Acta Psychologica Sinica ›› 2022, Vol. 54 ›› Issue (3): 300-312.doi: 10.3724/SP.J.1041.2022.00300
• Reports of Empirical Studies • Previous Articles Next Articles
LIU WenXing1, ZHU YangHao1, BAI Yang2(), WANG HaiJiang3, HAN Yi1
Received:
2021-05-07
Published:
2022-03-25
Online:
2022-01-25
Contact:
BAI Yang
E-mail:ybai@gsm.pku.edu.cn
Supported by:
LIU WenXing, ZHU YangHao, BAI Yang, WANG HaiJiang, HAN Yi. (2022). Indulge in self-admiration or offer help to others? The influence of employee narcissism on prosocial behavior. Acta Psychologica Sinica, 54(3), 300-312.
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URL: https://journal.psych.ac.cn/acps/EN/10.3724/SP.J.1041.2022.00300
Factors | χ² | df | χ²/df | ∆χ²/∆df | CFI | TLI | RMSEA | SRMR |
---|---|---|---|---|---|---|---|---|
Six-factor model (AN; RN; TI; APM; AVM; PSB) | 374.99 | 120 | 3.13 | / | 0.94 | 0.92 | 0.10 | 0.06 |
Five-factor model (AN + RN; TI; APM; AVM; PSB) | 748.51 | 125 | 5.99 | 373.52(5)*** | 0.85 | 0.82 | 0.15 | 0.10 |
Four-factor model (AN + RN; TI; APM + AVM; PSB) | 1495.17 | 129 | 11.59 | 1120.19(9)*** | 0.67 | 0.61 | 0.21 | 0.15 |
Three-factor model (AN + RN + TI; APM + AVM; PSB) | 2252.12 | 132 | 17.06 | 1877.14(12)*** | 0.49 | 0.41 | 0.26 | 0.19 |
Two-factor model (AN + RN + TI; APM + AVM + PSB) | 2799.65 | 134 | 20.89 | 2424.66(14)*** | 0.36 | 0.26 | 0.29 | 0.20 |
Single factor model (AN + RN + TI + APM + AVM + PSB) | 3573.91 | 135 | 26.47 | 3198.93(15)*** | 0.17 | 0.06 | 0.33 | 0.26 |
Table 1 Confirmatory factor analysis results
Factors | χ² | df | χ²/df | ∆χ²/∆df | CFI | TLI | RMSEA | SRMR |
---|---|---|---|---|---|---|---|---|
Six-factor model (AN; RN; TI; APM; AVM; PSB) | 374.99 | 120 | 3.13 | / | 0.94 | 0.92 | 0.10 | 0.06 |
Five-factor model (AN + RN; TI; APM; AVM; PSB) | 748.51 | 125 | 5.99 | 373.52(5)*** | 0.85 | 0.82 | 0.15 | 0.10 |
Four-factor model (AN + RN; TI; APM + AVM; PSB) | 1495.17 | 129 | 11.59 | 1120.19(9)*** | 0.67 | 0.61 | 0.21 | 0.15 |
Three-factor model (AN + RN + TI; APM + AVM; PSB) | 2252.12 | 132 | 17.06 | 1877.14(12)*** | 0.49 | 0.41 | 0.26 | 0.19 |
Two-factor model (AN + RN + TI; APM + AVM + PSB) | 2799.65 | 134 | 20.89 | 2424.66(14)*** | 0.36 | 0.26 | 0.29 | 0.20 |
Single factor model (AN + RN + TI + APM + AVM + PSB) | 3573.91 | 135 | 26.47 | 3198.93(15)*** | 0.17 | 0.06 | 0.33 | 0.26 |
Variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1. Gender | ||||||||||||
2. Age | 0.31** | |||||||||||
3.Education level | -0.06 | -0.29** | ||||||||||
4. Industry 1 | -0.08 | -0.01 | -0.12 | |||||||||
5. Industry 2 | 0.03 | 0.01 | 0.06 | -0.31** | ||||||||
6. Industry 3 | 0.04 | -0.02 | 0.07 | -0.33** | -0.37** | |||||||
7. AN | -0.11 | -0.27** | -0.19** | 0.10 | -0.03 | -0.05 | ||||||
