Name: Upasana Gutt, Fiza Bhateja
Country: India

Year: 2026
Volume: Volume No: 13, Issue No: 1, Year: 2026
Page Number: 543-558
DOI: https://doi.org/10.5281/zenodo.21238200

Understanding which cognitive biases most urgently demand managerial attention is a challenge that statistical significance alone cannot resolve. This study employs Importance Performance Map Analysis (IPMA) within a Partial Least Squares Structural Equation Modeling (PLS-SEM) framework to produce a priority map of behavioral biases and Theory of Planned Behavior (TPB) constructs affecting retail investors' investment intentions. Using data from 364 retail investors in Delhi-NCR, India, the model treats behavioral biases as a reflective second-order construct comprising seven sub dimensions: overconfidence, anchoring, availability bias, loss aversion, mental accounting, representativeness, and regret aversion alongside attitude, subjective norms, and perceived behavioral control as structural predictors. IPMA reveals that overconfidence (importance = 0.209, performance = 66.03) and loss aversion (importance = 0.175, performance = 55.46) are the highest-priority intervention
targets, exhibiting strong structural influence on investment intention yet operating below the sample's average performance benchmark. Regret aversion and anchoring constitute a secondary priority cluster, while perceived behavioral control, though structurally meaningful (β = 0.199), already performs well, implying diminishing returns to further investment in self-efficacy building. Subjective norms are both structurally negligible and already high performing, placing them firmly in the low-priority quadrant. The study advances the IPMA literature by providing a validated, resource allocation-oriented framework for debiasing retail investors in emerging economies, offering actionable guidance for financial advisors, regulators, and fintech platform developers.