Loading...
Reframing talent identification as a status-organising process: Examining talent hierarchies through data mining
Nijs,Sanne Dries ,Nicky Van Vlasselaer,Veronique Sels ,Luc
Nijs,Sanne
Dries ,Nicky
Van Vlasselaer,Veronique
Sels ,Luc
Abstract
We examine how peers form talent appraisals of team members, reframing talent identification as a status-organising social process. Using decision trees, we modelled configurations of characteristics and behaviours that predicted dominant versus parallel routes to achieving the status of most talented team member. Across 44 multidisciplinary teams, talent status was most often granted to peers perceived as having both leadership and analytic talent; a STEM degree served a dominant signalling function. Where previous studies assumed that degree operates as a specific status characteristic, we show that a STEM degree operates as a diffuse status characteristic, which predicts status in general. We thus discovered that status hierarchies in teams are also based on the type of talent—and not just the level of talent—members are perceived to possess. In so doing, we offer a proof of concept of what we call ‘talent hierarchies’ in teams, for future research to build on.
Description
Funding Information: This research was funded by an FWO project grant from the Research Foundation Flanders (G074418N) and an Internal Funds C1 grant from the KU Leuven (C14/17/014).
Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Keywords
talent management; talent identification; talent hierarchies; status; decision trees, data-mining.
Citation
Nijs, S, Dries , N, Van Vlasselaer, V & Sels , L 2022, 'Reframing talent identification as a status-organising process : Examining talent hierarchies through data mining', Human Resource Management Journal, vol. 32, no. 1, pp. 169-193. https://doi.org/10.1111/1748-8583.12401