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Modeling Data and Process Quality in Multi-Input, Multi-Output Information Systems


Author Info

  • Donald P. Ballou

    (Management Science Department, School of Business, State University of New York, Albany, New York 12222)

  • Harold L. Pazer

    (Management Science Department, School of Business, State University of New York, Albany, New York 12222)

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    This paper presents a general model to assess the impact of data and process quality upon the outputs of multi-user information-decision systems. The data flow/data processing quality control model is designed to address several dimensions of data quality at the collection, input, processing and output stages. Starting from a data flow diagram of the type used in structured analysis, the model yields a representation of possible errors in multiple intermediate and final outputs in terms of input and process error functions. The model generates expressions for the possible magnitudes of errors in selected outputs. This is accomplished using a recursive-type algorithm which traces systematically the propagation and alteration of various errors. These error expressions can be used to analyze the impact that alternative quality control procedures would have on the selected outputs. The paper concludes with a discussion of the tractability of the model for various types of information systems as well as an application to a representative scenario.

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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 31 (1985)
    Issue (Month): 2 (February)
    Pages: 150-162

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    Handle: RePEc:inm:ormnsc:v:31:y:1985:i:2:p:150-162

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    Related research

    Keywords: information systems: management; reliability: quality control; computers: systems design;


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    Cited by:
    1. Klein, Barbara D., 2001. "Detecting errors in data: clarification of the impact of base rate expectations and incentives," Omega, Elsevier, vol. 29(5), pages 391-404, October.
    2. So Sohn & Yoon Kim, 2013. "Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking," Small Business Economics, Springer, vol. 41(4), pages 931-943, December.
    3. Michnik, Jerzy & Lo, Mei-Chen, 2009. "The assessment of the information quality with the aid of multiple criteria analysis," European Journal of Operational Research, Elsevier, vol. 195(3), pages 850-856, June.
    4. Benita M. Gullkvist, 2013. "Drivers of change in management accounting practices in an ERP environment," International Journal of Economic Sciences and Applied Research (IJESAR), Technological Educational Institute (TEI) of Kavala, Greece, vol. 6(2), pages 149-174, September.
    5. Kon, Henry B. & Siegel, Michael D., 2003. "Error browsing and mediation : interoperability regarding data error," Working papers #94-15, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    6. Prat, Nicolas & Madnick, Stuart E., 2008. "Evaluating and Aggregating Data Believability across Quality Sub-Dimensions and Data Lineage," Working papers 40085, Massachusetts Institute of Technology (MIT), Sloan School of Management.


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