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autonomy was positively related to vigor. Keywords: job demands-resource model, vigor, emotional exhaustion, challenge and hindrance stressor, autonomy.
2009 International Conference on Management Science & Engineering (16th) September 14-16, 2009 Moscow, Russia

Challenge and Hindrance Job Demands, Job Resource, and Their Relationships with Vigor and Emotional Exhaustion LIN Lin1,2,3,SIU Oi-ling4,SHI Kan2,BAI Xin-wen1 1 Institute of Psychology, Chinese Academy of Sciences, P.R. China, 100101 2 Graduate University of Chinese Academy of Sciences, P.R. China, 100080 3 Central University of Finance and Economics, P.R. China, 100081 4 Lingnan University, Hong Kong Abstract: This study extended the job demandsresources model by investigating the different impact of challenge and hindrance stressors on vigor (key dimension of work engagement) and exhaustion (key dimension of job burnout). Data was collected from 199 nurses of a hospital in a two-time-period survey with a three-month time lag. Results supported those theoretical extensions that the relationship between job demands and vigor might depend on whether the demands are associated with hindrances or challenges. (a) Quantitative workload, a challenge stressor, was positively related to vigor. (b) Office politics, a hindrance stressor, was negatively related to vigor. (c) Both quantitative workload and office politics had positive effect on emotional exhaustion. (d) In addition, autonomy was positively related to vigor. Keywords: job demands-resource model, vigor, emotional exhaustion, challenge and hindrance stressor, autonomy

1 Introduction Organizations place great emphasis on employees’ work engagement because it has positive and beneficial consequences at the individual and organizational levels, such as organizational commitment, physical health, and even business-unit performance[1-3]. Some scholars have responded to this concern by conducting numerous studies on its antecedents in the theoretical context, which is the job demands-resources (JD-R) model[4, 5]. Research in this domain is potentially valuable because organization in the top quartile on engagement had at least $300,000 higher monthly revenue or sales than their counterparts[3]. Concomitantly, workforce in both eastern and western society is experiencing increasing levels of stress as a result of demands such as broadened job scopes, increased workloads, situational constraints, and job uncertainty [6, 7]. This becomes a major concern to managers because stressful work demands are thought to Supported by Grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project no: LU3111/04H), and the National Natural Science Foundation of China ( 70573108, 70802059)

reduce employee work engagement[2, 8, 9] and therefore cost business in productivity losses[10]. However, a close examination of the empirical literature reveals that stressors may not always be deleterious with respect to job attitudes. For example, using meta-analysis, researchers[11, 12] found that hindrance stressors were negatively associated with performance and challenge stressors were positively associated with performance and also that the differential effects on performance could be attributed to differential stressor effects on motivation, job satisfaction, and organizational commitment. These inconsistencies in the research findings suggest that existing theories linking, JD-R model, may not be sufficient to explain the mechanism of vigor. Recent extended studies on work stress suggest that it is important to distinguish the different forms of job demands (e.g. workload and organizational politics,). We therefore intended to assess the general idea that some types of job demands might be negatively related to work engagement, especially vigor; whereas other types of job demands might be positively related to work engagement. One of the objectives of the current study was to integrate the challenge stressor-hindrance stressor framework with a theoretical model that has been used to link stressors to employee work engagement so as to explain the divergent impacts of differential stressor might have on[4, 5]. In the current study, we treated each of these types of stressors individually rather than combining them into overall measures stressors, as they each represent distinct constructs. As depicted in Figure 1, the secondary objective of our study was to examine the effect of autonomy as one kind of job resource, which is thought to have a positive influence on vigor. 1.1 Vigor and emotional exhaustion Burnout is a psychological response to work-related stress that consists of emotional exhaustion, cynicism, and reduced professional efficacy[13]. Because this phenomenon has become organizational reality for many employees, now, burnout is the subject of thousands of research articles and dozens of books[14]. But with the rise of ‘positive psychology’ that focuses on human strengths and optimal functioning rather than on

