NONPARAMETRIC NUMERICAL APPROACHES TO PROBABILITY WEIGHTING FUNCTION CONSTRUCTION FOR MANIFESTATION AND PREDICTION OF RISK PREFERENCES

Basit Öğe Kaydı
dc.authoridGovindan, Kannan/0000-0002-6204-1196
dc.authoridChen, Zhen-Song/0000-0003-4360-5459
dc.authorwosidGovindan, Kannan/M-5996-2017
dc.authorwosidChen, Zhen-Song/K-3436-2019
dc.contributor.authorWu, Sheng
dc.contributor.authorChen, Zhen-Song
dc.contributor.authorPedrycz, Witold
dc.contributor.authorGovindan, Kannan
dc.contributor.authorChin, Kwai-Sang
dc.date.accessioned2024-05-19T14:46:18Z
dc.date.available2024-05-19T14:46:18Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractProbability weighting function (PWF) is the psychological probability of a decision-maker for ob-jective probability, which reflects and predicts the risk preferences of decision-maker in behavioral decision-making. The existing approaches to PWF estimation generally include parametric methodologies to PWF con-struction and nonparametric elicitation of PWF. However, few of them explores the combination of parametric and nonparametric elicitation approaches to approximate PWF. To describe quantitatively risk preferences, the Newton interpolation, as a well-established mathematical approximation approach, is introduced to task-specifi-cally match PWF under the frameworks of prospect theory and cumulative prospect theory with descriptive psy-chological analyses. The Newton interpolation serves as a nonparametric numerical approach to the estimation of PWF by fitting experimental preference points without imposing any specific parametric form assumptions. The elaborated nonparametric PWF model varies in accordance with the number of the experimental preference points elicitation in terms of its functional form. The introduction of Newton interpolation to PWF estimation into decision-making under risk will benefit to reflect and predict the risk preferences of decision-makers both at the aggregate and individual levels. The Newton interpolation-based nonparametric PWF model exhibits an inverse S-shaped PWF and obeys the fourfold pattern of decision-makers' risk preferences as suggested by previous empirical analyses.en_US
dc.description.sponsorshipNational Natural Science Foundation of China [72171182, 71801175, 71871171, 71971182, 72031009]; Chinese National Funding of Social Sciences [20ZD058]; Ger/HKJRS project [G-CityU103/17]; City University of Hong Kong SRG [7004969]en_US
dc.description.sponsorshipThis work was supported by the National Natural Science Foundation of China (grant Nos. 72171182, 71801175, 71871171, 71971182, and 72031009) , the Chinese National Funding of Social Sciences (grant No. 20&ZD058) , the Ger/HKJRS project (grant No. G-CityU103/17) , and partly by the City University of Hong Kong SRG (grant no. 7004969) .en_US
dc.identifier.doi10.3846/tede.2023.18551
dc.identifier.endpage1167en_US
dc.identifier.issn2029-4913
dc.identifier.issn2029-4921
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85174468551en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1127en_US
dc.identifier.urihttps://doi.org10.3846/tede.2023.18551
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5491
dc.identifier.volume29en_US
dc.identifier.wosWOS:000974373000001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherVilnius Gediminas Tech Univen_US
dc.relation.ispartofTechnological and Economic Development of Economyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240519_kaen_US
dc.subjectProbability Weighting Functionen_US
dc.subjectRisk Preferenceen_US
dc.subjectNonparametric Numerical Approachen_US
dc.subjectNewton Interpolationen_US
dc.subjectPreference Pointsen_US
dc.subjectDecision-Making Under Risken_US
dc.titleNONPARAMETRIC NUMERICAL APPROACHES TO PROBABILITY WEIGHTING FUNCTION CONSTRUCTION FOR MANIFESTATION AND PREDICTION OF RISK PREFERENCESen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu