The role of job control and job support in adjusting service employee's work-to-leisure conflict

ARTICLE IN PRESS

Tourism Management 28 (2007) 726–735 www.elsevier.com/locate/tourman

Research paper

The role of job control and job support in adjusting service employee’s work-to-leisure conflict Jehn-Yih Wong, Jo-Hui Lin Graduate Institute of Management, Ming Chuan University, 250, Chung Shan North Road, Sec 5, Taipei, 111 Taiwan, ROC Received 9 February 2006; accepted 5 May 2006

Abstract Many tourism employees are increasingly confronted with rising work stress levels, especially work-to-leisure conflict (WLC). The Job Demand–Control–Support model performance in this study predicted service employees’ WLC and tested two job strain hypotheses (i.e., iso-strain and buffering hypotheses). With a structural equation modeling data of 380 service workers, relationships between job stress variables and WLC were examined. Evidence suggests that job demands, job controls, and supervisor support have significant and direct effects on WLC, based on the iso-strain hypothesis. Job control’s and support’s moderating effect in the buffering hypothesis were found to attenuate job demand’s negative effect and drive coworker support buffering effect and lessen service workers’ WLC. Job design implications for the HR manager and employee stress management are discussed. r 2006 Elsevier Ltd. All rights reserved. Keywords: Job strain model; Job control; Job support; Stress management; Work-to-leisure conflict

1. Introduction A career in tourism is labor-intensive, and frontline personnel face huge demands. When customers are enjoying leisure time, touring, or shopping etc., tourism employees’ work in much the same way as service providers. Such a contrast is known as anti-social work hours (Law, Pearce, & Woods, 1995). Job demands also require much time and energy of service employees, leaving less opportunity to engage in leisure activities in their time off. However, according to the existential psychology perceptive, Iso-Ahola and Wessinger (1984) pointed out that a sense of freedom and control is critical for actual leisure involvement. Thus, the specific mode of job design may diminish tourism employees’ opportunities for leisure activity participation. Because of work limitations, service employees may perceive a higher work-to-leisure conflict (WLC) compared to those who work a Monday-to-Friday Corresponding author. Tel.: +886 2 27637217; fax: +886 2 28809727.

E-mail addresses: [email protected], , [email protected] (J.-Y. Wong), [email protected], , [email protected] (J.-H. Lin). 0261-5177/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.tourman.2006.05.003

schedule. Therefore, it is important for the manager to reduce employees’ WLC by improving work characteristics. Work and leisure consideration originates with theories of work and nonwork life. Based on border theory (O’Driscoll, 1996; Zedeck & Mosier, 1990), Guest (2002) concluded that five models are typically used to explain the relationship between work and nonwork life: (1) the Segmentation model claims that no relation exists between work and nonwork domains; (2) the Spillover model hypothesizes that individual work experiences will carry over into nonwork domains and affect attitudes and behaviors; (3) the Compensation model proposes that workers who feel deprived at work will compensate in their choice of nonwork activities; (4) the Instrumental model means through some activities in certain domains facilitate success in other life domains; (5) the Conflict model proposes that with high demand levels in all spheres of life, difficult choices have to be made when individual conflicts and overload occur. However, Chick and Hood (1996) suggested that the segmentation, spillover, and compensation models could not properly explain the work and leisure relationship. Since personal leisure life is

ARTICLE IN PRESS J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

obviously affected by work setting (Kelly, 1972), service employees will inevitably experience varying degrees of WLC. Relationships between job-related role stressors and tourism employees’ work–family conflicts have received empirical attention in organizational behavior literatures (Babin & Boles, 1996; Boles & Babin, 1996; Karatepe & Sokmen, 2006). Researchers took an ecological perspective in discussing relationships between work and nonwork conflict and life quality in various domains. For example, Rice, Frone, and McFarlin (1992) found that work-leisure conflict decreases employees’ job and leisure satisfaction and further affects global life satisfaction. Karatepe and Sokmen (2006) tested the relationships between work and family role variables (e.g., role stress and work–family conflict) and work-related outcomes (e.g., job satisfaction, intention to leave, and service recovery performance) among hotel industry frontline personnel. However, rare empirical studies regarding stress management and coping strategies can be found (Law et al., 1995). Since work characteristics have definite effects on employees’ leisure life, how to apply work resources to adjust WLC is worthy of study. Job strain theory views job demand, control, and support as work setting elements—they recognizably affect work outcomes (e.g., job satisfaction, burnout, emotional exhaustion, and well-being). This is known as the Job Demand–Control–Support model (JDCS model) (Johnson & Hall, 1988; Karasek & Theorell, 1990). Job demand represents employees’ workload or time demands, while job control and support are favorable resources, decreasing employees’ role conflict. In fact, work characteristics are the main cause of WLC. Yet up to the present, one can rarely find empirical research to support such a causal relationship. Hence, WLC is interpreted through the JDCS model in this work. The possibility of applying job control and support on buffering WLC is also explored. 2. Theoretical grounding and hypotheses Two main job strain models are among previous studies, the Job Demand–Control model (JDC model) (Karasek, 1979; Karasek & Theorell, 1990) and the JDCS model (Johnson & Hall, 1988; Karasek & Theorell, 1990). Accordingly, two hypotheses were concluded as iso-strain hypothesis and buffering hypothesis. The former asserts that job demand, control, and support mainly effect role conflict and ambiguity, emotional exhaustion, job satisfaction, etc. (e.g., Johnson & Hall, 1988; Rafferty, Friend, & Landsbergis, 2001; Rodrı´ guez, Bravo, Peiro´, & Schaufeli, 2001). On the contrary, researchers who highly value buffering or moderating effects believe job controls (e.g., Dwyer & Ganster, 1991; Parkes, Mendham, & Von Rabenau, 1994) and social support (e.g., Haines, Hurlbert, & Zimmer, 1991; Sargent & Terry, 2000; Van der Doef & Maes, 1999) are also coping mechanisms. Based on the JDCS model, work characteristics have been recognized as

