Value Propositions of Restaurant Delivery Systems: A Text Mining-Based Review.
Due to the e-commerce rapid development during the COVID pandemic, the demand for logistics and its importance is increasing. A satisfied customer can drive e-commerce business forward. As logistical needs become more complex and logistics market becomes more competitive, service companies must strive to continually improve their value proposition to maintain their competitive edge. This study investigates the impact of two types of presentation formats (qualitative: text reviews and quantitative: star ratings) of online restaurant customer reviews on the value proposition. The study examines online restaurant reviews based on the review’s usefulness and the service experience enjoyment. Text mining was applied to online reviews to identify the driving forces behind explicit recommendations. Using semantic analysis, text mining technique, online customer reviews were analyzed from 16 largest restaurant chains, in St. Petersburg, Russia, which include 242 restaurants. Data from 201 reviews were collected from TripAdvisor, using web data collection technology. The relationships in the model were tested using multivariate analysis of variance. The results show that the delivery menu, ordering possibility through aggregators and delivery time were significant factors in the directionality of the reviews tonality. These three factors all relate to the service format logistics and restaurant business value proposition. This provides restaurateurs with clues on how to increase their efficiency and reduce dissatisfaction with restaurant delivery services. In contrast to similar studies on the relationship between value proposition factors and online reviews, this article explores the perceptions of the online reviews usefulness and focuses on the customer experience sentiment.