| Literature DB >> 27375514 |
Abstract
Benevolent leadership, a traditional Chinese leadership style generated under the influence of Confucianism, has been under growing discussion since its proposal. However, existing research has focused mainly on the consequences of benevolent leadership, and research probing into its antecedents is scarce. To fill such research gap, the current study aims to explore the effect of the congruence between implicit positive followership prototype (PFP) and explicit positive followership trait (PFT) on benevolent leadership. Polynomial regression combined with the response surface methodology was used to test the hypotheses herein. The results, based on a sample of 241 leader-follower dyads from four Chinese family firms, indicated the following: (1) benevolent leadership is higher when leader PFP is congruent with follower PFT than when they are incongruent; (2) in cases of congruence, benevolent leadership is higher when leader PFP and follower PFT are both high rather than low; (3) in the case of incongruence, there is no significant difference for the level of benevolent leadership in two scenarios: "low leader PFP - high follower PFT" and "high leader PFP - low follower PFT".Entities:
Keywords: benevolent leadership; implicit followership theory; polynomial regression; positive followership prototype; positive followership trait
Year: 2016 PMID: 27375514 PMCID: PMC4895044 DOI: 10.3389/fpsyg.2016.00812
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
The four different scenarios of (in) congruence between leader PFP and follower PFT.
| Leader PFP | |||
|---|---|---|---|
| Low | High | ||
| Congruence scenario Low leader PFP-Low follower PFT | Incongruence scenario High leader PFP-Low follower PFT | ||
| Incongruence scenario Low leader PFP-High follower PFT | Congruence scenario High leader PFP-High follower PFT | ||
Means, standard deviations, and correlations.
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | |||
|---|---|---|---|---|---|---|---|---|---|
| 1. Gender similarity | 0.42 | 0.49 | |||||||
| 2. Age similarity | 8.15 | 5.27 | -0.05 | ||||||
| 3. Education similarity | 5.56 | 3.51 | -0.03 | 0.01 | |||||
| 4. Dyadic tenure | 2.97 | 7.20 | 0.13 | -0.39∗∗∗ | -0.02 | ||||
| 5. Firm size | 229.71 | 79.67 | 0.13∗ | -0.08 | 0.03 | 0.12 | |||
| 6. Leader PFP | 4.75 | 0.93 | -0.13 | 0.20∗∗ | 0.06 | 0.02 | 0.01 | ||
| 7. Follower PFT | 3.98 | 1.02 | 0.18∗∗ | -0.37∗∗∗ | -0.00 | 0.30∗∗∗ | 0.61∗∗∗ | 0.05 | |
| 8. Benevolent leadership | 4.07 | 0.74 | 0.08 | -0.05 | 0.02 | 0.04 | 0.04 | 0.15∗ | 0.21∗∗∗ |
Confirmatory factor analyses.
| Model | Δ | RMSEA | RMR | CFI | GFI | NFI | ||
|---|---|---|---|---|---|---|---|---|
| M1: PFP; PFT; BL | 48.34 | 17 | — | 0.08 | 0.07 | 0.97 | 0.95 | 0.96 |
| M2: PFP+PFT; BL | 256.27 | 19 | 207.93 (2) | 0.23 | 0.21 | 0.79 | 0.78 | 0.78 |
| M3: PFP; PFT+BL | 209.58 | 19 | 161.24 (2) | 0.20 | 0.11 | 0.83 | 0.85 | 0.82 |
| M4: PFP+BL; PFT | 218.61 | 19 | 170.27 (2) | 0.21 | 0.12 | 0.83 | 0.84 | 0.82 |
| M5: PFP+PFT+BL | 409.70 | 20 | 361.36 (3) | 0.29 | 0.22 | 0.66 | 0.72 | 0.65 |
Polynomial regressions.
| Variable | Benevolent leadership | ||
|---|---|---|---|
| Model 1 | Model 2 | Model 3 | |
| Constant | 4.00∗∗∗ | 4.21∗∗∗ | 4.37∗∗∗ |
| Age similarity | 0.10 | 0.10 | 0.12 |
| Gender similarity | -0.01 | -0.01 | -0.00 |
| Education similarity | 0.01 | 0.00 | 0.01 |
| Dyadic tenure | 0.00 | -0.02 | -0.02 |
| Firm size | 0.00 | 0.00 | -0.00 |
| Leader PFP (b1) | 0.12∗ | 0.13∗ | |
| Follower PFT (b2) | 0.21∗∗∗ | 0.23∗∗ | |
| Leader PFP2 (b3) | -0.06 | ||
| Leader PFP × Follower PFT (b4) | 0.16∗∗∗ | ||
| Follower PFT2 (b5) | -0.04 | ||
| 0.42 | 3.04∗∗ | 3.49∗∗∗ | |
| 0.01 | 0.08 | 0.13 | |
| Δ | 0.07∗∗∗ | 0.05∗ | |
| Slope | 0.36∗∗∗ | ||
| Curvature | 0.06 | ||
| Slope | -0.10 | ||
| Curvature | -0.26∗ | ||