Determinants of Satisfaction and Continuance Intention in Food DeliveryApplications
DOI:
https://doi.org/10.26439/pjm2026.n003.8276Keywords:
food delivery applications, expectation confirmation model, user satisfaction, continuance intention, partial least squares structural equation modelingAbstract
Purpose: This study aims to identify the determinants influencing continuance intention in food delivery
applications (FDAs) using an integrated framework based on the expectation confirmation model (ECM).
Although FDAs have transformed consumption habits in urban environments, retaining user engagement
remains a major challenge for digital platforms. This research examines the influence of delivery experience,
promotions, perceived time savings, expectation confirmation, and perceived usefulness on user satisfaction and continuance intention. Design/methodology/approach: The study employed a non-experimental, cross-sectional design with a quantitative and explanatory scope. Data were collected from 174 valid users in Metropolitan Lima and analyzed using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4. Findings: The results reveal that user satisfaction significantly mediates the relationship between operational factors (delivery experience, promotions, and time savings) and continuance intention. Expectation confirmation positively influences both perceived usefulness and satisfaction, reinforcing the role of cognitive judgment in post-usage behavior. Practical implications: The findings provide insights for platform managers and service designers seeking to strengthen user loyalty by improving operational performance and offering personalized value propositions. Originality/value: This study contributes to the literature on digital services by extending the ECM framework to the FDA context, incorporating functional service attributes that have been scarcely examined in prior research. By capturing both affective and cognitive factors, the study offers a more comprehensive understanding of user retention mechanisms in digital service ecosystems.
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