scholarly journals The Tourism Destination Image Perception of Guizhou Ethnic Village Based on Online Reviews

2019 ◽  
Author(s):  
Jianchun Yang ◽  
Jialian Wang
Keyword(s):  
Online Reviews ◽  
Destination Image ◽  
Tourism Destination ◽  
Image Perception

Image perception of surf tourism destination in Brazil

2019 ◽  
Vol 6 (4) ◽  
pp. 1111-1127
Author(s):  
Sabrina da Rosa ◽  
Francisco Antonio dos Anjos ◽  
Melise de Lima Pereira ◽  
Marcos Arnhold Junior
Keyword(s):  
Factor Analysis ◽  
Data Analysis ◽  
Destination Image ◽  
Equation Modeling ◽  
Multivariate Techniques ◽  
Tourism Destination ◽  
Image Perception ◽  
Public And Private ◽  
Content Type ◽  
Measurement Models

Purpose The purpose of this paper is to measure the image of surf tourism destination, Praia do Rosa, Santa Catarina, Brazil, in order to examine the complex relationship between destination image components and surfers’ behavior in relation to surfing itself and to the trips made to take part in surfing activities, in a surf spot. Design/methodology/approach From the tourist population in Praia do Rosa surf spot, in Brazil, a sample of 200 surfers was taken. Data analysis included the following multivariate techniques: exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling as a procedure for the development and reliability of the measurement models of destination image of surf tourism in Brazil. Data analysis was performed using PASW-SPSS 24 and Mplus 7. Findings Through EFA and CFA, it was possible to identify the attributes that make up the image of a surf destination and their relationship with the behavior profile of surfers. The results highlight the role of the different factors that make up the overall image of the destination, through the analysis of cognitive, affective and conative components. Research limitations/implications The results confirm and provide theoretical and empirical support for the research, showing that the set of observable variables and the specified latent dimensions are reliable. However, it is necessary to expand the sample studied so that the measurement model has better fit indices and show convergent and discriminant validity. Practical implications This study is relevant as it provides information that can be used by destination managers, especially regarding surf tourism. In the face of strong growth, the sector could benefit from the identification of destination image attributes which can be used in marketing campaigns put forward by both the public and private sector. Social implications The results of the current study provide both public and private tourism managers with insights into surf tourism demand useful in developing effective marketing and positioning strategies. Originality/value This study explored and tested the image perception in a surf destination. The results contribute theoretically and empirically to discussions about the components of destination image. Also, the findings add to the understanding of surfing behavior, one of the most popular sports in the world, with surfers willing to travel long distances in search of ideal surf conditions.

scholarly journals Research on image perception of Guilin tourism destination based on network text analysis

2019 ◽  
Vol 118 ◽  
pp. 03019
Author(s):  
Rongfang Liang ◽  
Shengfeng Luo
Keyword(s):  
Service Level ◽  
Destination Image ◽  
Analysis Method ◽  
Tourism Destination ◽  
Image Perception ◽  
Network Text Analysis ◽  
Content Analysis Method ◽  
Tourism Image ◽  
Information Characteristics ◽  
Marketing Methods

This article taking the travel notes of the ant mafengwo.com and Ctrip.com as a sample, using the content analysis method and ROST CM6 to analyze the visitors’ perception of the Guilin tourism destination image, through the analysis of the high-frequency vocabulary and the semantics of the network notes, and the spindle coding, From eight categories of humanistic attraction, natural attraction, tourism transportation, special food, accommodation conditions, overall impression, tourism consumption and service level, It is found that the tourists’ perception of Guilin tends to be positive. The basic information characteristics, cognitive image, emotional image and willingness to travel are comprehensively explored. The image of Guilin is proposed from the improvement of hardware elements, the innovation of tourism image marketing methods and the improvement of software image elements.

Cross-nationality importance performance analysis of Middle East all-inclusive mass tourism destination image

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Demet Ceylan ◽  
Beykan Cizel ◽  
Hatice Karakas
Keyword(s):  
Performance Analysis ◽  
Correlation Coefficients ◽  
Destination Image ◽  
Tourism Destination ◽  
Image Perception ◽  
Content Type ◽  
Mean Values ◽  
Mass Tourism ◽  
New Perspective ◽  
And Performance

PurposeThe paper aims to analyze cognitive attributes affecting the overall destination image perception of British, German and Russian tourists toward Antalya, a well-positioned mass tourism destination in the East Mediterranean region dominated by an all-inclusive (AI) system.Design/methodology/approachThe paper is an empirical study using a structured questionnaire conducted in the summer of 2018 with 274 British, 179 German and 231 Russian tourists departing to their respective source markets from Antalya International Airport. The mean values are used as performance and correlation coefficients of the relationship between each cognitive image dimension and overall image evaluation is used to express importance.FindingsThe paper provides empirical insights that these three nationalities prefer Antalya as an AI holiday destination for different reasons and that each nationality demands attention to different factors of the destination for improvement or preservation.Research limitations/implicationsThis study provides specific recommendations for AI destinations such as Antalya for the German, British and Russian source markets. When other source markets or types of destinations are considered, the findings of this study should be re-considered. Utilization of the original and modernized importance performance analysis (IPA) plot interpretations in this research reveals a deeper understanding of current findings and provides a new perspective for further research and guidance for destination managers and marketers.Practical implicationsUtilization of both original and modernized IPA plot interpretation in this research not only reveals a deeper understanding of current findings but also provides a new perspective for future studies and guidance for destination managers and marketers.Originality/valueUnlike the majority of destination image research, this study of destination image based on individual nationalities enables tailor-made destination image development according to diversified importance and performance of destination attributes affecting the overall destination image for each nationality.

