The role of dark pattern stimuli and personality in online impulse shopping: An application of S‐O‐R theory

Abstract Online impulse shopping is a growing industry. This paper uses the Stimulus‐Organism‐Response framework to model online impulse purchase behavior using a novel combination of stimuli and organism characteristics. The stimuli: social proof, limited‐quantity scarcity, and high‐demand, are three commonly used website features known as dark patterns. The organism characteristic personality is measured by the big 5 personality traits and persona generated through latent profile analysis. Using the machine learning algorithm XGBoost, impulse purchasing response was predicted separately for each dark pattern stimuli. Results show personality characteristics are important features when predicting consumer impulse purchasing in response to dark pattern messages. Moreover, the personality traits (and personas) most predictive of impulse shopping behavior varied by type of dark pattern. Findings suggest personality influences susceptibility to different dark patterns, indicating a need for tailored interventions to mitigate individual consumer vulnerabilities to impulse shopping.