Exploring user-generated content related to dining experiences of consumers with food allergies

Abstract

The purpose of this research was to explore and assess factors influencing perceptions of consumers with food allergies toward restaurants when accommodating allergen-free requests. Mixed approaches, including big data analytics (i.e., topic modeling), content analysis, and multiple regression analyses were performed to analyze user-generated reviews for restaurants listed on AllergyEats.com , an information-sharing platform for consumers with food allergies. Among the 40 topics identified, "knowledgeable staff" was the most prevalent topic. Results of topic correlation analyses revealed five groups of topics: customized orders, efforts of staff, menu options, fried foods and oil, and communication with shared latent features. Four topics in the group of "efforts of staff" had the highest positive impact on restaurant ratings, while two topics in the group of "communications" had the strongest negative impacts. Foodservice managers and educators may use the results of this study to better accommodate consumers with food allergies and develop appropriate training programs.