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An AHP analysis of quality in AI and DSS journals

  • Forgionne, Guisseppi A.
  • Kohli, Rajiv
  • Jennings, Darniet
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    Over the years, a number of researchers have assessed the quality of information systems (IS) journals. Most of these studies have assessed general IS journals, but few have specifically examined journals that focus on decision-making support systems. Furthermore, even though there are many factors that measure journal quality, very few gauges have been used in the previous evaluations. Recently, the authors reported a study that utilized the analytical hierarchy process to evaluate 20 top decision-making support system journals. This paper extends the earlier work by providing separate ratings for artificial intelligence and decision support system journals. Initially, the article reviews the criteria and AHP methodology to evaluate decision-making support system journal quality. Next, there is an updated discussion of the data collection process and the resulting multiple criteria evaluation. The paper concludes with a summary of the evaluation and the implications for information systems theory and practice.

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    Article provided by Elsevier in its journal Omega.

    Volume (Year): 30 (2002)
    Issue (Month): 3 (June)
    Pages: 171-183

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    Handle: RePEc:eee:jomega:v:30:y:2002:i:3:p:171-183
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