Dual-brain dynamics underlying consumer preferences for recommendations in choice assortments: evidence from computational modeling and fNIRS-based hyperscanning

With the continual expansion of product options provided by retailers, the range of product options in the choice assortment may exert a considerable effect on consumer preferences for real-time recommendations. We combined hierarchical drift-diffusion modeling with functional near-infrared spectroscopy (fNIRS)-based hyperscanning to delve into neurocomputational signatures of dual-brain synchronization that underlie the effect of varying choice assortment sizes on consumer preferences for real-time recommendations. Behavioral and computational results identified that consumers exhibited stronger consumer preferences for real-time recommendations and deliberative decision-making strategies within small choice assortments. Neural results demonstrated disparate inter-brain synchronization patterns across different successive phases underlying the effect of choice assortment sizes on consumer preferences for real-time recommendations. The predictive role of distinct dual-brain temporal dynamics on consumers’ decision-making strategies within small and large choice assortments was also determined with a support vector machine algorithm, thus demonstrating the value of dual-brain approaches in capturing the complexity of real-world decision-making environments.