Exploring the multi-dimensionality of authenticity in dining experiences using online reviews. (August 2021)

• Record Type: Journal Article
• Authors: Le, Truc H.; Arcodia, Charles; Abreu Novais, Margarida; Kralj, Anna; Phan, Thanh Cong
• Is Part Of: Tourism management. Volume 85(2021)
• Publication Date: 2021-08
• Subjects: Authenticity -- Restaurant -- User-generated content (UGC) -- Text mining -- Integrated learning -- Human-machine learning -- Machine learning -- Classification; Tourism -- Periodicals; 338.4791
• DOI: 10.1016/j.tourman.2021.104292
• Languages: English
• ISSNs: 0261-5177

Abstract

Abstract: The quest for authenticity in dining experiences has become increasingly important. This paper explores authenticity dimensions that are of value to customers in dining experiences, and by that gains a multi-dimensional understanding of authenticity in this context. Following an integrated learning approach using text mining and classification techniques, this paper explores and confirms different dimensions of authenticity by identifying and classifying authenticity judgements in online restaurant reviews. The results suggest that authenticity is a multi-dimensional concept encompassing Authenticity of the Other, Authenticity of the Producer, and Authenticity of the Self as first-level dimensions . Additionally, besides historical and categorical authenticity which have been previously explored in the literature, a new type of authenticity - Deviated Authenticity - emerged as a second-level dimension falling under Authenticity of the Other . This paper enhances existing conceptualisations of authenticity and establishes avenues for exploring the multi-dimensionality of other consumer research concepts using user-generated content.