory of generations. Eur. J. Soc. Theory 1998, 1, 91–106. [Google Scholar] [CrossRef]
  60. Beldona, S.; Nusair, K.; Demicco, F. Online travel purchase behavior of generational cohorts: A longitudinal study. J. Hosp. Mark. Manag. 2008, 18, 406–420. [Google Scholar] [CrossRef]
  61. Eyoun, K.; Chen, H.; Ayoun, B.; Khliefat, A. The relationship between purpose of performance appraisal and psychological contract: Generational differences as a moderator. Int. J. Hosp. Manag. 2020, 86, 102449. [Google Scholar] [CrossRef]
  62. Smola, K.W.; Sutton, C.D. Generational differences: Revisiting generational work values for the new millennium. J. Organ. Behav. 2002, 23, 363–382. [Google Scholar] [CrossRef]
  63. Brown, E.A.; Thomas, N.J.; Bosselman, R.H. Are they leaving or staying: A qualitative analysis of turnover issues for generation Y hospitality employees with a hospitality education. Int. J. Hosp. Manag. 2015, 46, 130–137. [Google Scholar] [CrossRef] [Green Version]
  64. Strauss, B.; Strauss, W.; Howe, N. Generations: The History of America’s Future; William Morrow and Company: New York, NY, USA, 1991; pp. 1584–2069. [Google Scholar]
  65. Gursoy, D.; Maier, T.; Chi, C.G.Q. Generational differences: An examination of work values and generational gaps in the hospitality workforce. Int. J. Hosp. Manag. 2008, 27, 448–458. [Google Scholar] [CrossRef]
  66. Tulgan, B. Trends point to a dramatic generational shift in the future workplace. Employ. Relat. Today 2004, 30, 23–31. [Google Scholar] [CrossRef]
  67. Chen, P.; Choi, Y. Generational differences in work values: A study of hospitality management. Int. J. Contemp. Hosp. Manag. 2008, 6, 595–615. [Google Scholar] [CrossRef]
  68. Walsh, K.; Taylor, M. Developing in-house careers and retaining management talent: What hospitality professionals want from their jobs. Cornell Hotel. Restaur. Adm. Q. 2007, 48, 163–182. [Google Scholar] [CrossRef]
  69. Sakdiyakorn, M.; Golubovskaya, M.; Solnet, D. Understanding Generation Z through collective consciousness: Impacts for hospitality work and employment. Int. J. Hosp. Manag. 2021, 94, 102822. [Google Scholar] [CrossRef]
  70. Ozkan, M.; Solmaz, B. The changing face of the employees: Generation Z and their perceptions of work (a study applied to university students). Procedia Econ. Financ. 2015, 26, 476–483. [Google Scholar] [CrossRef]
  71. Self, T.; Gordon, S.; Jolly, P. Talent management: A Delphi study of assessing and developing Gen Z hospitality leaders. Int. J. Contemp. Hosp. Manag. 2019, 31, 4126–4149. [Google Scholar] [CrossRef]
  72. Robinson, R.N.; Martins, A.; Solnet, D.; Baum, T. Sustaining precarity: Critically examining tourism and employment. J. Sustain. Tour. 2019, 27, 1008–1025. [Google Scholar] [CrossRef]
  73. Brislin, R.W. Translation and Content Analysis of Oral and Written Material. In Handbook of Cross-cultural Psychology: Methodology; Triandis, H.C., Berry, J.W., Eds.; Allyn and Bacon: Boston, MA, USA, 1980; pp. 389–444. [Google Scholar]
  74. Aziz, S.; Uhrich, B.; Wuensch, K.L.; Swords, B. The workaholism analysis questionnaire: Emphasizing work-life imbalance and addiction in the measurement of workaholism. J. Behav. Appl. Manag. 2013, 14, 72–86. [Google Scholar] [CrossRef]
  75. Maslach, C.; Schaufeli, W.B.; Leiter, M.P. Job burnout. Annu. Rev. Psychol. 2001, 52, 397–422. [Google Scholar] [CrossRef] [Green Version]
  76. Seashore, S.E.; Lawler, E.E.; Mirvis, P.H.; Cammann, C. Observing and Measuring Organizational Change: A Guide to Field Practice; John Wiley and Sons Publishers: New York, NY, USA, 1982. [Google Scholar]
  77. Schaufeli, W.B.; Salanova, M.; Gonzalez-Roma, V.; Bakker, A.B. Burnout and engagement in university students. J. Cross–Cult. Psychol. 2002, 33, 464–481. [Google Scholar] [CrossRef] [Green Version]
  78. Schaufeli, B.W.; Bakker, A.B.; Salanova, M. The measurement of work engagement with a short questionnaire. Educ. Psychol. Meas. 2006, 66, 701–716. [Google Scholar] [CrossRef]
