Navigating the Future of Commerce: A Structural Equation Modelling Approach to Q-Commerce, Operational Optimization, and Human Capital Management

Abstract

The rapid expansion of Quick Commerce (Q-commerce) has reshaped consumer expectations by promising delivery within minutes. This study investigates how operational technologies and human capital strategies influence the overall performance of Q-commerce firms. Using Structural Equation Modeling (SEM), the research empirically tests the relationships between AI adoption, employee training and development, inventory management, delivery efficiency, workforce productivity, customer satisfaction, and composite operational performance. Data collected from 120 professionals in leading Indian Q-commerce companies, including Blinkit, Zepto, and Swiggy Instamart, was analyzed using SmartPLS. The results confirm that AI adoption significantly improves delivery efficiency, training enhances workforce productivity, and real-time inventory visibility boosts customer satisfaction. These three intermediate factors—delivery efficiency, workforce productivity, and customer satisfaction—strongly predict overall operational performance. The study provides a validated SEM framework for Q-commerce performance, emphasizing the synergistic role of technology and human capital. These insights inform both managerial strategies and future research directions in digital retail ecosystems.