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.
Citation: Ehsan Ahmadi, Parastoo Mohammadi, Farimah Mokhatab Rafei, Shib Sankar Sana. Behavioral factors and capital structure: identification and prioritization of influential factors[J]. Data Science in Finance and Economics, 2025, 5(1): 76-104. doi: 10.3934/DSFE.2025005
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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Ehsan Ahmadi, Parastoo Mohammadi, Farimah Mokhatab Rafei, Shib Sankar Sana. Behavioral factors and capital structure: identification and prioritization of influential factors[J]. Data Science in Finance and Economics, 2025, 5(1): 76-104. doi: 10.3934/DSFE.2025005
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