727

employees’ work strain source. The JDCS model (Johnson & Hall, 1988; Karasek & Theorell, 1990) states that the isostrain hypothesis predicts a lower well-being among workers under high demands, low control, and low social support. In contrast, the buffering hypothesis states that job control and job support can moderate high strain negative impact on well-being. The JDCS model was applied to conduct iso-strain hypothesis and buffering hypothesis on predicting logic relationships between job stress variables and work-to-leisure conflict in this study. Work and nonwork domains, like family or leisure, are both main fields of individual personal life. Many researchers have worked on the relationship between work and leisure, and it seems reasonable to approach this issue with factors among working settings (Chick & Hood, 1996; Kelly, 1972; Snir & Harpaz, 2002). Work and leisure are two totally different aspects of life. Since both are limited by personal time and energy, they may conflict or compete. Kelly (1972) assumed work as remunerative and necessary for individual and family maintenance. Nevertheless, he also believed that leisure is not remunerative, but may be influenced by work roles or constraints. Thomas and Ganster (1995) indicated that frontline employees found little time and energy for other activities beyond those required by their job and family. Specifically, in order to arrange available resources for work and nonwork, one often experiences mutually exclusive dilemmas (Staines, 1980). Like other fundamental living functions, leisure offers individuals the potential for enjoyment and good life. Active participation in nonwork domains, such as family, recreation, and community, can buffer individual’s work strains (Kirchmeyer, 1992).

2.1. Iso-strain hypothesis The term workload, in regard to work setting, means excess work which employees cannot finish in a certain time or employee perception of not being able to finish (Van Sell, Brief, & Schuler, 1981). Practically, in order to provide better service and greater customer satisfaction, service employees must often perform repetitive tasks. Also because of a high turnover rate, employees in an understaffed situation are stretched beyond their limits. McFillen, Reigel, and Enz (1986) articulated, ‘‘Long work hours and job pressure are usually the reasons for restaurant managers to leave.’’ Law et al. (1995) also pointed out that at tourist attraction sites, the job is full of interpersonal contact, job-related role stress, long working hours, and anti-social scheduling design, etc. Especially with high visitor flow, the job is overloaded and employees often have to work overtime. Time-based conflict occurs when time pressures associated with one role prevents fulfilling expectations of the other role (Greenhaus & Beutell, 1985). The work hour mode leads service employees to have to work on holidays. Their leisure times are significantly different from employees of other occupations and the shift

ARTICLE IN PRESS 728

J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

system is more complicated, less regular, and lacks flexibility. Another study of work characteristic effects upon coach drivers’ health also suggested that high job demand or low job control would harm their health (Sluiter, Van der Beek, & Frings-Dresen, 1999). Similarly, Jamal (2004) found that Canadian workers involved in weekend work reported significantly higher emotional exhaustion, job stress, and psychosomatic health problems than employees without weekend work. Behavior-based conflict occurs when specific behaviors required in one role are incompatible with behavior expectations in another role (Greenhaus & Beutell, 1985). In sum, when workload or time demand diminishes employees’ time and energy, their willingness for leisure activities during nonwork times will most likely reduce and lessen their opportunity to gather with family or friends. On the other hand, more relevant papers on job control and work time design are being published which facilitate management policies. Many industries have gradually adopted work-life or flexible working policies, empowering employees with more autonomy and job control. This not only allows employees to plan a better nonwork life, but also reduces the conflict of work interference with nonwork. As for service employees, if shift scheduling or time-off arrangement is employee based, it will be more beneficial for a leisure vacation. Social resources such as empathy, support, and social contact can reduce job stress or strain. There are practical social support benefits for employees at work. For example, Ross (1993) suggested that restaurant supervisors facilitate a supportive climate to alleviate interpersonal pressures between colleagues and customers. Moreover, Babin and Boles (1996) surveyed 261 service employees from full-service restaurants and found that employees’ perception of coworker involvement and supervisory support can reduce role stress and increase job satisfaction. Hull and Michael (1995) also pointed out that a brief chitchat with colleagues during work not only lifts spirits, but also soothes negative emotions. Specifically, since supervisors arrange service employees’ work hours, their considerate accommodation will encourage employees to enjoy their leisure. Similarly, colleagues’ support through work setting interactions may also enable employees to direct energy toward leisure. That work-related support is helpful in situations where work interference conflict with leisure is proposed. Moreover, Rodrı´ guez et al. (2001) investigated human service workers about the effects of job stress variables (i.e., job demands, job control, and job support) on job dissatisfaction. They found the three stress variables to significantly affect long-term job dissatisfaction. Thus, tourism employees’ WLC may be interpreted using the iso-strain hypothesis of the JDCS model. Based on previous literature and logic argument, the following hypothesis is assumed: Hypothesis 1. Job demands (H1-1) will significantly and positively affect service employee WLC. However, job