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weaknesses and malfunctioning, burnout research seems to shift towards its positive antipode: work engagement. Work engagement is defined as a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption[15]. Vigor, the first and key dimension of work engagement, refers to high levels of energy and mental resilience while working, the willingness to invest effort in one’s work, and persistence in the face of difficulties [15] . As the negative opposite of vigor, emotional exhaustion is defined as the feelings of being overextended and depleted of one’s emotional and physical resources[13]. In this study, we focus on the vigor component of work engagement and the emotional exhaustion component of job burnout. This approach is justified, in large part, because of three issues. First, vigor and emotional exhaustion are the central variables for understanding the engagement and burnout process respectively. Conceptually, emotional exhaustion best capture the “core meaning” of burnout[13, 16, 17]; empirically, emotional exhaustion exhibits somewhat stronger relationships than do the other components to important outcome variables[18]. Meanwhile, as the conceptual opposite of emotional exhaustion, vigor is also considered to be the core dimension of engagement[16]. Second, emphasizing vigor and emotional exhaustion has allowed scholars to more clearly distinguish engagement and burnout from related concepts, such as job involvement and self-efficacy[19, 20]. Third, the results of confirmatory factor analysis in some studies shows that reduced professional efficacy is included in the extended engagement factor, other than burnout factor[2, 15, 21], suggesting that three burnout dimensions and the three engagement dimensions is not stable to some extent. In keeping with these empirical findings and conceptual frameworks, we explored the relationship of vigor and emotional exhaustion to job demands, resources, job performance, and physical/psychological health. 1.2 The job demands-resources model The Job Demands-Resources (JD-R) model[4, 5] is employed by scholar to specify the two basic dimensions of work place factors, job demands and job resources namely, which associate with employee well-being. Job demands represent characteristics of the job that potentially evoke strain, in case they exceed the employee’s adaptive capability. More specifically, job demands are those physical, psychological, social, or organizational aspects of the job that require sustained physical and/or psychological (cognitive and emotional) effort or skills and are therefore associated with certain physiological and/or psychological costs[4, 5]. In the present study, we included quantitative work overload as well as office politics. Quantitative workload refers to the amount of work required and the time limit during which work must be completed[22]. Workload is a major stressor, and has been found to be positively related to

employees’ emotional exhaustion among many occupations which require emotional labor, such as nurses[23, 24], call center employees[25], teachers and bank employees[26] and so on. Office politics depicts the ill atmosphere that prevents employees from actively participating and openly communicating, and was negatively related to job satisfaction [27]. On the other hand, job resources refer to those physical, psychological, social, or organizational aspects of the job that (a) reduce job demands and the associated physiological and psychological costs, (b) are functional in achieving work goals, or (c) stimulate personal growth, learning, and development[5]. In the present study, we selected autonomy as an important aspect of job resources. A main assumption in the JD-R model is that working characteristics may evoke two psychologically different processes. In the first, health impairment process, poorly designed jobs or chronic job demands (e.g. work overload, emotional demands) exhaust employees’ mental and physical resources and may therefore lead to the depletion of energy (i.e. a state of exhaustion) and to health problems[1, 2, 5]. It’s demanding to work under high job demands while maintaining performance at the usual level, and can readily exceed employees’ strained emotional capacity[28]. Consistent with previous studies[23-26], we propose that job demand, workload and office politics. The second process proposed by the JD-R model is motivation process, whereby it is assumed that job resources have motivational potential and lead to high work engagement and positive outcomes such as organizational commitment and employee performance[2, 29]. Autonomy has long been identified as a crucial determinant of intrinsic motivation[30], and is positively related to work engagement[5]. Accordingly, as depicted in Figure 1, we hypothesized that: Hypothesis 1: Quantitative workload will be positively associated with emotional exhaustion. Hypothesis 2: Office politics will be positively associated with emotional exhaustion. Hypothesis 3: Autonomy will be negatively associated with emotional exhaustion. Hypothesis 4: Autonomy will be positively associated with vigor. 1.3 The challenge stressor-hindrance stressor framework Demands in this JD-R model or nearly any theory of occupational stress are considered to be stressors[4, 31], and stressors should be negatively related to vigor and this relationship could be moderated by job resources. However, literature on stressors suggests that stressors may not always lead to harmful individual reactions. Studies revealed that stressors that people tend to appraise as potentially promoting their personal growth and achievement (i.e., challenge stressors) should be distinguished from stressors that people tend to appraise

