The impact of personality, behavior, and geography on participation in the private pension system in Türkiye: A machine learning approach

dc.contributor.authorVerberi, Can
dc.contributor.authorKaplan, Muhittin
dc.date.accessioned2026-01-22T19:52:05Z
dc.date.issued2025
dc.departmentŞırnak Üniversitesi
dc.description.abstractThis study examines regional disparities in the factors that affect participation in the Private Pension System (PPS) in T & uuml;rkiye, focusing on sociodemographic characteristics, personality traits and behavior, and pension and financial literacy. The behavioral factors identified encompass procrastination, locus of control, pessimism, compulsive buying, and time perspective, and the personality traits include openness, agreeableness, extraversion, neuroticism, and conscientiousness. The study employs data on two provinces in T & uuml;rkiye, S,& imath;rnak and Istanbul, and uses XGBoost and Tree SHAP algorithms and a probit model. Our findings indicate that personality traits such as openness, agreeableness, and conscientiousness have a positive influence on individual engagement in pension plans, whereas extraversion has a negative impact. Additionally, basic pension literacy is more influential than advanced pension literacy. The results also show that regional geography significantly influences personality and behavioral factors. Finally, a perception of protection is a critical factor in PPS participation.
dc.identifier.doi10.1016/j.bir.2024.12.010
dc.identifier.endpage162
dc.identifier.issn2214-8450
dc.identifier.issn2214-8469
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85214785792
dc.identifier.scopusqualityQ1
dc.identifier.startpage149
dc.identifier.urihttps://doi.org/10.1016/j.bir.2024.12.010
dc.identifier.urihttps://hdl.handle.net/11503/3663
dc.identifier.volume25
dc.identifier.wosWOS:001421831900001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofBorsa Istanbul Review
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20260122
dc.subjectBehavioral factors
dc.subjectMachine learning algorithms
dc.subjectPersonality traits
dc.subjectPrivate pension system
dc.subjectTree SHAP
dc.titleThe impact of personality, behavior, and geography on participation in the private pension system in Türkiye: A machine learning approach
dc.typeArticle

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