The research project Knowledge Management 2.0 develops a typology of ESN knowledge actor roles as well as an approach to discover these roles based on the analysis of ESN data. The derived insights support the identification of knowledge-in-practice and, thus, enhance organisational knowledge transparency.
Traditionally, knowledge management initiatives have focused on the capture and storage of what an employee knows. Yet, many of these attempts to manage knowledge have failed due to not paying sufficient attention to the social context of knowledge work. As such, knowledge work is often conducted in informal organisational structures that exist next to the organisational chart and are not obvious to a company’s management. As a result, there is only a limited understanding of the performed knowledge practices and the involved actors.
Enterprise Social Networks (ESN) are internal social networking sites that are increasingly used by companies to reinforce knowledge sharing and collaboration among employees. Performing knowledge (inter)actions on an ESN, e.g. gathering opinions or discussing a work-related problem, employees leave digital traces that are stored as log files in the platform’s back end. The relationships emerging on the ESN reflect a subset of an organisation’s knowledge flows. While ESN use practices have been studied in prior works, little is known about the extent to which users engage in different use practices and how combinations of use practices contribute to behavioural patterns and different user roles. Moreover, prior work has mostly relied on qualitative analysis of message content. To enable the analysis of larger datasets, there is a need to characterise ESN interactions quantitatively.
It is the goal of this research project to discover ESN knowledge actor roles in order to identify the knowledge embedded in the organisational practice. The research project addresses the following main research question: Which knowledge actor roles can be distinguished in ESN and how can they be recognised based on the analysis of the accumulated data?
The main steps of the research project include the development of a literature-based ESN knowledge actor role framework. This framework suggests roles potentially identifiable in ESN, their behavioural dimensions and metrics to measure these dimensions. The actual data analysis is performed using a real ESN dataset provided by a professional services firm. Informed by the literature review and by the features of the dataset, a set of metrics is developed and calculated for each ESN user. Following an explorative research design, knowledge actor roles are discovered based on a cluster analysis. Having assigned the users to different clusters, rules describing how the different behavioural dimensions contribute to a cluster, i.e. a knowledge actor role, are generated. The results of the analysis are compared with the literature-based ESN knowledge actor role framework and discussed with representatives of the case company.
The contributions of the research project include a quantitative approach to discover behavioural dimensions and knowledge actor roles on ESN. The findings of the project lead to an improved understanding of knowledge work which, in turn, can enable more evidence based decision-making at the intersection between knowledge management and human resources management.
Related Student Reports (excerpt)
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