Abstract
Purpose - The paper provide a methodology by which organisational knowledge can be extracted and visualised dynamically over time, providing a glimpse into the knowledge evolution processes that occur within organisations.Design/methodology/approach - Recursive analysis of email interactions is offered as a case to account for the knowledge structure evolution related to the different programs of INGO. Several methods are used: analysis of the network expansion to see if the process is random or uniform is performed, visualisation of the network configuration change throughout studied time period; and the statistical examination of network formation.Findings - The results of presented study indicate that content structure of electronic knowledge networks exhibits hierarchical and centralised tendencies. The social network analysis results suggest that INGO exhibits non-hierarchical and decentralized structure of the individuals contributing to the discussion lists. Research limitations/implications - By providing the means to carry out network evolution analysis of content structure dynamics and social interactions, presented work provides a means for probabilistically modelling patterns of organisational knowledge evolution. Practical implications - The approach allows the exploration of the dynamics of tacit to explicit knowledge, from individual to the group and from informal groups to the whole organisation.Originality/value - By displaying the large collection of the key phrases that reflected the evolution of the organisational knowledge structure over the time, organisational emails are placed in meaningful context explaining the language of the organisation and context of knowledge structure evolution.
Purpose - The paper provide a methodology by which organisational knowledge can be extracted and visualised dynamically over time, providing a glimpse into the knowledge evolution processes that occur within organisations.Design/methodology/approach - Recursive analysis of email interactions is offered as a case to account for the knowledge structure evolution related to the different programs of INGO. Several methods are used: analysis of the network expansion to see if the process is random or uniform is performed, visualisation of the network configuration change throughout studied time period; and the statistical examination of network formation.Findings - The results of presented study indicate that content structure of electronic knowledge networks exhibits hierarchical and centralised tendencies. The social network analysis results suggest that INGO exhibits non-hierarchical and decentralized structure of the individuals contributing to the discussion lists. Research limitations/implications - By providing the means to carry out network evolution analysis of content structure dynamics and social interactions, presented work provides a means for probabilistically modelling patterns of organisational knowledge evolution. Practical implications - The approach allows the exploration of the dynamics of tacit to explicit knowledge, from individual to the group and from informal groups to the whole organisation.Originality/value - By displaying the large collection of the key phrases that reflected the evolution of the organisational knowledge structure over the time, organisational emails are placed in meaningful context explaining the language of the organisation and context of knowledge structure evolution.