Due to the Covid-19 pandemic, the world became the largest work-from-home experiment in history (Bernstein et al., 2020), making both a strong acceleration of the future of work and stripping back the organizational structures to their foundation (Green, 2020). Professionals worldwide have started exploring this enforced by the pandemic experimentation by investigating, for example, how HR Analytics can benefit smart-working practices, motivate the team or how managers can support remote employees. Despite this promised potential of HR Analytics to reveal or strengthen smart-working practices or their impacts during the pandemic, its application is still not well understood in the business or academic communities or beyond HR innovators circles. As such we propose to search and analyze the existing evidence base concerning smart-working emerged during the Covid-19 emergency to explore and document how HR Analytics is discussed or used by researchers and industry experts, and to identify gaps, priorities, and recommendations for implementing these ways of working as well as approaches to enhancing it with HR Analytics practices. Specifically, an iterative ‘scoping review’ method is planned to be employed to capture and synthesize relevant academic and grey literature. This research method is suited to emerging areas of innovation where formal research lags behind evidence from professional or technical sources. The review was prompted by findings of recent literature reviews on People Analytics (Tursunbayeva et al., 2018; Marler & Boudreau, 2017). It also addresses calls from within the industry for “independent scientific research” on PA (Levenson & Pillans, 2017) and on the effects of Covid-19 on HRM practices. The results will represent a snapshot of the field to date indicating the directions for future developments and scholarly and market demands. This will guarantee future research as well as provide a base for practitioners to design more tailored and evidence-informed ways of smart-working, as well as new applications of HR Analytics.
Remote work at the time of Covid-19 pandemic and beyond: A scoping review
Di Lauro S.
;Antonelli G.
2021-01-01
Abstract
Due to the Covid-19 pandemic, the world became the largest work-from-home experiment in history (Bernstein et al., 2020), making both a strong acceleration of the future of work and stripping back the organizational structures to their foundation (Green, 2020). Professionals worldwide have started exploring this enforced by the pandemic experimentation by investigating, for example, how HR Analytics can benefit smart-working practices, motivate the team or how managers can support remote employees. Despite this promised potential of HR Analytics to reveal or strengthen smart-working practices or their impacts during the pandemic, its application is still not well understood in the business or academic communities or beyond HR innovators circles. As such we propose to search and analyze the existing evidence base concerning smart-working emerged during the Covid-19 emergency to explore and document how HR Analytics is discussed or used by researchers and industry experts, and to identify gaps, priorities, and recommendations for implementing these ways of working as well as approaches to enhancing it with HR Analytics practices. Specifically, an iterative ‘scoping review’ method is planned to be employed to capture and synthesize relevant academic and grey literature. This research method is suited to emerging areas of innovation where formal research lags behind evidence from professional or technical sources. The review was prompted by findings of recent literature reviews on People Analytics (Tursunbayeva et al., 2018; Marler & Boudreau, 2017). It also addresses calls from within the industry for “independent scientific research” on PA (Levenson & Pillans, 2017) and on the effects of Covid-19 on HRM practices. The results will represent a snapshot of the field to date indicating the directions for future developments and scholarly and market demands. This will guarantee future research as well as provide a base for practitioners to design more tailored and evidence-informed ways of smart-working, as well as new applications of HR Analytics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