controls (H1-2), supervisor support (H1-3), and coworker support (H1-4) will significantly and negatively affect service employee WLC. 2.2. Buffering hypothesis The JDCS model emphasizes three work characteristic interactions, including psychological demands, job control, and social support. Even though Van der Doef and Maes (1999) and many empirical studies tend to support isostrain hypothesis, they also believe it necessary for researchers to clarify the actual relationships among the three job stress variables. Karasek (1979) originally reported evidence of interaction between job demand and job control. Beehr, Glaser, Canali, and Wallwey (2001) also consider that without demand–control interaction, the JDC model would be meaningless. For example, Karasek, Triantis, and Chaudry (1982) surveyed the US workforce as an example and found that job control moderated the relationships between demands and life dissatisfaction, job dissatisfaction, and job-related moods. Furthermore, Dwyer and Ganster (1991) evidenced that interaction between perceived workload and job control predicted employees’ absence, tardiness, sick days, and job satisfaction among blue collar and trade occupations. Service employees’ job control is assumed in this study to have a buffering workload effect and reduce work-to-leisure conflict. When stressors and social support come from similar settings, then social support becomes an effective resource, reducing personal strain (Haines et al., 1991). Moreover, previous researches in accordance suggested that work supports from both supervisor and colleague might moderate work stress. For example, de Jonge, Janssen, and Van Breukelen (1996) found that work autonomy with high support from supervisors and colleagues helps reduce feelings of exhaustion and health complaints in health-care professionals. They also suggested that high autonomy might attenuate negative job demand effect on emotional exhaustion. Furthermore, Sargent and Terry (2000) examined that high supervisor support alleviates negative high strain job effect on job satisfaction and reduced reported depersonalization levels. Hence, support from both supervisors and coworkers will moderate relationships between work stress variables and work-to-leisure conflict. Moreover, Parkes et al. (1994) found that work demands and discretion showed significant effects on health-care workers, and the interaction of demand with discretion could also predict job satisfaction. Interaction among work demand, discretion, and support, could also correctly predict employee somatic symptoms. A longitudinal research analysis duplicated on teachers, also made a successful prediction. Daniels and Guppy (1994) surveyed 244 accountants, showing significant 3-way interactions between job demand, locus of control, and social support (or job autonomy) in predicting psychological well-being. These interactions also buffer stressor effects

ARTICLE IN PRESS J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

upon well-being. Therefore, three job stress variables are hypothesized as interactive upon work-to-leisure conflict and reducing job demand effect on work-to-leisure conflict. In other words, the JDCS model-buffering hypothesis can interpret tourism employees’ perceived work-to-leisure conflict. Accordingly, this work hypothesizes the following. Hypothesis 2. The four interactions (H2-1–H2-4) will moderate job demand effect on service employee WLC.

3. Methodology Actual work characteristics include (1) job control (i.e., timing control and method control), (2) demands (i.e., monitoring demands and problem-solving demands), and (3) production responsibility (Jackson, Wall, Martin, & Davids, 1993). Except for timing control, the other characteristics do not seem to be associated with employees’ nonwork domain behavior and could be skipped for this research. The main tourism industry suppliers include transportation service, lodging, restaurant, and destination or attraction. Since many restaurants are self-employed with mainly part-time staff, those in food and beverage hotel sectors are the focused subjects of this research. Because of the timing regulation, these service employees will not be allowed to take a day off during the weekend, definitely increasing their WLC. The subjects are tourism industry service employees. Because of subject attribution, applying its result may be somewhat limited. However, similar leisure service industries may be reasonably inferred, such as those who work as customer-contacts in luxury restaurants, gyms, entertainment, and recreation industries. Based on the JDCS model (Johnson & Hall,

729

1988; Karasek & Theorell, 1990), Fig. 1 shows the hypothesized model of this study. 3.1. Participants and procedure The subjects are full-time service employees working longer than one year in the tourism industry. Since job strain research requires a homogeneous sample for a better analysis (Rodrı´ guez et al., 2001), three subjects were recruited including: (1) International tourist and resort hotels (e.g., food and beverage service, and room service sector). (2) Private tourist attraction. Prior to the survey, business owners were contacted for their consent before proceeding. Questionnaires were distributed by internal post to employees within the customer encounter sector. (3) International airline attendants were only sampled with snowball sampling. All questionnaires were postage-paid preaddressed and returned by the respondents. Questionnaires were delivered to 700 subjects, with 517 responses, among which 137 were invalid. The total valid sample is 380. The response rate is 73.86% and the effective response rate is 54.29%. The character of this sample is as follows: airline attendants comprise 39.5%, hotel employees, 35.5% and tourist attraction employees, 25%. Seventy-five percent are female, with about half (49.2%) younger than thirty years. Over three-fifths of respondents (63.4%) earned college/ university degree, and 54.2% are single. Work experience is less than two years in 29.5% and 2–5 years in 25.5%. Most respondents (83.7%) are in nonsupervising positions, and only 16.3% hold a supervisor title. In order to test for nonresponse bias, the Armstrong and Overton’s method (1977) for analyzing time responses across early and late respondents was employed. Early (n ¼ 286, 75.26%) and

Job demands

Job controls

Job supports

Work-to-leisure conflict

Job demands × Job controls

Job demands × Job supports

Job supports × Job controls

Job demands × controls × supports Fig. 1. The hypothesized model.

ARTICLE IN PRESS 730

J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

late respondents (n ¼ 94, 24.74%) were tested across a number of demographic variables using a w2 difference test. The respondents’ gender ðp ¼ 0:074Þ, age ðp ¼ 0:061Þ, and education level ðp ¼ 0:245Þ showed insignificant difference between early and late respondents. Results thus suggest that response bias was not a significant problem in the study.

was adapted from workfamily conflict studies by Anderson, Coffey, and Byerly (2002). Items are scored on a 5point rating scale ranging from 1 (never) to 5 (very often). According to interviewees’ personal self-evaluation, the higher the score, the more frequent he or she perceives the conflict between work interference with leisure life.

