Impulse buying behavior in mobile commerce: a partial least squares structural equation modeling analysis

Abstract

Efficient online transactions now thrive through websites (e-commerce) and mobile apps (m-commerce). With the growth of m-commerce, marketers aim to boost profits by understanding impulsive buying behavior. This study investigates factors influencing online impulse buying (OIB) in m-commerce by analyzing key variables. Data were gathered via questionnaires from 449 Indonesian consumers who had made digital payments and impulsive purchases using smartphones. The framework includes sales promotion (SP), attractive advertising (EA), and mobile digital payment systems (MDPS) as situational factors; hedonic shopping motivation (HSM) as a motivational factor; and impulsiveness (I) and smartphone addiction (SA) as personal traits. Analysis used partial least squares structural equation modeling (PLS-SEM), with gender, income, and smartphone usage time as control variables. Results show that EA, MDPS, HSM, I, and SA significantly influence OIB, while SP does not. For consumer segmentation, t-distributed stochastic neighbor embedding (t-SNE) outperformed ISOmap and principal component analysis (PCA), achieving a silhouette score of 0.72. A paired t-test (p<0.01) confirmed t-SNE’s superior clustering accuracy. These findings reveal that t-SNE better captures consumer segmentation patterns, helping businesses refine marketing strategies and deepen their understanding of psychological drivers behind impulsive m-commerce purchases.