Causal maps are diagrammatical representations of the cause-effect relationships perceived to exist among the elements of a given phenomenon. Given this, these maps would seem to possess qualities that could help information systems analysts in determining information requirements in ill-structured, complex problem situations. Unfortunately, the effectiveness of causal maps is often undermined in real world situations because the maps grow so complex that participants become cognitively overloaded. This study addresses the issue of complexity in causal maps, and attempts to determine whether physical attributes such as signs, diagrammatic aids, and model symmetry can enable participants to more easily understand maps. A series of four laboratory experiments utilizing a total of 162 subjects is used to investigate these issues. These experiments result in four main findings. First, the major finding of the study is that understanding of a causal map can be significantly facilitated through the use of model symmetry. Second, subjects' perceptions of complexity increase when either the number of constructs or the number of causal interconnections between constructs in the map increases. Third, using signs to indicate relationship direction does not significantly influence understanding nor perceptions of complexity. Finally, the addition of diagrammatic aids to a causal map results in higher perceptions of complexity. / Source: Dissertation Abstracts International, Volume: 52-10, Section: A, page: 3655. / Major Professor: Robert W. Zmud. / Thesis (Ph.D.)--The Florida State University, 1991.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_77759 |
| Contributors | Hauser, Richard Doub, Jr., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 233 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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