Destination image analytics through traveller-generated content

The explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users' opinions, because researchers can get this information freely on social media. In the field of tourism, online travel reviews (OTRs) hosted on travel-related websites stand out. The objective of this article is to demonstrate the usefulness of OTRs to analyse the image of a tourist destination. For this, a theoretical and methodological framework is defined, as well as metrics that allow for measuring different aspects (designative, appraisive and prescriptive) of the tourist image. The model is applied to the region of Attica (Greece) through a random sample of 300,000 TripAdvisor OTRs about attractions, activities, restaurants and hotels written in English between 2013 and 2018. The results show trends, preferences, assessments, and opinions from the demand side, which can be useful for destination managers in optimising the distribution of available resources and promoting sustainability

Web 2.0 and destination marketing: current trends and future directions

Over the last decade, destination marketers and Destination Marketing Organizations (DMOs) have increasingly invested in Web 2.0 technologies as a cost-effective means of promoting destinations online, in the face of drastic marketing budgets cuts. Recent scholarly and industry research has emphasized that Web 2.0 plays an increasing role in destination marketing. However, no comprehensive appraisal of this research area has been conducted so far. To address this gap, this study conducts a quantitative literature review to examine the extent to which Web 2.0 features in destination marketing research that was published until December 2019, by identifying research topics, gaps and future directions, and designing a theory-driven agenda for future research. The study’s findings indicate an increase in scholarly literature revolving around the adoption and use of Web 2.0 for destination marketing purposes. However, the emerging research field is fragmented in scope and displays several gaps. Most of the studies are descriptive in nature and a strong overarching conceptual framework that might help identify critical destination marketing problems linked to Web 2.0 technologies is missing

Understanding destination brand love using machine learning and content analysis method

This study aims to apply the concept of brand love in tourist destinations in order to identify the core-elements that could have influential impacts on generating destination brand love. This has been carried out by using a mixed-method of machine learning and content analysis. We have discovered that the topics have been generated for historical landmarks and destinations by analyzing the visitors’ on-line reviews are architecture, historical sites, tradition and shrine places, which could be similar to other tourist historical destinations in different part of the world. However, this study has the potential to be a model for other researches related to different destinations with possible different topics emerged. Our study contributes by providing both researchers and managers a novel method to understand what attributes of destination brand love they need to posit more emphasize to attract more visitors based on the destination type

A netnography study on branded customer experience: Evidence from the red sea

This study addresses the question of what are the underlying dimensions and messages to self and others that constitute the construct of customer experience. The study uses a netnography method to validate or refute and extend a priori concepts that the literature identifies within the context of resort-hotel brands in a Sharm El Sheikh resort in Egypt. The results identify eight dimensions (comfort, educational, hedonic, novelty, recognition, relational, safety and sense of beauty) and unique configurations of these eight dimensions that extend prior research on customer experience

Application of an opinion consensus aggregation model based on OWA operators to the recommendation of tourist sites

Given the growth in tourism online data as a result of a large number of users posting their personal opinions in social networks and other online platforms with the idea to help other visitants, many authors have proposed a huge variety of ways to classify the sentiments contained in these opinions in order to recommend services (hotels, restaurants, etc.) and destinations to the users with the intention of facilitating their trip planning. In this paper, the authors propose a model to rank tourist sites of a city, based on OWA operators, with the objective of being used as a recommender system.The authors would like to acknowledge the financial support from the EU project H2020-MSCA-IF-2016- DeciTrustNET-746398. This paper has been elaborated with the financing of FEDER funds in the Spanish National research project TIN2016-75850-R

A netnography study to uncover the underlying dimensions of customer experience with resort brands

The interest in customer experience has increased at a phenomenal rate. However, research to capture the true meaning of the concept is limited. This study aims to address the question of what are the underlying dimensions that constitute the construct of customer experience. The netnography method is utilized to validate a priori concepts that have been identified in the literature within the context of resort-hotel brands in a Sharm El Sheikh resort in Egypt. The results identified eight dimensions; comfort, educational, hedonic, novelty, recognition, relational, safety and sense of beauty which are consistent with major studies on experience

Exploring user-generated content for improving destination knowledge: the case of two world heritage cities

This study explores twoWorld Heritage Sites (WHS) as tourism destinations by applying several uncommon techniques in these settings: Smart Tourism Analytics, namely Text mining, Sentiment Analysis, and Market Basket Analysis, to highlight patterns according to attraction, nationality, and repeated visits. Salamanca (Spain) and Coimbra (Portugal) are analyzed and compared based on 8,638 online travel reviews (OTR), from TripAdvisor (2017–2018). Findings show that WHS reputation does not seem to be relevant to visitors-reviewers. Additionally, keyword extraction reveals that the reviews do not di er from language to language or from city to city, and it was also possible to identify several keywords related to history and heritage; in particular, architectural styles, names of kings, and places. The study identifies topics that could be used by destination management organizations to promote these cities, highlights the advantages of applying a data science approach, and confirms the rich information value of OTRs as a tool to (re)position the destination according to smart tourism design tenets.FCT: UIDB/04470/2020info:eu-repo/semantics/publishedVersio

Exploring the components of meal-sharing experiences with local foods: A netnography approach

This study aims to explore and ascertain the components of meal-sharing experiences with local foods of international travellers. This study offers insights into the factors influencing local food tourists’ evaluation of destination experiences of a sharing economy platform. A netnography approach is applied to understand the meal-sharing experience and 957 online reviews are examined which were posted on Eatwith by visitors who participated in the meal-sharing economy platform in Rome (Italy) between 2013 and 2020. Findings reveal seven components of meal-sharing experiences with local foods: authenticity, social interaction, local hospitality, awe, local culture, novelty, and servicescape. Findings show that participants can interpret their meal-sharing experience in different ways. To the authors’ knowledge, this is the first research that uses online reviews to explore and understand the meal-sharing experience with local foods. This study has unique theoretical contribution by exploring the components of meal-sharing experience with local foods, as well as practical implications for service providers in order to enhance their service and experience quality