Abstract
We present analytic framework for evidence-based management, design, and engineering of collaborative intranet environments. The analytics target elucidation of essential elements of human-system interactions. Temporal segmentation of human behavior in digital environments permits identification of crucial navigational points as well as higher order abstractions. Explorations of these elements provide fertile grounds for assessment of usability and behavioral characteristics that directly translate to actionable knowledge indispensable for improvements of collaboration portals. We extrapolate the analytic findings from a case study of a large scale collaborative organizational intranet; in order to identify three crucial domains facilitating alignment between observed evidence and best management and engineering practices.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Davenport, T.H., Harris, J.G.: Competing on Analytics: The New Science of Winning. Harvard Business School Press, Boston (2007)
Géczy, P., Akaho, S., Izumi, N., Hasida, K.: Knowledge worker intranet behaviour and usability. Int. J. Business Intelligence and Data Mining 2, 447–470 (2007)
Huntington, P., Nicholas, D., Jamali, H.R.: Website usage metrics: A re-assessment of session data. International Journal of Information Processing and Management 44(1), 358–372 (2008)
Petre, M., Minocha, S., Roberts, D.: Usability beyond the website: an empirically-grounded e-commerce evaluation for the total customer experience. Behaviour and Information Technology 25, 189–203 (2006)
Park, Y.-H., Fader, P.S.: Modeling browsing behavior at multiple websites. Marketing Science 23, 280–303 (2004)
Moe, W.W.: Buying, searching, or browsing: Differentiating between online shoppers using in-store navigational clickstream. Journal of Consumer Psychology 13, 29–39 (2003)
Barabasi, A.-L.: The origin of bursts and heavy tails in human dynamics. Nature 435, 207–211 (2005)
Catledge, L., Pitkow, J.: Characterizing browsing strategies in the world wide web. Computer Networks and ISDN Systems 27, 1065–1073 (1995)
Thakor, M.V., Borsuk, W., Kalamas, M.: Hotlists and web browsing behavior–an empirical investigation. Journal of Business Research 57, 776–786 (2004)
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17, 734–749 (2005)
Symeonidis, P., Nanopoulos, A., Papadopoulos, A.N., Manolopoulos, Y.: Collaborative recommender systems: Combining effectiveness and efficiency. Expert Systems with Applications 34(4), 2995–3013 (2008)
Jin, R., Si, L., Zhai, C.: A study of mixture models for collaborative filtering. Information Retrieval 9, 357–382 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Géczy, P., Izumi, N., Akaho, S., Hasida, K. (2009). Analytics and Management of Collaborative Intranets. In: Bertino, E., Joshi, J.B.D. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2008. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03354-4_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-03354-4_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03353-7
Online ISBN: 978-3-642-03354-4
eBook Packages: Computer ScienceComputer Science (R0)