Abstract:
Across different disciplinary boundaries, research into algorithmic
surveillance (Newlands, 2020), people analytics (Gal et al., 2020;
Marler & Boudreau, 2017; Tursunbayeva et al., 2018), human resource
management (HRM) algorithms (Cheng & Hackett, 2021), and algo rithmic control (Kellogg et al., 2020; Veen et al., 2020) is gaining
traction. Moreover, these various concepts are studied alongside –
and at times interchangeably with – related phenomena including
Big Data (Garcia-Arroyo & Osca, 2019), artificial intelligence
(Strohmeier & Piazza, 2015; Tambe et al., 2019) and online labor
platforms (Duggan et al., 2020; Newlands, 2020; Veen et al., 2020).
These terms and developments are often loosely linked to, or aggre gated as, ‘digital HRM’ which, as a broad notion covers a multitude
of topics and issues with unclear and ambiguous relations between
them (Strohmeier, 2020b). Studies into HR analytics ( Marler &
Boudreau, 2017; Minbaeva, 2017; Tursunbayeva et al., 2018; Van den
Heuvel & Bondarouk et al., 2017 ), HRM algorithms (Cheng &
Hackett, 2021; Leicht-Deobald et al., 2019), and artificial intelligence
(AI) deployed in HRM practices (Strohmeier & Piazza, 2015; Vrontis
et al., 2021), while beginning to coalesce around key issues, tend to
use different terms to describe seemingly similar content leading to a lack of construct clarity that may prevent the scholarly community
from building a collective and coherent body of knowledge
(Suddaby, 2010).
