An Empirical Study of Factors Shaping Quick Commerce Adoption Among Indian Gen-Z

Quick commerce or the delivery of everyday consumer items within a window of ten to thirty minutes after an order is places has rapidly transitioned from a pilot concept to a mainstream retail channel across India’s metros. Platforms such as Blinkit, Zepto and Swiggy Instamart have managed to develop brand loyalty most distinctly among Gen Z, whose digital nativity, strong convenience orientation and high interface expectations not only render them the ideal quick commerce audience but also the most unforgiving critics. Empirical studies investigating the specific factors associated with quick commerce adoption among this group, despite the commercial weight of this convergence, remain few. This research will fill that gap using descriptive, quantitative design. A structured online questionnaire based on a five-point Likert scale was used to collect primary data from 384 respondents belonging to Indian Gen-Zs residing in Tier – I cities. The Cochran formula (1977) was used to determine sample size. There were two analytical techniques used to analyze the data for this research. The first is the Chi-Square Test of Independence which has been used to analyze whether the demographic variables like gender and age group are significantly associated with the frequency of quick commerce usage. The second is Multiple Linear Regression (MLR) which has been used to analyze the relative impact of the seven independent constructs (convenience, price and offers, trust and security, UI/UX, delivery issues, payment issues and product quality issues) as independent variables on Adoption Intention taken as the dependent variable. The resultant regression model of the predictors was found to be satisfactory. R² obtained was 0.653. The F-statistic was 101.159 with p < .001. It means predictors collectively account for 65.3 per cent variance in adoption intention. The largest positive driver of adoption was UI/UX with a β-coefficient of 0.466 at p < 0.001. The second strongest negative driver was Payment Issues at β = −0.092 and at p < 0.05. Chi-Square analysis show that there is no significant relationship between gender and usage frequency (χ² = 12.669, p = 0.124), However, usage pattern varies significantly among age sub-groups. The results of the study are significant for platform developers, marketers and regulators in India’s rapidly evolving quick commerce sector.