Purpose: In the realm of investment management, selecting an appropriate investment portfolio for holding companies constitutes one of the most critical decisions. Owing to their diversified investment activities and their strategic role in resource management, these companies require a precise analysis of various factors, particularly behavioral ones. Behavioral factors such as risk aversion, overconfidence, and fear of failure can significantly influence investment decisions. This study examines and prioritizes these factors with a focus on one of the active holding companies in the country.
Design/Methodology/Approach: This research is applied in terms of purpose and descriptive survey in terms of method. The statistical population and sample are assessed at two levels: at the first level, the target holding companies were considered; at the second level, experts and investment managers within these holding companies were selected to complete the relevant questionnaires. Since this study is conducted as a case study, it does not involve a statistical sample; instead, one active holding company and its associated experts were selected as the study sample. The data were collected through academic literature, interviews with academic and executive experts, relevant questionnaires, and the documents and records of the selected company. After identifying the behavioral factors influencing investment decision making among managers in holding companies, the DEMATEL technique was applied to determine the direct relations among the criteria. Through the direct relation matrix, the causal relationships were identified, specifying which behavioral factors influence others and which ones are influenced. Subsequently, the prioritization of these factors was determined using pairwise comparisons based on the Analytic Network Process (ANP). For this purpose, a questionnaire designed to assess the relative importance of the criteria was employed. After collecting the completed questionnaires, the collective expert judgment was calculated using the geometric mean. In this step, following the construction of the network model in Super Decisions software and establishing the interrelations among criteria, the DANP method was applied to determine the weights of the factors. The aggregated judgments were entered into the initial supermatrix as pairwise comparisons. The weighted supermatrix was then raised to a sufficiently large power (Z) until convergence and stability were achieved. To conduct the analysis, the first phase of the study involved identifying behavioral factors affecting investment decisions in holding companies through semi structured interviews with experts. The interviews were analyzed in stages using a qualitative content analysis approach. The results were compared with the existing literature to determine the final set of behavioral factors.
Findings: The findings indicate that among the cognitive biases, self attribution (A2), overconfidence (A3), and the gambler’s fallacy (A5) have a causal nature, while the remaining criteria are effect type. Overconfidence (A3) is the most influential criterion, affecting all six other cognitive factors, whereas limited attention (A4) is the most influenced (effect type) factor. Among emotional biases, regret aversion (B3), increased risk taking (B5), and loss aversion (B6) were found to be causal. Loss aversion (B6) influences all six other emotional subcriteria and is one of the most influential factors. Calendar effects (B2) are the most influenced subcriterion, affected by five other factors except herd behavior (B1). The causal relationships among the subcriteria of other behavioral characteristics reveal mutual influence between the secure anxious (C1) and conservative daring (C2) traits, with C1 exerting a slightly stronger effect on C2, thus rendering C1 a causal factor. Ultimately, the results of the data analysis show that among the main criteria, cognitive bias—with a weight of 0.3573—represents the most significant behavioral factor affecting portfolio selection in holding companies. Emotional bias (0.3381) and other behavioral characteristics (0.2281) follow in order of importance. Among the subcriteria, the secure anxious trait holds the highest importance (0.1212), followed by conservative daring (0.1069) and loss aversion (0.0642).
Discussion and Conclusion: The findings suggest that cognitive and emotional factors play a more important role than personality traits in investment decision making in holding companies. Among other behavioral characteristics, managers’ levels of confidence or anxiety and their conservative or risk seeking tendencies exert the greatest influence on portfolio selection. The results demonstrate that the behavioral factors of decision makers in holding companies do not act independently; rather, they influence the portfolio selection process through a causal and interconnected network. Some biases and personality traits function as causal factors, while others act as outcomes, with varying intensities of influence. This highlights the necessity of adopting a systemic and network based perspective toward managerial behavior in investment decision making. From a managerial standpoint, the findings suggest that improving the quality of investment decisions in holding companies cannot be achieved solely by enhancing financial analytical tools. Instead, it requires managing behavioral risks, designing collective decision making mechanisms, and employing scenario analysis to mitigate anxiety and cognitive biases.