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New statistical analysis in marketing research with fuzzy data

Author

Listed:
  • Lin, Hsin-Cheng
  • Wang, Chen-Song
  • Chen, Juei Chao
  • Wu, Berlin

Abstract

This research proposes new statistical methods for marketing research and decision making. The study employs a soft computing technique and a new statistical tool to evaluate people's thinking. Because the classical measurement system has difficulties in dealing with the non-real valued information, the study aims to find an appropriate measurement system to overcome this problem. The main idea is to decompose the data into a two-dimensional type, centroid and its length (area). The two-dimensional questionnaires this study proposes help reaching market information.

Suggested Citation

  • Lin, Hsin-Cheng & Wang, Chen-Song & Chen, Juei Chao & Wu, Berlin, 2016. "New statistical analysis in marketing research with fuzzy data," Journal of Business Research, Elsevier, vol. 69(6), pages 2176-2181.
    • Handle: RePEc:eee:jbrese:v:69:y:2016:i:6:p:2176-2181
    DOI: 10.1016/j.jbusres.2015.12.026
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    References listed on IDEAS

    as
    1. Nguyen, Hung T. & Wu, Berlin, 2006. "Random and fuzzy sets in coarse data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 70-85, November.
    2. Concepción Costas & Pedro Marañon & Juan Cabrera, 1994. "Application of diffuse measurement to the evaluation of psychological structures," Quality & Quantity: International Journal of Methodology, Springer, vol. 28(3), pages 305-313, August.
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    Cited by:

    1. Sudtasan, Tatcha & Mitomo, Hitoshi, 2016. "Effects of OTT services on consumer's willingness to pay for optical fiber broadband connection in Thailand," 27th European Regional ITS Conference, Cambridge (UK) 2016 148709, International Telecommunications Society (ITS).
    2. Ozge Yasar & Tulay Korkusuz Polat, 2022. "A Fuzzy-Based Application for Marketing 4.0 Brand Perception in the COVID-19 Process," Sustainability, MDPI, vol. 14(24), pages 1-22, December.

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