3.2. Measures

3.2.2. Main variables on job strain model Job stress variables in this study are defined as job demands in the tourism occupation, as well as available resources employees may control and apply in the work setting. A lack of favorable resources means employees have low control, less support, and perceive more job stress and strain. Job stress variables are measured according to three indicators: Job demands, job controls (i.e., scheduling control and time-off control), and job supports (i.e.,

3.2.1. Work-to-leisure conflict The interference of work domain to leisure life alone is explored in this study. Work-to-leisure conflict then is defined as the domination of service employees’ work role over other life roles or employees’ energy exhaustion due to work demands causing decreased time, energy, and leisure opportunity. The work-to-leisure conflict (5 items) scale

Table 1 Results of measurement model—JDCS Model Completely standardized estimatesa

R2 (errors)

Job demands My job requires working fast My job requires working hard I have a great deal of work to be done My time is not enough My job is an excessive work

0.76 0.67 0.75 0.71 0.81

0.58 0.45 0.56 0.50 0.66

(0.42) (0.45) (0.39) (0.36) (0.25)

Job control I have control over the scheduling of my work I have some control over the sequencing of my work activities My job is such that I can decide when to do particular work activities I have control over the scheduling of my time-off I have some control over the sequencing of my nonwork activities I can decide when to do particular nonwork activities (e.g. vacation)

0.61 0.80 0.80 0.84 0.87 0.70

0.38 0.64 0.64 0.71 0.75 0.50

(0.62) (0.36) (0.30) (0.35) (0.26) (0.48)

Supervisor support My supervisor is supportive when I have a life problem My supervisor accommodates me when I have a life problem (e.g. vacation) My supervisor understands when I talk about personal issues My supervisor really cares about the effects that work demands have on my personal life

0.61 0.88 0.93 0.89

0.38 0.77 0.86 0.79

(0.62) (0.29) (0.13) (0.20)

Coworker support My coworker is supportive when I have a life problem My coworker accommodates me when I have a life problem. (e.g. vacation) My coworker understands when I talk about personal issues My coworker really cares about the effects that work demands have on my personal life

0.71 0.86 0.62 0.62

0.51 0.74 0.39 0.38

(0.49) (0.17) (0.37) (0.32)

0.72 0.71

0.52 (0.47) 0.50 (0.47)

0.80 0.86 0.60

0.64 (0.33) 0.74 (0.24) 0.36 (0.53)

Measures

Work-to-leisure conflict I do not have enough time for leisure activites because of my job I do not have enough time to participate in leisure activities with my family/friends because of my job I do not have energy to participate in leisure activities because of my job I am not able to participate in leisure activities because of my job I have never been in a suitable frame of mind to participate in leisure activities because of my job a

All completely standardized estimates (l) are statistically significant, po0:05. P P 2 P CR ¼ ( l)2(var)/(( errors)) P 2 l) (var)+( P 2 P Jo¨reskog and So¨rbom (1992). c AVE (rvc) ¼ ( l )(var)/(( l )(var)+( errors)) Jo¨reskog and So¨rbom (1992). b

Construct reliabilityb

AVEc

0.88

0.60

0.90

0.59

0.90

0.69

0.85

0.60

0.87

0.57

ARTICLE IN PRESS J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

supervisor and coworker support). Table 1 shows all job stress variable measures. Time demand scale (Karasek, 1979) assessed job demands (5 items), with a 5-point scale ranging from (1) never to (5) always. The higher the score, the higher the job demands for service employees in the work setting. Work schedule (job control) refers to discretion in controlling scheduling, sequencing, and timing of job activities (Breaugh, 1985). Job control included scheduling and time-off control in this study. Although their coordination may highly correlate, service employees still need to routinely arrange their own time-off. Scheduling control (3 items) was measured using the work scheduling autonomy scale of Breaugh (1985). Time-off control (3 items) was reworded according to the scheduling control autonomy scale. Interviewees rated according to their perceived autonomy in scheduling and time-off with a 5-point scale ranging from (1) strongly disagree to (5) strongly agree. The higher the rated score, the more convenient and flexible the respondent’s work setting. Referring to the research of Anderson et al. (2002), interviewees evaluate their supervisor support (4 items) and coworker support (4 items), providing actual perception of work-related support; thus job support and its benefit towards nonwork life may be understood. Interviewees reported on a 5-point scale ranging from (1) strongly disagree to (5) strongly agree. The higher the score, the better job support and help the respondent perceives. 3.2.3. Interactions of job strain variables This study defines the interactions of work stress variables as job demands, job control, and work-related support which moderate work-to-leisure conflict or adjust negative job demand effect as an effective strain-coping mechanism. The selected interactions are based on de Jonge et al. (1996), Parkes et al. (1994), and Rodrı´ guez et al. (2001). There are four interactions, three types of twoway (job demands  controls, job demands  supports, job controls  supports) and one three-way (job demands  controls  supports). 3.3. Data description, reliability, and validity Table 3 presents the means, standard deviations, and correlations for all variables used in the job strain model. A two-step approach to structural equation modeling (SEM)

