scholarly journals Measuring Gastronomic Image Online

2019 ◽  
Vol 16 (23) ◽  
pp. 4631 ◽  
Author(s):  
Estela Marine-Roig ◽  
Berta Ferrer-Rosell ◽  
Natalia Daries ◽  
Eduard Cristobal-Fransi
Keyword(s):  
Big Data ◽  
Content Analysis ◽  
Business Intelligence ◽  
Cultural Tourism ◽  
Destination Image ◽  
User Generated Content ◽  
Thematic Content Analysis ◽  
Image Identity ◽  
Online Travel Reviews ◽  
Online Travel

Culinary or gastronomic tourism has become one of the main exponents of cultural tourism and a key element of a destination’s image identity. Since travellers consult and produce online travel reviews (OTR) before and during a trip, this research aims to provide and implement a framework for analysing OTRs of dining establishments to measure their contribution to destination image formation in their designative (cognitive) and appraisive (affective and evaluative) aspects. To do this, a website was selected from which to download OTRs, extract useful information from the textual and paratextual elements, build a keyword frequency matrix, and perform a quantitative and thematic content analysis. This method was applied to a random sample of 500,000 OTRs from the TripAdvisor restaurants section, written in English, between 2013 and 2017, by tourists visiting the Canary Islands. Results show that, although the gastronomic image of the destination is positive in general, the local and regional gastronomy representative of the community’s sociocultural identity is not the most popular nor the best valued in tourists’ comments. This research shows a method to measure the main aspects that make up the gastronomic image of a destination and that allow for extracting insights and business intelligence through big data from user-generated content.

scholarly journals A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 4720
Author(s):  
Tao Liu ◽  
Ying Zhang ◽  
Huan Zhang ◽  
Xiping Yang
Keyword(s):  
Big Data ◽  
Travel Behavior ◽  
Yunnan Province ◽  
Movement Patterns ◽  
User Generated Content ◽  
Great Opportunity ◽  
Tourist Destinations ◽  
Online Travel Reviews ◽  
Online Travel

Insights into the association rules of destinations can help to understand the possibility of tourists visiting a destination after having traveled from another. These insights are crucial for tourism industries to exploit strategies and travel products and offer improved services. Recently, tourism-related, user-generated content (UGC) big data have provided a great opportunity to investigate the travel behavior of tourists on an unparalleled scale. However, existing analyses of the association of destinations or attractions mainly depend on geo-tagged UGC, and only a few have utilized unstructured textual UGC (e.g., online travel reviews) to understand tourist movement patterns. In this study, we derive the association of destinations from online textual travel reviews. A workflow, which includes collecting data from travel service websites, extracting destination sequences from travel reviews, and identifying the frequent association of destinations, is developed to achieve the goal. A case study of Yunnan Province, China is implemented to verify the proposed workflow. The results show that the popular destinations and association of destinations could be identified in Yunnan, demonstrating that unstructured textual online travel reviews can be used to investigate the frequent movement patterns of tourists. Tourism managers can use the findings to optimize travel products and promote destination management.

Projected Versus Perceived Destination Image

2020 ◽  
Vol 25 (2) ◽  
pp. 227-237 ◽  
Author(s):  
Berta Ferrer-Rosell ◽  
Estela Marine-Roig
Keyword(s):  
Content Analysis ◽  
Compositional Analysis ◽  
Destination Image ◽  
Destination Marketing ◽  
Or Management ◽  
Projected Image ◽  
Quantitative Content ◽  
Online Travel Reviews ◽  
Image Component ◽  
Online Travel

Due to the spectacular growth of traveler-generated content (TGC), researchers are using TGC as a source of data to analyze the image of destinations as perceived by tourists. In order to analyze a destination's projected image, researchers typically look to websites from destination marketing or management organizations (DMOs). The objective of this study is to calculate the gap between the projected and perceived images of Barcelona, Catalonia, in 2017, using Gartner's classification and applying compositional analysis. The official online press dossier is used as an induced source, the Lonely Planet guidebook as an autonomous source, and a collection of more than 70,000 online travel reviews hosted on TripAdvisor as an organic source. In addition to quantitative content analysis, this study undertakes two thematic analyses: the masterworks of architect Gaudi recognized as UNESCO WHS as part of the cognitive image component and feeling-related keywords as part of the affective image component. The results reveal strong differences between the induced and organic sources, but much smaller differences between the autonomous and organic sources. These results can be useful for DMOs to optimize promotion and supply.

An Evaluation of Toronto's Destination Image Through Tourist Generated Content on Twitter

2020 ◽  
Vol 11 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Hillary Clarke ◽  
Ahmed Hassanien
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Data Analysis ◽  
Information Exchange ◽  
Destination Image ◽  
User Generated Content ◽  
Cognitive Component ◽  
Research Outcomes ◽  
Textual Content ◽  
Insight Into

This study aims at evaluating the cognitive, affective, and conative components of destination image from the perception of tourists on social media. The netnography technique is used for data analysis and interpretation. Through a textual content analysis approach, an interpretation of meaning of content produced from tweets by tourists is conducted. The findings show that destination attractions were the most commented on component of the cognitive component. Throughout the travelling process, tourists assessed the affective destination image. It was found that tourists' evaluation was of favourable emotions towards Toronto as a destination. The conative component was assessed before, during, and after visiting Toronto. Tourists provided insight into their behaviour online through personal updates and information sharing. The research outcomes provide scholars and practitioners with greater insight into the dimensions of destination image formed by user-generated content from tourists and their usefulness for information exchange in various settings.

scholarly journals Destination Image Analytics through Traveller-Generated Content

2019 ◽  
Vol 11 (12) ◽  
pp. 3392 ◽  
Author(s):  
Marine-Roig
Keyword(s):  
Social Media ◽  
Mobile Devices ◽  
Random Sample ◽  
Paradigm Shift ◽  
Destination Image ◽  
Methodological Framework ◽  
Demand Side ◽  
Tourist Destination ◽  
Online Travel Reviews ◽  
Online Travel

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.

