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Gender and DSS design: the research implications
No full textAlthough decisions and decision-making lie at the heart of decision support system (DSS) research, certain aspects of human decision-making have been neglected by DSS builders. One of these is the role of gender in decision-making. Decision support systems are constructed largely upon the assumption of an androgynous user, but, clearly, if males and females take decisions in different ways or prefer different styles of information, then their use of DSS may differ. This may have important organisational implications, especially as women ascend the corporate ladder. The purpose of this paper is to evaluate the literature on gender differences and to highlight explicitly the role of this literature in DSS design. It is hoped that, by raising dormant questions, the debate may be stimulated. Finally, a research agenda is suggested
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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