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        Data, Methods and Theory in the Organizational Sciences

        Proposal review

        A New Synthesis

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        Contributor(s)
        Murphy, Kevin (editor)
        Language
        English
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        Abstract
        In both Management and I/O Psychology, contributions to theory remain an important, and in many cases, sole criterion for evaluating submissions to top journals. In many ways, the definition of theory and the primacy of theory in the organizational sciences is an outlier; in most sciences, articles rarely even mention theories, much less build themselves around advancing theory. We propose that the classic description of the scientific methods provides a better guide to understanding the relationships between data, methods and theory than our current model, which often starts and ends with proposing a theory, which may never again be referenced or tested. We describe a pyramid of types of evidence that is useful for assessing the reliability and worth of particular sorts of data and show how this approach to evidence informs the scientific method and assists in identifying and building useful theories.
        URI
        https://library.oapen.org/handle/20.500.12657/52884
        Keywords
        organizational research; SIOP; SIOP Organizational Frontiers; SIOP Organizational Frontiers Series; organizational frontiers; organizations; Society for Industrial and Organizational Psychology; I/O psychology
        DOI
        10.4324/9781003015000
        ISBN
        9780367857707, 9780367857646, 9781003015000
        Publisher
        Taylor & Francis
        Publisher website
        https://taylorandfrancis.com/
        Publication date and place
        2022
        Imprint
        Routledge
        Classification
        Organizational theory and behaviour
        Psychology
        Occupational and industrial psychology
        Chapters in this book
        • Chapter 13 Rebuilding Relationships between Data, Method, and Theories
        Rights
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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