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Business Intelligence 2.0

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Business Intelligence for New-Generation Managers

Abstract

The increasing use of enterprise social networks (ESN) generates vast amounts of data, giving researchers and managerial decision makers unprecedented opportunities for analysis. However, more transparency about the available data dimensions and how these can be combined is needed to yield accurate insights into the multi-facetted phenomenon of ESN use. In order to address this issue, we present a framework of available data dimensions and describe possible methods and insights as well as opportunities and limitations of each data dimension. We then adopt this framework exemplary to comprehensively analyze an empirical ESN case.

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Notes

  1. 1.

    http://www.r-project.org

  2. 2.

    http://www.commetrix.de

  3. 3.

    13 Interviews with officers/officer candidates from different ranked were conducted.

  4. 4.

    Analysis of 445 connections based on 1,155 messages by 204 users

    • Nodes: users that generated a content, e.g., appointment, blog, article, comment

    • Edges: comments on initial contents

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Author information

Authors and Affiliations

  1. Bundeswehr University, Neubiberg, Germany

    Sebastian Behrendt

  2. University of Zurich, Zurich, Switzerland

    Alexander Richter

Authors
  1. Sebastian Behrendt
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  2. Alexander Richter
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Corresponding author

Correspondence to Sebastian Behrendt .

Editor information

Editors and Affiliations

  1. School of Management, University of St. Gallen, St. Gallen, Switzerland

    Jörg H. Mayer

  2. Chair of Accounting and Auditing, Darmstadt University of Technology, Darmstadt, Germany

    Reiner Quick

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Behrendt, S., Richter, A. (2015). Business Intelligence 2.0. In: Mayer, J., Quick, R. (eds) Business Intelligence for New-Generation Managers. Springer, Cham. https://doi.org/10.1007/978-3-319-15696-5_8

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