Fairness perceptions of supervisor feedback, LMX, and employee well-being at work

Figures & data

Figure 1. Model examined in the study. Partial mediation between fairness of feedback and well-being and control at work via LMX is hypothesized in Hypotheses 6 and 7. Signs in parentheses indicate the direction of the postulated relationships.

TABLE 1 Means, standard deviations, reliabilities, and intercorrelations

Variable	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. Industry	1.80	0.40	–
2. Trait negative affectivity	1.80	0.65	.06	.90
3. Frequency negative supervisor feedback (T1)	1.36	0.76	−.06	.29**	–
4. Frequency positive supervisor feedback (T1)	2.22	1.22	.01	−.07	.00	–
5. Supervisory position (T1)	1.71	0.46	−.05	.10	−.16	−.14	–
6. Fairness perceptions of feedback (T1)	3.26	0.87	−.17	−.17	−.23*	.62**	−.08	.95
7. Distributive fairness (T1)	3.24	1.07	−.08	−.22*	−.24*	.59**	−.04	.92**	.93
8. Procedural fairness (T1)	2.86	0.90	−.29**	−.10	−.11	.56**	−.11	.87**	.75**	.82
9. Interpersonal fairness (T1)	3.96	0.93	−.09	−.28**	−.38**	.47**	−.11	.85**	.77**	.60**	.92
10. Informational fairness (T1)	3.08	0.98	−.17	−.05	−.14	.55**	−.02	.91**	.77**	.74**	.75**	.86
11. LMX (T2)	3.02	0.94	−.11	−.39**	−.10	.43**	.04	.57**	.55**	.49**	.49**	.49**	.92
12. Job anxiety (T2)	3.01	1.26	−.15	.57**	.39**	−.11	.02	−.25*	−.30**	−.14	−.33**	−.14	−.32**	.76
13. Job depression (T2)	2.57	1.56	.04	.56**	.27**	−.04	.07	−.35**	−.37**	−.23*	−.39**	−.31**	−.48**	.48**	.88
14. Job satisfaction (T2)	5.06	1.43	−.13	−.52**	−.12	.02	−.10	.31**	.34**	.24*	.31**	.25*	.52**	−.42**	−.74**	–
15. Turnover intentions (T2)	3.13	2.04	−.11	.35**	.03	.03	.06	−.24*	−.24*	−.13	−.31**	−.23*	−.35**	.27**	.65**	−.61**	.89
16. Control at work (T2)	4.16	1.16	.09	−.28**	−.12	.17	−.22*	.29**	.27**	.22*	.29**	.26*	.46**	−.30**	−.50**	.55**	−.38**	.85
T1 = Time 1, T2 = Time 2; Industry was coded 1 = “R&D”, 2 = “public administration”. Supervisory position was coded 1 = “yes”, 2 = “no”. Cronbach's alphas appear along the diagonal. *p < .05, two-tailed; **p < .01, two-tailed.

TABLE 2 Regression results for Hypothesis 1

	LMX (T2)
	ß	t
Step 1
Industry	−.086	−1.018
Trait negative affectivity	−.373	−4.159***
Frequency negative supervisor feedback (T1)	.029	0.321
Frequency positive supervisor feedback (T1)	.424	4.979***
Supervisory position (T1)	.138	1.582
	R ^2 = .339***
Step 2
Industry	.001	0.009
Trait negative affectivity	−.351	−4.265***
Frequency negative supervisor feedback (T1)	.136	1.576
Frequency positive supervisor feedback (T1)	.143	1.414
Supervisory position (T1)	.156	1.951
Fairness perceptions of feedback (T1)	.463	4.372***
	R ^2 = .453
	ΔR ^2 = .114***
T1 = Time 1, T2 = Time 2; Industry was coded 1 = “R&D”, 2 = “public administration”. Supervisory position was coded 1 = “yes”, 2 = “no”. *p < .05, **p < .01, ***p < .001.

TABLE 3 Regression results for Hypothesis 2 and Hypothesis 3

	Job anxiety (T2)		Job depression (T2)		Job satisfaction (T2)		Turnover intentions (T2)		Control at work (T2)
	ß	t	ß	t	ß	t	ß	t	ß	t
Step 1
Industry	−.166	−2.069*	.019	0.219	−.103	−1.172	−.133	−1.385	.084	0.872
Trait negative affectivity	.508	5.989***	.517	5.695***	−.521	−5.595***	.388	3.813***	−.236	−2.305*
Frequency negative supervisor feedback (T1)	.226	2.641**	.124	1.358	.023	0.247	−.093	−0.906	−.072	−0.698
Frequency positive supervisor feedback (T1)	−.077	−0.953	.004	0.043	−.025	−0.277	.058	0.603	.131	1.351
Supervisory position (T1)	−.011	−0.135	.035	0.391	−.051	−0.566	.009	0.091	−.182	−1.831
	R ^2 = .410***		R ^2 = .325***		R ^2 = .289***		R ^2 = .150**		R ^2 = .144*
Step 2
Industry	−.177	−2.199*	−.016	−0.201	−.061	−0.778	−.167	−1.817	.126	1.425
Trait negative affectivity	.461	5.010***	.367	4.021***	−.340	−3.769***	.245	2.337*	−.055	−0.543
Frequency negative supervisor feedback (T1)	.229	2.691**	.136	1.610	.009	0.109	−.082	−0.843	−.086	−0.916
Frequency positive supervisor feedback (T1)	−.024	−0.261	.175	1.951	−.231	−2.613*	.221	2.146*	−.074	−0.745
Supervisory position (T1)	.006	0.074	.090	1.091	−.119	−1.452	.062	0.652	−.249	−2.713**
LMX (T2)	−.125	−1.283	−.402	−4.161***	.486	5.091***	−.383	−3.443**	.436	4.499***
	R ^2 = .420		R ^2 = .432		R ^2 = .445		R ^2 = .247		R ^2 = .298
	ΔR ^2 = .010		ΔR ^2 = .107***		ΔR ^2 = .156***		ΔR ^2 = .097**		ΔR ^2 = .154***
T1 = Time 1, T2 = Time 2; Industry was coded 1 = “R&D”, 2 = “public administration”. Supervisory position was coded 1 = “yes”, 2 = “no”. *p < .05, **p < .01, ***p < .001.

