What are customers commenting on, and how is their satisfaction affected? Examining online reviews in the on-demand food service context

Abstract

The on-demand economy has prospered with the rapid development of digital platforms. Many customers use on-demand service platforms to order services and then post online reviews. Using text-mining approaches, this study examines customers' online review-writing behavior and their overall satisfaction with restaurants in the context of on-demand food service. We use customers' overall ratings in their reviews to measure their overall satisfaction. We find that customers comment on the main service provider, the restaurants, and the auxiliary service providers, which include the drivers and on-demand service platform; in their online customer reviews, which are posted on the restaurants' web pages on the on-demand service platform. From text regressions, we found the determinants of customer satisfaction with the restaurants through their online reviews. There is a spillover effect from the performance of auxiliary providers on customer satisfaction with the main provider. That is, the performance of the drivers and the platform affects customers' overall satisfaction with the restaurants. In addition, we find that a higher cost of the order makes customers comment more on the attributes offered by the restaurants to show their overall satisfaction. Further, we find the type of listed merchants categorized by their properties (i.e., chain or independent) and participation in the platform programs affect the influence of the various attributes, offered by different providers, on customer satisfaction with the main provider. The findings shed light on the determinants of customers' overall satisfaction and urge improvement in collaboration and coordination between various participants in the on-demand service context.