Group Decision Support System (GDSS) pre-session planning is a complex task requiring considerable expertise. GDSS pre-session planning involves the selection of group participants and GDSS tools for a subsequent computer-supported group meeting. An effective plan is required to achieve a successful meeting (success measured by the time and cost necessary to reach an outcome satisfactory to group participants). This research investigates the nature of GDSS pre-session planning and the knowledge that is applied when expert human facilitators plan for collaborative work. A model of and a prototype expert system for GDSS tool selection were developed from the documented knowledge of pres-session planning. The model and system were then revised as a result of extensive consultations with domain experts. The expert system was verified by comparing human experts' recommendations with the system's recommendations (there was no significant difference between the two sets of recommendations). The usefulness of the system was tested by comparing facilitators' and non-facilitators' (with and without the use of the expert system) recommendations with those of human experts in a 2 by 2 factorial design. Results show that facilitators and non-facilitators who use the system are better able to select the tools experts have chosen than they would have otherwise. When they are not using the system, facilitators and non-facilitators perform equally well in selecting the tools experts have judged most appropriate (both groups differ significantly from the experts' recommendations). This research contributes to knowledge of pre-session planning for GDSS sessions with a particular emphasis on the tool selection process. However, further research on the development of a complete session agenda is needed.

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.

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Thesis (Ph. D.)--Ohio State University, 1983. / Includes vita. Includes bibliographical references (leaves 238-251). Available online via OhioLINK's ETD Center.

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

This thesis investigates the emergence and influence of expertise in group decision making while performing a judgmental task. Previous studies focused on intellective tasks or compared the group performance with the performance of the best individual in the group. In this study, performance feedbacks are provided to groups to help group members compare the individual performances and identify the expert. Laboratory experiments were conducted in which the task was to select a proverb that Canadians would like the most from the list of four proverbs from countries other than Canada. The four proverbs for each question were guaranteed to have equal selection probability based on the pretest survey. 18 four-person cooperative groups were asked to perform the task for eight iterations each. One member in each group was selected randomly to be the expert. Groups received performance feedbacks that reinforced the expert at the end of each iteration. The amount of information conveyed to each group regarding the expertise level of each group member was measured with a novel application of information analysis that captures the expert's gradual emergence. Experiment results supported the hypotheses of this study that (1) group members recognize the expert when working on a judgmental task with performance feedback and (2) while performing a judgmental task, the expert has more influence on the group decision making compared to others.

This thesis investigates the emergence and influence of expertise in group decision making while performing a judgmental task. Previous studies focused on intellective tasks or compared the group performance with the performance of the best individual in the group. In this study, performance feedbacks are provided to groups to help group members compare the individual performances and identify the expert. Laboratory experiments were conducted in which the task was to select a proverb that Canadians would like the most from the list of four proverbs from countries other than Canada. The four proverbs for each question were guaranteed to have equal selection probability based on the pretest survey. 18 four-person cooperative groups were asked to perform the task for eight iterations each. One member in each group was selected randomly to be the expert. Groups received performance feedbacks that reinforced the expert at the end of each iteration. The amount of information conveyed to each group regarding the expertise level of each group member was measured with a novel application of information analysis that captures the expert's gradual emergence. Experiment results supported the hypotheses of this study that (1) group members recognize the expert when working on a judgmental task with performance feedback and (2) while performing a judgmental task, the expert has more influence on the group decision making compared to others.

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.

Thesis--M. Phil., University of Hong Kong, 1978.

published_or_final_version / abstract / toc / Business / Master / Master of Philosophy