rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: An
    title: expert system model of organizational climate and performance
  name:
    name part: Holt, James Richard.
    role:
      role term: creator
  name:
    name part: Ellis, Newton C.
    role:
      role term: degree committee member.
  name:
    name part: Fox, Milden J.
    role:
      role term: degree committee member.
  name:
    name part: Garcia-Diaz, Alberto
    role:
      role term: degree committee member.
  name:
    name part: Hennigan, James K.
    role:
      role term: degree supervisor.
  name:
    name part: Morgan, Stephen M.
    role:
      role term: degree committee member.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  genre: Academic theses
  origin info:
    place:
      place term: xx
    date issued: 1987
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: x, 236 leaves : illustrations ; 29 cm
  abstract: 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.
  note: Typescript (photocopy).
  note: Vita.
  note: Ph. D. in Industrial Engineering Texas A & M University 1987
  note: Includes bibliographical references (leaves 66-76).
  subject:
    topic: Expert systems (Computer science)
  subject:
    topic: Industrial management
  subject:
    topic: Organizational behavior
  subject:
    topic: Major industrial engineering
  identifier: http://proxy.library.tamu.edu/login
  identifier: https://hdl.handle.net/1969.1/DISSERTATIONS-32990
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: https://hdl.handle.net/1969.1/DISSERTATIONS-32990
  record info:
    record content source: TXA
    record creation date: 880913
    record change date: 20220104090755.0
    record identifier: in00000029200
    language of cataloging:
      language term: eng