Demographic and Interactional Predictors of Online Shopping Behavior: A Two-Way ANOVA Analysis in NCR

Abstract

This study examines the demographic and interactional predictors that shape the frequency of online shopping among consumers in the National Capital Region (NCR) of India. Using a structured questionnaire and a sample of 542 respondents, the research applied Pearson correlation, One-Way ANOVA, and Two-Way ANOVA to evaluate the influence of delivery time, payment terms, education, income, age, advertisement exposure, and social media activity on digital shopping behavior. Findings indicate that education and income, as standalone variables, do not significantly affect online shopping frequency, challenging traditional assumptions about socioeconomic determinants. However, a significant interaction effect between age and income was identified, suggesting that income’s influence varies by generational cohort. Other interactional variables, such as education × income and social media × advertisement exposure, were not statistically significant. Delivery time had a weak but significant correlation with shopping frequency, while payment terms did not show a meaningful association. The results highlight the declining predictive power of static demographics and emphasize the need for behavioral and intersectional segmentation in digital commerce strategies.