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The assessment of the information quality with the aid of multiple criteria analysis

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  • Michnik, Jerzy
  • Lo, Mei-Chen

Abstract

The virtual business work flow depends on the information quality (IQ) which is essential attribute of information. The IQ depends strongly on organization of the information system (IS) and how the information is processed. In our approach we incorporate the four-aspect representation of IQ: (1) intrinsic, (2) contextual, (3) representational, and (4) accessibility. These four-aspects are divided into several criteria at the next level of hierarchy. The weights, representing the relative importance of criteria, have been assessed by pair-wise comparisons made by group of experts. Based on discussion with experts, six alternative strategies, that could be used for improving the IQ, were designed. For each given criterion, the group of subjects revealed the opinion about the level of achievement of every alternative. The set of scores, assigned to the alternative by different subjects, formed the discrete distribution that is used for a comparison of alternatives with the aid of stochastic dominances. In analogy to the Electre I methodology, the simple algorithm for the aggregate evaluation of analyzed alternatives was proposed. The benefits of proposed approach were demonstrated in a case study of the semiconductor industry. The results of our study suggest, that in case of matured company, the external strategies, that point out to the information exchange and strategic networked alliance with customers and suppliers, are preferred to the internal ones. The latter ones might be of greater importance for the new set up or for a young company.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:3:p:850-856
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    References listed on IDEAS

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    1. Donald P. Ballou & Harold L. Pazer, 1985. "Modeling Data and Process Quality in Multi-Input, Multi-Output Information Systems," Management Science, INFORMS, vol. 31(2), pages 150-162, February.
    2. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
    3. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
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    Cited by:

    1. Claudia Rodríguez-Hidalgo & Diana Rivera-Rogel & Luis M. Romero-Rodríguez, 2020. "Information Quality in Latin American Digital Native Media: Analysis Based on Structured Dimensions and Indicators," Media and Communication, Cogitatio Press, vol. 8(2), pages 135-145.
    2. Zhou, Chang & Li, Xiang & Chen, Lujie, 2023. "Modelling the effects of metro and bike-sharing cooperation: Cost-sharing mode vs information-sharing mode," International Journal of Production Economics, Elsevier, vol. 261(C).
    3. Majchrzak Joanna & Goliński Marek & Mantura Władysław, 2020. "The concept of the qualitology and grey system theory application in marketing information quality cognition and assessment," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(2), pages 817-840, June.
    4. Jonas Wanner & Christian Janiesch, 2019. "Big data analytics in sustainability reports: an analysis based on the perceived credibility of corporate published information," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 143-173, April.
    5. Wu, Cheng-Ru & Lin, Chin-Tsai & Tsai, Pei-Hsuan, 2010. "Evaluating business performance of wealth management banks," European Journal of Operational Research, Elsevier, vol. 207(2), pages 971-979, December.

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