Testing a model of resilience for women leaders: a strengths based approach

Figures & data

Figure 1. Proposed conceptual model tested in this study.

Source: Author’s own work

Table 1. Common method bias (inner variance inflation factors).

	Behaviour	Cognition	Emotion	Resilience
Behaviour		2.332	1.946	2.491
Cognition	1.682		1.762	1.846
Emotion	2.042	2.562		2.336
Resilience	1.584	1.599	1.461

Table 2. Quality criteria (outer model).

	Composite Reliability	Average Variance Extracted (AVE)
Behaviour	.71	.534
Cognition	.797	.663
Emotion	.861	.757
Resilience	1	1

Table 3. Outer loadings.

	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values
Approach Avoidance Style <- Behaviour	.784	.03	26.499	.000
Generalised Self-Efficacy <- Cognition	.853	.023	37.49	.000
Mindfulness <- Cognition	.773	0.039	20.054	.000
Positive Affect <- Emotion	.832	.028	29.618	.000
Personal Control <- Behaviour	.806	.024	33.275	.000
Problem-solving Confidence <- BEH	.749	.039	18.98	.000
Rational Transparency <- BEH	−.623	.054	11.545	.000
Self-Awareness <- Behaviour	.675	.035	19.05	.000
Self-Regulation <- Emotion	.907	.011	85.534	.000
Resilience <- Resilience	1	0

Table 4. Inner model (path coefficients).

	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values
Behaviour -> Resilience	.175	.092	1.904	.029
Cognition -> Behaviour	.294	.056	5.272	.000
Cognition -> Emotion	.624	.039	16.039	.000
Cognition -> Resilience	.104	.069	1.498	.067
Emotion -> Behaviour	.565	.048	11.732	.000
Emotion -> Resilience	.4	.084	4.742	.000

Table 5. Specific indirect effects.

	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values
C -> E -> B -> R	0.062	0.033	1.868	0.031
C -> E -> R	0.250	0.057	4.361	0.000
C -> B -> R	0.051	0.03	1.731	0.042

C = Cognition; E = Emotion; B = Behaviour; R = Resilience.

Table 6. PLS-SEM criteria values for alternative models 1-3.

	Criteria	Model 1 (Behaviour)	Model 2 (Emotion)	Model 3 (Serial)
Asymptotically Efficient (model selection criteria)	AIC	−91.934	−113.206	−115.714
	AICc	165.226	143.954	141.527
PLS Based (in-sample prediction)	R^2	.316	.371	.382
	Adjusted R^2	.311	.366	.375
PLSpredict (out-of-sample prediction)	RMSE	.897	.897	.900
	MAE	.705	.703	.706

AIC = Akaike Information Criterion; AICc = Corrected Akaike Information Criterion; RMSE = Root Mean Square Error; MAE = Mean Absolute Error.

Data availability statement

The data that support the findings of this study are available from the corresponding author, [DPN], upon reasonable request.