Teaming man and machine? A bibliometric analysis deconstructing research on how cognitive technologies affects man-machine collaboration
Master thesis
Submitted version
Permanent lenke
https://hdl.handle.net/11250/2824538Utgivelsesdato
2020Metadata
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Sammendrag
The field of research addressing artificial intelligence (AI), and related topics, is rapidly
increasing. However, despite this emerging interest, the currently body of published research
remains complex and unstructured. In particular, it remains to be understood how these
technologies is implemented and cause changes in man-machine collaboration. In order to
inform this issue, we conducted a bibliometric analysis of extant literature on AI and manmachine
collaboration to take stock of extant published research in order to provide a
foundation upon which both future theory and practice can be built. We based our analysis of
an exhaustive structured literature search of published academic research in Web of Science
(WoS) until 2019. Using the keywords digi* AND transform* OR artificial intelligence, 8 728
articles were identified. The bibliometric analysis enabled us first to identify 202 relevant
articles published within the fields of business and management, and subsequently to further
narrowing our scope to 25 core contributions using bibliometric coupling. A content analysis of
these 25 articles revealed that whereas there is a lot of attention to the technological
complexities related to the emerging cognitive technologies, there is to date limited empirical
descriptions of the consequences for individuals, organizations or value creation of adopting
these technologies. Our study identifies four important dimensions of man-machine
collaboration; Knowledge worker, Organization, Market, and Society. Moreover, our findings
reveal extant research is inconclusive with respect to the forces affecting these dimensions
as different authors record both proactive forces and constraining forces associated with
each of the four dimensions. Our contribution, as well as, the identification of a core canon of
relevant research articles provides a foundation upon which future research and practice can
be built by identifying core dimension and the forces acting upon them.