Guest editorial: Mass collaboration and knowledge management: reflections to achieve best practices

Abstract

Mass collaboration and knowledge management: reflections to achieve best practicesInfection with COVID-19 has become a severe public health concern all over the world, caused by novel coronavirus, which emerged from Wuhan, China.In March 2020, the World Health Organization (WHO) declared that the novel coronavirus can be considered a pandemic (WHO, 2020).It is consequently of paramount importance to inhibiting any additional dissemination of the virus in the public and health-care environments (Alkhwaldi and Absulmuhsin, 2021;Nguyen, 2021).Many countries worldwide have enforced different measures, guidelines and strategies such as social distancing, staying home and avoiding social crowds.However, other countries have implemented stricter measures to contain the pandemic outbreak, such as lockdowns and quarantine.As a result, the WHO and government organizations highly recommended working from home by using available ICT collaboration tools to protect people's health, whereas economic, educational and various activities were being carried out normally (WHO, 2020).IT collaborative tools offer a channel for individuals and organizations to benefit from uninterrupted services, even in crisis times.Mass collaboration (MC) assists to change the way of inventing, producing, marketing as well as distributing goods, services and information on a global basis, and this change presents far-reaching opportunities for all organizations and institutions and for every individual who gets connected (Borjigen, 2015;Scuotto et al., 2017).This novel pattern of collaborative working has revolutionized the methods of creating and sharing knowledge.Also, it subtly influences organizational knowledge management (KM) as: it arouses self-protection awareness of key staff; and it requires the organizations to extend their knowledge chains (Abdulmuhsin et al., 2021;Borjigen, 2015).

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 19 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.