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T his does not mean we should abandon models or the use of decision support systems (DSS) to support decisions.Rather, DSS should blend analytical tools with intuitive heuristics to improve managers' insights about factors too complex to build into models. In particular, DSS must facilitate the modification of results of analytical tools when they contradict intuition [2]. This is consistent with the basic goals of model use as noted by Jones [5], "developing insight into model behavior is ultimately a process of discovery, of finding trends, surprising behaviors, and comparing the behavior of the model to what is expected or observed in the real system." Alternatively, analytical tools can test and verify intuition before applying it to the decision-making process. Decision-makingManagers have four types of decision-making styles: left-brain, right-brain, accommodating, and integrated. The left-brain style stresses analytical and quantitative techniques and employs rational and logical methods of reasoning. Decision-makers decompose problems, approaching each subproblem sequentially using logic and data. Quantitative analyses of database-stored information lend themselves to this style of decision-making [1].The literature documents the benefits of this approach, and designers know how to build necessary support into DSS. However, analytic methods do not always provide the Today's worldwide marketplace provides not only more customers, suppliers and competitors, but also increased complexity for the decision-making process. Simultaneously, the speed of communications makes the environment less stable and predictable and reduces the available time for examining data and relationships [10]. As a result, necessary data often is unavailable to the decision-maker for analysis or the requisite analyses are infeasible. Not surprisingly, managers are increasingly dissatisfied with established procedures for making decisions [1].

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Unfortunately, although increasing in quantity, research concerning the use of analytically-based information (ABI) in public sector organizations has not greatly enriched our knowledge of the use of ABI. In this article, we consider some prominent methodological problems involved in such studies that we believe have greatly inhibited progress in developing powerful knowledge concerning the use of ABI. In addition, some suggestions for avoiding these methodological problems or reducing their effects are offered.

The declining proportion of women in the IT profession contributes to the shortage of IT professionals and potentially has a detrimental effect on the success of design projects. However, we do not fully understand why that decrease is happening. Some studies have utilized a construct called stereotype threat to explain why women are rejecting IT as a profession. Others have claimed that the results of stereotype threat apply only in computer science programs housed in engineering schools. This study tests whether stereotype threat exists in an MIS program in a college of business and, if so, how it affects women's confidence in their ability and motivation to continue their IT education. The results show no support for the stereotype threat hypothesis. Further analysis, however, shows that positive, supportive messages have more effect on these women than do the negative messages. Thus, while stereotype threat has been a successful model for explaining the behavior of women in the sciences, mathematics, and computer science, it does not appear to explain the decreases in the number of women in MIS programs in business schools. A discussion of the aspects of MIS programs that may attract women and possible ways to increase women are provided.