The Impact of Cognitive Bias on the Quality of Managerial Decision-Making: A Qualitative Meta-Synthesis

Mediaty; Asri Usman; Andi Shahrani Awalya; Dedeh Cahyani Toresa

doi:10.38142/jebd.v4i1.402

Authors

Mediaty Hasanuddin University, Indonesia
Asri Usman Hasanuddin University, Indonesia
Andi Shahrani Awalya Hasanuddin University, Indonesia
Dedeh Cahyani Toresa

DOI:

https://doi.org/10.38142/jebd.v4i1.402

Keywords:

Award Decisions Credit, Human Resource Management, Metasynthesis

Abstract

Purpose:
This study aims to analyze the impact of cognitive bias on the quality of managerial decision-making using the perspective of Bounded Rationality Theory. The study focuses on how cognitive limitations, heuristics, and psychological distortions influence managerial judgment in management accounting, budgeting, reporting, risk management, investment, strategy implementation, and technology-assisted decision-making.
Methodology:
This research applies a qualitative meta-synthesis approach by integrating findings from prior qualitative reviews, systematic literature reviews, and conceptual studies related to cognitive bias and managerial decision-making. The synthesis process involved identifying relevant studies, extracting major findings, grouping recurring themes, and developing an integrated interpretation of the relationship between cognitive bias and decision quality.
Findings:
The synthesis shows that overconfidence, anchoring, confirmation bias, availability bias, loss aversion, hindsight bias, illusion of control, and herding behavior are dominant forms of cognitive bias in managerial decision-making. These biases reduce decision quality by distorting information interpretation, weakening the objective evaluation of alternatives, and increasing errors in assessing risk, opportunity, and decision consequences.
Implication:
The study indicates that organizations need to integrate debiasing strategies, choice architecture, collective evaluation, independent review, professional skepticism, and critical supervision of artificial intelligence-based systems to improve the quality of managerial decisions in complex and uncertain environments.

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