How does the position of firms in the supply chain affect their performance? An empirical study

Applied Network Science

Table 6 GLS regression results—productivity

	Standardised estimate—dependent variable: productivity
	Model 1 (Base Model 1)	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8 (Base Model 2)
Intercept	− 0.087	− 0.008	− 0.982	− 0.731	− 0.786	− 0.714	0.785	− 0.755
Independent variables
SNTL1		− 0.477***		− 0.255***	− 0.266**	− 0.329***	− 0.224***	− 1.362***
SNTL2			− 0.654**
SNC		0.162*	0.908*	0.127*				0.829*
(SNC)²				− 0.436**
ST					0.453***		0.033	0.002
SSH					− 0.040			− 0.179
BT						0.819***	0.085	0.501*
BSH						− 0.314*		− 0.89***
ST × BT							− 0.438
Control variables
AGE	0.212*	0.121	0.128**	0.002	0.008**	0.002**	0.007	0.010
PUB	− 0.205*	− 0.292*	0.054	0.754	0.811	0.163*	0.182*	0.016**
JAP	0.257	0.098	0.718	0.003	0.001	0.009	0.811	0.779
DL
R²	0.11	0.28	0.40	0.28	0.39	0.38	0.32	0.48
Adjusted R²	0.09	0.27	0.37	0.29	0.38	0.37	0.30	0.47
F	5.019	10.01	12.47	17.17	18.44	16.87	16.39	25.04
p value	7.91e−04	2.70e−09	1.061e−10	< 2.2e−16	< 2.2e−16	< 2.2e−16	< 2.2e−16	< 2.2e−16
Improvement over base R²		0.17	0.29	0.17	0.28	0.27	0.21	0.37
Max VIF	4.01	4.33	1.38	4.19	4.58	9.31	34.39	93.83