Overconfidence Bias in Financial Decision-Making: Evidencefrom Culinary MSMEs in Banjarmasin, Indonesia

This study examines the role of overconfidence bias in shaping financial decision-making among culinary MSMEs in ‎Banjarmasin, Indonesia. Although overconfidence has been recognized as a behavioral bias influencing financial ‎decisions, empirical evidence in the context of MSMEs in developing countries is still limited. This study used a ‎quantitative approach, collecting data from 80 culinary MSMEs, which were then analyzed using Partial Least Squares–‎Structural Equation Modeling (PLS-SEM). Overconfidence was operationalized as a multidimensional construct ‎consisting of overestimation, overprecision, and illusion of control. The results showed that only the illusion of control ‎dimension had a positive and significant effect on financial decision-making, while overestimation and overprecision did ‎not show a significant effect. This finding indicates that MSMEs tend to rely on subjective perceptions of self-control ‎rather than measurable financial analysis in making financial decisions. This study contributes to the behavioral finance ‎literature by highlighting the heterogeneity of overconfidence dimensions in the micro-enterprise context and providing ‎practical implications for the development of behavior-based financial literacy programs for entrepreneurs in emerging ‎markets‎.

Authors

Institutions

Publication Details

Journal
International Journal of Accounting and Economics Studies
Published
2026-01-14
DOI
https://doi.org/10.14419/vn7scf57
Primary Topic
Financial Literacy and Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Overconfidence Bias in Financial Decision-Making: Evidencefrom Culinary MSMEs in Banjarmasin, Indonesia

Dian Masita Dewi, Asrid Juniar, Sarwani, Rika Sylvia
International Journal of Accounting and Economics Studies
Financial Literacy and Behavior
article

Overconfidence Bias in Financial Decision-Making: Evidencefrom Culinary MSMEs in Banjarmasin, Indonesia

Dian Masita Dewi, Asrid Juniar, Sarwani, Rika Sylvia
article en

Abstract

This study examines the role of overconfidence bias in shaping financial decision-making among culinary MSMEs in ‎Banjarmasin, Indonesia. Although overconfidence has been recognized as a behavioral bias influencing financial ‎decisions, empirical evidence in the context of MSMEs in developing countries is still limited. This study used a ‎quantitative approach, collecting data from 80 culinary MSMEs, which were then analyzed using Partial Least Squares–‎Structural Equation Modeling (PLS-SEM). Overconfidence was operationalized as a multidimensional construct ‎consisting of overestimation, overprecision, and illusion of control. The results showed that only the illusion of control ‎dimension had a positive and significant effect on financial decision-making, while overestimation and overprecision did ‎not show a significant effect. This finding indicates that MSMEs tend to rely on subjective perceptions of self-control ‎rather than measurable financial analysis in making financial decisions. This study contributes to the behavioral finance ‎literature by highlighting the heterogeneity of overconfidence dimensions in the micro-enterprise context and providing ‎practical implications for the development of behavior-based financial literacy programs for entrepreneurs in emerging ‎markets‎.

International Journal of Accounting and Economics StudiesVol. 13(1)
Lambung Mangkurat University (ID)
Quality Education
Openalex Percentile: Top 89%
Financial Literacy and Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.