8. RN | 0.03 | -0.06 | -0.22** | 0.04 | -0.08 | 0.02 | 0.41** | |||||
9. TI | 0.04 | 0.07 | 0.17** | 0.03 | 0.09 | -0.11 | -0.10 | 0.02 | ||||
10. APM | 0.06 | -0.19** | 0.11 | -0.09 | 0.07 | -0.05 | 0.18** | 0.03 | -0.01 | |||
11. AVM | 0.06 | -0.05 | -0.11 | 0.10 | -0.08 | 0.03 | 0.07 | 0.20** | 0.04 | -0.30** | ||
12. PSB | -0.07 | -0.24** | 0.21** | -0.12 | 0.11 | -0.01 | 0.18** | -0.20** | -0.03 | 0.44** | -0.19** | |
M | 0.57 | 29.05 | 3.36 | 0.22 | 0.26 | 0.28 | 3.84 | 2.25 | 3.50 | 5.55 | 1.40 | 5.78 |
SD | 0.50 | 6.59 | 1.07 | 0.42 | 0.44 | 0.45 | 0.57 | 0.73 | 1.38 | 0.93 | 0.67 | 0.91 |
Table 2 Variable description statistics and correlation analysis results
Variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1. Gender | ||||||||||||
2. Age | 0.31** | |||||||||||
3.Education level | -0.06 | -0.29** | ||||||||||
4. Industry 1 | -0.08 | -0.01 | -0.12 | |||||||||
5. Industry 2 | 0.03 | 0.01 | 0.06 | -0.31** | ||||||||
6. Industry 3 | 0.04 | -0.02 | 0.07 | -0.33** | -0.37** | |||||||
7. AN | -0.11 | -0.27** | -0.19** | 0.10 | -0.03 | -0.05 | ||||||
8. RN | 0.03 | -0.06 | -0.22** | 0.04 | -0.08 | 0.02 | 0.41** | |||||
9. TI | 0.04 | 0.07 | 0.17** | 0.03 | 0.09 | -0.11 | -0.10 | 0.02 | ||||
10. APM | 0.06 | -0.19** | 0.11 | -0.09 | 0.07 | -0.05 | 0.18** | 0.03 | -0.01 | |||
11. AVM | 0.06 | -0.05 | -0.11 | 0.10 | -0.08 | 0.03 | 0.07 | 0.20** | 0.04 | -0.30** | ||
12. PSB | -0.07 | -0.24** | 0.21** | -0.12 | 0.11 | -0.01 | 0.18** | -0.20** | -0.03 | 0.44** | -0.19** | |
M | 0.57 | 29.05 | 3.36 | 0.22 | 0.26 | 0.28 | 3.84 | 2.25 | 3.50 | 5.55 | 1.40 | 5.78 |
SD | 0.50 | 6.59 | 1.07 | 0.42 | 0.44 | 0.45 | 0.57 | 0.73 | 1.38 | 0.93 | 0.67 | 0.91 |
Figure 2. Path analysis results of the whole model. Note. The report is a non-standardized coefficient, and the standard error is in brackets; The solid line indicates that the path coefficient is significant, while the dashed line indicates that the path coefficient is not significant. For brevity, the control variable path coefficient has been omitted. * p < 0.05, ** p < 0.01.
Task interdependence | Indirect effect | Standard error | 95% CI of indirect effects | |
---|---|---|---|---|
Low task interdependence | 0.06 | 0.05 | -0.02 | 0.16 |
High task interdependence | 0.21 | 0.07 | 0.08 | 0.36 |
Difference of indirect effects under high and low conditions | 0.14 | 0.07 | 0.03 | 0.30 |
Table 3 Results of mediating effect analysis
Task interdependence | Indirect effect | Standard error | 95% CI of indirect effects | |
---|---|---|---|---|
Low task interdependence | 0.06 | 0.05 | -0.02 | 0.16 |
High task interdependence | 0.21 | 0.07 | 0.08 | 0.36 |
Difference of indirect effects under high and low conditions | 0.14 | 0.07 | 0.03 | 0.30 |
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