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as potentially constraining their personal development and work-related accomplishment (i.e., hindrance stressors) because these two types of stressors are differentially associated with employee job attitudes such as job satisfaction and loyalty[11, 32-34], cognitions such as turnover intentions[11, 33], and behaviors such as withdrawal behavior and task performance[11, 12]. Researchers proposed that challenge stressors was composed of quantitative and subjective workload, time pressure, job or role demands, pressure to complete tasks, job scope, and responsibility, and hindrance stressors consisted of situational constraints, hassles, organizational politics, resource inadequacies, role ambiguity, role conflict, role overload, and concerns about job security[11, 12, 34]. From this perspective, quantitative workload and office politics are both positively related to emotional exhaustion. The explanation for this relationship is that exhaustion results from elevated levels of arousal and information processing associated with the desire to understand and cope with the demands of an ongoing situation[35]. This expectation is in line with the previous hypothesis which is raised based on the JD-R model. In contrast to the linking stress to exhaustion, however, the linkage between stressors and vigor is complicated. Similar to emotional exhaustion, office politics, a kind of hindrance stressors, is negatively associated with vigor. However, different from exhaustion, workload, a challenge stressor, tends to increase the level of vigor. This is because when experiencing challenge stress, employees will feel that the situation is positive and fulfilled, so that they will likely cope with their stress behaviorally by allocating more of their effort to work (increased the level of vigor). Alternatively, when facing hindrance stressor, employees will feel that the situation is negative, they will tend to cope cognitively, and less effort will be focused toward working (decreased the level of vigor). The divergent relationships among different types of stressors and motivation might be interpreted by attribution theory[36]. Perrewe and Zellars suggested that stressors are associated with cognitions of motivational incongruence (which is similar to expectancy) and relevance (which is similar to instrumentality) and that these cognitions ultimately influence the degree to which individuals attempt to cope with stressors either in an active/problem-solving mode or in a passive/emotionbased mode. Quantitative workload is perceived to be controllable for which a coping strategy is obvious, and are likely to be met with an active/problem-solving mode of coping (e.g., increase in effort, vigor). Office politics is perceived to be uncontrollable or without an obvious coping strategy, and therefore is not likely to be met with an increase in effort, but with withdrawal and cognitive distancing . In summary, as depicted in Figure 1, we hypothesized that: Hypothesis 5: Quantitative workload will be positively associated with vigor.

Hypothesis 6: Office politics will be negatively associated with vigor. Quantitative workload

+ Vigor

+ Autonomy

+

Office politics

+

Emotional exhaustion

Fig.1 Hypothesized research model

2 Method 2.1 Procedure and participants Analyses were based on a two-time-period survey conducted among nurses of a hospital from Beijing, the major city of the PRC. All nurses were invited to participate on a voluntary basis. Questionnaires contained an administration number for second-round identification. For reasons of confidentiality, we knew the code of the administration number, and questionnaires could be returned in sealed envelopes. The surveys were administered with a three-month time lag, to reduce the possibility of common method variance[37]. Thus, predictor variables and control variables were collected in the first survey, while criterion variables were collected in survey two. In essence, the ability of criterion variables to be influenced by answers to predictor variables is nullified by the three-month time gap. This self-reported questionnaire was distributed on two occasions: in November 2005 (Time 1) and in February 2006 (Time 2). At Time 1, 223 employees received a questionnaire, which 200 employees returned (response rate of 89.7%). The Time 2 questionnaires were sent solely to those who participated in the first data collection wave. That is, at Time 199 out of 200 returned the usable questionnaires, resulting in a response rate of 99.5%. Consequently, the final wave of the study consisted of 199 persons (89.2% of the initial group) who responded to the questionnaire on both occasions. The demographic characteristics of the respondents in the final wave of the study showed that the ages ranged from 19 to 54 years (M = 33.6, SD = 9.0). Most respondents were female (88.4%). The mean working tenure was 11.3 years (SD = 9.1). 2.2 Measures Stressors were collected at Time 1 while the ratings of vigor and emotional exhaustion were collected at

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Time 2. All materials were presented in Chinese and all scales we used were translated into Chinese from English. Quantitative workload. Three items extracted from Spector and Jex[38] were used, and they have also been found reliable in Chinese samples[39]. Each item was rated by the frequency ranged from “Very inaccurate” (1) to “Very accurate” (6). In our study, coefficient alpha was .85. Office politics. Seven items extracted from Western scales were used, with one from An Organizational Stress Screening Tool (ASSET)[40], two items from Occupational Stress Indicator (OSI)[41], and four items from OSI-2[42]. This 7-item scale was also found reliable in Chinese samples[27, 43]. Each item was rated by the frequency ranged from “Very inaccurate” (1) to “Very accurate” (6). Its coefficient alpha in our study was .78. Autonomy. The 3-item job autonomy subscale from Job Diagnostic Survey[30] was used (e.g., ‘You decide on your own how to go about doing the work’). Each item was rated by the frequency ranged from “Very inaccurate” (1) to “Very accurate” (6). In this study, coefficient alpha was .84. Vigor. We used six items from the Work Engagement Scale[15], which has been translated into Chinese and shown to have good psychometric properties[44]. All items were scored on a 7-point frequency rating scale ranging from 0 (never) to 6 (always).Coefficient alpha for this scale in our study was .85. Emotional exhaustion. Five-item measure adapted from the emotional exhaustion subscale of the Maslach Burnout Inventory[45] was used to assess emotional exhaustion. Respondents were asked to indicate how often they had certain feelings at work using a 0–6 Likert scale (0 = “never”, 6 = “always”). A Chinese version of this scale has shown good psychometric properties[46]. Coefficient alpha for this scale in our study was .90.

