Framing Effects in Risky Decision-Making: An Emotion–Value Dual-Dimensional Model Based on Eye-Tracking Evidence

Framing effects have been extensively documented in risky decision-making, yet the attentional mechanisms through which they operate remain poorly understood—particularly whether framing influences how widely versus how deeply decision-makers sample information. Using eye-tracking, we addressed this question across two experiments by dissociating attentional breadth (fixation count) from attentional depth (fixation duration). Experiment 1 revealed that loss framing did not globally prolong fixation duration; rather, it reconfigured the allocation of attention between probability and outcome information. Specifically, for outcome information, loss framing increased fixation count relative to gain framing without reliably prolonging single-fixation duration—a pattern that challenges strong versions of both fuzzy-trace theory and effort-asymmetry accounts. Experiment 2 extended these findings by manipulating amount, probability, and payoff ratio, uncovering a coordinated "cognition–motivation–emotion" regulatory architecture. Critically, amount anchored motivational activation with diminishing marginal returns, while probability and payoff ratio operated as conditional cognitive regulators rather than autonomous drivers. Building on these dissociable oculomotor signatures. Building on these dissociable oculomotor signatures, we propose a tentative Emotion–Value Dual-Dimensional interpretive framework. This framework organizes the observed patterns of motivational arousal, cognitive load, and attention allocation, and posits that risky choices emerge from the synergistic interplay between an emotion dimension (governing arousal and search termination) and a value dimension (governing expected utility and cognitive load management). As a process-level account, it distinguishes itself from prospect theory, fuzzy-trace theory, and dual-process frameworks by specifying how valence exerts its effects on attention and when framing effects are most pronounced. These findings offer precise quantitative targets for theoretical modeling and highlight the utility of eye-tracking metrics in bridging cognitive and emotional mechanisms in choice under risk.