000048570 000__ 01913nam\a2200433\i\4500
000048570 001__ 48570
000048570 005__ 20240708150410.0
000048570 006__ m    eo  d        
000048570 007__ cr bn |||m|||a
000048570 008__ 231029s2023\\\\sz\\\\\\\\\\\\000\0\eng\d
000048570 0247_ $$2doi$$a10.1016/j.wpi.2023.102193
000048570 035__ $$a(OCoLC)1411270660
000048570 040__ $$aSzGeWIPO$$beng$$erda$$cSzGeWIPO$$dCaBNVSL
000048570 041__ $$aeng
000048570 24500 $$aForecasting labor needs for digitalization :$$bA bi-partite graph machine learning approach.
000048570 264_1 $$aOxford [England] :$$bElsevier Ltd.,$$c2023
000048570 300__ $$a1 volume.
000048570 336__ $$atext$$2rdacontent
000048570 337__ $$acomputer$$2rdamedia
000048570 338__ $$aonline resource$$bcr$$2rdacarrier
000048570 4901_ $$aWorld Patent Information ;$$v73, June, 2023
000048570 520__ $$aWe use a unique database of digital, and cybersecurity hires from Swiss organizations and develop a method based on a temporal bi-partite network, which combines local and global indices through a Support Vector Machine. We predict the appearance and disappearance of job openings from one to six months horizons. We show that global indices yield the highest predictive power, although the local network does contribute to long-term forecasts. At the one-month horizon, the “area under the curve” and the “average precision” are 0.984 and 0.905, respectively. At the six-month horizon, they reach 0.864 and 0.543, respectively. Our study highlights the link between the skilled workforce and the digital revolution and the policy implications regarding intellectual property and technology forecasting.
000048570 542__ $$fhttps://www.sciencedirect.com/science/article/abs/pii/S0172219023000108
000048570 588__ $$aCrossref
000048570 590__ $$aPublished online: 28-Mar-23
000048570 650_0 $$aIntellectual property.
000048570 650_0 $$aSkilled labor.
000048570 650_0 $$aPatents.
000048570 650_0 $$aCopyright.
000048570 7001_ $$aDavid, Dimitri Percia,$$eauthor.
000048570 7001_ $$aMoreno, Santiago Anton,$$eauthor.
000048570 7001_ $$aMaréchal, Loïc,$$eauthor.
000048570 7001_ $$aMaillart, Thomas,$$eauthor.
000048570 7001_ $$aMermoud, Alain,$$eauthor.
000048570 7730_ $$tWorld Patent Information$$wWPI
000048570 830_0 $$aWorld Patent Information ;$$v73, June, 2023.
000048570 85641 $$uhttps://doi.org/10.1016/j.wpi.2023.102193$$yonline version
000048570 904__ $$aJournal article
000048570 980__ $$aWPI