3 Results 3.1 Confirmatory factor analysis Prior to assessing our structural model and hypotheses, we assessed the measurement model. Given the computational limitation for LISREL models, we constructed parcels for the three constructs, office politics, vigor, and emotonal exhaustion, on the basis of their unidimensionality. We formed three indicators for each latent construct by sequentially averaging their items with the highest and lowest loadings, respectively[47]. The first model freely estimated the relationships among all five variables. Following recommendations by Hoyle and Panter[48], we evaluated model fit by using several fit indices, including RMSEA, CFI, NFI, and IFI. Results of this model are shown in Table 1 and suggest good fit with the data. Although the chi-square test was statistically significant (χ2(80) = 192.6, p < .001), the CFI, NFI, IFI and RMSEA all suggested good fit (.93, .88, .93

and .084, respectively), showing all indices falling within acceptable ranges[49]. We also noted that for each indicator, there was a statistically significant loading on the corresponding latent variable (p < .001). Furthermore, we compared these results with those of two alternative models: model 1, in which quantitative workload and office politics were combined into one factor, and model 2, in which emotional exhaustion and vigor were combined into a single factor. As shown in Table 1, models 1 and 2 exhibited significantly poorer fit than the baseline model, as can be seen from the significant chisquare difference tests and model fit indexes. These results in tandem provide clear evidence of the distinctiveness of the main variables in the study. 3.2 Descriptive statistics Table 2 shows the means, standard deviations, internal consistency reliabilities, and correlations among the variables in this study. The zero-order correlation between vigor and emotional exhaustion was .32 (p < .01). Supporting our CFA tests, these measures appeared conceptually and empirically distinguishable. 3.3 Assessing the structural model We started assessing the structural model similar to that depicted in Figure 1. The coefficient of each path is shown in Figure 2. As shown in row 1 of Table 3, this model (Hypothesized model) fit the data well. Although the chi-square was statistically significant, χ2 (81, N = 199) = 171.8, p < .01, the CFI and IFI were greater than .90, and the RMSEA was low (.075). Row 3 of Table 3 shows the results of a job demands combination model (Model 1). Quantitative workload and office politics were combined into one factor to test the JD-R model used in the past majority studies. The chi-square was statistically significant, χ2 (85, N = 199) = 353.2, p < .01, the CFI, NFI and IFI (all much lower than .90), and the RMSEA (.126) suggested poor fit. 3.4 Assessing the hypotheses Quantitative workload, office politics, and autonomy explained 25.1% of the variance in emotional exhaustion. Consistent with Hypotheses 1 and 2, Quantitative workload and office politics were both positively related to emotional exhaustion (γ = .38, p < .01, and γ = .20, p < .05, respectively). Thus Hypothesis 1 and 2 was supported. Quantitative workload, office politics, and autonomy explained 13.6% of the variance in vigor. Consistent with our expectations, Quantitative workload, as a challenge stressor, and office politics, as a hindrance stressor, had differential relationships with vigor. In support of Hypotheses 5 and 6, quantitative workload had a positive effect on vigor (γ = .21, p < .05) while office politics had a negative effect on vigor (γ = -.33, p < .05). Consistent with Hypothesis 4, autonomy was positively but marginally related to vigor (γ = .16, p = .055). However, autonomy was not significantly

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related to emotional exhaustion (β = -.02, p < .05), which means Hypothesis 3 was not supported. Quantitative workload

.21* .16†

Vigor

-.33** Autonomy .38**

Office politics

.20*

Emotional exhaustion

Fig.2 Standardized parameter estimates for the structural model Note. † p< .10; * p < .05; ** p < .01

4 Discussion The aim of the current study was to test a research model that specifies possible predictors of burnout and engagement, based on an energetically driven and a motivational driven process, respectively. To accomplish this purpose, we extended JD-R theory[4] to include challenge stressor–hindrance stressor framework[11]. At a general level, the results of our study support these theoretical extensions that the relationship between job demands and vigor may depend on whether the demands are associated with hindrances or challenges. In particular, we found that quantitative workload was positively related to vigor. In contrast, quantitative workload and office politics were positively related to emotional exhaustion. In addition, autonomy was positively related to vigor. 4.1 Theoretical implications The findings of this study contribute to the literature on work engagement by incorporating challenge stressor–hindrance stressor framework into its theoretical framework, JD-R model. Whereas the JD-R model states that job demands are negatively associated with work engagement and the majority of the previous research on work engagement treated the challenge job demands the same as the hindrance job demands, this view is challenged by our findings. Indeed, in our study the relationship between an undifferentiated measure of job demands (formed by taking the items of quantitative workload and office politics together) and vigor was -.04 (statistically non-significant). However, the research findings that vigor could be boosted by quantitative workload as well as autonomy suggested that challenge job demands and hindrance job demands should be differentiated when we consider the mechanism of work engagement. On the one hand, following the energetic process, challenge job demands cause physical and psychological symptoms through emotional exhaustion,

