Table 8

Economic consequence test results

Variable(1)(2)(3)
FPFnedum = 1Fnedum = 0
Robot0.002***0.002*0.002
(3.04)(1.70)(1.45)
Size−0.0000.001−0.003
(−0.35)(1.07)(−1.17)
Lev−0.016−0.037***0.017
(−1.33)(−5.86)(1.65)
Growth0.0090.0110.013***
(1.24)(1.28)(3.55)
Age−0.003−0.001−0.008***
(−1.30)(−0.27)(−4.22)
ROA0.642***0.690***0.533***
(10.68)(9.63)(8.22)
Board0.051***0.063**0.030*
(3.98)(2.41)(1.79)
Indep0.099**0.129*0.084***
(2.37)(1.70)(4.66)
Dual0.001−0.004*0.008*
(0.27)(−1.75)(1.72)
Mshare−0.004−0.005−0.010***
(−1.38)(−0.91)(−5.16)
FM−0.006−0.0040.052
(−0.94)(−0.34)(1.29)
Child−0.003−0.006−0.000
(−1.65)(−1.59)(−0.20)
HT−0.006***−0.007***−0.007**
(−3.11)(−2.61)(−2.05)
Law0.0000.000−0.001
(0.12)(0.32)(−0.80)
YearYYY
IndustryYYY
Cons−0.108**−0.184**−0.006
(−2.17)(−2.58)(−0.10)
N610424186
R20.4850.4470.662

Note(s): This table reports the regression results of the economic consequence test. Column (1) reports the result of robot adoption on future performance. Columns (2) and (3) report the results of the impact of family non-executive directors on the relationship between robot adoption and future performance. We report t-statistics in parentheses. All models include year and industry-fixed effects. *, ** and *** indicate two-tailed statistical significance at the 10%, 5% and 1% levels, respectively. All variables are defined in  Appendix

Source(s): Table by authors

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