• DocumentCode
    1303065
  • Title

    The impact of data quality information on decision making: an exploratory analysis

  • Author

    Chengalur-Smith, InduShobha N. ; Ballou, Donald P. ; Pazer, Harold L.

  • Author_Institution
    Sch. of Bus., State Univ. of New York, Albany, NY, USA
  • Volume
    11
  • Issue
    6
  • fYear
    1999
  • Firstpage
    853
  • Lastpage
    864
  • Abstract
    This paper describes an experiment that explores the consequences of providing information regarding the quality of data used in decision making. The subjects in the study were given three types of information about the data´s quality: none, two-point ordinal, and interval scale. This information was made available to the subjects, along with the actual data. Two decision strategies were explored: conjunctive and weighted linear additive. Two decision environments were used: a simple environment and a relatively complex environment. Various combinations of these factors were employed to explore several issues. These include complacency, consensus, and consistency. The paper provides preliminary insights into which type of data-quality information is most effective and the circumstances in which data-quality information is most effective. Such knowledge would be of value to those responsible for designing databases that support decision-makers. Overall, we find that in a situation where subjects are confronted with clearly differentiated alternatives, the inclusion of data-quality information impacted the selection of the preferred alternative while maintaining group consensus
  • Keywords
    data mining; database management systems; decision support systems; complacency; consensus; consistency; data quality information; data-quality information; databases; decision making; decision strategies; exploratory analysis; group consensus; Data warehouses; Decision making; Information analysis; Notice of Violation; Quality control; Quality management; Tagging; Transaction databases;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.824597
  • Filename
    824597