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Crowdfunding project evaluation based on Fermatean fuzzy SAHARA three-way decision method

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Abstract

Crowdfunding is a web-based financing scheme which aims to generate initial capital for startups. Nowadays, there are numerous programs which face the shortage in capital has already launching by crowdfunding. Meanwhile, there are always lots of potential investors who are puzzled by their choices and are thus cannot join them. In this paper, an assessment framework of crowdfunding projects founded on the three-way decision (TWD) is offered to solve the issue. The fuzziness and uncertainty in the evaluation information are the major factors affecting the accuracy of the output and the Fermatean fuzzy sets (FFS) of the proposed model conquers the problem. A Preference Selection Index - Standard Deviation Bayesian method is arranged to determine objective attribute weights with the precise and reliable data. Traditional fuzzy aggregation operators do not perform well in extreme and contradictory information processing situations, and FFS - evidence reasoning methodology (ERM) is proposed to gather messages, while the conditional probability is exported from the similarity metric. Improved FFS objective relative utility function supports TWD classifications and rankings, and the TWD-SAHARA utility function offers non-linear benefits tailored to human psychology. The proposed FF-PSI-SD-ERM-TWD has been utilized on eight crowdsourcing projects, and its effectiveness has been proven by sensitivity analysis and the results comparison.

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References

  1. Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Google Scholar 

  2. Senapati T, Yager RR (2020) Fermatean fuzzy sets. J Ambient Intell Humaniz Comput 11:663–674

    Google Scholar 

  3. Yager RR (2013) Pythagorean fuzzy subsets. Ifsa World Congress & Nafips Meeting

  4. Maniya K, Bhatt MG (2010) A selection of material using a novel type decision-making method: preference selection index method. Mater Des 31(4):1785–1789

    Google Scholar 

  5. Diakoulaki D, Mavrotas G, Papayannakis L (1995) Determining objective weights in multiple criteria problems: the critic method. Comput Oper Res 22(7):763–770

    Google Scholar 

  6. Yang J, Singh MG (1994) An evidential reasoning approach for multiple-attribute decision making with uncertainty. IEEE Trans Syst Man Cybern 24(1):1–18

    Google Scholar 

  7. Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96

    MathSciNet  Google Scholar 

  8. Bakioglu G, Atahan AO (2021) AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Appl Soft Comput 99:106948

    Google Scholar 

  9. Zhou F, Chen T-Y (2022) A hybrid approach combining AHP with TODIM for blockchain technology provider selection under the Pythagorean fuzzy scenario. Artif Intell Rev 55(7):5411–5443

    Google Scholar 

  10. Akram M, Luqman A, Alcantud JCR (2022) An integrated ELECTRE-I approach for risk evaluation with hesitant Pythagorean fuzzy information. Expert Syst Appl 200:116945

    Google Scholar 

  11. Jana C, Garg H, Pal M (2022) Multi-attribute decision making for power Dombi operators under Pythagorean fuzzy information with MABAC method. J Ambient Intell Humanized Comput pp 1–18

  12. Fei L, Feng Y (2021) A dynamic framework of multi-attribute decision making under Pythagorean fuzzy environment by using Dempster-Shafer theory. Eng Appl Artif Intell 101:104213

    Google Scholar 

  13. Paul TK, Pal M, Jana C (2021) Multi-attribute decision making method using advanced Pythagorean fuzzy weighted geometric operator and their applications for real estate company selection. Heliyon 7(6):07340

    Google Scholar 

  14. Zhang C, Ding J, Zhan J, Li D (2022) Incomplete three-way multi-attribute group decision making based on adjustable multigranulation Pythagorean fuzzy probabilistic rough sets. Int J Approx Reason 147:40–59

    MathSciNet  Google Scholar 

  15. Senapati T, Yager RR (2019) Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods. Eng Appl Artif Intell 85:112–121

    Google Scholar 

  16. Hadi A, Khan W, Khan A (2021) A novel approach to MADM problems using Fermatean fuzzy Hamacher aggregation operators. Int J Intell Syst 36(7):3464–3499

    Google Scholar 

  17. Aydemir SB, Yilmaz Gunduz S (2020) Fermatean fuzzy TOPSIS method with Dombi aggregation operators and its application in multi-criteria decision making. J Intell Fuzzy Syst 39(1):851–869

    Google Scholar 

  18. Mishra AR, Chen S-M, Rani P (2023) Multicriteria decision making based on novel score function of Fermatean fuzzy numbers, the critic method, and the glds method. Inf Sci 623:915–931