and the effect is stronger than that of hindrance job demands; on the other hand, following the motivation process, challenge job demands improve job performance through vigor, and the effect is also stronger than that of job resources. That is, motivation process exists not only between job resources and work engagement but also between challenge job demands and work engagement. At the very least, therefore, our findings suggest that job demands are not created equally and that this complexity needs to be considered in work engagement theories and research. 4.2 Managerial implications Knowledge gained from our research might be useful in designing work environments that not only promote job performance, but also consider employees work well-being. Given the findings reported in this article, it may be possible for managers to motivate employees by providing sufficient job resources and assigning welldesigned challenging jobs. In fact, quantitative workload had a stronger absolute positive impact than autonomy on vigor. This practical implication is much more operational because it does not require organizations to increase the job resources to the maximum level and decrease the job demands to the minimum level. Providing challenging job together with sufficient job resources can let employees engage in their job more deeply and efficiently. Our findings also revealed that both challenge and hindrance job demands are related to work psychological state but in opposite directions. These divergent relationships may have important implications for employee motivation and stress intervention in the workplace. In particular, our findings suggest that employees may attempt to be exhausted where job demands are constraining, whereas job demands that are developmental in nature may be viewed as beneficial to staff. Consequently, job demands or stress should not be considered as being solely negative and bad. It may be appropriate for managers to differentiate between the two categories of stressors when considering stress management practices. Quantitative workload, a challenge job demand, is a double-edged sword. It both benefits and costs the individual as well as the organization much. The implication for employers who are worried about the impact stress has on organizations, is that by focusing on job aspects that are positive and challenging they may actually enhance positive outcomes. For example, providing jobs that are structured to allow greater amounts of responsibility, with greater scope, may encourage positive outcomes. However, our research also highlights a potential tradeoff with respect to perceptions of challenge stress in the workplace, and this may have practical value. That is, although challenge stress may be motivational, such stress also has costs with respect to personal well-being. There is a need to caution employers about seeing challenge stressors as the

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Tab.1 Comparison of measurement models for main variables in the study Factors

Model Baseline model Model 1 Model 2

Five factors Four factors; quantitative workload and office politics were combined into one factor. Four factors; emotional exhaustion and vigor were combined into one factor.

χ2

df

χ2/df

192.6

80

2.41

350.0

84

4.20

421.5

84

5.02

Δχ2

CFI

NFI

IFI

RMSEA

.93

.88

.93

.084

157.4**

.83

.79

.83

.127

228.9**

.78

.74

.78

.142

** p < .01 Tab.2 Means, standard deviations, and correlations among variables Variables

M

SD

1

2

3

4

5

1. Quantitative workload

4.16

1.09

(.85)

2. Office politics

3.24

0.85

.38**

(.78)

3. Autonomy

3.65

1.09

-.15*

-.27**

(.84)

4. Vigor

3.49

1.15

.04

-.24**

.22**

(.85)

5. Emotional exhaustion

2.61

1.41

.38**

.33**

-.13

-.32**

(.90)

Note. a n =. Cronbach alpha coefficients for multi-item scales are listed on the diagonal in parentheses. * p < .05; ** p < .01; Two-tailed tests. Tab.3 Comparison of fit of the alternative models Model

χ2

df

χ2/df

CFI

NFI

IFI

RMSEA

Hypothesized model

171.8

81

2.12

0.94

0.89

0.94

0.075

Model 1 Quantitative workload and organizational climate were combined into one factor.

353.2

85

4.12

0.83

0.79

0.83

0.126

‘panacea’ to stress concerns. For example, an employer might load employees with more job roles, responsibilities and autonomy, and while they perform these well and enjoy more positive work attitudes, they still might suffer debilitating personal health. Hence, the physical and mental effects of stress should be a dual focus of an organization’s human resource department in dealing with stress worries and organizations should well structure the challenging task demands with cautious to reduce the probability of health impairment. Nevertheless, given that people in many occupations appear to seek out and persist in highly challenging jobs[50], organizations could implement training (e.g., time management, coping skills), managerial support practices, and other programs (e.g., time off to exercise) that could effectively reduce the associated strain[51]. In contrast to the apparent tradeoff associated with challenge job demands, our research suggests that hindrance job demands may be detrimental to work wellbeing, and this has potential implications for the way work psychological environments might be managed with respect to instructional design and administration. Managers could seek to reduce the presence of hindrance stressors in the workplace. Previous research evidence suggested that employees and organizations would be

