Examining the interplay of information, emotions, and behavior: PLS-ANN analysis

Abstract

This study investigates the interplay between platform information push, consumer emotions, and purchase behavior in Macau’s cross-border e-commerce context using PLS-ANN analysis and piecewise linear regression. The findings reveal nuanced effects of information push on pleasure and annoyance, with distinct patterns emerging at different levels. These emotional responses significantly influence purchase intentions and actual behavior. Pleasure has a positive impact, while annoyance negatively affects outcomes. To optimize consumer sentiment and drive sales, e-commerce platforms should strategically manage information content, presentation, and timing. Harnessing positive emotions, balancing information sufficiency and overload prevention, and fostering long-term emotional connections are crucial. Adapting push strategies to diverse market preferences is vital for cross-border success. The study expands affect-as-information and emotional contagion theories, offering actionable suggestions for precision marketing. Future research should explore additional emotive dimensions, individual differences, and contextual moderators to enrich the model.