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Correlation coefficient evaluation for the fuzzy interval data

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  • Yang, Chih-Ching

Abstract

The issue of evaluating an appropriate correlation with fuzzy data is an important topic in the econometrics and management science, especially when the data sets illustrate uncertainty, inconsistence, and incompleteness. This study extends the concept of Pearson's correlation coefficient to compute the correlation coefficient of the data sets that are fuzzy in nature. However, no common proposal for such extension exists. This study proposes several ways to evaluate the correlation coefficient when the fuzzy data are with interval types. Two empirical studies show that the methods that this study proposes for evaluating the coefficient of fuzzy correlations are useful and efficient from the perspective of econometrics and management.

Suggested Citation

  • Yang, Chih-Ching, 2016. "Correlation coefficient evaluation for the fuzzy interval data," Journal of Business Research, Elsevier, vol. 69(6), pages 2138-2144.
  • Handle: RePEc:eee:jbrese:v:69:y:2016:i:6:p:2138-2144
    DOI: 10.1016/j.jbusres.2015.12.021
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    References listed on IDEAS

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    1. Ye, Jun, 2010. "Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 202-204, August.
    2. Tóth, Zsófia & Thiesbrummel, Christoph & Henneberg, Stephan C. & Naudé, Peter, 2015. "Understanding configurations of relational attractiveness of the customer firm using fuzzy set QCA," Journal of Business Research, Elsevier, vol. 68(3), pages 723-734.
    3. Huang, Chieh-Wei & Huarng, Kun-Huang, 2015. "Evaluating the performance of biotechnology companies by causal recipes," Journal of Business Research, Elsevier, vol. 68(4), pages 851-856.
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    Cited by:

    1. Avijit De & Sujit Das & Samarjit Kar, 2021. "Ranking of interval type 2 fuzzy numbers using correlation coefficient and Mellin transform," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 1018-1048, December.

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