well served if hindrances such as organizational politics and interpersonal conflict were kept to a minimum. 4.3 Limitations and future research As with all studies, limitations in our work exist. A limitation of this study is we did not study motivation directly. However, previous literature found that challenge stressors associate with desirable work outcomes (i.e., enhanced loyalty, improved performance) through motivation or felt challenge[12, 33, 52]. This evidence supports the idea that motivation process not only exists between job resources and engagement but also exists between challenge job demands and engagement. Employees who experience stress associated with workload may feel a heightened sense of job challenge and ultimately enhanced vigor. It should also be noted that we only assessed quantitative workload and office politics as the representatives of challenge and hindrance stressors, and we only focus on their relationships with vigor and emotional exhaustion. This variable-sampling approach, on the one hand, allowed us to apply the challenge stressor-hindrance stressor framework to the JD-R model in a more specific way; on the hand, it impaired the generalizability of this finding. We recommend that

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continued research is needed to further identify additional challenge and hindrance job demands and investigate how these different types of stress relate to each dimension of work engagement. Another limitation of the study is that we investigated a specific group of employees, namely individuals working in a single Chinese hospital as nurses. This means that future research is needed to clarify the generalizability of our findings in different organizational and occupational settings and countries. While we expect that the separation of challenge job demands and hindrance job demands should not necessarily vary with occupation, the relevant job demands and job resources may be different. Nevertheless, the quantitative workload, non-supportive organizational, and autonomy tested in this study have a solid basis in the literature and should not be neglected in future research. Strength of this study was that while self-reported data were typical in well-being research, data were collected in two time periods with a sizable gap between surveys (three months) to control common method variance. Consequently, the relationships found between predictor and criterion variables were not likely to be found because answers from one set of questions (e.g., job demands and job resources) encouraged answers to the other sets of questions (e.g., well-beings). This strengthens the findings of the present study. However, ‘stressor time 1 and strain time 2 designs’ design is also the limitation of this study. We tried to reduce the likelihood of percept–percept bias by asking respondents to assess the level of the stressors and resources at Time 1 and well-being at Time 2. The finding that both quantitative workload and office politics associated with the work well-being but in opposite directions suggests that percept–percept bias was not a significant threat to the validity of this research. It is not simply the case that employees reporting a high level of stress also reported a high level of negative outcomes. However, we could not make strong inferences with respect to causality. For example, it is unclear whether employees who feel a great deal of quantitative workload are consequently more vigorous, or whether vigorous employees put in extra effort and take on more responsibility thus resulting in higher levels of quantitative workload. Given the limitation of ‘stressor time 1 and strain time 2 designs’, additional research needs to use longitudinal or quasiexperimental designs to better assess the nature of the causal relationships among job demands, job resources and work engagement. 4.4 Conclusion In conclusion, with the limitations of this research in mind, our study suggests that it may be useful to distinguish challenge job demands from hindrance job demands when study work engagement within the framework of JD-R model. Future research should closely examine the mechanisms that explain why and how job demands are related to work engagement.

Knowledge gained from such research might be useful in designing workplace environments that not only promote job performance, but also consider employee well-being. References