731

was used in this research, as recommended by Anderson and Gerbing (1988). Specifically, to establish the discriminant validity of job stress variables, each measurement model must be tested. A confirmatory factor analysis was applied to evaluate the measurement model fit. According to de Jonge et al. (1996), then, SEM was used to assess the fit of the hypothesized model. First, the normalized residuals and residual input data Q-plot suggest that the input and implied covariance matrices are reasonably equivalent (Bagozzi & Yi, 1988). This result shows that the sampling error terms are normally distributed. Secondly, a job stress variable is combined into a 3-factor model (i.e., job demands, job controls, and job supports), a 4-factor model (i.e., job demands, job controls, supervisor, and coworker support), and a 5-factor model (i.e., job demands, scheduling and timeoff control, supervisor and coworker support). Then the most appropriate one is tested out. Regarding the high value of the CFI, NFI, PNFI, and RMSEA, Table 2 shows that the 4-factor model has a better statistical fit than the 3-factor and 5-factor one. The w2 difference test is significant which means that the three measurement models are significantly different. Thus the 4factor model will be applied in further study. The LISREL 8.53 for data analysis was applied with maximum likelihood estimation. This method used a sample covariance matrix as input and with w2 test for the model’s statistical fit, followed by a parameters estimate and hypotheses test in order to understand how the surveyed data fit in the theoretical model (Bagozzi & Yi, 1988). The individual item reliability of construct evaluates the measurement model (1) if it has an R2 over 0.50; (2) if the measured variable to the construct has completely standardized estimates between 0.50 and 0.95, and if it is statistically significant which means the measurement model reaches the ideal model fit (Bagozzi & Yi, 1988). Table 1 shows the 24 measures and 18 measures have R2 larger than 0.50. Except for one item, the other completely standardized estimates are between 0.61 and 0.93 which all reach the significance (t-value 41.96). The composite reliability (CR) of construct measures latent variable’s internal consistency. The higher the CR, the more precisely the measures can predict construct reliability. According to Fornell and Larcker (1981), CR should be above 0.60. Table 1 shows that the CR of all constructs are between 0.85 and 0.90.

Table 2 Results of the confirmatory factor analysis Model

w2ðdf Þ

CFI

NFI

PNFI

RMSEA

Model comparison

w2ðdf Þ diff

Sig.

4-factor 3-factor 5-factor

897.7(234) 966(237) 1018.6(230)

0.95 0.94 0.94

0.93 0.93 0.92

0.80 0.80 0.79

0.062 0.079 0.067

4–3 factor 4–5 factor

68.3(3)a,c 120.9(4)b,c

po0:01 po0:01

a 2

w statistics is 68.3 with 3 degrees of freedom and above the critical value (11.35) of significant level ðp ¼ 0:01Þ. w statistics is 120.9 with 4 degrees of freedom and above the critical value (13.28) of significant level ðp ¼ 0:01Þ. c 2 w difference tests are significant which means these comparison models are different significantly. b 2

ARTICLE IN PRESS J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

732

Table 3 Means, standard deviations, and correlationsa Constructs

Means

SD

1

2

3

4

5

1. 2. 3. 4. 5.

3.48 2.96 3.03 3.48 3.18

0.59 0.85 0.93 0.59 0.77

0.77b 0.36* 0.26 0.14 0.57*

0.77 0.68* 0.46* 0.57*

0.83 0.55* 0.47*

0.77 0.28

0.75

Job demands Job control Supervisor support Coworker support Work-to-leisure conflict

*po0:05. a Correlations are estimates from a confirmatory factor measurement model. b Bold numbers on the diagonal parentheses are square root of each construct’s AVE.

Fornell and Larcker (1981) suggested that an adequate convergent validity contains less than 50% average variances extracted (AVE). In other words, AVE should be 0.50 or above. Table 1 shows that each AVE is between 0.57 and 0.69. They also suggested that discriminant validity is based on a comparison of squared pair-wise correlations between constructs and the AVE for each of the constructs. As shown in Table 3, bold numbers on the diagonal are the square root of each construct’s AVE (between 0.75 and 0.83) and are greater than their correlations with other constructs. The correlations between each construct and other constructs are listed off the diagonal. Thus, the discriminant validity is achieved.

Table 4 Model fit and comparison of job strain hypotheses Fit statistics

Iso-strain model

Buffering model

w2 df NCI(w2/df) GFI AGFI SRMR RMSEA Dw2(df)

921.7 (po0:01) 236 3.91 0.86 0.82 0.074 0.063 —

1796.9 (po0:01) 483 3.72 0.80 0.75 0.080 0.074 875.2(247)a

a 2 w statistics is 875.2 with 247 degrees of freedom and above the critical value (353.8) of significant level (p ¼ 0.01). w2 difference test is significant which means these two models are different significantly.

4. Results 4.1. Analysis of model The first step applied the four main job strain model variables as predictors of service employees’ WLC perception. It showed that the model w2 value is significant (w2ð236Þ ¼ 921:7, po0:01), which means that both the theoretical iso-strain model and empirical data do not fit each other significantly (Bagozzi & Yi, 1988). However, both GFI and AGFI are below 0.90 (threshold) and both SRMR and RMSEA are less than 0.08 (Bollen, 1990). Furthermore, when testing with NCI (normed w2 index, w2/ df) as an alternative indicator of the w2 test, the smaller the value, the better. If NCI is between 2 and 5, that would also be acceptable (Marsh & Hocevar, 1985). This model’s NCI is 3.91, which suggests a moderate fit of the iso-strain model with the data, as shown in Table 4. All job stress variables were kept in the second step, and four interaction variables were also put into the model. The results showed that the model’s w2 is significant (w2ð483Þ ¼ 1796:9, po0:01) which means the theoretical buffering model does not significantly fit the empirical data (Bagozzi & Yi, 1988). This model’s GFI and AGFI are 0.80 and 0.75 and both SRMR and RMSEA are less than 0.08. The obtained fit statistics suggests a weaker fit of the buffering model with the data (Bollen, 1990). Table 4 displays the NCI as 3.72, which means an acceptable fit statistic for the buffering model. In order to determine the discriminant between two hypotheses of the job strain

