LEADER 02334nam  22003613a 450 
001 9910831803203321
005 20250710152355.0
010   $a9789286155192
010   $a9286155190
035   $a(CKB)5690000000124158
035   $a(ScCtBLL)4d75e209-20c7-4ccf-a91f-bafba50f3c6d
035   $a(ScCtBLL)f2b4af00-dbb9-4fdf-9d58-f3163fdbd5f1
035   $a(EXLCZ)995690000000124158
100   $a20240402i20232024  uu 
101 0 $aeng
135   $auru||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aEIB Working Paper 2023/01 - Advanced digital technologies and investment in employee training : $eComplements or substitutes? /$fEuropean Investment Bank
210  1$a[s.l.] :$cEuropean Investment Bank,$d2023.
215   $a1 online resource (56 p.)
330   $a"  The use of advanced digital technologies such as 3D printing, advanced robotics, drones, big data analytics and artificial intelligence is spreading. These technologies have uncertain implications for labour demand. Affected workers may need to re-train to adapt to changing tasks or new jobs. At the same time, it is unclear whether or not advanced digital technologies encourage firms to invest in workforce re-training.  Using firm-level data covering the 27 EU countries, the UK and the US, this paper shows that employers tend to reduce investment in training per employee, after adopting advanced digital technologies. It estimates, with a control function approach, firm-level production functions augmented with two factors: training per employee and digital technology use. We show that these are in fact substitutes in production, implying that an increase in the former negatively affects the marginal productivity of the latter, and that a decline in the cost of introducing advanced digital technologies reduces employers' investment in training per employee. These findings point to challenges in realising high levels of firm-sponsored training for employees in increasingly digital economies. "
606   $aBusiness & Economics$2bisacsh
606   $aEconomics
615  7$aBusiness & Economics
615  0$aEconomics.
801  0$bScCtBLL
801  1$bScCtBLL
906   $aBOOK
912   $a9910831803203321
996   $aEIB Working Paper 2023$93396814
997   $aUNINA