Understanding How Branding, Social Media & Payment Options Influence Buying Decisions Among Urban Young Adults

Abstract

In this capstone project, Brandwashed, we examined how branding, social media, and payment methods (EMI and BNPL) influence the purchase decision-making process of urban young adults in India. It is based on a mixed-method design (a primary survey of 113 actual respondents, an AI-generated pilot study of 40 responses, which is only used to test the research instrument, and thematic analysis of open-ended survey questions). The survey was conducted to compare five constructs on Likert-scale questions, including: Social Media Influence (SM), Aspirational Value (ASP), Brand Perception (BRAND), Purchase Intention (PI), and EMI/Payment Attitude (EMI). The internal reliability of all scales was strong to excellent (Cronbach's 0.807-0.901). All the scores above the neutral midpoint of 3.0 indicate that the sample is widespread in its positive orientations to aspiration, brand trust, and even to EMI to some extent. This is interesting to note that there were two items on aspirational value that were given zero disagreements among all the 113 respondents. The analysis of Pearson correlation indicated that the strongest relationship in the research was between brand perception and aspirational value (r=0.815, p=0.001), which indicates that brand perception and aspirational value are basically a single psychological player in this consumer group. The regression model was able to account 62.2% of the purchase intention variance with the aspirational value (0.322) followed by brand perception ( 0.287) being the most significant predictors. The results of ANOVA tests indicated that there are significant differences in EMI attitudes between age groups (F=4.123, p=0.008) and purchase intentions between occupational groups (F=3.795, p=0.026).Thematic analysis identified four themes from qualitative data: Aspirational Influence, Financial Caution, Payment Pragmatism, and Perceived Social Value. Comparing the AI-generated pilot data with real survey responses also revealed significant distortions in the simulated data, most notably a sign reversal in the relationship between budget willingness and purchase intention. This confirms that AI-generated data cannot replace real respondent data in behavioural research.