Destination Image Recognition And Emotion Analysis: Evidence From User-Generated Content Of Online Travel Communities

2020 ◽  
Author(s):  
Weidong Huang ◽  
Shuting Zhu ◽  
Xinkai Yao
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Empirical Analysis ◽  
Image Recognition ◽  
Emotional Experience ◽  
Destination Image ◽  
User Generated Content ◽  
Community Data ◽  
Online Travel ◽  
Tourism Community

Abstract The tourism destination image is an intangible value that enhances the internal and external spiritual value of the region. To improve tourist experiences and provide reference for relevant departments, we applied the GooSeeker web data crawler tool and Python data mining kit to crawl and analyze the representative online tourism community data. We conduct an empirical analysis through data from the online tourist community ‘mafengwo’. The result, based on the user-generated content data analysis of online travel community, shows that the tourists' perception of the destination image, cognitive theme and emotional experience has different effects on the tourist experience. This research offers insights into destination image cognitive theme and traveler behavior habits, which can provide guidance for platform and destination managers.

scholarly journals Measuring Online Destination Image, Satisfaction, and Loyalty: Evidence from Barcelona Districts

2021 ◽  
Vol 2 (1) ◽  
pp. 62-78
Author(s):  
Estela Marine-Roig
Keyword(s):  
Big Data Analytics ◽  
Destination Image ◽  
Tourist Satisfaction ◽  
One Step ◽  
Data Source ◽  
Positive Feelings ◽  
Online Travel Reviews ◽  
Online Travel ◽  
The Impact ◽  
The Relationship

The relationships between destination image and tourist satisfaction and loyalty have been studied extensively through surveys. This study aims to measure these constructs through big data analytics by going one step further in a line of research undertaken 8 years ago. The data source is content generated by travelers and shared on social media regarding the 10 districts of the city of Barcelona (Catalonia): more than 750,000 online travel reviews (OTRs) hosted on the Airbnb platform. This study also explores a relationship demonstrated by numerous researchers through surveys: the impact of destination image on tourist loyalty through satisfaction. However, the results are not satisfactory due to the great weight of the lodging price variable that unbalances the relationship. For example, the first district in the ranking of cognitive image categories is also the first in the ranking of average scores and of positive feelings and moods. However, the last two districts in the ranking of cognitive categories are the first in the rankings of satisfaction, positive recommendations, and cheaper prices. Additionally, the findings show that the location of the accommodation significantly determines the theme of the OTR narrative. Moreover, the results confirm previous studies on the exaggerated positivity of peer-to-peer accommodation scores: only 0.92% of 15,625 rated properties had negative overall scores.

scholarly journals Comparing online travel review platforms as destination image information agents

2021 ◽  
Author(s):  
Xinxin Guo ◽  
Juho Pesonen ◽  
Raija Komppula
Keyword(s):  
Destination Image ◽  
Analysis Method ◽  
Important Data ◽  
Information Agents ◽  
Content Analysis Method ◽  
Managerial Implications ◽  
Data Source ◽  
Online Travel Reviews ◽  
Online Travel ◽  
Online Travel Review

AbstractOnline travel reviews have been extensively used as an important data source in tourism research. Typically, data for online travel review research is collected only from one platform. However, drawing definite conclusions based on single platform analyses may thus produce biases and lead to erroneous conclusions and decisions. Therefore, this research verifies whether or not there are discrepancies and commonalities between different travel review platforms. In this study, five native Chinese travel review platforms were selected: Ctrip; Qyer; Mafengwo; Tuniu; and Qunar. Using a mixed content analysis method, the destination image of Finland was extracted from 10,197 travel reviews in Simplified Chinese as the destination image is a popular topic in online review research. Results show Finland’s destination image representation varies between Chinese travel review platforms. This discrepancy is especially prominent in the dimension of functional and mixed functional-psychological destination attributes. Significant theoretical contributions and managerial implications for the analysis of online travel reviews and destination image research are discussed.

scholarly journals The image of Barcelona in Online Travel Reviews during 2017 Catalan independence process

2020 ◽  
Vol 33 (3) ◽  
pp. 33-49
Author(s):  
Natàlia Lozano-Monterrubio ◽  
Assumpció Huertas
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Brand Image ◽  
Negative Impact ◽  
Google Maps ◽  
Politics And Religion ◽  
Social Media Platforms ◽  
Online Travel Reviews ◽  
Destination Brand ◽  
Online Travel

Since the emergence of Online Travel Reviews (OTRs), the collective co-creation of a destination brand image has been more evident than ever before. Stories and emotions expressed in these platforms by experienced tourists can significantly influence other users’ intention to visit. This study explores the extent to which political matters like the incidents that occurred during the last quarter of 2017 related with the Catalan independence process may have a negative impact on the brand image of a destination. This paper has used a specific methodology for content analysis of social media in the field of tourism to study the worst rated OTRs (one-star) of seven different attractions of Barcelona in three social media platforms that are able to geolocate places (TripAdvisor, Google Maps and Facebook) to determine the nature, discourses and the emotions raised. Although most complaints refer to the intrinsic problems of the attractions like high entrance prices and long queues due to tourism overcrowding, results reveal that OTR platforms also include tourists’ personal opinions on such issues as politics and religion. The originality of this research paper is that it delves into users’ co-creation of destination brand image through the analysis of negative OTRs and the emotions expressed in their comments.

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