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An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R

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Abstract

The assessment of investment risk for the countries along the route in Belt and Road (B&R) can be deemed as a multiple criteria group decision making (MCGDM) issue since multiple investment options based on diverse criterions are assessment by experts. Pondering that the complexity and uncertainty of the assessment setting and the cognition fuzziness and psychological behavior of experts bring challenges to risk assessment, this paper designed an integrated MCGDM risk investment evaluation framework by synthesizing MABAC method and prospect theory under Fermatean fuzzy setting. Firstly, a Fermatean fuzzy interactive distance measure is presented to ascertain the weight of evaluation experts and criterions. Next, some Fermatean fuzzy Frank aggregation operators based upon the proposed Frank operations are developed to fuse Fermatean fuzzy information efficiently. In addition, an innovative evaluation framework for risk investment is designed based on improved prospect theory MABAC and CRITIC approaches. Conclusively, an empirical concerning risk investment issues in B&R is employed to confirm the applicability and feasibility of the constructed evaluation framework, involving the simulation experiments on sensitivity analysis and contrast studies. The assessment information provided by investors using the linguistic assessment terms based upon their cognition ability of them. These outcomes obtained by the propounded method and comparison analysis further emphasize the validity and salient merits of the propounded framework and provide several auxiliary suggestions for investors.

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Notes

  1. Ministry of Commerce of the people’s Republic of China, statistical bulletin of China’s foreign direct investment in 2019, http://hzs.mofcom.gov.cn/article/date/202009/20200903001523.shtml.

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Acknowledgements

The author especially wishes to thank the School of Science at Xihua University for their support in the preparation of this paper.

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Authors and Affiliations

  1. School of Science, Xihua University, Chengdu, 610039, Sichuan, People’s Republic of China

    Jiade Tan

  2. School of Mathematics and Information Sciences, Neijiang Normal University, Neijiang, 641100, Sichuan, People’s Republic of China

    Yi Liu

  3. Department of Mathematics, Padima Janakalyan Banipith, Kukrakhupi, 721517, India

    Tapan Senapati

  4. School of Mathematics and Statistics, Southwest University, Beibei, 400715, Chongqing, China

    Tapan Senapati

  5. School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala, 147004, Punjab, India

    Harish Garg

  6. School of Management, Shanghai University, Baoshan District, 200444, Shanghai, People’s Republic of China

    Yuan Rong

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  1. Jiade Tan
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Correspondence to Yuan Rong.

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Appendix

Appendix

All Abbreviations and symbols used throughout the manuscript are illustrated in Tables 11 and 12 respectively.

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Tan, J., Liu, Y., Senapati, T. et al. An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R. J Ambient Intell Human Comput 14, 13067–13096 (2023). https://doi.org/10.1007/s12652-022-03769-1

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