    Google Scholar 

  19. Kirişci M (2023) New cosine similarity and distance measures for Fermatean fuzzy sets and TOPSIS approach. Knowl Inf Syst 65(2):855–868

    Google Scholar 

  20. Deng Z, Wang J (2022) New distance measure for Fermatean fuzzy sets and its application. Int J Intell Syst 37(3):1903–1930

    Google Scholar 

  21. Keshavarz-Ghorabaee M, Amiri M, Hashemi-Tabatabaei M, Zavadskas EK, Kaklauskas A (2020) A new decision-making approach based on Fermatean fuzzy sets and WASPAS for green construction supplier evaluation. Mathematics 8(12):2202

    Google Scholar 

  22. Rani P, Mishra AR (2021) Fermatean fuzzy Einstein aggregation operators-based MULTIMOORA method for electric vehicle charging station selection. Expert Syst Appl 182:115267

    Google Scholar 

  23. Rani P, Mishra AR, Saha A, Hezam IM, Pamucar D (2022) Fermatean fuzzy Heronian mean operators and MEREC-based additive ratio assessment method: an application to food waste treatment technology selection. Int J Intell Syst 37(3):2612–2647

    Google Scholar 

  24. Simic V, Gokasar I, Deveci M, Isik M (2021) Fermatean fuzzy group decision-making based codas approach for taxation of public transit investments. IEEE Trans Eng Manag

  25. Narayanamoorthy S, Parthasarathy TN, Pragathi S, Shanmugam P, Baleanu D, Ahmadian A, Kang D (2022) The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location. Sustainable Energy Technol Assess 53:102488

    Google Scholar 

  26. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281

    MathSciNet  Google Scholar 

  27. Rezaei J (2015) Best-worst multi-criteria decision-making method. Omega 53:49–57

    Google Scholar 

  28. Pamučar D, Stević Ž, Sremac S (2018) A new model for determining weight coefficients of criteria in MCDM models: full consistency method (FUCOM). Symmetry 10(9):393

    Google Scholar 

  29. Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379–423

    MathSciNet  Google Scholar 

  30. Hatefi MA (2019) Indifference threshold-based attribute ratio analysis: a method for assigning the weights to the attributes in multiple attribute decision making. Appl Soft Comput 74:643–651

    Google Scholar 

  31. Demir G (2022) Hayat dışısigorta sektöründe kurumsal performansın psi-sd tabanlı MABAC metodu ile ölçülmesi: Anadolu sigorta örneği. Ekonomi Politika ve Finans Araştırmaları Dergisi 7(1):112–136

    Google Scholar 

  32. Foroozesh F, Monavari SM, Salmanmahiny A, Robati M, Rahimi R (2022) Assessment of sustainable urban development based on a hybrid decision-making approach: group fuzzy BWM, AHP, and TOPSIS-GIS. Sustain Cities Soc 76:103402

    Google Scholar 

  33. Tsai P-H, Wang Y-W, Chang W-C (2023) Hybrid MADM-based study of key risk factors in house-for-pension reverse mortgage lending in Taiwan’s banking industry. Socioecon Plann Sci 86:101460

    Google Scholar 

  34. Dempster A (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 38(2):325–339

    MathSciNet  Google Scholar 

  35. Shafer G (1976) A mathematical theory of evidence. Princeton University Press 42

  36. Zadeh LA (1984) Book review: a mathematical theory of evidence. AI Mag 5(3):81–83

    Google Scholar 

  37. Li Z, Hu S, Zhu X, Gao G, Yao C, Han B (2022) Using DBN and evidence-based reasoning to develop a risk performance model to interfere ship navigation process safety in Arctic waters. Process Saf Environ Prot 162:357–372

    Google Scholar 

  38. Zhou M, Liu X-B, Yang J-B, Chen Y-W, Wu J (2019) Evidential reasoning approach with multiple kinds of attributes and entropy-based weight assignment. Knowl-Based Syst 163:358–375

    Google Scholar 

  39. Fan X, Xu Z (2023) Double-level multi-attribute group decision-making method based on intuitionistic fuzzy theory and evidence reasoning. Cogn Comput pp 1–18

  40. Peng B, Zheng C, Zhao X, Wei G, Wan A (2021) Pythagorean fuzzy multiattribute group decision making based on risk attitude and evidential reasoning methodology. Int J Intell Syst 36(11):6180–6212

