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Using fuzzy AHP for evaluating the dimensions of data quality

Author

Listed:
  • Davod Khosroanjom
  • Masoud Ahmadzade
  • Ali Niknafs
  • Reza Kiani Mavi

Abstract

The business work flow depends on the data quality which is applied in the organisation. Therefore, data quality has become increasingly important to many organisations such as semiconductor industry. Data quality depends strongly on organisation of the information system (IS) and how the data is processed. Measuring and improving data quality in an organisation is a complex task. The purpose of this paper is to provide a good insight into the use of fuzzy analytical hierarchy process (fuzzy AHP) to incorporate four aspect dimensions of data quality: 1) intrinsic; 2) accessibility; 3) contextual; 4) representational. Findings demonstrate that the intrinsic criteria and accessibility criteria are the preferred key decision dimensions of data quality in semiconductor industry. Fuzzy AHP as a decision-making analysis tool is used for handling uncertain and imprecise data.

Suggested Citation

  • Davod Khosroanjom & Masoud Ahmadzade & Ali Niknafs & Reza Kiani Mavi, 2011. "Using fuzzy AHP for evaluating the dimensions of data quality," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 8(3), pages 269-285.
    • Handle: RePEc:ids:ijbisy:v:8:y:2011:i:3:p:269-285
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    Cited by:

    1. Risto Silvola & Janne Harkonen & Olli Vilppola & Hanna Kropsu-Vehkapera & Harri Haapasalo, 2016. "Data quality assessment and improvement," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 22(1), pages 62-81.

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