model, the between-group w2 difference test was applied. Table 4 shows that both have significant difference, which means a discriminant between them. Two job strain models explain tourism employees’ perceived WLC. As shown in Table 5, job demands, job controls, and supervisor support explained about 39% of the total WLC variance in the isostrain model. Except for the interaction between job controls and supports, four main stress variables and three interactions in the buffering model also accounted for service employees’ WLC with 41% of the explanatory.

4.2. Hypotheses testing In the iso-strain model, the structural estimate of 0:24ðt ¼ 4:89Þ shown in Table 5 suggests that job demands had a significant and positive effect on service employees’ WLC. The structural job controls estimate on WLC is 0:39ðt ¼ 5:00Þ. This implies that the more flexible service employees’ time-scheduling autonomy, the more significantly lower WLC they perceived. In addition, the structural estimates of supervisor and coworker support on WLC are 0:15ðt ¼ 2:01Þ and 0:01ðt ¼ 0:17Þ. When service employees accept more supervisor support, they perceive a significantly lower WLC. Thus, H1-1, H1-2, and H1-3 were supported. There are three significant interactive WLC items in the buffering model, especially the three-way interaction. This

ARTICLE IN PRESS J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

733

Table 5 Job strain models analysis and hypotheses test Estimates

t-value

Results

Iso-strain model (R2 ¼ 0:39, t ¼ 5:51) H1-1 Job demands-WLC H1-2 Job controls-WLC Supervisor support-WLC H1-3 H1-4 Coworker support-WLC

0.24* 0.39* 0.15* 0.01

4.89 5.00 2.01 0.17

Supported Supported Supported Not supported

Moderating model (R2 ¼ 0:41, t ¼ 5:56) Job demands-WLC Job controls-WLC Supervisor support-WLC Coworker support-WLC H2-1 Job demands  controls-WLC H2-2 Job demands  supports-WLC H2-3 Job supports  controls-WLC H2-4 Job demands  controls  supports-WLC

0.20* 0.32* 0.26* 0.19* 0.13* 0.14* 0.01 0.35*

4.21 4.25 3.16 5.44 2.45 1.98 0.28 2.97

Decreasea

Path relationships

Increaseb Supported Supported Not supported Supported

*po0.05. a In the moderating model, the estimate of job demands has significantly decreased from 0.24 to 0.20, which means the interactions moderate the negative effect of job demands on the WLC. b In the moderating model, the estimates of coworker support have significantly increased from 0.01 to 0.19, which means it buffers the WLC.

effect toward service employees’ WLC is 0.35 (2.97), higher than other main effective items and interactive ones. As for moderating effect, structural job demands estimates decreased from 0.24 to 0.20, which means work-related resource interactions moderate service employee work demands. This insignificant coworker support in the isostrain model shows significant negative effects on WLC in the buffering model. The structural estimate is 0.19 (5.44). In other words, coworker support buffers service employees’ conflict of work inference with leisure and also supports H2-1, H2-2, and H2-4. 5. Discussion The goal of this study is to test the explanatory of various job stress variables to predict work-to-leisure conflict of tourism service employees. Specifically, isostrain and buffering hypotheses are examined to determine if they exist in tourism work settings. According to the structural equation modeling theory, the same data may fit in different theoretical models. That is, there might be several equivalent models in the same study with the same data. In sum, job demands, job controls, and supervisor support of the job strain model show significant direct effect. As for iso-strain hypothesis, this study’s result agreed with the conclusions of Parkes et al. (1994) and Rodrı´ guez et al. (2001) that negative work stress (i.e., job demands, low job control, and low job support) is the main effect of employees’ perception. On the other hand, coworker support is insignificant. One reason may be that the moderating mechanism should be taken into consideration. So the moderating model is analyzed as follows. Similar to the JDCS model, job control and job support are both favorable resources for adjusting job stress and

alleviating job demands. Except for job controls and supports interaction, the other three interactions in the moderating model are significant, which means two-way interaction (job demands  controls, job demands  supports) and three-way interaction (job demands  controls  supports) may affect work-to-leisure conflict simultaneously, so it also confirmed that these interactions have moderating effects in the job strain model. Interactions can also buffer the negative effect of job demands on work-to-leisure conflict. Although job demands effect is decreased, it still makes a significant bad effect on work-toleisure conflict. This is because the characteristics of service occupations supporting labor service will make employees feel the workload strongly. Perhaps long working hours or overtime work is the main reason for employees’ perception of long-term stress, yet it is inevitable. First, the result of this study is in accordance with Parkes et al. (1994) as well as Dwyer and Ganster (1991), showing a significant interaction between job demands and control (autonomy). But it is different from Beehr et al. (2001), finding no interaction between job control and work demands (i.e., workload demands, monitoring demands, problem-solving demands and time demands). Second, this study also did not find that job supports showed an interaction with job controls. This differs from de Jonge et al. (1996) findings that work autonomy and job support may actually moderate emotional exhaustion. A reasonable explanation may be that the job control measures differ from Karasek’s decision latitude variable. This study more accurately operationalized this construct. Third, this study found that job supports interacting with job demands affects work-to-leisure conflict, which agreed with the conclusion of Daniels and Guppy (1994). They found that social support is considered a means by which individuals can buffer workplace stressor effects on

