Exploring the impact of behavioural factors and personality traits on private pension system participation: A machine learning approach

Basit Öğe Kaydı
dc.authorid0000-0003-4876-8564
dc.authorid0000-0002-0685-7641
dc.contributor.authorVerberi, Can
dc.contributor.authorKaplan, Muhittin
dc.contributor.otherYönetim Bilimleri Fakültesi, İktisat Bölümü
dc.date.accessioned2024-08-29T07:04:38Z
dc.date.available2024-08-29T07:04:38Z
dc.date.issued2024
dc.departmentİHÜ, Yönetim Bilimleri Fakültesi, İktisat Bölümü
dc.description.abstractThis study aims to investigate the effects of personality traits, in addition to basic financial literacy, private pension literacy and behavioural factors on Private Pension System (PPS) participation using machine learning algorithms. The PPS participation model was trained using both random forest and LightGBM algorithms, and the contributions of model inputs in the prediction of pension participation were interpreted using the Tree SHAP algorithms with swarmplots. The data employed in the empirical analysis is survey data collected from the Şırnak province of Türkiye with a sample size of 449. The findings of the study shows that: (i) PPS participation is more likely for females and middle-aged people; (ii) High basic financial literacy has a negative impact on PPS participation; (iii) Extraversion is the key personality trait affecting PPS participation; (iv) Advanced pension literacy has more impact on participation than simple pension literacy: (v) Present-fatalistic tendency is key behavioural factor and it negatively affects PPS; (vi) Present-hedonistic, conscientiousness, future-time orientation, and locus of control tendencies increase PPS participation. Furthermore, the distribution of colours in LightGBM has a greater degree of uniformity in both directions compared with the random forest algorithm. Finally, to increase PPS participation, the results of the study suggest the implementation of the following policy measures: Tailored pension literacy programmes can help to increase pension participation rates. Incentives should be created to prevent narrow-minded behaviour and establish a sense of protection and control around PPS, targeting middle-aged individuals and women.
dc.identifier.citationVerberi, C. ve Kaplan, M. (2024). Exploring the impact of behavioural factors and personality traits on private pension system participation: A machine learning approach. İstanbul İktisat Dergisi-Istanbul Journal Of Economics, 74(1), 281-314. https://www.doi.org/10.26650/ISTJECON2023-1360545
dc.identifier.doi10.26650/ISTJECON2023-1360545
dc.identifier.endpage314
dc.identifier.issn2602-4152
dc.identifier.issn2602-3954
dc.identifier.issue1
dc.identifier.startpage281
dc.identifier.trdizinid1280792
dc.identifier.urihttps://www.doi.org/10.26650/ISTJECON2023-1360545
dc.identifier.urihttps://hdl.handle.net/20.500.12154/2985
dc.identifier.volume74
dc.identifier.wosWOS:001292730900010
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorKaplan, Muhittin
dc.institutionauthorid0000-0002-0685-7641
dc.language.isoen
dc.publisherİstanbul University Press
dc.relation.ispartofİstanbul İktisat Dergisi-Istanbul Journal Of Economics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectPrivate Pension System
dc.subjectBehavioural Factors
dc.subjectPersonality Traits
dc.subjectMachine Learning Algorithms
dc.subjectTree SHAP
dc.titleExploring the impact of behavioural factors and personality traits on private pension system participation: A machine learning approach
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication04e6333a-2ec2-4c28-a02b-c49e3f178e90
relation.isAuthorOfPublication.latestForDiscovery04e6333a-2ec2-4c28-a02b-c49e3f178e90
relation.isOrgUnitOfPublication9d1809d1-3541-41aa-94ed-639736b7e16f
relation.isOrgUnitOfPublication.latestForDiscovery9d1809d1-3541-41aa-94ed-639736b7e16f

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
kaplan-m.pdf
Boyut:
695.46 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
[ N/A ]
İsim:
license.txt
Boyut:
1.17 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

İktisat Bölümü Koleksiyonu
TR-Dizin İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu