| Literature DB >> 34916994 |
Bo Huang1, Lina Ma2, Wei Xia3.
Abstract
The findings of existing studies of how role overload affects employees' performance in organizations have been mixed and controversial. We draw on the hindrance-challenge framework to suggest that role overload contains both hindrance and challenge stressor components. We integrate this theory with the behavioral inhibition and behavioral activation systems (BIS and BAS) perspective to develop hypotheses about the effects of role overload on employees' extra-role performance (voice). We suggest that although role overload is positively associated with withdrawal (a prototypical response of the BIS system) and ultimately negatively influences extra-role performance, it can also trigger job crafting (a prototypical response of the BAS system) and is, consequently, positively associated with extra-role performance. We further posit that the strength of these indirect effects is moderated by the quality of leader-member exchange (LMX). To support these hypotheses, we conducted a time-lagged study of 450 full-time pre-school teachers from various Chinese kindergartens. As hypothesized, we found that withdrawal and job crafting mediated the relationship between role overload and extra-role performance. Further, LMX strengthens the positive relationship between role overload and job crafting. Taken together, our results suggest that role overload can be a mixed stressor that activates both negative and positive behaviors, thus ultimately having an impact on extra-role performance.Entities:
Keywords: challenge stressors; extra-role performance; hindrance stressors; job crafting; leader-member exchange; role overload; voice; withdrawal
Year: 2021 PMID: 34916994 PMCID: PMC8669351 DOI: 10.3389/fpsyg.2021.748732
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Theoretical model of the current research.
Confirmatory factor analysis (CFA) of measurement models.
| Model | x2 | df | x2/df | CFI | TLI | SRMR | RMSEA |
| Four-factor model | 212.979 | 98 | 2.173 | 0.972 | 0.966 | 0.036 | 0.051 |
| Three-factor model | 477.412 | 101 | 4.727 | 0.908 | 0.891 | 0.090 | 0.091 |
| Two-factor model | 834.540 | 103 | 8.102 | 0.821 | 0.792 | 0.140 | 0.126 |
| One-factor model | 2276.217 | 104 | 21.887 | 0.469 | 0.387 | 0.226 | 0.216 |
A four-factor model composed of role overload, withdrawal, job crafting, voice. A three-factor model with role overload, withdrawal combined. A two-factor model with role overload, withdrawal, and job crafting combined. A one-factor model with role overload, withdrawal, job crafting, and voice loaded onto a single factor.
Means, standard deviations, and correlations among the variables.
|
| SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
| 1. Age | 30.40 | 8.27 | – | ||||||||
| 2. Education | 2.59 | 0.64 | −0.11* | – | |||||||
| 3. Income | 7.56 | 9.06 | 0.86** | 0.00 | – | ||||||
| 4. Tenure | 3.68 | 1.64 | 0.30** | 0.48** | 0.37** | – | |||||
| 5. Role Overload | 3.40 | 0.98 | 0.07 | 0.20** | 0.07 | 0.13** | (0.93) | ||||
| 6. Withdrawal | 2.05 | 0.78 | −0.22** | 0.26** | −0.13** | 0.03 | 0.29** | (0.88) | |||
| 7. Job Crafting | 3.52 | 0.41 | 0.20** | 0.03 | 0.17** | 0.06 | 0.14** | −0.10* | (0.80) | ||
| 8. Voice | 3.78 | 0.55 | 0.23** | −0.10* | 0.20** | 0.04 | –0.05 | −0.32** | 0.31** | (0.91) | |
| 9. LMX | 3.88 | 0.87 | 0.23** | −0.15** | 0.16** | –0.06 | −0.13** | −0.34** | 0.34** | 0.45** | (0.87) |
n = 466; **p < 0.01, *p < 0.05. Cronbach’s alpha is in parentheses.
Summary of indirect effects and moderated indirect effects.
| Effects | Estimates |
| 95% confidence intervals |
|
| |||
| Indirect effects | –0.039 | 0.010 | [−0.061, −0.022] |
| Moderated mediation | |||
| High-LMX | –0.030 | 0.011 | [−0.053, −0.010] |
| Low-LMX | –0.047 | 0.013 | [−0.075, −0.023] |
|
| |||
| Indirect effects | 0.017 | 0.007 | [0.005, 0.032] |
| Moderated mediation | |||
| High-LMX | 0.042 | 0.011 | [0.021, 0.065] |
| Low-LMX | 0.011 | 0.010 | [−0.007, 0.032] |
Regression analyses for the effect of perceived role overload and withdrawal.
| Withdrawal | ||||
| M1 | M2 | M3 | M4 | |
| Age | −0.312*** | −0.350*** | −0.264** | −0.267** |
| Education | 0.244*** | 0.184*** | 0.173*** | 0.174*** |
| Income | –0.049 | –0.048 | –0.071 | –0.073 |
| Tenure | 0.157 | 0.171* | 0.147 | 0.155 |
| Role overload | 0.273*** | 0.241*** | 0.465** | |
| LMX | −0.251*** | –0.067 | ||
| Role overload × LMX | –0.276 | |||
|
| 0.109 | 0.179 | 0.236 | 0.239 |
| Δ | 0.071 | 0.057 | 0.003 | |
|
| 13.553*** | 19.415*** | 22.864*** | 19.878*** |
| Δ | 38.315*** | 33.092*** | 1.735 | |
n = 466; ***p < 0.001, **p < 0.01, *p < 0.05.
FIGURE 2The interactive effect of perceived role overload and LMX on withdrawal.
Regression analyses for the effect of perceived role overload and job crafting.
| Job Crafting | ||||
| M5 | M6 | M7 | M8 | |
| Age | 0.239** | 0.223* | 0.105 | 0.112 |
| Education | 0.082 | 0.056 | 0.071 | 0.070 |
| Income | –0.050 | –0.049 | –0.018 | –0.014 |
| Tenure | –0.014 | –0.008 | 0.024 | 0.010 |
| Role overload | 0.118* | 0.162*** | –0.256 | |
| LMX | 0.341*** | –0.002 | ||
| Role overload × LMX | 0.516* | |||
|
| 0.046 | 0.059 | 0.165 | 0.175 |
| Δ | 0.013 | 0.105 | 0.010 | |
|
| 5.399*** | 5.616*** | 14.583*** | 13.426*** |
| Δ | 6.23* | 55.942*** | 5.581* | |
n = 466; ***p < 0.001, **p < 0.01, *p < 0.05.
FIGURE 3The interactive effect of perceived role overload and LMX on job crafting.