Key points are not available for this paper at this time.
Across different disciplinary boundaries, research into algorithmic surveillance (Newlands, 2020), people analytics (Gal et al., 2020; Marler Tursunbayeva et al., 2018), human resource management (HRM) algorithms (Cheng 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 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 aggregated 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 Minbaeva, 2017; Tursunbayeva et al., 2018; Van den Heuvel Leicht-Deobald et al., 2019), and artificial intelligence (AI) deployed in HRM practices (Strohmeier 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).
Meijerink et al. (Thu,) studied this question.