Complexity and uncertainty have long been problems for organizations of all types. Organizational members do not do a very good job of dealing with the complexity and uncertainty as research shows that when faced with complex situations humans often turn to the same sources of information repeatedly (a practice that will eventually betray them), and/or reduce the amount of scanning that they do (Weick 1995; Boyd and Fulk 1996). Organizations often turn to information systems to help them deal with the complexity, but they often take a techno-centric view of knowledge that does not incorporate the human qualities needed for unstructured decisions (Malhotra 1997; Courtney 2001; Malhotra 2001). Additionally, there are times when the information systems that we are using may hinder the processes of dealing with the complexity (Weick and Meader 1993). Weick's (1995) concept of sensemaking is believed to help us to deal with this complexity. In his work with Meader (1993) he wonders what the effects of a sensemaking support system would have, but he does not have the answer because they state that it has not been asked. This dissertation answers the call of Weick and Meader as well as other scholars that have called for sensemaking and human intuition to be included in our information systems. This is accomplished by viewing sensemaking from an inquiring systems perspective (Churchman 1971) to develop a kernel theory that will be used in the context of design science to develop design requirements and principles for a sensemaking system. These design principles are then used to build an instantiation of the system in the form of SenseMan, a system designed to help a local government agency deal with complexity in the context of software updates. Finally the design is evaluated for its effectiveness in dealing with the complexity of in this context using both quantitative and qualitative methods.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-4466 |
Date | 01 January 2008 |
Creators | Parrish, James |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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