Beyond Choice: Affective Representations of Economic and Moral Decisions

Abstract

Decision-making in economic and moral contexts involves complex affective processes that shape judgments of fairness, responsibility, and conflict resolution. While previous studies have primarily examined behavioral choices in economic games and moral dilemmas, less is known about the underlying affective structure of these decisions. This study investigated how individuals emotionally represent economic (ultimatum game) and moral (trolley dilemma) decision-making scenarios using multidimensional scaling (MDS) and classification. Participants rated their emotional responses, including positive (pleased, calm, happy, peaceful) and negative (irritated, angry, gloomy, sad, fearful, anxious) affective states, to 16 scenarios varying by game type, the presence or absence of conflict, and intensity. MDS revealed two primary affective dimensions of distinguishing conflict from no-conflict and economic from moral scenarios. No-conflict-economic scenarios were strongly associated with positive affective responses, while the no-conflict-moral scenarios elicited heightened fear and anxiety rather than positive emotions. Increasing unfairness in the ultimatum game affected affective representation, while variations in the number of lives at stake in the trolley dilemma did not. Cross-participant classification analyses demonstrated that game type and conflict conditions could be reliably predicted from affective ratings, indicating systematic and shared emotional representations across participants. These findings suggest that economic and moral decisions evoke distinct affective structures, with fairness modulating conflict perception in economic contexts, while moral decisions remain affectively stable despite changes in intensity.

Keywords: affect; classification; fairness; multidimensional scaling; trolley dilemma; ultimatum game.

Figure 1

The results of rotated three-dimensional MDS with the vector fitting of the economic and moral decision-making scenarios. Each vector indicates the adjectives used to rate the affective responses of the scenarios. r = Pearson’s correlation coefficient between the coordinates of the rotated MDS solution and the design values.

Figure 2

The results of the within- (left) and cross-participant classification (right). Each bar of the graphs indicates the accuracy of each test. The dotted lines indicate the chance level, and the solid red lines indicate the critical value.