Identification of Delighters and Frustrators in Vegan-friendly Restaurant Experiences via Semantic Network Analysis: Evidence from Online Reviews

Munhyang Oh, Frank Badu Baiden, Seongseop Kim, Joseph Lema

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

The purpose of this paper is to provide an understanding of vegan-friendly restaurant customers’ experiences by investigating the “delighters” and “frustrators” characteristics. A qualitative approach is used to examine the semantic networks of vegan-friendly restaurant customers’ online reviews. Results indicate that salient factors which delight vegan-friendly restaurant customers relate to the attributes of vegan food and menus, social interaction, and unique characteristics of a vegan-friendly restaurant. By contrast, factors that frustrate vegan-friendly restaurant customers associate with perceived overpriced vegan foods, poor restaurant staff attitudes/negative service encounters, and hygiene issues. The results of this study have academic and practical implications through the use of an attribute performance model to understand the experiences of vegan restaurant customers. This research is an initial empirical attempt to thoroughly understand vegan-friendly restaurant experiences using big data.

Original languageEnglish
JournalInternational Journal of Hospitality and Tourism Administration
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • delighters and frustrators
  • experience
  • online reviews
  • semantic network analysis
  • Vegan food
  • vegan-friendly restaurant

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management

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