ARTICLE IN PRESS 734

J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735

psychological well-being. Finally, three-way interaction was found to have significant effect on interpreting service employees’ work-to-leisure conflict. Specifically, flexible scheduling with high work-related support has beneficial effects on reducing service employees’ workload plus leading to lower work-to-leisure conflict. Though de Jonge et al. (1996), Rodrı´ guez et al. (2001), Van der Doef and Maes (1999) did not demonstrate the three-way interaction effect, this study found its effect on work-to-leisure conflict. Perhaps it is due to empirical industry characteristics. Such interaction has a higher effect on service employees’ work-to-leisure conflict than other interactive items. This is actually an important finding in this study, which is in accordance with the conclusion of Parkes et al. (1994). The result of this study may reasonably interpret the special work settings tourism occupation employees’ experience. The empirical data consists of many previous literatures which assume that job control and job support play a key role in forming work strain (i.e., de Jonge et al., 1996; Rodrı´ guez et al., 2001; Van der Doef & Maes, 1999), and this resource can be viewed as an advantageous buffer for moderating service employees’ work-to-leisure conflict.

flexibility and accommodating requests for time off. Additionally, creating a supportive organizational culture or establishing team base training may help employees to be open with each other and more willing to provide mutual support. These actions would not cost much, but would be of great benefit, enhancing a sense of coherence and forming a beneficial organizational climate. Service employees should also keep a positive spirit of service and occupational attitude. They should maintain work flexibility in order to arrange individual leisure activities. Only in this way will they experience a balanced life of work and leisure. This study is a cross-sectional questionnaire survey and applies the JDCS model to interpret service employees’ perceived work-to-leisure conflict. An additional study comparison of the work-to-leisure conflict with other occupational groups is still needed. Helping service employees achieve improved work balance and quality of life in the work-to-leisure conflict raises questions about other types of effective management policies, such as leisure-oriented benefits, that may be investigated by business owners. This would be an issue worthy of future study.

6. Implications and further research The three job stress variables of the JDCS model were used to interpret the work-to-leisure conflict which tourism employees experience. Results of this study indicate that direct and interactive effects of job stress variables actually exist among tourism industries. Though the outcome variables differ from previous literature, parts of the result seem to be congruent as predicted. First the main effects of job controls and supervisor support in the job strain model are investigated. Then it was demonstrated that three job stress variable interactions not only moderate work-toleisure conflict, but also attenuate the bad effect of job demand on work-to-leisure conflict. Tourism occupations are mostly composed of a team cooperate organized work design. Therefore, it may be easier to switch service employees’ shifts to balance their needs between work and leisure over the support of supervisors and colleagues. In other words, the implication of this study confirms that job control and support seem to be effective resources in adjusting the ill-effect of job demands upon service employees’ leisure life. In order to alleviate work-to-leisure conflict, human resource managers need to redesign work scheduling, such as flexible working hours, so service employees can plan leisure life on a personal basis, or hiring part-time workers on holidays so employees may have regular time-off. Both seem to be effective practices for balancing service employees’ work and leisure life. Similar to what Snir and Harpaz (2002) said, extended vacation time is a job design, which facilitates employees’ leisure-oriented life. Moreover, Thomas and Ganster (1995) discovered that workers’ perceived nonwork support reflects accurately on practices available to them, such as work scheduling

References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Anderson, S. E., Coffey, B. S., & Byerly, R. T. (2002). Formal organizational initiatives and informal workplace practices: Links to work-family conflict and job-related outcomes. Journal of Management, 28(6), 787–810. Armstrong, J. S., & Overton, T. S. (1977). Estimating non-response bias in mail surveys. Journal of Marketing Research, 14(3), 396–402. Babin, B. J., & Boles, J. S. (1996). The effects of perceived coworker involvement and supervisor support on service provider role stress, performance, and job satisfaction. Journal of Retailing, 72(1), 57–75. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation model. Journal of the Academy of Marketing Sciences, 16(1), 74–94. Beehr, T. A., Glaser, K. M., Canali, K. G. ., & Wallwey, D. A. (2001). Back to basics: Re-examination of demand–control theory of occupational stress. Work & Stress, 15(2), 115–130. Boles, J. S., & Babin, B. J. (1996). On the frontlines: Stress, conflict, and the customer service provider. Journal of Business Research, 37(1), 41–50. Bollen, K. A. (1990). A comment on model evaluation and modification. Multivariate Behavioral Research, 25(2), 181–185. Breaugh, J. A. (1985). The measurement of work autonomy. Human Relations, 38(6), 551–570. Chick, G., & Hood, R. D. (1996). Working and recreating with machines: Outdoor recreation choices among machine-tool workers in western Pennsylvania. Leisure Sciences, 18(4), 333–354. Daniels, K., & Guppy, A. (1994). Occupational stress, social support, job control, and psychological well-being. Human Relations, 47(12), 1523–1544. de Jonge, J., Janssen, P. P. M., & Van Breukelen, G. J. P. (1996). Testing the Demand–Control–Support Model among health-care professionals: A structural equation model. Work & Stress, 10(3), 209–224. Dwyer, D. J., & Ganster, D. C. (1991). The effects of job demands and control on employee attendance and satisfaction. Journal of Organizational Behavior, 12(4), 595–608.

