Behavioral factors and capital structure: identification and prioritization of influential factors

Our objective of this research was to identify and rank the factors that influence the capital structure decisions of Iranian companies, focusing on the role of behavioral elements as intermediaries. To construct the research framework, we employed a two-phase, mixed-method design that encompassed both qualitative insights and quantitative methodologies. In the qualitative phase, experts in the capital market are consulted using a snowball sampling technique, and key research factors were identified through coding analysis. Subsequently, for the quantitative phase, managers from leading Tehran Stock Exchange–listed companies were surveyed to prioritize the model components via the Analytic Hierarchy Process (AHP). Moreover, Factor Analysis with expert feedback using structural equation modeling (SEM) were performed in the model. Initially, we identified 63 concepts, later refined to 58 after expert consultation, and categorized them into behavioral, macroeconomic, political, socio-cultural, corporate characteristics, and governance factors. Quantitative analysis revealed that macroeconomic factors exhibit the highest influence (0.266), followed by behavioral factors (0.230), corporate governance (0.201), company-specific characteristics (0.141), political factors (0.103), and socio-cultural factors (0.059) in shaping financial structures. This research thus offers a more detailed examination of how behavioral biases and broader market conditions are converged to influence capital structure, underscoring the importance of integrating cognitive perspectives—particularly those of financial managers—into corporate decision-making processes. Future investigations can be benefited from integrating broader market data, such as share price movements, to further refine insights into the dynamic interplay of behavior and capital structure.

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Publication Details

Journal
Data Science in Finance and Economics
Published
2025-01-01
DOI
https://doi.org/10.3934/dsfe.2025005
Citations
1
Primary Topic
Corporate Finance and Governance
Type
article
Field-Weighted Citation Impact
3.91
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article

Behavioral factors and capital structure: identification and prioritization of influential factors

Shib Sankar Sana, Parastoo Mohammadi, Farimah Mokhatab Rafei, Ehsan Ahmadi
1 citations
Data Science in Finance and Economics
Corporate Finance and Governance
3.91
article

Behavioral factors and capital structure: identification and prioritization of influential factors

Shib Sankar Sana, Parastoo Mohammadi, Farimah Mokhatab Rafei, Ehsan Ahmadi
article en
1 citations

Abstract

Our objective of this research was to identify and rank the factors that influence the capital structure decisions of Iranian companies, focusing on the role of behavioral elements as intermediaries. To construct the research framework, we employed a two-phase, mixed-method design that encompassed both qualitative insights and quantitative methodologies. In the qualitative phase, experts in the capital market are consulted using a snowball sampling technique, and key research factors were identified through coding analysis. Subsequently, for the quantitative phase, managers from leading Tehran Stock Exchange–listed companies were surveyed to prioritize the model components via the Analytic Hierarchy Process (AHP). Moreover, Factor Analysis with expert feedback using structural equation modeling (SEM) were performed in the model. Initially, we identified 63 concepts, later refined to 58 after expert consultation, and categorized them into behavioral, macroeconomic, political, socio-cultural, corporate characteristics, and governance factors. Quantitative analysis revealed that macroeconomic factors exhibit the highest influence (0.266), followed by behavioral factors (0.230), corporate governance (0.201), company-specific characteristics (0.141), political factors (0.103), and socio-cultural factors (0.059) in shaping financial structures. This research thus offers a more detailed examination of how behavioral biases and broader market conditions are converged to influence capital structure, underscoring the importance of integrating cognitive perspectives—particularly those of financial managers—into corporate decision-making processes. Future investigations can be benefited from integrating broader market data, such as share price movements, to further refine insights into the dynamic interplay of behavior and capital structure.

Data Science in Finance and EconomicsVol. 5(1)
Visva-Bharati University (IN), Tarbiat Modares University (IR)
Openalex Percentile: Top 10%
Corporate Finance and Governance
3.91
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