Table 2.

Estimation results

	(1)	(2)	(3)	(4)	(5)	(6)
	$\widehat{{\beta }_c}$	$\widehat{{\beta }_c}$	$\widehat{{\beta }_c}$	$\widetilde{{\theta }_c}$	$\widehat{{\beta }_c}$$\widetilde{{\theta }_c}$	Percentage of Explained Variation
C1: Dig. increases the time pressure at work	$-$ 0.0741***	$-$ 0.0683***	$-$ 0.0776***	3.23	$-$ 0.21	1.7
	(0.014)	(0.014)	(0.0139)
C2: Dig. puts my job at risk	$-$ 0.0312**	$-$ 0.0287**	$-$ 0.0343***	1.94	$-$ 0.067	0.52
	($-$ 0.0147)	($-$ 0.015)	($-$ 0.0148)
C3: Dig. worsens the work–life balance	$-$ 0.102***	$-$ 0.0953***	$-$ 0.102***	2.72	$-$ 0.278	3.45
	($-$ 0.0151)	($-$ 0.015)	($-$ 0.0148)
C4: Dig. leads to a smooth transition between working hours and leisure time	$-$ 0.0056	0.00145	0.00174	3.01	0.5	0.35
	($-$ 0.0139)	($-$ 0.0139)	($-$ 0.0137)
C5: Dig. makes my work more interesting	0.165***	0.170***	0.155***	3.4	0.527	6.51
	($-$ 0.0169)	($-$ 0.0171)	($-$ 0.0171)
C6: Dig. reduces the proportion of repetitive tasks	0.0138	0.0182	0.0193	3.24	0.063	1.22
	($-$ 0.0137)	($-$ 0.0137)	( $-$ 0.0136)
C7: Dig. increases my productivity	0.281***	0.271***	0.255***	3.65	0.928	11.01
	($-$ 0.0177)	($-$ 0.0177)	($-$ 0.0179)
C8: Dig. increases my autonomy at work	0.0405**	0.0403**	0.0380**	3.15	0.119	1.94
	($-$ 0.0167)	($-$ 0.0167)	($-$ 0.0164)
C9: Dig. enables more flexible forms of working time	0.0231**	0.0344***	0.0269**	3.25	0.087	1.48
	($-$ 0.0119)	($-$ 0.0122)	($-$ 0.0122)
C10: Dig. simplifies interactions with colleagues and superiors	0.0595***	0.0541***	0.0548***	3.41	0.187	3.12
	($-$ 0.0148)	($-$ 0.0148)	($-$ 0.0148)
How strongly does Dig. affect the work over the last year?			0.112***		0.386	3.24
			($-$ 0.0134)
Worker characteristics		Yes	Yes			3.37
N	3089	3089	3089
$R^2$ (%)	34.5	36.2	37.9

Columns (1) to (3) reports the results of the OLS regression having as dependent variable the effect of digitalization on job satisfaction, which is measured on a five point Likert scale (1 = “less satisfied”, 3 = “no change”, 5 = “more satisfied”). Robust standard errors in parentheses. *$p<0.10$, **$p<0.05$, ***$p<0.01$. Worker characteristics is a vector of control variables as described in Table 1 plus industry dummies according to 1-digit NACE Rev. 2 classification. Column (4) shows $\widetilde{{\theta }_c}$, the average effect of digitalization on job characteristics as reported in Table 1. Column (5) multiplies the ${\beta }_c$ from column (3) with the $\widetilde{{\theta }_c}$ from column (4). Column (6) reports the Shapley values, which describe the absolute contribution of each regressor in the goodness-of-fit of the estimation in column (3)