Examining the Impact of Behavioral-Psychological Components of Investors’ Model for Decision-Making Based on Environmental Drivers in the Tehran Stock Exchange

Mohammad Hosein Shiehmorteza; Payman Ghafari Ashtiani; Majid Davooudinasr

doi:10.61838/

Authors

Mohammad Hosein Shiehmorteza Department of Financial Management, Arak Branch, Islamic Azad University, Arak, Iran

Payman Ghafari Ashtiani * Department of Business Management, Arak Branch, Islamic Azad University, Arak, Iran Pe.ghafari@iau.ac.ir

Majid Davooudinasr Department of Accounting, Arak Branch, Islamic Azad University, Arak, Iran

https://doi.org/10.61838/

Keywords:

Behavioral-psychological model, investor decision-making, environmental drivers, Tehran Stock Exchange, structural equation modeling

Abstract

Objective: This study aims to develop and validate a behavioral-psychological model of investors' decision-making influenced by environmental drivers in the Tehran Stock Exchange.

Methodology: The study employed a grounded theory approach using Strauss and Corbin's methodology, with data collected from semi-structured interviews conducted in 2021 and 2022. The participants comprised 384 investment managers and experts from the Tehran Stock Exchange, selected through random-cluster sampling based on Morgan’s table. Data were collected using a 5-point Likert scale questionnaire to assess perceptions and behavior patterns and were analyzed through structural equation modeling (SEM) using SmartPLS software.

Findings: The results revealed that investors’ decisions are shaped by several dimensions, including causal factors (such as diagnostic ability and sentiment analysis), contextual factors (including positive and negative environmental drivers and regulatory requirements), intervening factors (such as behavioral outcomes, cultural characteristics, investor beliefs, and government economic policy), and strategic factors (like strategic financial planning). These dimensions collectively impact the central phenomenon of behavioral-psychological decision-making. The model’s outcomes were also validated, showing enhancements in investors’ perceptual levels, strengthened long-term perspectives, and expanded investment goals. The model's reliability and validity were confirmed using Cronbach's alpha, composite reliability, and AVE measures, with all indicators falling within acceptable ranges.

Conclusion: Recognizing these drivers and investor biases allows for a more comprehensive understanding of market dynamics, suggesting that investment firms and policymakers should consider these behavioral patterns in strategic planning.