Study On Student Centric Quick Commerce Application

Quick commerce (q-commerce) has rapidly emerged as a transfo rmative force in the e-commerce sector, catering to the demand for ultra-fast delivery through hyperlocal logistics, AI-driven inventory management, and dark store networks. While existing q-commerce models have primarily targeted urban consumers, this research investigates its applicability and potential within student communities, a demographic with unique purchasing behaviors and immediate consumption needs. This study presents a data-driven analysis of market demand, operational feasibility, and financial sustainability for a student-centric q-commerce platform. Through primary research involving extensive student surveys and secondary data evaluation, the study assesses consumer behavior patterns, preferred product categories, and logistical challenges. The findings highlight the viability of a specialized model tailored to student communities, underpinned by AI-powered operational efficiencies. Additionally, the study explores historical investment trends in the q-commerce space, providing insights into the funding potential for such ventures. By establishing an academic foundation through empirical research and industry analysis, this paper offers a structured framework for evaluating q-commerce's role in student consumer ecosystems. The insights derived serve as a reference for future business models, investment considerations, and strategic decision-making in this evolving sector.