TABLE 4 Regression results for Hypothesis 4 and Hypothesis 5 (Step 2), Hypothesis 6 and Hypothesis 7 (Step 3)

	Job anxiety (T2)		Job depression (T2)		Job satisfaction (T2)		Turnover intentions (T2)		Control at work (T2)
	ß	t	ß	t	ß	t	ß	t	ß	t
Step 2
Industry	−.199	−2.417*	−.063	−0.765	−.026	−0.306	−.223	−2.411*	.137	1.399
Trait negative affectivity	.500	5.927***	.496	5.874***	−.501	−5.711***	.365	3.844***	−.222	−2.210*
Frequency negative supervisor feedback (T1)	.186	2.101*	.024	0.272	.118	1.278	−.203	−2.040*	−.007	−0.069
Frequency positive supervisor feedback (T1)	.028	0.275	.267	2.579*	−.273	−2.534*	.349	2.985**	−.039	−0.315
Supervisory position (T1)	−.018	−0.218	.018	0.216	−.035	−0.415	−.010	−0.103	−.171	−1.754
Fairness perceptions of feedback (T1)	−.173	−1.596	−.434	−3.995***	.409	3.623***	−.477	−3.905***	.280	2.164*
	R ^2 = .426		R ^2 = .424		R ^2 = .377		R ^2 = .271		R ^2 = .185
	ΔR ^2 = .016		ΔR ^2 = .100***		ΔR ^2 = .089***		ΔR ^2 = .121***		ΔR ^2 = .041*
Step 3
Industry	−.199	−2.409*	−.063	−0.791	−.026	−0.333	−.223	−2.454*	.137	1.497
Trait negative affectivity	.474	5.121***	.394	4.420***	−.360	−4.022***	.278	2.722**	−.061	−0.597
Frequency negative supervisor feedback (T1)	.196	2.179*	.064	0.736	.063	0.723	−.169	−1.709	−.070	−0.700
Frequency positive supervisor feedback (T1)	.039	0.371	.309	3.058**	−.331	−3.263**	.384	3.314**	−.104	−0.898
Supervisory position (T1)	−.006	−0.076	.063	0.782	−.099	−1.214	.029	0.317	−.243	−2.615*
Fairness perceptions of feedback (T1)	−.139	−1.163	−.299	−2.598*	.222	1.924	−.362	−2.746**	.067	0.510
LMX (T2)	−.074	−0.687	−.291	−2.825**	.404	3.902***	−.249	−2.103*	.458	3.866**
	R ^2 = .429		R ^2 = .471		R ^2 = .467		R ^2 = .304		R ^2 = .300
	ΔR ^2 = .003		ΔR ^2 = .046**		ΔR ^2 = .089***		ΔR ^2 = .034*		ΔR ^2 = .115***
Step 1 is left out because it is similar to Step 1 in Table 3. T1 = Time 1, T2 = Time 2; Industry was coded 1 = “R&D”, 2 = “public administration”. Supervisory position was coded 1 = “yes”, 2 = “no”. *p < .05, **p < .01, ***p < .001.

TABLE 5 Overview over the results from multiple regression analyses with single fairness dimensions

	LMX	Job anxiety	Job depression	Job satisfaction	Turnover intentions	Control at work
Step 2
Distributive fairness	.383***	−.171	−.391***	.406***	−.385**	.218^+
Procedural fairness	.353***	−.127	−.274*	.286*	−.287*	−.207^+
Interpersonal fairness	.345***	−.143	−.317**	.288*	−.459***	.197
Informational fairness	.356***	−.107	−.403***	.340**	−.431***	.264*
Step 3
Distributive fairness		−.141	−.271*	.252*	−.273*	.038
LMX		−.078	−.312**	.403***	−.293*	.471***
Procedural fairness		−.093	−.148	.128	−.171	.041
LMX		−.096	−.356**	.446***	−.330**	.471***
Interpersonal fairness		−.112	−.199^+	.135	−.366**	.034
LMX		−.090	−.340**	.444***	−.269*	.473***
Informational fairness		−.072	−.297**	.190^+	−.336**	.105
LMX		−.100	−.299**	.420***	−.267*	.447***
Values in the cells are standardized beta coefficients of the respective regression analyses. ^+ p < .10, *p < .05, **p < .01, ***p < .001.