No description available.

The increasing complexity of decision situations has required organizations to integrate more types of expertise and consider more criteria for effective group decision making. Researchers have begun to examine how computer based support in the form of a Group Decision Support System (GDSS) can enhance the process and outcomes of decision making groups. This dissertation investigated the impact of GDSS for strategic planning impact analysis. The GDSS was based on the Stakeholder Identification and Assumption Surfacing Model. A controlled laboratory experiment was used to compare the process and outcomes of 4-person groups which had GDSS support, comparable manual support, and no support. The experimental task was a policy statement requiring undergraduates to have a personal computer for admittance to a business college. Groups were asked to determine a list of the most critical stakeholders who would be impacted by the policy, and their assumptions regarding the policy statement. Measures were taken on decision outcomes (decision quality, decision time, and satisfaction with the outcomes) and decision process variables (quantity of unique alternatives, distribution of individual participation, and satisfaction with the process). Additionally, observational data was recorded through the use of videotape recordings of the sessions. The major findings of the study are: (1) Decision quality is enhanced when groups use a structured methodology; (2) Decision time was shortest in the unstructured groups, with GDSS groups finishing somewhat faster than manual structured groups; (3) Satisfaction with the outcomes was not different between structured and unstructured groups, however it was higher in the GDSS groups compared to the structured manual groups; (4) Quantity of unique alternatives was much higher in the groups using a structured methodology; (5) Distribution of individual participation was more equal in groups using a structured methodology; and (6) Satisfaction with the process was not different between structured and unstructured groups, however the GDSS groups were more satisfied than the structured manual groups.

Mathematical aggregation frameworks are general and precise settings in which to study ways of forming a consensus or group point of view from a set of potentially diverse points of view. Yet the standard frameworks have significant limitations. A number of results show that certain sets of desirable aggregation properties cannot be simultaneously satisfied. Drawing on work in the theory of imprecise probabilities, I propose philosophically-motivated generalizations of the standard aggregation frameworks (for probability, preference, full belief) that I prove can satisfy the desired properties. I then look at some applications and consequences of these proposals in decision theory, epistemology, and the social sciences.

Thesis (Ph. D.)--Ohio State University, 1974. / Includes vita. Includes bibliographical references (leaves 363-372). Available online via OhioLINK's ETD Center

Thesis (Ph. D.)--Florida State University, 2004. / Advisor: Dr. Richard C. Feiock, Florida State University, College of Social Sciences, Dept. of Political Science. Title and description from dissertation home page (viewed June 16, 2004). Includes bibliographical references.

No description available.

Thesis (MBus)--University of South Australia, 1998

Thesis (PhD) -- University of South Australia, 1998

Thesis (MBus)--University of South Australia, 1998

Thesis (B.A. Hons. 1973) from the Department of Psychology, University of Adelaide.