Breaking The Bias: The Role of Adversity Quotient in Navigating CSR Disclosures and Investor Heuristics
DOI:
https://doi.org/10.61255/jeemba.v4i6.1563Keywords:
Corporate Social Responsibility, Adversity Quotient, Bias Heuristics, Representativeness, Anchoring-adjustmentAbstract
Purpose – This study examines the role of the adversity quotient as a mental ability in mitigating heuristic bias in earnings forecasting, using earnings information and corporate social responsibility disclosures.
Design/methodology/approach – This study employs a quantitative mixed-design framework, combining a repeated-measures task structure with a measured between-person moderator (Adversity Quotient). All participants completed both representativeness and anchoring-adjustment heuristic tasks in a counterbalanced sequence to control for potential order, learning, and carryover effects. Rather than a pure 2×3 full-factorial design, AQ is treated as a measured individual-difference characteristic rather than an experimentally manipulated factor, allowing the analysis to explicitly model this mixed experimental structure.
Finding/Results – This study revealed that skepticism causes investors to ignore impression management-based CSR narratives and prioritize objective fundamental analysis. This results in representativeness bias not affecting earnings projections. However, investors were found to be highly susceptible to anchoring and adjustment bias, in which the initial target figure from management becomes the dominant cognitive anchor. Despite the availability of additional information, investors' adjustments tend to be inadequate, leaving forecasts close to the anchor figure. This weakness can be mitigated by the Adversity Quotient (AQ); investors with high AQ show cognitive resilience, resisting the influence of anchors and making more accurate adjustments based on CSR data.
Originality/Value – The novelty of this research lies in the analysis of the adversity quotient factor specifically in relation to CSR information disclosure—an analysis that has not been conducted previously.
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