Voice in Words: A Mixed-Method Approach for Decoding Digital Footprints Using Online Reviews

Abstract

ABSTRACT Using a mixed-method technique, the present study investigates the causal relationship between consumer judgments about airline service quality and their online recommendations. It also examines the essential attributes that determine key airline service quality dimensions. The current research was conducted on passenger reviews, ratings, and recommendations data (1270 business class and 2464 economy class passengers) from Skytraxratings.com of three major airlines using logistic regression and sentiment analysis. The empirical investigation of service ratings depicts that the fitted logit model adequately explains airline service quality–airline recommendation relationship for business and economy class travelers. Furthermore, this study identifies the crucial service attributes and their sentiment strengths toward key service dimensions. The study results enable a comprehensive understanding of airline service quality based on real-time consumer insights, which can help strategize and develop customized interventions for airline service designs and realignments.