Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93643
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Management and Marketingen_US
dc.creatorChai, Jen_US
dc.creatorNgai, EWTen_US
dc.date.accessioned2022-07-19T08:14:00Z-
dc.date.available2022-07-19T08:14:00Z-
dc.identifier.issn0167-9236en_US
dc.identifier.urihttp://hdl.handle.net/10397/93643-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Chai, J., & Ngai, E. W. (2020). The variable precision method for elicitation of probability weighting functions. Decision Support Systems, 128, 113166 is available at https://doi.org/10.1016/j.dss.2019.113166.en_US
dc.subjectBehavioral decision makingen_US
dc.subjectNonparametric elicitationen_US
dc.subjectProbability weightingen_US
dc.subjectProspect theoryen_US
dc.subjectTradeoff methoden_US
dc.titleThe variable precision method for elicitation of probability weighting functionsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume128en_US
dc.identifier.doi10.1016/j.dss.2019.113166en_US
dcterms.abstractThis study introduces a nonparametric method to elicit decision weights under prospect theory. These weights carry the attitudes and subjective beliefs of individuals toward risks and uncertainties. Our variable precision method adopts a dynamic mechanism that can elicit the measuring points of individual probability weighting flexibly. These points are used to exhibit violations of expected utility theory, which measures individual risk attitudes and captures subjective beliefs on probabilities. Our method is flexible, tractable, and cognitively less demanding compared with other nonparametric elicitations in the literature. Experimental studies are conducted on a sample of Hong Kong (China) residents to verify our method. Our experimental results yield a prevailing inverse-S shape. We conduct the analyses and uncover their implications by comparing them with the results of residents of Beijing, Shanghai, Paris, and Amsterdam.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationDecision support systems, Jan. 2020, v. 128, 113166en_US
dcterms.isPartOfDecision support systemsen_US
dcterms.issued2020-01-
dc.identifier.scopus2-s2.0-85074436436-
dc.identifier.eissn1873-5797en_US
dc.identifier.artn113166en_US
dc.description.validate202207 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberMM-0099-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextBeijing Normal University-Hong Kong Baptist University United International Collegeen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS26741458-
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Ngai_Variable_Precision_Method.pdfPre-Published version1.33 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

38
Last Week
0
Last month
Citations as of May 12, 2024

Downloads

47
Citations as of May 12, 2024

SCOPUSTM   
Citations

8
Citations as of May 16, 2024

WEB OF SCIENCETM
Citations

4
Citations as of May 16, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.