    Google Scholar 

  41. Pawlak Z (1982) Rough sets. Int J Comput Inform Sci 11:341–356

    Google Scholar 

  42. Yao Y (2009) Three-way decision: an interpretation of rules in rough set theory, Springer, pp 642–649

  43. Yao Y (2018) Three-way decision and granular computing. Int J Approx Reason 103:107–123

    Google Scholar 

  44. Wang Y, He S, Zamora DG, Pan X, Martínez L (2023) A large scale group three-way decision-based consensus model for site selection of new energy vehicle charging stations. Expert Syst Appl 214:119107

    Google Scholar 

  45. Zhan J, Ye J, Ding W, Liu P (2021) A novel three-way decision model based on utility theory in incomplete fuzzy decision systems. IEEE Trans Fuzzy Syst 30(7):2210–2226

  46. Lin T, Yang B (2023) Three-way group conflict analysis based on q-rung orthopair fuzzy set theory. Comput Appl Math 42(1):30

    MathSciNet  Google Scholar 

  47. Huang X, Zhan J, Xu Z, Fujita H (2023) A prospect-regret theory-based three-way decision model with intuitionistic fuzzy numbers under incomplete multi-scale decision information systems. Expert Syst Appl 214:119144

    Google Scholar 

  48. Wang T, Li H, Zhang L, Zhou X, Huang B (2020) A three-way decision model based on cumulative prospect theory. Inf Sci 519:74–92

    MathSciNet  Google Scholar 

  49. Zhu J, Ma X, Zhan J, Yao Y (2022) A three-way multi-attribute decision making method based on regret theory and its application to medical data in fuzzy environments. Appl Soft Comput 123:108975

    Google Scholar 

  50. Belleflamme P, Lambert T, Schwienbacher A (2014) Crowdfunding: tapping the right crowd. J Bus Ventur 29(5):585–609

    Google Scholar 

  51. Belleflamme P, Lambert T, Schwienbacher A (2010) Crowdfunding: an industrial organization perspective. In: Prepared for the workshop digital business models: understanding strategies’, Held in Paris on June, pp 25–26

  52. Zheng H, Li D, Wu J, Xu Y (2014) The role of multidimensional social capital in crowdfunding: a comparative study in China and US. Inform Manag 51(4):488–496

    Google Scholar 

  53. Anglin AH, Short JC, Drover W, Stevenson RM, McKenny AF, Allison TH (2018) The power of positivity? the influence of positive psychological capital language on crowdfunding performance. J Bus Ventur 33(4):470–492

    Google Scholar 

  54. Taeuscher K, Bouncken R, Pesch R (2021) Gaining legitimacy by being different: optimal distinctiveness in crowdfunding platforms. Acad Manag J 64(1):149–179

    Google Scholar 

  55. Chan HF, Moy N, Schaffner M, Torgler B (2021) The effects of money saliency and sustainability orientation on reward based crowdfunding success. J Bus Res 125:443–455

    Google Scholar 

  56. Borrero-Domínguez C, Cordón-Lagares E, Hernández-Garrido R (2020) Analysis of success factors in crowdfunding projects based on rewards: a way to obtain financing for socially committed projects. Heliyon 6(4):03744

    Google Scholar 

  57. Vinogradova I, Podvezko V, Zavadskas EK (2018) The recalculation of the weights of criteria in MCDM methods using the Bayes approach. Symmetry 10(6):205

    Google Scholar 

  58. Jia F, Liu P (2019) A novel three-way decision model under multiple-criteria environment. Inf Sci 471:29–51

    MathSciNet  Google Scholar 

  59. Shit C, Ghorai G (2021) Multiple attribute decision-making based on different types of Dombi aggregation operators under Fermatean fuzzy information. Soft Comput 25(22):13869–13880

    Google Scholar 

  60. Mishra AR, Chen S-M, Rani P (2023) Multicriteria decision making based on novel score function of Fermatean fuzzy numbers, the critic method, and the glds method. Inf Sci 623:915–931. https://doi.org/10.1016/j.ins.2022.12.031

    Article  Google Scholar 

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MW: visualization, investigation. JS: conceptualization, methodology, software, investigation, formal analysis, writing - original draft. JF: review & editing.

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Correspondence to Jianping Fan.

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Wu, M., Song, J. & Fan, J. Crowdfunding project evaluation based on Fermatean fuzzy SAHARA three-way decision method. Appl Intell 54, 3566–3590 (2024). https://doi.org/10.1007/s10489-024-05334-z

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