Journal of Mathematical Sciences: Advances and Applications[1] W. J. L. Adams and R. Saaty, Super Decisions Software Guide, Super
Decisions 9 (2003), 43.
[2] E. W. Anderson, E. Ghysels and J. L. Juergens, The impact of risk
and uncertainty on expected returns, Journal of Financial Economics
94(2) (2009), 233-263.
DOI: https://doi.org/10.1016/j.jfineco.2008.11.001
[3] E. Ballestero, M. Bravo, B. Pérez-Gladish, M. Arenas-Parra and
D. Pla-Santamaria, Socially responsible investment: A multicriteria
approach to portfolio selection combining ethical and financial
objectives, European Journal of Operational Research 216(2) (2012),
487-494.
DOI: https://doi.org/10.1016/j.ejor.2011.07.011
[4] G. Beliakov, A. Pradera and T. Calvo, Aggregation functions: A
guide for practitioners, Volume 221, Heidelberg: Springer, 2007.
DOI: https://doi.org/10.1007/978-3-540-73721-6
[5] G. Choquet, Theory of Capacities, In Annales de l'Institut
Fourier, 5 (1954), 131-295.
DOI: https://doi.org/10.5802/aif.53
[6] M. Ehrgott, K. Klamroth and C. Schwehm, An MCDM approach to
portfolio optimization, European Journal of Operational Research
155(3) (2004), 752-770.
DOI: https://doi.org/10.1016/S0377-2217(02)00881-0
[7] E. Fernández, N. Rangel-Valdez, L. Cruz-Reyes and C.
Gomez-Santillan, A new approach to group multi-objective optimization
under imperfect information and its application to project portfolio
optimization, Applied Sciences 11(10) (2021); Article 4575.
DOI: https://doi.org/10.3390/app11104575
[8] L. Ganassin, Analisi della Relazione tra la Profilatura della
Clientela ed il Portafoglio d’Investimento, 2016.
[9] B. A. Joo and K. Durri, Comprehensive review of literature on
behavioural finance, Indian Journal of Commerce and Management Studies
6(2) (2015), 11-19.
[10] D. Keirsey, Please Understand Me II: Temperament, Character,
Intelligence, 2 (1998).
[11] W. J. Kickert, Fuzzy Theories on Decision Making: A Critical
Review, 1979.
[12] I. M. Lami, F. Abastante, M. Bottero, E. Masala and S. Pensa,
Integrating multicriteria evaluation and data visualization as a
problem structuring approach to support territorial transformation
projects, EURO Journal on Decision Processes 2(3-4) (2014),
281-312.
DOI: https://doi.org/10.1007/s40070-014-0033-x
[13] C. T. Leondes, Fuzzy Theory Systems: Techniques and Applications,
1999.
[14] C. Liang and Q. Li, Enterprise information system project
selection with regard to BOCR, International Journal of Project
Management 26(8) (2008), 810-820.
DOI: https://doi.org/10.1016/j.ijproman.2007.11.001
[15] G. Loewenstein and D. Prelec, Anomalies in intertemporal choice:
Evidence and an interpretation, The Quarterly Journal of Economics
107(2) (1992), 573-597.
DOI: https://doi.org/10.2307/2118482
[16] A. Mardani, A. Jusoh and E. K. Zavadskas, Fuzzy multiple criteria
decision-making techniques and applications –Two decades review
from 1994 to 2014, Expert Systems with Applications 42(8) (2015),
4126-4148.
DOI: https://doi.org/10.1016/j.eswa.2015.01.003
[17] R. Martino and V. Ventre, An Analytic Network Process to Support
Financial Decision-Making in the Context of Behavioural Finance,
Mathematics 11(18) (2023); Article 3994.
DOI: https://doi.org/10.3390/math11183994
[18] R. Martino, V. Ventre and G. di Tollo, Analytic hierarchy process
for classes of economic behavior in the context of intertemporal
choices, Ratio Mathematica 47 (2023), 408-436.
DOI: http://dx.doi.org/10.23755/rm.v47i0.1137
[19] R. Martino and V. Ventre, A multidisciplinary approach to
decompose decision-making process in the context of intertemporal
choices, Ratio Mathematica 43 (2022), 231-246.
DOI: http://dx.doi.org/10.23755/rm.v43i0.880
[20] M. M. Pompian, Using behavioral investor types to build better
relationships with your clients, Journal of Financial Planning 21(10)
(2008), 64-76.
