Impact Of Online Reviews And Ratings On Consumer Trust Towards Food Delivery Apps In Coimbatore District

Abstract

The proliferation of food delivery applications such as Zomato, Swiggy, and other apps in Tier-II Indian cities has radically transformed consumer purchasing behaviour. In this competitive landscape, online reviews and star ratings have emerged as powerful trust-building mechanisms that significantly influence consumer decisions. This study empirically investigates the impact of online reviews and ratings on consumer trust towards food delivery apps among users in Coimbatore District, Tamil Nadu, India. Anchored in the Technology Acceptance Model (TAM), the Information Adoption Model (IAM), and the Signalling Theory, the research employs a structured questionnaire administered to 819 respondents selected via stratified random sampling. Data were analysed using IBM SPSS Statistics 28 and IBM AMOS 26. The analytical framework includes Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Structural Equation Modelling (SEM), Pearson Correlation, Multiple Linear Regression, and one-way ANOVA. Key findings reveal that review helpfulness (β = 0.423, p < 0.001), reviewer credibility (β = 0.318, p < 0.001), and aggregate star ratings (β = 0.274, p < 0.001) are the most significant determinants of consumer trust. SEM results confirm adequate model fit (χ²/df = 2.14; CFI = 0.962; TLI = 0.956; RMSEA = 0.047; SRMR = 0.052). The study provides actionable managerial insights for food delivery platform operators seeking to leverage user-generated content as a trust-building tool in Coimbatore's rapidly expanding digital food economy.