References [1]J. J. Hakanen, A. B. Bakker, W. B. Schaufeli. Burnout and work engagement among teachers[J]. Journal of School Psychology, 2006, 43:495-513. [2]W. B. Schaufeli, A. B. Bakker. Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study[J]. Journal of Organizational Behavior, 2004, 25(3): 293-315. [3]J. K. Harter, F. L. Schmidt and T. L. Hayes. Businessunit-level relationship between employee satisfaction, employee engagement, and business outcomes: A metaanalysis[J]. Journal of Applied Psychology, 2002, 87(2): 268-279. [4]A. B. Bakker, E. Demerouti. The job demandsresources model: state of the art[J]. Journal of Managerial Psychology, 2007, 22(3): 309-328. [5]E. Demerouti, A. B. Bakker, F. Nachreiner, W. B. Schaufeli. The job demands-resources model of burnout[J]. Journal of Applied Psychology, 2001, 86(3): 499-512. [6]S. M. Jex. Stress and job performance: Theory, research, and implications for managerial practice[M]. Sage, 1998. [7]J. L. Xie, G. Johns. Job scope and stress: Can job scope be too high?[J]. Academy of Management Journal, 1995, 38: 1288-1309. [8]E. Demerouti, A. B. Bakker, J. De Jonge, P. P. Janssen, W. B. Schaufeli. Burnout and engagement at work as a function of demands and control[J]. Scandinavian Journal of Work, Environment & Health, 2001, 27(4): 279-286. [9]J. J. Hakanen, A. B. Bakker, E. Demerouti. How dentists cope with their job demands and stay engaged: The moderating role of job resources[J]. European Journal of Oral Sciences, 2005, 113(6): 479-487. [10]Gallup. Unhappy workers are unhealthy too[J]. Gallup Management Journal, 2005, October 5. [11]N. P. Podsakoff, J. A. Lepine, M. A. Lepine. Differential challenge stressor-hindrance stressor relationships with job attitudes, turnover intentions, turnover, and withdrawal behavior: A meta-analysis[J]. Journal of Applied Psychology, 2007, 92(2): 438-454. [12]J. A. Lepine, N. P. Podsakoff, M. A. Lepine. A metaanalytic test of the challenge stressor-hindrance stressor framework: An explanation for inconsistent relationships among stressors and performance [J]. Academy of Management Journal, 2005, 48(5): 764-775. [13]C. Maslach, W. B. Schaufeli, M. P. Leiter. Job burnout[J]. Annual Review of Psychology, 2001, 52: 397-422. [14]J. R. B. Halbesleben, M. R. Buckley. Burnout in organizational life[J]. Journal of Management, 2004, 30: 859-879.

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[15]W. B. Schaufeli, M. Salanova, V. Gonzalez-Roma, A. B. Bakker. The measurement of engagement and burnout: A two sample confirmatory factor analytic approach[J]. Journal of Happiness Studies, 2002, 3: 71-92. [16]V. Gonzalez-Roma, W. B. Schaufeli, A. B. Bakker, S. Lloret. Burnout and work engagement: Independent factors or opposite poles?[J]. Journal of Vocational Behavior, 2006, 68(1): 165-174. [17]A. Shirom. Feeling vigorous at work? The construct of vigor and the study of positive affect in organizations: Research in organizational stress and well-being[M]. Greenwich, CN: JAI Press, 2003: 135-165. [18]R. T. Lee, B. E. Ashforth. A meta-analytic examination of the correlates of the three dimensions[J]. Journal of Applied Psychology, 1996, 81(2): 123-133. [19]U. E. Hallberg, W. B. Schaufeli. “Same Same” but different: Can work engagement be discriminated from job involvement and organizational commitment?[J]. European Psychologist, 2006, 11(2): 119-127. [20]A. Shirom. Burnout in work organizations: International review of industrial and organizational psychology[M]. New York: Wiley, 1989: 25-48. [21]W. B. Schaufeli, I. M. Martinez, P. A. Marques, M. Salanova, A. B. Bakker. Burnout and engagement in university students: A cross-national study[J]. Journal of Cross-Cultural Psychology, 2002, 33(5): 464-481. [22]C. L. Cooper, P. J. Dewe, M. P. O'Driscoll. Organizational stress: A review and critique of theory, research and applications[M]. Sage, 2001. [23]M. P. Leiter. Perception of risk: An organizational model of occupational risk, burnout, and physical symptoms[J]. Anxiety, Stress, and Coping, 2005, 18(2): 131-144. [24]E. R. Greenglass, R. J. Burke, K. A. Moore. Reactions to increased workload: Effects on professional efficacy of nurses[J]. Applied Psychology: An International Review, 2003, 52(4): 580-597. [25]S. Deary, R. Iverson, J. Walsh. Work relationships in telephone call centres: Understanding emotional exhaustion and employee withdrawal[J]. Journal of Management Studies, 2002, 39(4): 471-496. [26]I. Houkes, P. P. Janssen, J. De Jonge, F. J. Nijhuis. Specific relationships between work characteristics and intrinsic work motivation, burnout and turnover intention: A multi-sample analysis[J]. European Journal of Work & Organizational Psychology, 2001, 10(1): 1-23. [27]O. Siu, C. L. Cooper, I. Donald. Occupational stress, job satisfaction, and mental health among employees of an acquired TV company in Hong Kong[J]. Stress Medicine, 1997, 13(2): 274-288. [28]M. P. Leiter. Coping patterns as predictors of burnout: The function of control and escapist coping patterns[J]. Journal of Organizational Behavior, 1991, 12(2): 123144. [29]M. Salanova, S. Agut, J. M. Peiro. Linking organizational resources and work engagement to employee performance and customer loyalty: The mediation of service climate[J]. Journal of Applied Psychology, 2005, 90(6): 1217-1227.

