The Internet of Things (‘IoT’) refers to the ability to connect physical objects (‘things’) to the Internet and thus equip them with the unprecedented functionality of autonomous context-adequate behaviour. Thus, physical objects that are connected to the Internet are called ‘smart things’ (or ‘cyber-physical systems’, as an earlier designation). Consequently, the IoT is broadly discussed as a future core technology with the potential for disruptive changes (e.g. Ashton, 2009; Atzori, Iera, & Morabito, 2010; Borgia, 2014; Chui, Löffler, & Roberts, 2010; Fleisch, 2010; Miorandi, Sicari, De Pellegrini, & Chlamtac, 2012; National Intelligence Council, 2008). At present, there is a broad range of actual and potential IoT application domains. Following an established naming convention, such application domains are designated with the prefix ‘smart’ (e.g. Guillemin & Friess, 2009; Vermesan et al., 2013). It is expected that business, in particular, constitutes an important future application domain (e.g. Fantana et al., 2013; Fleisch, 2010), and there are already diverse business application domains, such as smart manufacturing (e.g. Chand & Davis, 2010), smart logistics (e.g. Resch & Blecker, 2012), smart retailing (e.g. Pantano & Timmermans, 2014) or smart health (e.g. Solanas et al., 2014). In these application domains, larger and even disruptive changes with copious opportunities and threats are expected. Consequently, broad research initiatives accompany the emerging application of the IoT to contribute to a better understanding of its application and consequences (e.g. Baiyere et al., 2016; Miorandi et al., 2012; Vermesan et al., 2013). As a prominent example, manufacturing research has notably turned towards ‘smart manufacturing’. This is manifested in a large number of research contributions regarding the IoT in manufacturing. In the meantime, smart manufacturing is widely understood as a ‘new paradigm’ and ‘the fourth revolution’ of manufacturing (e.g. Kang et al., 2016; Thoben, Wiesner, & Wuest, 2017). Contrary to these developments, in HRM the IoT does not seem to be a topic of larger interest, and so far, there are very few publications on the topic (Habraken & Bondarouk, 2017; Bondarouk, Ruël, & Parry, 2017). The initial research first refers to new possibilities that the IoT offers for HRM. In particular, technical disciplines developed a few application scenarios of the IoT in HRM. These scenarios first refer to employing smart things for advanced automation of HRM, such as automating HR training by smart things that novice users autonomously introduce into their usage (e.g. Charmonman, Mongkhonvanit, Dieu, & Linden, 2015; Watson & Ogle, 2013). These scenarios secondly refer to employing smart things for advanced HRM information, such as sensing HR information including staffing requirements, working times, qualification deficits or break needs (e.g. Bersin, Mariani, & Monahan, 2016; Mathur, Broeck, Vanderhulst, Mashhadi, & Kawsar, 2015; Waber, 2013). Furthermore, the initial research refers to the changes caused by the IoT in HRM, such as changes in job design (Habraken & Bondarouk, 2017) or workforce systems (McDonald, Fisher, & Connelly, 2017).