Talent turnover and the contagion effect: the case of the aerospace industry

Figures & data

Figure 1. POCC-OC-IQ model.

Table 1. Demographic characteristics.

	All talents (N = 56)
Sex
Female (%)	18 (32.14)
Male (%)	38 (67.86)
Age
Minimum	24
Maximum	63
Mean (SD)	33.66 (9.04)
Education
Master’s degree (%)	38 (67.86)
PhD or MBA (%)	18 (32.14)
Mean (SD)	3.54 (0.97)
Position
Executive level (%)	3 (5.4)
Managerial level (%)	14 (25)
General staff (%)	39 (69.6)
Mean (SD)	1.36 (0.58)
Salary(log)
Minimum	4.43
Maximum	5.08
Mean (SD)	4.65 (0.17)

Table 2. Means, standard deviations, and correlations.

Variables	Mean (SD)	1	2	3	4	5	6	7	8
(1) Age	33.66 (9.04)	1
(2) Sex	0.32 (0.47)	0.040	1
(3) Education	3.54 (0.97)	−0.076	−0.145	1
(4) Position	1.36 (0.58)	0.356**	−0.160	−0.055	1
(5) Salary(log)	4.65 (0.17)	0.476**	−0.213	0.237	0.329*	1
(6) Organizational commitment	-	0.134	−0.042	−0.069	0.340*	−0.024	1
(7) Perceived OC of co-workers	-	0.093	−0.022	−0.301*	0.262	−0.166	0.598**	1
(8) Intention to quit	-	−0.062	−0.253	0.331*	−0.170	0.341*	−0.531**	−0.425**	1

Note: We report coefficients for the variables used (Pearson correlation). *Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).

Table 3. Overview of the mediating and moderating effects determined using multiple regression.

Variables	Organizational commitment (OC)	Intention to quit (IQ)
Constant	−0.9477	−0.8612
Age	0.0028	−0.0103
Sex	0.0277	−0.3799
Education	0.1132	0.1909
Position	0.2933	−0.1393
Salary(log)	0.0000	0.0000
POCC	0.5443***	0.0030
OC		−0.5040***
R	0.6381	0.6976
R2	0.4072	0.4866
F	5.6089***	6.4996***

Note: N = 56. ***p < 0.001; **<0.01; *p < 0.05.

We report coefficients for the variables used.

Table 4. Direct and indirect effects of the POCC-OC-IQ model.

	Effect	Se	t	p	LLCI	ULCI
Direct effect (POCC – IQ)	0.0030	0.1388	−0.0214	.9830	−0.2819	0.2760
	Effect	BootSE	BootLLCI	BootULCI
Indirect effect (POCC – OC - IQ)	−0.2743	0.1083	−0.4986	−.0822