  79. Anderson, J.C.; Gerbing, D.W. An updated paradigm for scale development incorporating unidimensionality and its assessment. J. Mark. Res. 1988, 25, 186–192. [Google Scholar]
  80. Lindell, M.K.; Whitney, D.J. Accounting for common method variance in cross-sectional research designs. J. Appl. Psychol. 2001, 86, 114–121. [Google Scholar] [CrossRef] [Green Version]
  81. Podsakoff, P.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
  82. Gorrell, G.; Ford, N.; Madden, A.D.; Holdridge, P. Countering method bias in questionnaire-based user studies. J. Doc. 2011, 67, 507–524. [Google Scholar] [CrossRef] [Green Version]
  83. Hon, A.H.Y.; Lu, L. The mediating role of trust between expatriate procedural justice and employee outcome in Chinese hotel industry. Int. J. Hosp. Manag. 2010, 29, 669–676. [Google Scholar] [CrossRef]
  84. Rindskopf, D.; Rose, T. Sone theory and applications of confirmatory second-order factor analysis. Multivar. Behav. Res. 1988, 23, 51–67. [Google Scholar] [CrossRef]
  85. Nunnally, J.C. Psychometric Theory, 2nd ed.; McGraw-Hill: New York, NY, USA, 1978. [Google Scholar]
  86. Triandis, H.; Bontempo, R.; Villareal, M.J.; Asai, M. Individualism and collectivism: Cross-cultural perspectives on self-ingroup relationship. J. Personal. Soc. Psychol. 1988, 54, 323–338. [Google Scholar] [CrossRef]
Figure 1. Research model.
Figure 1. Research model.
Sustainability 15 05227 g001
Table 1. Profile of the sample (n = 350).
Table 1. Profile of the sample (n = 350).
CharacteristicNPercentage
Gender
Male25071.4
Female10028.6
Age
Z generation 21 to 29 years7521.4
Y generation 30 to 39 years17650.3
X generation9928.3
Education level
Community college degree (2 years)10128.9
University degree (4 years)21962.6
Grad. University degree (2 years)308.6
Tenure
5 years or fewer12034.3
6–9 years12535.7
10 years or more10530.0
Position
FOH (Front of the house)13638.9
BOH (Back of the house)15143.1
Others6318.0
Table 2. Means, standard deviations, and correlation analyses.
Table 2. Means, standard deviations, and correlation analyses.
Construct12345678910Mean ± SD a
1. Gender1 -
2. Age−0.356 **1 -
3. Education level−0.0630.214 **1 -
4. Tenure−0.419 **0.709 **0.198 **1 -
5. Emotional exhaustion−0.1020.138 **−0.0190.108 *1 0.746 **0.573 **3.89 ± 1.29
6. Depersonalization−0.151 **0.152 **−0.0140.137 *0.715 **1 0.802 **0.355 **3.61 ± 1.41
7. Person accomplishment−0.162 **0.164 **−0.0490.134 *0.689 **0.772 **1 0.819 **0.399 **3.39 ± 1.48
8. Workaholism−0.166 **0.165 **0.0810.247 **0.624 **0.559 **0.580 **10.475 **0.634 **4.32 ± 1.40
9. Burnout−0.155 **0.168 **−0.0310.140 **0.877 **0.919 **0.914 **0.648 **10.558 **3.63 ± 1.26
10. Turnover intent−0.0540.0010.0010.122*0.752 **0.647 **0.658 **0.741 **0.0755 **13.93 ± 1.45
Note: a SD = standard deviation, All variables were measured on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree), * p < 0.05; ** p < 0.01; Yellow box: marker variable partial correlational analysis (correlation between work engagement and the marker variable in this study) (mean = 4.54, SD = 1.94).
Table 3. Confirmatory factor analysis and reliability analysis.
Table 3. Confirmatory factor analysis and reliability analysis.
Construct
(Cronbach’s Alpha)
Standardized Estimatet-ValueCCR aAVE b
Workaholism
(0.976)
0.9530.838
WH10.907fixed
WH20.90127.823 ***
WH30.91328.588 ***
WH40.93430.514 ***
WH50.92329.525 ***
WH60.91728.916 ***
WH70.91128.369 ***
WH80.92029.172 ***
Burnout
(0.887)
0.8390.766
Emotional exhaustion0.872fixed
Depersonalization0.88817.019 ***
Person accomplishment0.86716.623 ***
Emotional exhaustion
(0.942)
0.8930.802
BN10.889fixed
BN20.88124.096 ***
BN30.89725.073 ***
BN40.91726.399 ***
Depersonalization
(0.948)
0.8890.821
BN50.912fixed
BN60.88225.769 ***
BN70.91528.447 ***
BN80.91728.563 ***
