Managerial ties, external resources, and business model innovation: Interplay and mediation analysis

Figures & data

Figure 1. Hypotheses.

Table 1. Correlation matrix and descriptive statistics - latent constructs.

	Mean	SD	Max	Min	INC	TIES	EE	BMI	SIZE	PRIOR	RHO
INC	2.71	0.72	4.42	0.76	1						0.90
TIES	2.04	0.59	3.72	0.72	0.319	1					0.87
EE	1.96	0.48	3.38	0.67	0.430	0.312	1				0.93
BMI	2.31	0.69	3.84	0.77	0.464	0.290	0.388	1			0.93
SIZE	2.71	1.24	5.00	1.00	0.107	0.212	0.024	0.170	1
PRIOR	4.63	3.27	12.00	1.00	0.128	0.034	0.017	0.234	0.324	1

Note: Pairwise correlations based on latent constructs build from factor scores in SEM estimation for the full model. Various models did not change results. Rho is Dillon-Goldstein Rho Chin (1998) considered a more reliable measure of internal validity than Cronbachs Alpha.

Table 2. PLS-SEM results.

			Model 1			Model 2			Model 3			Model 4
			Beta	t-value		Beta	t-value		Beta	t-value		Beta	t-value
IMR	->	BMI	-0.28	-2.21		0.10	0.87		-0.18	-1.23		0.09	0.75
PRIOR	->	BMI	0.09	1.67		0.12	2.28		0.10	1.54		0.12	2.12
SZ	->	BMI	0.10	1.67		0.02	-0.29		0.10	1.65		0.01	0.17
TIES	->	BMI	0.25	5.26		0.10	2.09		0.12	2.35		0.04	0.78
TIES	->	INC				0.33	6.87					0.32	6.28
INC	->	BMI				0.44	6.93					0.36	6.29
TIES	->	EE							0.33	7.64		0.33	6.39
EE	->	BMI							0.34	6.14		0.22	4.07
Incubator Fixed Effects				YES			YES			YES			YES
R2				0.24			0.37			0.33			0.40
Goodnes of fit				0.37			0.37			0.33			0.32
BIC				-349			-486			-495			-581
N				442			442			409			409

Note: Standard errors estimated using boostrapping with 10 000 simulations. VIF test exposed no severe multicolinearity.

Figure 2. Mediation results.

Figure 3. Summarized relationships and support.

Table A1. Factor loadings.

Latent	Item	Lambda	Std. Error	z-value	Latent	Item	Lambda	Std.Error	z-value
TIES	-> Q20.1	0.71	0.04	19.97	EE	-> Q26.1	0.45	0.05	9.63
	-> Q20.2	0.71	0.03	21.56		-> Q26.10	0.64	0.04	17.01
	-> Q20.3	0.70	0.04	17.77		-> Q26.11	0.60	0.04	13.46
	-> Q20.4	0.72	0.03	26.58		-> Q26.12	0.40	0.05	8.15
	-> Q20.5	0.83	0.02	49.12		-> Q26.13	0.69	0.03	22.96
	-> Q20.6	0.72	0.04	20.30		-> Q26.14	0.73	0.03	28.81
						-> Q26.15	0.77	0.02	33.91
INC	-> Q10.3	0.76	0.02	32.26		-> Q26.16	0.65	0.04	17.18
	-> Q10.6	0.83	0.02	42.36		-> Q26.17	0.66	0.04	18.31
	-> Q10.7	0.81	0.02	36.43		-> Q26.18	0.75	0.02	32.11
	-> Q10.8	0.77	0.03	26.65		-> Q26.2	0.61	0.04	16.81
	-> q14_r	0.71	0.03	27.75		-> Q26.3	0.62	0.03	19.94
	-> q15_r	0.75	0.02	34.52		-> Q26.4	0.56	0.04	14.04
						-> Q26.5	0.69	0.03	23.01
BMI	-> Q25.1	0.70	0.03	21.07		-> Q26.6	0.75	0.03	27.04
	-> Q25.2	0.81	0.02	41.53		-> Q26.7	0.71	0.03	23.61
	-> Q25.3	0.81	0.02	39.79		-> Q26.8	0.75	0.02	30.92
	-> Q25.4	0.79	0.02	39.23		-> Q26.9	0.44	0.06	7.82
	-> Q25.5	0.82	0.02	42.03
	-> Q25.6	0.74	0.03	27.50
	-> Q25.7	0.75	0.02	29.94
	-> Q25.8	0.81	0.02	37.40
	-> Q25.9	0.70	0.03	20.39

Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Methodology for business and management. Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.

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