Multi-factor model of the antecedents of unplanned conversations at work

Abstract

PurposeDuring everyday work, individuals often engage in unplanned conversations that help them develop relationships, share information and coordinate tasks. Unfortunately, the work-from-home mandates issued due to the pandemic have reduced the frequency of unplanned conversations among employees. So, as businesses reopen, organizations are considering post-pandemic workplace solutions that can facilitate unplanned conversations. To aid these efforts and move research and theory on unplanned conversations forward, this study proposes and tests a multi-factor model of the antecedents of unplanned conversations.Design/methodology/approachThis study adopted a multi-methodological approach and collected data using automated sensing technology, structured observations and cross-sectional survey methods. A total of 5,297 unplanned conversations among 61 employees were recorded using the custom mobile application and structured observations. Cross-sectional survey data about these employees' work contexts were also collected.FindingsThe study results showed that the model significantly predicted the frequency of unplanned conversations. Notably, technical expertise, perceived time pressure and team psychological safety significantly predicted the frequency of unplanned conversations. The study findings have both theoretical and practical significance.Originality/valuePrevious research studies have primarily focused on the influence of workplace designs on unplanned conversations. However, this study demonstrates that several other factors facilitate unplanned conversations. This research theorizes and empirically tests the relationship between unplanned conversations and several individual, team and organizational factors.