Adressing Replication and Model Uncertainty: A Bayesian Averaging Approach Applied to Innovation Survey Data

Bernd Ebersberger, Fabrice Galia, Keld Laursen, Ammon Salter

    Publikation: KonferencebidragPaperForskningpeer review

    Resumé

    Many fields of strategic management are subject to an important degree of model uncertainty. This is because the true model, and therefore the selection of appropriate explanatory variables, is essentially unknown. Drawing on the literature on the determinants of innovation, and by analyzing innovation survey data for France, Germany and the UK, we conduct a ‘large-scale’ replication using the Bayesian averaging approach of classical estimators. Our method tests a wide range of determinants of innovation suggested in the prior literature, and establishes a robust set of findings on the variables which shape the introduction of new to the firm and new to the world innovations. We provide some implications for innovation research, and explore the potential application of our approach to other domains of research in strategic management.
    OriginalsprogEngelsk
    Publikationsdato2016
    Antal sider36
    StatusUdgivet - 2016
    BegivenhedThe DRUID 20th Anniversary Conference 2016: Innovation and the Dynamics of Change - Copenhagen Business School, København, Danmark
    Varighed: 13 jun. 201615 jun. 2016
    Konferencens nummer: 38
    http://druid8.sit.aau.dk/druid/registrant/index/login/cid/20

    Konference

    KonferenceThe DRUID 20th Anniversary Conference 2016
    Nummer38
    LokationCopenhagen Business School
    LandDanmark
    ByKøbenhavn
    Periode13/06/201615/06/2016
    AndetThe DRUID Society Conference 2016
    SponsorCopenhagen Business School
    Internetadresse

    Emneord

    • Model uncertainty
    • Replication
    • Innovation
    • Strategic management

    Citer dette

    Ebersberger, B., Galia, F., Laursen, K., & Salter, A. (2016). Adressing Replication and Model Uncertainty: A Bayesian Averaging Approach Applied to Innovation Survey Data. Afhandling præsenteret på The DRUID 20th Anniversary Conference 2016, København, Danmark.
    Ebersberger, Bernd ; Galia, Fabrice ; Laursen, Keld ; Salter, Ammon. / Adressing Replication and Model Uncertainty : A Bayesian Averaging Approach Applied to Innovation Survey Data. Afhandling præsenteret på The DRUID 20th Anniversary Conference 2016, København, Danmark.36 s.
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    title = "Adressing Replication and Model Uncertainty: A Bayesian Averaging Approach Applied to Innovation Survey Data",
    abstract = "Many fields of strategic management are subject to an important degree of model uncertainty. This is because the true model, and therefore the selection of appropriate explanatory variables, is essentially unknown. Drawing on the literature on the determinants of innovation, and by analyzing innovation survey data for France, Germany and the UK, we conduct a ‘large-scale’ replication using the Bayesian averaging approach of classical estimators. Our method tests a wide range of determinants of innovation suggested in the prior literature, and establishes a robust set of findings on the variables which shape the introduction of new to the firm and new to the world innovations. We provide some implications for innovation research, and explore the potential application of our approach to other domains of research in strategic management.",
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    Ebersberger, B, Galia, F, Laursen, K & Salter, A 2016, 'Adressing Replication and Model Uncertainty: A Bayesian Averaging Approach Applied to Innovation Survey Data' Paper fremlagt ved The DRUID 20th Anniversary Conference 2016, København, Danmark, 13/06/2016 - 15/06/2016, .

    Adressing Replication and Model Uncertainty : A Bayesian Averaging Approach Applied to Innovation Survey Data. / Ebersberger, Bernd; Galia, Fabrice; Laursen, Keld; Salter, Ammon.

    2016. Afhandling præsenteret på The DRUID 20th Anniversary Conference 2016, København, Danmark.

    Publikation: KonferencebidragPaperForskningpeer review

    TY - CONF

    T1 - Adressing Replication and Model Uncertainty

    T2 - A Bayesian Averaging Approach Applied to Innovation Survey Data

    AU - Ebersberger, Bernd

    AU - Galia, Fabrice

    AU - Laursen, Keld

    AU - Salter, Ammon

    PY - 2016

    Y1 - 2016

    N2 - Many fields of strategic management are subject to an important degree of model uncertainty. This is because the true model, and therefore the selection of appropriate explanatory variables, is essentially unknown. Drawing on the literature on the determinants of innovation, and by analyzing innovation survey data for France, Germany and the UK, we conduct a ‘large-scale’ replication using the Bayesian averaging approach of classical estimators. Our method tests a wide range of determinants of innovation suggested in the prior literature, and establishes a robust set of findings on the variables which shape the introduction of new to the firm and new to the world innovations. We provide some implications for innovation research, and explore the potential application of our approach to other domains of research in strategic management.

    AB - Many fields of strategic management are subject to an important degree of model uncertainty. This is because the true model, and therefore the selection of appropriate explanatory variables, is essentially unknown. Drawing on the literature on the determinants of innovation, and by analyzing innovation survey data for France, Germany and the UK, we conduct a ‘large-scale’ replication using the Bayesian averaging approach of classical estimators. Our method tests a wide range of determinants of innovation suggested in the prior literature, and establishes a robust set of findings on the variables which shape the introduction of new to the firm and new to the world innovations. We provide some implications for innovation research, and explore the potential application of our approach to other domains of research in strategic management.

    KW - Model uncertainty

    KW - Replication

    KW - Innovation

    KW - Strategic management

    KW - Model uncertainty

    KW - Replication

    KW - Innovation

    KW - Strategic management

    M3 - Paper

    ER -

    Ebersberger B, Galia F, Laursen K, Salter A. Adressing Replication and Model Uncertainty: A Bayesian Averaging Approach Applied to Innovation Survey Data. 2016. Afhandling præsenteret på The DRUID 20th Anniversary Conference 2016, København, Danmark.