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Modeling corporate entrepreneurship success with ANFIS

Author

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  • Reza Kiani Mavi

    (Qazvin Branch, Islamic Azad University (IAU))

  • Neda Kiani Mavi

    (Qazvin Branch, Islamic Azad University (IAU))

  • Mark Goh

    (RMIT University)

Abstract

Albeit the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) in many real world problems, it is not used in the entrepreneurship studies. The aim of this paper is to develop an ANFIS model to forecasting corporate entrepreneurship (CE) success at industrial organizations. A conceptual model consisting critical success factors (motivations) and critical failure factors (barriers) of CE success is proposed. 11 experts (academic and industrial) validated the CE success and failure factors with the help of ANFIS rules. 464 MBA graduates who are working at industrial organizations have participated in this research. For the sake of ANFIS, data was divided into two groups (training and checking). Findings reveal that ANFIS testing error with training data is 0.057103 and ANFIS testing error with checking data is 0.03342. So that, the developed fuzzy inference system has the best applicability and predictability for CE success.

Suggested Citation

  • Reza Kiani Mavi & Neda Kiani Mavi & Mark Goh, 2017. "Modeling corporate entrepreneurship success with ANFIS," Operational Research, Springer, vol. 17(1), pages 213-238, April.
    • Handle: RePEc:spr:operea:v:17:y:2017:i:1:d:10.1007_s12351-015-0223-8
    DOI: 10.1007/s12351-015-0223-8
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    2. Carayannis, Elias G. & Grigoroudis, Evangelos & Wurth, Bernd, 2022. "OR for entrepreneurial ecosystems: A problem-oriented review and agenda," European Journal of Operational Research, Elsevier, vol. 300(3), pages 791-808.

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