Mixed Methods Analysis of Enterprise Social Networks

Sebastian Behrendt, Alexander Richter, Matthias Trier

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    Resumé

    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 first conducted a systematic literature review to identify available data dimensions and integrated them into a conceptual framework. We then adopted this framework as part of a mixed methods research approach to comprehensively analyze an empirical ESN case. With our results serving as a proof of concept we show the insights that can be derived from different data dimensions and how combining these can improve the validity of the analysis. The application of the framework also allows us to derive a detailed guideline for combining different data sources in ESN analysis to support researchers and decision makers
    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 first conducted a systematic literature review to identify available data dimensions and integrated them into a conceptual framework. We then adopted this framework as part of a mixed methods research approach to comprehensively analyze an empirical ESN case. With our results serving as a proof of concept we show the insights that can be derived from different data dimensions and how combining these can improve the validity of the analysis. The application of the framework also allows us to derive a detailed guideline for combining different data sources in ESN analysis to support researchers and decision makers
    SprogEngelsk
    TidsskriftComputer Networks
    Vol/bind75
    Udgave nummerPart B
    Sider560–577
    ISSN1389-1286
    DOI
    StatusUdgivet - 2014

    Emneord

    • Mixed methods
    • Social software
    • Enterprise social networks
    • Evaluation
    • Social network analysis
    • Case study

    Citer dette

    Behrendt, Sebastian ; Richter, Alexander ; Trier, Matthias. / Mixed Methods Analysis of Enterprise Social Networks. I: Computer Networks. 2014 ; Bind 75, Nr. Part B. s. 560–577
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    Behrendt, S, Richter, A & Trier, M 2014, 'Mixed Methods Analysis of Enterprise Social Networks' Computer Networks, bind 75, nr. Part B, s. 560–577. DOI: 10.1016/j.comnet.2014.08.025

    Mixed Methods Analysis of Enterprise Social Networks. / Behrendt, Sebastian; Richter, Alexander; Trier, Matthias.

    I: Computer Networks, Bind 75, Nr. Part B, 2014, s. 560–577.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    TY - JOUR

    T1 - Mixed Methods Analysis of Enterprise Social Networks

    AU - Behrendt,Sebastian

    AU - Richter,Alexander

    AU - Trier,Matthias

    PY - 2014

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    N2 - 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 first conducted a systematic literature review to identify available data dimensions and integrated them into a conceptual framework. We then adopted this framework as part of a mixed methods research approach to comprehensively analyze an empirical ESN case. With our results serving as a proof of concept we show the insights that can be derived from different data dimensions and how combining these can improve the validity of the analysis. The application of the framework also allows us to derive a detailed guideline for combining different data sources in ESN analysis to support researchers and decision makers

    AB - 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 first conducted a systematic literature review to identify available data dimensions and integrated them into a conceptual framework. We then adopted this framework as part of a mixed methods research approach to comprehensively analyze an empirical ESN case. With our results serving as a proof of concept we show the insights that can be derived from different data dimensions and how combining these can improve the validity of the analysis. The application of the framework also allows us to derive a detailed guideline for combining different data sources in ESN analysis to support researchers and decision makers

    KW - Mixed methods

    KW - Social software

    KW - Enterprise social networks

    KW - Evaluation

    KW - Social network analysis

    KW - Case study

    U2 - 10.1016/j.comnet.2014.08.025

    DO - 10.1016/j.comnet.2014.08.025

    M3 - Journal article

    VL - 75

    SP - 560

    EP - 577

    JO - Computer Networks

    T2 - Computer Networks

    JF - Computer Networks

    SN - 1389-1286

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    ER -

    Behrendt S, Richter A, Trier M. Mixed Methods Analysis of Enterprise Social Networks. Computer Networks. 2014;75(Part B):560–577. Tilgængelig fra, DOI: 10.1016/j.comnet.2014.08.025