User generated content for exploring factors affecting intention to use travel and food delivery services

Abstract

Customer reviews/comments on product-websites and on social-media pages can serve as great information sources for both customers and service-providers. For exploring the drivers of usage intention in context of Online-Food-Delivery services (OFDs) and Online-Travel-Agency services (OTAs), traditional-based (qualitative or quantitative or mixed-method) approaches may not be enough. This study utilizes a multi-method approach comprising of both traditional and Natural-Language-Processing (NLP)-based approaches. This study has captured the emic-perspectives using qualitative semi-structured-interviews and etic-perspectives using NLP-based analysis of extant literature. The conceptual model developed from the model of online-decision-making stance, was tested quantitatively using survey data and by NLP-based approach using online user reviews. The path-model was tested using Structural-Equation-Modeling (SEM). Results of this study reveal that price benefits and trust-in-service are major predictors of customer’s usage intention in OFD and OTA contexts. The study concludes with the various implications, limitations and future directions.