[21] M. Pompian, Risk profiling through a behavioral finance lens, CFA
Institute Research Foundation, 2016.
[22] D. Prelec, Decreasing impatience: a criterion for
nonâ€stationary time preference and “hyperbolicâ€
discounting, The Scandinavian Journal of Economics 106(3) (2004),
511-532.
DOI: https://doi.org/10.1111/j.0347-0520.2004.00375.x
[23] S. Cruz Rambaud and M. J. Muñoz Torrecillas, Measuring
impatience in intertemporal choice, PLoS One 11(2) (2016); Article
e0149256.
DOI: https://doi.org/10.1371/journal.pone.0149256
[24] D. Read, Blackwell Handbook of Judgment and Decision Making; John
Wiley & Sons: Hoboken, NJ, USA, 2008, pp. 424-443.
[25] K. I. Rohde, The hyperbolic factor: A measure of time
inconsistency, Journal of Risk and Uncertainty 41 (2010), 125-140.
[26] T. L. Saaty and L. G. Vargas, The Analytic Network Process (pp.
1-40), Springer US, 2013.
[27] P. A. Samuelson, A note on measurement of utility, The Review of
Economic Studies 4(2) (1937), 155-161.
DOI: https://doi.org/10.2307/2967612
[28] P. A. Samuelson, Probability, utility, and the independence
axiom, Econometrica: Journal of the Econometric Society 20(4) (1952),
670-678.
[29] V. Ventre and R. Martino, Quantification of aversion to
uncertainty in intertemporal choice through subjective perception of
time, Mathematics 10(22) (2022); Article 4315.
DOI: https://doi.org/10.3390/math10224315
[30] V. Ventre, R. Martino and F. Maturo, Subjective perception of
time and decision inconsistency in interval effect, Quality & Quantity
57(5) (2023), 4855-4880.
DOI: https://doi.org/10.1007/s11135-022-01581-9
[31] V. Ventre, G. di Tollo and R. Martino, Consensus reaching process
for portfolio selection: A behavioral approach, 4OR- A Quarterly
Journal of Operations Research (2023 a).
DOI: https://doi.org/10.1007/s10288-023-00552-6
[32] V. Ventre, S. Cruz Rambaud, R. Martino and F. Maturo, An analysis
of intertemporal inconsistency through the hyperbolic factor, Quality
& Quantity 57(1) (2023), 819-846.
DOI: https://doi.org/10.1007/s11135-022-01352-6
[33] V. Ventre, C. R. Salvador, R. Martino and F. Maturo, A behavioral
approach to inconsistencies in intertemporal choices with the analytic
hierarchy process methodology, Annals of Finance 19(2) (2023 c),
233-264.
DOI: https://doi.org/10.1007/s10436-022-00419-6
[34] V. Ventre, R. Martino, R. Castellano and P. Sarnacchiaro, The
analysis of the impact of the framing effect on the choice of
financial products: An analytical hierarchical process approach,
Annals of Operations Research (2023 d), 1-17.
DOI: https://doi.org/10.1007/s10479-022-05142-z
[35] P. Xidonas and J. Psarras, Equity portfolio management within the
MCDM frame: A literature review, International Journal of Banking,
Accounting and Finance 1(3) (2009), 285-309.
DOI: https://doi.org/10.1504/IJBAAF.2009.022717
[36] Q. Wu, X. Liu, J. Qin and L. Zhou, Multi-criteria group
decision-making for portfolio allocation with consensus reaching
process under interval type-2 fuzzy environment, Information Sciences
570 (2021), 668-688.
DOI: https://doi.org/10.1016/j.ins.2021.04.096
[37] L. A. Zadeh, Fuzzy sets, Information and Control 8(3) (1965),
338-353.
DOI: https://doi.org/10.1016/S0019-9958(65)90241-X
[38] L. A. Zadeh, Fuzzy sets as a basis for a theory of possibility,
Fuzzy Sets and Systems 1(1) (1978), 3-28.
DOI: https://doi.org/10.1016/0165-0114(78)90029-5
[39] P. Zimbardo and J. Boyd, The time paradox: The new psychology of
time that will change your life, Simon and Schuster, 2008.
[40] H. Zhang, I. Palomares, Y. Dong and W. Wang, Managing
non-cooperative behaviors in consensus-based multiple attribute group
decision making: An approach based on social network analysis,
Knowledge-Based Systems 162 (2018), 29-45.
DOI: https://doi.org/10.1016/j.knosys.2018.06.008
