Do behavioural biases shape personal financial decisions: a structural equation modelling (SEM) approach

Ajaz Ul Islam

International Journal of Behavioural Accounting and Finance2025https://doi.org/10.1504/ijbaf.2025.150269article
ABDC C
Weight
0.50

What the paper says

The study investigated the impact of behavioural biases on personal financial decision-making by applying partial least square structural equation modelling (PLS-SEM). Specifically, it investigated the impact of cognitive and emotional biases on personal financial decisions and analysed the interconnections between cognitive and emotional behavioural biases and personal financial decisions. The findings suggest that behavioural biases significantly impact personal financial decisions and, if ignored, can lead to significant losses while making financial decision-making (Chaudhary, 2013). Both cognitive and emotional biases inferred a significant negative impact on personal financial decisions. Thus, it is inferred that individual behaviour significantly influences financial decisions. The inferences from the study can be used by financial advisors and planners to understand their client's decision-making processes and develop strategies to mitigate the negative impacts. Policymakers can recommend educational programs to improve financial literacy to help individuals make more rational financial decisions.

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https://doi.org/https://doi.org/10.1504/ijbaf.2025.150269

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@article{ajaz2025,
  title        = {{Do behavioural biases shape personal financial decisions: a structural equation modelling (SEM) approach}},
  author       = {Ajaz Ul Islam},
  journal      = {International Journal of Behavioural Accounting and Finance},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijbaf.2025.150269},
}

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Do behavioural biases shape personal financial decisions: a structural equation modelling (SEM) approach

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.