Understanding and Conceptualising Authenticity in Dining Experiences Using Online Reviews

Abstract

The quest for authentic experiences has been evidenced in modern society, either as a pursuit for product purchases, leisure experiences, or true self. Many studies have investigated authenticity and attempted to operationalise this complex concept in several ways. While being well examined since the 1970s by tourism researchers such as MacCannell (1973, 1976) and Cohen (1979), scholarly interest in authenticity remains prevalent in current hospitality and tourism research. In the dining context, the extant literature has only studied authenticity from the dimensions of the cultural/ethnic theme displayed, the food, and the servicescape, lacking a multi-dimensional approach for understanding authenticity in dining experiences. Nevertheless, a small number of studies have started considering dining experiences as a product, which directs research attention to the backstage role of the producer-organisation in constructing authenticity cues. Delivering authentic experiences in restaurants has moved beyond the core product itself (the food), and increasingly demands the producerorganisation to project its own true qualities to co-construct these dining experiences. This thesis attempts to offer a comprehensive understanding of consumers’ perceptions of authenticity in dining experiences. In doing so, it also conceptualises authenticity as a multidimensional notion by incorporating conceptualisations of authenticity from various disciplines. Following this line of argument, the overarching proposition of the thesis is that authenticity is a multi-dimensional concept, encompassing Authenticity of the Other, Authenticity of the Producer, and Authenticity of the Self. The thesis was guided by three interrelated research objectives to address the proposition. A three-phase mixed-methods design was adopted to fulfil the research objectives and a dataset of over a million online reviews was scraped from a popular restaurant review platform, which was subsequently sampled and analysed using an integrated learning approach. This thesis is structured as a series of papers. The research began with a systematic review (Paper 1) to investigate the gaps in the existing literature and three research directions were subsequently explored in the papers which followed. Informed by the gaps identified in the review regarding advanced analytical approaches of online reviews, Paper 2 served as the methodology employed in the thesis, proposing a systematic approach that integrates traditional research methods and machine learning to conceptualise multi-dimensional concepts using online reviews. Reflecting the utility of the methodological approach proposed in Paper 2, Paper 3 used traditional data collection and analysis method (quota sampling and thematic analysis) in the examination of online reviews to understand how consumers form authenticity perceptions in dining experiences. In addition, Paper 4 applied integrated learning which used the outcomes from proportionate random sampling and manual classification to direct machine learning in classification modeling, in order to determine the multi-dimensionality of authenticity in dining experiences. Overall, the findings suggest that authenticity is a multi-dimensional concept, encompassing Authenticity of the Other, Authenticity of the Producer, and Authenticity of the Self, thus supporting the overarching proposition. Additionally, beside historical and categorical authenticity which have been previously explored in the literature, a new type of authenticity - Deviated Authenticity – emerged as a sub-dimension of Authenticity of the Other. Through the close-up examination of online reviews, a demonstration of consumers’ judgements about authenticity in dining experiences is also provided, which depicts several authenticity cues in the dining context. This thesis offers theoretical, methodological, and practical contributions. Theoretically, it advances the current conceptualisations of authenticity not only in dining experiences, but also in tourism, management and organisational studies contexts. Methodologically, the thesis calls for greater attention to well-documented and systematic integrated learning approaches in text analytics to conceptualise multi-dimensional concepts in consumer research. It does this, while heightening the important complementary role of traditional research methods in the era of more prevalent machine learning and big data analytics. Practically, this thesis informs restaurants and other service-based businesses how to identify and segment their consumers based on their assessments and expectations of authenticity, as well as what constitutes authenticity in dining experiences, and the interaction of restaurant attributes in constructing authentic dining experiences.