Managing a software development project presents many difficulties. Most software development projects are considered less than successful, and many are simply canceled. Ineffective project management has been cited as a major factor contributing to these failures. Project management tools can greatly assist managers in tracking and controlling their projects. However, project management tools are very structured and analytical in nature, which is not necessarily supported by decision-making styles of the managers. This research examined the influence that decision style has on a project manager's use of a project management tool.

Stock market investors are making investment decisions in an information-rich environment. In their attempt to afford investors all the decision-relevant information, standard setters are continually adding to the already weighty load seemingly oblivious to the cognitive limitations of humans. Information overload has long been recognized as a problem to decision-makers. The information overload literature is robust with studies supporting the inverted U hypothesis: Decision accuracy will increase with additional information to the point of maximum processing capability, then decline. The decision style literature has supported the theory that individuals can be classified according to the quantity of information that they are able to process effectively. This study combined the two theories to develop hypotheses about how investors with differing decision styles might behave differently in an information-rich environment. The hypotheses were tested in an internet-based stock market investment experiment. In general, the study did not find significant differences in the decisions of investors with different decision styles. Though the results of the experiment failed to support most of the hypotheses, the study revealed some interesting facts about the investors who participated in this study. There was an unusually high concentration of the analytic decision style in this group. This style, according to the theory, is the one best able to manage high information processing demands. A further analysis of the respondent style dominance reveals that all of the styles had significant analytic influence. This could explain the lack of variation in the decision accuracy of the respondents. It is also possible that the respondents in this study did not reach a point of information overload. Based on prior literature, the study incorporated ten information items. However, the particular items selected may not have created a sense of information overload for the respondents. Future research should increase the information available to respondents and observe whether differences in decisions can be explained by differences in decision styles in an information overload situation. This study provides a baseline for future studies examining how investors make decisions when so much information is available.

Part one provides a literature review on the development of attitude theory in marketing research and addresses concerns regarding the effects of common method variance (CMV) in published studies based on the reasoned-action paradigm of consumer behavior and decision making. The results of a marker-variable analysis, logit analysis, and reanalysis of path estimates support the validity of self-report survey research designs. Part two employs a survey design to develop and validate a scale to measure a consumer s tendency to use a complex decision style (CDS) in conceptualizing and negotiating high-stakes decision situations. Drawing from literature on cognitive style theory and complexity science, a complex approach to decision making is characterized as being complexity-focused; decision makers tend to rely more heavily on strategies such as collaborating with others and integrating a variety of information. The CDS scale is also applied within a conceptual model of choice of elective healthcare treatment, specifically, women s decisions regarding the use of hormone therapy, commonly referred to as HRT.