Tracking Tourism Destination Image Perception

2009 ◽  
Vol 36 (4) ◽  
pp. 715-718 ◽  
Author(s):  
Samuel Seongseop Kim ◽  
Bob McKercher ◽  
Hyerin Lee
Keyword(s):  
Destination Image ◽  
Tourism Destination ◽  
Image Perception

scholarly journals Urban Tourism Destination Image Perception Based on LDA Integrating Social Network and Emotion Analysis: The Example of Wuhan

2021 ◽  
Vol 14 (1) ◽  
pp. 12
Author(s):  
Xu Chen ◽  
Jun Li ◽  
Wenxin Han ◽  
Shudong Liu
Keyword(s):  
Social Network ◽  
Urban Tourism ◽  
Destination Image ◽  
City Image ◽  
Tourism Destination ◽  
Image Perception ◽  
Emotion Analysis ◽  
The Sustainable Development ◽  
The Social ◽  
Tourism Image

Tourism destination image perception aims to depict the urban tourism image from the perspective of the perception of tourists, which, therefore, sheds new light on the advancement and innovation of urban tourism. The model proposed in this study can effectively describe the image perception of a tourism destination, with its research conclusions providing a vital referential basis for the sustainable development of urban tourism. Combined with LDA, we construct the research framework of tourism destination image perception and then take the online comments of popular scenic spots in Wuhan on Ctrip Travel as an example. The results show that four aspects are included in tourists’ perception of the city image of Wuhan: experience, history culture, leisure service, and tourist destination. Among them, the social network of the experience dimension is most closely related. In addition, emotion analysis illustrates that tourists’ emotional tendencies tend to be positive under the four perceptual dimensions.

Exploring destination image through online reviews: an augmented mining model using latent Dirichlet allocation combined with probabilistic hesitant fuzzy algorithm

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuyan Luo ◽  
Tao Tong ◽  
Xiaoxu Zhang ◽  
Zheng Yang ◽  
Ling Li
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Small Sample ◽  
Destination Image ◽  
Tourism Destination ◽  
Fuzzy Algorithm ◽  
Content Type ◽  
Dirichlet Allocation

PurposeIn the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for tourists and scenic-area managers. The study aims to help scenic-area managers determine the strengths and weaknesses in the development process of scenic areas and to solve the practical problem of tourists' difficulty in quickly and accurately obtaining the destination image of a scenic area and finding a scenic area that meets their needs.Design/methodology/approachThe study uses a variety of machine learning methods, namely, the latent Dirichlet allocation (LDA) theme extraction model, term frequency-inverse document frequency (TF-IDF) weighting method and sentiment analysis. This work also incorporates probabilistic hesitant fuzzy algorithm (PHFA) in multi-attribute decision-making to form an enhanced tourism destination image mining and analysis model based on visitor expression information. The model is intended to help managers and visitors identify the strengths and weaknesses in the development of scenic areas. Jiuzhaigou is used as an example for empirical analysis.FindingsIn the study, a complete model for the mining analysis of tourism destination image was constructed, and 24,222 online reviews on Jiuzhaigou, China were analyzed in text. The results revealed a total of 10 attributes and 100 attribute elements. From the identified attributes, three negative attributes were identified, namely, crowdedness, tourism cost and accommodation environment. The study provides suggestions for tourists to select attractions and offers recommendations and improvement measures for Jiuzhaigou in terms of crowd control and post-disaster reconstruction.Originality/valuePrevious research in this area has used small sample data for qualitative analysis. Thus, the current study fills this gap in the literature by proposing a machine learning method that incorporates PHFA through the combination of the ideas of management and multi-attribute decision theory. In addition, the study considers visitors' emotions and thematic preferences from the perspective of their expressed information, based on which the tourism destination image is analyzed. Optimization strategies are provided to help managers of scenic spots in their decision-making.

Revisiting Tourism Destination Image: A Holistic Measurement Framework Using Big Data

2021 ◽  
pp. 004728752110247
Author(s):  
Vinh Bui ◽  
Ali Reza Alaei ◽  
Huy Quan Vu ◽  
Gang Li ◽  
Rob Law
Keyword(s):  
Large Scale ◽  
Structural Model ◽  
Destination Image ◽  
Tourism Destination ◽  
Computational Framework ◽  
Four Dimensions ◽  
Tourism Management ◽  
Measurement Framework ◽  
Compare And Contrast

Understanding and being able to measure, analyze, compare, and contrast the image of a tourism destination, also known as tourism destination image (TDI), is critical in tourism management and destination marketing. Although various methodologies have been developed, a consistent, reliable, and scalable method for measuring TDI is still unavailable. This study aims to address the challenge by proposing a framework for a holistic measure of TDI in four dimensions, including popularity, sentiment, time, and location. A structural model for TDI measurement that covers various aspects of a tourism destination is developed. TDI is then measured by a comprehensive computational framework that can analyze complex textual and visual data on a large scale. A case study using more than 30,000 images, and 10,000 comments in relation to three tourism destinations in Australia demonstrates the effectiveness of the proposed framework.

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