Candidate Screening for the Recruitment of Critical Research and Development Workers – A Report and Preliminary Results with Evidence from Experimental Data from German High-Tech Firms

Abstract

Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. AbstractThe report focuses on résumé-based screening strategies for the recruitment of highly qualified research and development (R&D) workers (critical R&D workers) in high-tech firms. We investigate which kinds of professional background, job-related experience, motivations, specific skills, and previous inventive activity make a candidate attractive for firms specializing in clean technology or mechanical elements. The report is based on a combination of survey and experimental data collected from 194 HR decision makers in German high-tech firms and from 89 technology experts in the clean technology and mechanical elements fields. A mixed logit model is used to analyse hiring preferences because this model allows us to deal with repeated choices. We find that HR decision makers prefer candidates with technology-specific patenting experience, an engineering background, analytical thinking skills, and a strong desire to develop path-breaking technologies. Furthermore, no one-size-fits-all candidate exists that is equally preferred in both technology fields. HR decision makers in mechanical element firms prefer specialists to generalists, whereas those in clean technology attach special importance to a candidate's orientation towards environmental concerns and sustainability.

Individual Determinants of Inventor Productivity: Report and Preliminary Results with Evidence from Linked Human Capital and Patent Data

“…In a second step, we identified unique inventors listed on the patent documents who had an address in Germany at the time of the patent filing. We removed 458 inventors from the sample (305 inventors mentioned on CT patents and 153 inventors mentioned on ME patents) because we wanted to question them in another survey (Frosch et al, 2014). In addition, 150 inventors were used to pretest our survey instrument (100 inventors mentioned on CT patents and 25 inventors each mentioned on NT and ME patents).…”

Do recruiters select workers with different personality traits for different tasks? A discrete choice experiment

“…Other discrete choice experimental studies have analysed the importance of the applicants' educational background (Teijeiro et al, 2013;Di Stasio, 2014; Di Stasio and van de Werfhorst, 2016), study abroad experiences (Petzold, 2017) or origin (Protsch and Solga, 2017) in the firm's hiring process. Moreover, some studies have focussed on specific sectors such as health institutions or high-tech firms (Biesma et al, 2007;Frosch et al, 2015).…”

Do Recruiters Select Workers with Different Personality Traits for Different Tasks? A Discrete Choice Experiment

“…Other discrete choice experimental studies have analysed the importance of the applicants' educational background (Teijeiro et al, 2013;Di Stasio, 2014;Di Stasio and van de Werfhorst, 2016), study abroad experiences (Petzold, 2017) or origin (Protsch and Solga, 2017) in the firm's hiring process. Moreover, some studies have focussed on specific sectors such as health institutions or high-tech firms (Biesma et al, 2007;Frosch et al, 2015).…”