Person accomplishment
(0.950)
0.8840.827
BN90.915fixed
BN100.89126.712 ***
BN110.90527.856 ***
BN120.92829.922 ***
Turnover intent
(0.957)
0.9050.849
TI10.931fixed
TI20.89028.114 ***
TI30.92631.951 ***
TI40.94033.636 ***
Work engagement
(0.959)
0.8530.887
WE10.948fixed
WE20.93334.502 ***
WE30.94536.789 ***
Note: a CCR = composite construct reliability; b AVE = average variance extracted; WH = Workaholism; BN = Burnout; TI = Turnover intent; WE = Work engagement; Standardized estimate = β-value; χ2 = 498.602 (df = 315) p < 0.001; χ2/df = 1.583; Goodness-of-Fit Index (GFI) = 0.906; Normed Fit Index (NFI) = 0.960; Tucker–Lewis Index (TLI) = 0.983; Comparative Fit Index (CFI) = 0.985; Incremental Fit Index (IFI) = 0.985; Root Square Error of Approximation (RMSEA) = 0.072; Root Mean Square Residual (RMR) = 0.041; *** p < 0.001.
Table 4. Structural parameter estimates.
Table 4. Structural parameter estimates.
Hypothesized Path
(Stated as Alternative Hypothesis)
Standardized
Path Coefficients
t-ValueResults
Hypothesis 1: Workaholism → Burnout0.69712.894 ***Accepted
Hypothesis 2: Workaholism → Turnover intent0.37810.017 ***Accepted
Hypothesis 3: Burnout → Turnover intent0.5557.744 ***Accepted
Goodness-of-fit statisticsχ2(246) = 391.554 (p < 0.001)
χ2/df = 1.592
GFI = 0.914
NFI = 0.964
CFI = 0.986
RMSEA = 0.041
Note: *** p < 0.001; GFI = Goodness-of-Fit Index; NFI = Normed Fit Index; CFI = Comparative Fit Index; RMSEA = Root Mean Square Error of Approximation.
Table 5. Model fit indices.
Table 5. Model fit indices.
χ2dfCFIRMSEARMR∆χ2
Generation
characteristics
Configural invariance model1026.4047380.9730.0340.08840.810 ns
Metric invariance model1067.2147760.9730.0340.120
Note: ∆df = 40, ∆χ2 = 55.758 (p < 0.05); CFI = Comparative Fit Index; RMSEA = Root Mean Square Error of Approximation; RMR = Root Mean Square Residual; ns Not significant.
Table 6. Moderating effects on employee generation characteristics.
Table 6. Moderating effects on employee generation characteristics.
X-Generation
(N = 99)
Y-Generation
(N = 176)
Z-Generation
(N = 75)
Unconstrained
Model
Chi-Square
(df = 738)
Constrained
Model
Chi-Square
(df = 740)
∆χ2
(df = 2)
Standardized
Coefficients
t-ValueStandardized
Coefficients
t-ValueStandardized
Coefficients
t-Value
H4a: Workaholism
→ Burnout
0.6195.577 ***0.6027.257 ***0.7446.874 ***1026.4041032.4956.09 *
H4b: Workaholism
→ Turnover intent
0.2923.132 **0.4496.817 ***0.2782.731 **1026.4041028.4392.03 ns
Note: χ2/df = 1.391; Goodness-of-Fit Index (GFI) = 0.816; Normed Fit Index (NFI) = 0.912; Tucker–Lewis Index (TLI) = 0.970; Comparative Fit Index (CFI) = 0.973; Root Mean Square Error of Approximation (RMSEA) = 0.034; * p < 0.05, ** p < 0.01, *** p < 0.001, ns Not significant.
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Jung, H.-S.; Jung, Y.-S.; Yoon, H.-H. The Effects of Workaholism on Employee Burnout and Turnover Intent at Deluxe Hotels during the COVID-19 Pandemic: Evidence across Generations. Sustainability 2023, 15, 5227. https://doi.org/10.3390/su15065227

AMA Style

Jung H-S, Jung Y-S, Yoon H-H. The Effects of Workaholism on Employee Burnout and Turnover Intent at Deluxe Hotels during the COVID-19 Pandemic: Evidence across Generations. Sustainability. 2023; 15(6):5227. https://doi.org/10.3390/su15065227

Chicago/Turabian Style

Jung, Hyo-Sun, Yoon-Sik Jung, and Hye-Hyun Yoon. 2023. "The Effects of Workaholism on Employee Burnout and Turnover Intent at Deluxe Hotels during the COVID-19 Pandemic: Evidence across Generations" Sustainability 15, no. 6: 5227. https://doi.org/10.3390/su15065227

APA Style

Jung, H. -S., Jung, Y. -S., & Yoon, H. -H. (2023). The Effects of Workaholism on Employee Burnout and Turnover Intent at Deluxe Hotels during the COVID-19 Pandemic: Evidence across Generations. Sustainability, 15(6), 5227. https://doi.org/10.3390/su15065227

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