ARTICLE IN PRESS J.-Y. Wong, J.-H. Lin / Tourism Management 28 (2007) 726–735 Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39–50. Greenhaus, J. H., & Beutell, N. J. (1985). Sources of conflict between work and family roles. Academy of Management Review, 10(1), 76–88. Guest, D. E. (2002). Perspectives in the study of work–life balance. Social Science Information, 41(2), 255–279. Haines, V. A., Hurlbert, J. S., & Zimmer, C. (1991). Occupational stress, social support, and the buffer hypothesis. Work and Occupations, 18(1), 212–235. Hull, R. B., & Michael, S. E. (1995). Nature-based recreation, mood change and stress restoration. Leisure Sciences, 17(1), 1–14. Iso-Ahola, S. E., & Wessinger, E. (1984). Leisure and well-being: Is there a connection? Parks and Recreation, 19(6), 40–44. Jackson, P. R., Wall, T. D., Martin, R., & Davids, K. (1993). New measures of job control, cognitive demand, and production responsibility. Journal of Applied Psychology, 78(5), 753–762. Jamal, M. (2004). Burnout, stress and health of employees on nonstandard work schedules: A study of Canadian workers. Stress and Health, 20(3), 113–119. Johnson, J. V., & Hall, E. M. (1988). Job strain, work place social support, and cardiovascular disease: A cross-sectional study of a random sample of the Swedish working population. American Journal of Public Health, 78(10), 1336–1342. Jo¨reskog, K. G., & So¨rbom, D. (1992). LISEREL: A guide to the program and applications (3rd ed). Chicago: Scientific Software International. Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative Science Quarterly, 24(2), 285–308. Karasek, R. A., & Theorell, T. (1990). Healthy Work: Stress, Productivity and the Reconstruction of Working Life. New York: Basic Books. Karasek, R. A., Triantis, K. P., & Chaudry, S. S. (1982). Coworker and supervisor support as moderators of associations between task characteristics and mental strain. Journal of Occupational Behavior, 3, 181–200. Karatepe, O. M., & Sokmen, A. (2006). The effects of work role and family role variables on psychological and behavioral outcomes of frontline employees. Tourism Management, 27(2), 255–268. Kelly, J. R. (1972). Work and leisure: A simplified paradigm. Journal of Leisure Research, 4(1), 50–62. Kirchmeyer, C. (1992). Non-work participation and work attitudes: A test of scarcity vs. expansion models of personal resources. Human Relations, 45(8), 775–795. Law, J., Pearce, P. L., & Woods, B. A. (1995). Stress and coping in tourist attraction employees. Tourism Management, 16(4), 277–284. Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First and higher order factor

735

models and their invariance across groups. Psychological Bulletin, 97(3), 562–582. McFillen, J. M., Reigel, C. D., & Enz, C. A. (1986). Why restaurant managers quit and how to keep them. Cornell Hotel & Restaurant Administration Quarterly, 27(3), 37–43. O’Driscoll, M. (1996). The interface between job and off-job roles: Enhancement and conflict. In C. Cooper, & I. Robertson (Eds.), International review of industrial and organizational psychology, Vol. 11 (pp. 279–306). Chichester: Wiley. Parkes, K. R., Mendham, C. A., & Von Rabenau, C. (1994). Social support and the demand–discretion model of job stress: Tests of additive and interactive effects in two samples. Journal of Vocational Behaviour, 44(1), 91–113. Rafferty, Y., Friend, R., & Landsbergis, P. A. (2001). The association between job skill discretion, decision authority and burnout. Work & Stress, 15(1), 73–85. Rice, R. W., Frone, M. R., & McFarlin, D. B. (1992). Work–nonwork conflict and the perceived quality of life. Journal of Organizational Behavior, 13(2), 155–168. Rodrı´ guez, I., Bravo, M. J., Peiro´, J. M., & Schaufeli, W. (2001). The Demands Control Support model, locus of control and job dissatisfaction: A longitudinal study. Work & Stress, 15(2), 97–114. Ross, G. F. (1993). Type, severity and incidence of work stressors among Australian hospitality industry employees. Australian of Journal Leisure and Recreation, 3(4), 5–12. Sargent, L. D., & Terry, D. J. (2000). The moderating role of social support in Karasek’s job strain model. Work & Stress, 14(3), 245–261. Sluiter, J. K., Van der Beek, A. J., & Frings-Dresen, M. H. W. (1999). The influence of work characteristics on the need for recovery and experienced health: A study on coach drivers. Ergonomics, 42(2), 573–583. Snir, R., & Harpaz, I. (2002). Work–leisure relations: Leisure orientation and the meaning of work. Journal of Leisure Research, 34(2), 178–203. Staines, G. L. (1980). Spillover versus compensation: A review of the literature on the relationship between work and non-work. Human Relations, 33(2), 111–129. Thomas, L. T., & Ganster, D. C. (1995). Impact of family-supportive work variables on work–family conflict and strain: A control perspective. Journal of Applied Psychology, 80(1), 6–15. Van der Doef, M. P., & Maes, S. (1999). The Job Demand-Control (Support) Model and psychological well-being: A review of 20 years of empirical research. Work & Stress, 13(2), 87–114. Van Sell, M., Brief, A. P., & Schuler, R. S. (1981). Role conflict and role ambiguity: Integration of literature, and direction for future research. Human Relations, 34(1), 43–71. Zedeck, S., & Mosier, K. (1990). Work in the family and employing organization. American Psychologist, 45(2), 240–251.