[30]J. R. Hackman, G. R. Oldham. Development of the job diagnostic survey[J]. Journal of Applied Psychology, 1975, 60(2): 159-170. [31]R. L. Kahn, P. Byosiere. Stress in organizations[C]// EA Locke & MD Dunnette, Ed. Handbook of Industrial and Organizational Psychology. Palo Alto, CA, US: Consulting Psychologists Press, 1992: 571-650. [32]J. M. Haar. Challenge and hindrance stressors in New Zealand: Exploring social exchange theory outcomes[J]. The International Journal of Human Resource Management, 2006, 17(11): 1942-1950. [33]W. R. Boswell, J. B. Olson-Buchanan, M. A. Lepine. Relations between stress and work outcomes: The Role of felt challenge, job control, and psychological strain[J]. Journal of Vocational Behavior, 2004, 64(1): 165-181. [34]M. A. Cavanaugh, W. R. Boswell, M. V. Roehling, J. W. Boudreau. An empirical examination of self-reported work stress among us managers[J]. Journal of Applied Psychology, 2000, 85(1): 65-74. [35]C. L. Cooper, P. J. Dewe, D. M. O. Organizational stress: A review and critique of theory, research and applications[J]. Sage, 2001. [36]P. L. Perrewe, K. L. Zellars. An examination of attributions and emotions in the transactional approach to the organizational stress process[J]. Journal of Organizational Behavior, 1999, 20(5): 739-752. [37]P. M. Podsakoff, S. B. Mackenzie, J. Y. Lee, N. P. Podsakoff. Common method biases in behavioral research: A critical review of the literature and recommended remedies[J]. Journal of Applied Psychology, 2003, 88(5): 879-903. [38]P. E. Spector, S. M. Jex. Development of four selfreport measures of job stressors and strain: Interpersonal conflict at work scale, organizational constraints scale, quantitative workload inventory, and physical symptoms inventory[J]. Journal of Occupational Health Psychology, 1998, 3(4): 356-367. [39]O. Siu, P. E. Spector, C. L. Cooper, C. Lu. Work stress, self-efficacy, chinese work values, and work wellbeing in Hong Kong and Beijing[J]. International Journal of Stress Management, 2005, 12(3): 274-288. [40]S. Cartwright, C. L. Cooper. Asset: An organizational stress screening tool, the management guide[M]. RCL Ltd., 2002. [41]C. L. Cooper, S. J. Sloan, S. Williams. Occupational stress indicator: Management guide[M]. NFER-Nelson, 1988. [42]C. L. Cooper, S. Williams. Occupational stress indicator Version 2.0[M]. NFER-Nelson, 1996. [43]O. Siu, D. R. Phillips. Study of stress among staff in Mtrcl[R]. Commissioned by Mtr Corporation Limited, 2005. [44]Y. Zhang, Y. Gan, H. Cham. Perfectionism, academic burnout and engagement among chinese college students: A structural equation modeling analysis[J]. Personality and Individual Differences, 2007, 43(6): 1529-1540. [45]C. Maslach, S. E. Jackson, M. P. Leiter. Maslach burnout inventory manual[M]. Consulting Psychologists Press, 1996.

- 1105 -

Authorized licensed use limited to: Sheffield University. Downloaded on January 8, 2010 at 06:57 from IEEE Xplore. Restrictions apply.

[46]S. Wu, W. Zhu, Z. Wang, M. Wang, Y. Lan. Relationship between burnout and occupational stress among nurses in China[J]. Journal of Advanced Nursing, 2007, 59(3): 233-239. [47]T. D. Little, W. A. Cunningham, G. Shahar, K. F. Widaman. To parcel or not to parcel: Exploring the question, weighing the merits[J]. Structural Equation Modeling, 2002, 9(2): 151-173. [48]R. H. Hoyle, A. T. Panter. Writing about structural equation models[C]// RH Hoyle Ed. Structural Equation Modeling: Concepts, Issues, and Applications, 1995: 158-176. [49]L. Hu, P. M. Bentler. Evaluating model fit.[C]//RH

Hoyle Ed. Structural Equation Modeling: Concepts, Issues, and Applications. Thousand Oaks, CA: Sage, 1995: 76-99. [50]J. Miller, M. Miller. Get a life![M]. 2005, 152: 109124. [51]S. Sonnentag, M. Frese. Stress in organizations[C]// I. B. Weiner. Handbook of Psychology: Industrial and Organizational Psychology. Hoboken, New Jersey, USA: John Wiley & Sons, Inc., 2003: 453-491. [52]J. A. Lepine, M. A. Lepine, C. L. Jackson. Challenge and hindrance stress: Relationships with exhaustion, motivation to learn, and learning performance[J]. Journal of Applied Psychology, 2004, 89(5): 883-891.

- 1106 -

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