An expert system model of organizational climate and performance.

Bibliographic Details
Main Author: Holt, James Richard
Other Authors: Ellis, Newton C. (degree committee member.), Fox, Milden J. (degree committee member.), Garcia-Diaz, Alberto (degree committee member.), Morgan, Stephen M. (degree committee member.)
Format: Thesis Book
Language:English
Published: 1987.
Subjects:
Online Access:Link to ProQuest copy
Link to OAKTrust copy

MARC

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049 |a TXAM 
099 |a 1987  |a Dissertation  |a H758 
100 1 |a Holt, James Richard. 
245 1 3 |a An expert system model of organizational climate and performance. 
264 1 |c 1987. 
300 |a x, 236 leaves :  |b illustrations ;  |c 29 cm 
336 |a text  |b txt  |2 rdacontent 
337 |a unmediated  |b n  |2 rdamedia 
338 |a volume  |b nc  |2 rdacarrier 
500 |a Typescript (photocopy). 
500 |a Vita. 
502 |b Ph. D. in Industrial Engineering  |c Texas A & M University  |d 1987 
504 |a Includes bibliographical references (leaves 66-76). 
520 3 |a Application of computer technology has greatly increased the manager's ability to make informed decisions about inanimate resources (e.g., money, materials, equipment, space and time). However, very little has been done to automate decisions involving human behavior because of the complexities involved. This research uses a third generation expert system development shell to create a prototype management consultant for behavioral issues. The frame-based, object-oriented expert system represents individuals and organizations in a decision support system. The expert system allows managers to make real time inquiries about the effect of changes in individual attitudes in specific organizations upon organizational performance. A survey questionnaire is developed to measure 133 individual attitudes. Selected organizational behavior and group dynamics findings are translated into 52 production rules. The rules are written as methods which are activated by the system following the structure of current behavioral models to predict performance. The system is validated by situational analysis. Individual attitudes are adjusted using fuzzy logic algorithms in 18 different situations, and the changes in calculated performance are compared with managers' predictions. Statistical analysis shows it is possible to predict changes in performance due to changes in attitude and circumstances. 
650 0 |a Expert systems (Computer science) 
650 0 |a Industrial management. 
650 0 |a Organizational behavior. 
650 4 |a Major industrial engineering. 
655 7 |a Academic theses  |2 lcgft 
700 1 |a Ellis, Newton C.,  |e degree committee member. 
700 1 |a Fox, Milden J.,  |e degree committee member. 
700 1 |a Garcia-Diaz, Alberto,  |e degree committee member. 
700 1 |a Hennigan, James K.,  |e degree supervisor. 
700 1 |a Morgan, Stephen M.,  |e degree committee member. 
710 2 |a Texas A & M University,  |e degree granting institution. 
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