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    Eight key issues for the decision support systems discipline

    Access Status
    Fulltext not available
    Authors
    Arnott, David
    Pervan, Graham
    Date
    2008
    Type
    Journal Article
    
    Metadata
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    Citation
    Arnott, David and Pervan, Graham. 2008. Eight key issues for the decision support systems discipline. Decision Support Systems 44 (3): pp. 657-672.
    Source Title
    Decision Support Systems
    DOI
    10.1016/j.dss.2007.09.003
    ISSN
    01679236
    Faculty
    Curtin Business School
    School of Information Systems
    Remarks

    The link to the journal’s home page is: http://www.elsevier.com/wps/find/journaldescription.cws_home/505540/description#description

    Copyright © 2008 Elsevier Ltd. All rights reserved

    URI
    http://hdl.handle.net/20.500.11937/26910
    Collection
    • Curtin Research Publications
    Abstract

    This paper integrates a number of strands of a long-term project that is critically analysing the academic field of decision support systems (DSS). The project is based on the content analysis of 1,093 DSS articles published in 14 major journals from 1990 to 2004. An examination of the findings of each part of the project yields eight key issues that the DSS field should address for it to continue toplay an important part in information systems scholarship. These eight issues are: the relevance of DSS research, DSS research methods and paradigms, the judgement and decision-making theoretical foundations of DSS research, the role of the IT artifact in DSS research, the funding of DSS research,inertia and conservatism of DSS research agendas, DSS exposure in general "A" journals, and discipline coherence. The discussion of each issue is based on the data derived from the article content analysis. A number of suggestions are made for the improvement of DSS research. These relate tocase study research, design science, professional relevance, industry funding, theoretical foundations,data warehousing, and business intelligence. The suggestions should help DSS researchers constructhigh quality research agendas that are relevant and rigorous.

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