Abstract

Purpose: This study examines the relationships among switching intention, switching behavior, customer forgiveness, and continuance intention in quick commerce (Q-commerce) among IT professionals in Chennai, India. Design/methodology/approach: This quantitative, cross-sectional study used a structured questionnaire with a 7-point Likert scale. Data were obtained from 500 IT professionals aged 18-34 who had used at least one Q-commerce platform within the previous three months. A non-probability convenience sampling approach, supplemented by snowball recruitment for online distribution, was used. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4.0. Findings: All four hypothesized direct relationships were statistically significant. Switching intention was negatively associated with customer forgiveness (β = -0.486, p < 0.001), while customer forgiveness was positively associated with continuance intention (β = 0.683, p < 0.001). Switching intention was positively associated with switching behavior (β = 0.588, p < 0.001), whereas continuance intention was negatively associated with switching behavior (β = -0.330, p < 0.001). The model explained 61.1% of the variance in switching behavior. The sequential indirect effect through customer forgiveness and continuance intention was also significant (β = 0.110, p < 0.001), indicating complementary partial mediation. Because the data are cross-sectional, these findings are interpreted as associations rather than definitive causal effects. Research Limitations/Implications: The study is limited to IT professionals aged 18-34 in Chennai and uses non-probability sampling, which restricts generalizability. Future studies should examine other demographic groups and geographical contexts and use longitudinal or experimental designs to test the temporal sequence and causal interpretation of the proposed relationships.

Keywords

Digital Platforms, IT Professionals, PLS-SEM, Service Recovery, User Retention,

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