Start Date
10-12-2017 12:00 AM
Description
Communication and collaboration software for knowledge workers are introduced with high expectations, especially in knowledge-intense industries. While advantages of such tools are well documented in theory, many initiatives have yet to achieve the desired outcomes in practice. Research has dealt with roles in the digital workplace and found that one-size-fits-all solutions are not suitable. However, for a lack of real-world data the matter is still not sufficiently understood. To close this gap, we conduct a sequential mixed method study. We perform an exploratory analysis based on trace data within a service organization and reconstruct its social structure. Through a cluster analysis, eight distinct emergent user roles are identified. Additionally, we analyze covariates of cluster membership, such as organizational hierarchy, through statistical testing. Lastly, semi-structured interviews help to explain our findings qualitatively. We contribute to research and practice by deepening the understanding of heterogeneous user behavior in a digital workplace.
Recommended Citation
Frank, Leonhard; Gimpel, Henner; Schmidt, Marco; and Schoch, Manfred, "Emergent User Roles of a Digital Workplace: A Network Analysis Based on Trace Data" (2017). ICIS 2017 Proceedings. 10.
https://aisel.aisnet.org/icis2017/SocialMedia/Presentations/10
Emergent User Roles of a Digital Workplace: A Network Analysis Based on Trace Data
Communication and collaboration software for knowledge workers are introduced with high expectations, especially in knowledge-intense industries. While advantages of such tools are well documented in theory, many initiatives have yet to achieve the desired outcomes in practice. Research has dealt with roles in the digital workplace and found that one-size-fits-all solutions are not suitable. However, for a lack of real-world data the matter is still not sufficiently understood. To close this gap, we conduct a sequential mixed method study. We perform an exploratory analysis based on trace data within a service organization and reconstruct its social structure. Through a cluster analysis, eight distinct emergent user roles are identified. Additionally, we analyze covariates of cluster membership, such as organizational hierarchy, through statistical testing. Lastly, semi-structured interviews help to explain our findings qualitatively. We contribute to research and practice by deepening the understanding of heterogeneous user behavior in a digital workplace.