Tourism destination image based on tourism user generated content on internet

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jun Wang ◽  
Yunpeng Li ◽  
Bihu Wu ◽  
Yao Wang
Keyword(s):  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Three Dimensional ◽  
Transformation Model ◽  
Destination Image ◽  
User Generated Content ◽  
Tourism Destination ◽  
Methodological Innovation ◽  
Content Type ◽  
Social Sensing

Purpose The purpose of this paper is to study tourists’ spatial and psychological involvement reflected through tourism destination image (TDI), TDI is divided into on-site and after-trip groups and the two groups are compared in the frame of three-dimensional continuums. Design/methodology/approach By conducting latent Dirichlet allocation (LDA) modeling to tourism user-generated content, structural topic models are established. The topics separated out from unstructured raw texts are structural themes and representations of TDI. Social network analysis (SNA) reveals the quantitative and structural differences of three-dimensional continuums of the two TDI groups. Findings The findings reveal that from the stage of on-site to after-trip, tourist perception of TDI shifts from psychologically to functionally-oriented, from common to unique, and from holistic to more attribute focused. Also, it is suggested that from a postmodernism perspective, TDI is never unique, fixed or universal, but has different image perceptions and feedbacks for different tourists. Research limitations/implications With the assistance of social sensing, a panoramic view of TDI could be established. Targeted and precision destination marketing and image promotion could be applied out to each individual tourist. Originality/value Combining with the perspectives of the tourist-destination space system and the tourism involvement theory, this research proposes a TDI transformation model and an explanation of the internal mechanism. The originality of research also lies in the methodological innovation of social sensing data and the LDA topic model.

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.

Like, tag and share: bolstering social media marketing to improve intention to visit a nature-based tourism destination

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vanessa Gaffar ◽  
Benny Tjahjono ◽  
Taufik Abdullah ◽  
Vidi Sukmayadi
Keyword(s):  
Social Media ◽  
Structural Equation ◽  
Botanical Garden ◽  
Equation Model ◽  
Destination Image ◽  
Social Media Marketing ◽  
Tourism Destination ◽  
Content Type ◽  
Future Value ◽  
Tourism Destinations

Purpose This paper aims to explore the influence of social media marketing on tourists’ intention to visit a botanical garden, which is one of the popular nature-based tourism destinations in Indonesia. Design/methodology/approach This study sent questionnaires to 400 followers of the botanical garden’s Facebook account who responded to the initial calls for participation and declared that they have not visited the garden before. Analyses were conducted on 363 valid responses using the structural equation model. Findings The findings revealed several key determinants influencing the image of the botanical garden and its future value proposition, particularly in supporting the endeavour to shift from a mere recreational destination to a nature-based tourism destination offering educational experiences. Originality/value This paper offers a fresh look into the roles of social media marketing in increasing the intention to visit a tourism destination that is considerably affected by the destination image.

Destination image through social media analytics and survey method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael S. Lin ◽  
Yun Liang ◽  
Joanne X. Xue ◽  
Bing Pan ◽  
Ashley Schroeder
Keyword(s):  
Social Media ◽  
Survey Data ◽  
Destination Image ◽  
Social Media Analytics ◽  
Tourism Destination ◽  
Social Media Data ◽  
Content Type ◽  
Holistic Understanding ◽  
Intercept Survey ◽  
Media Data

Purpose Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the methodologies of SMA and intercept surveys would provide a more in-depth understanding of both methodologies and a more holistic understanding of TDI than each method on their own. This study aims to investigate the unique merits and biases of SMA and a traditional visitor intercept survey. Design/methodology/approach This study collected and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination image represented from both methods. Findings The results indicated that the survey data and social media data shared major similarities in the identified key image phrases. Social media data revealed more diverse and more specific aspects of the destination, whereas survey data provided more insights in specific local landmarks. Survey data also included additional subjective judgment and attachment towards the destination. Together, the data suggested that social media data should serve as an additional and complementary source of information to traditional survey data. Originality/value This study fills a research gap by comparing two methodologies in obtaining TDI: SMA and a traditional visitor intercept survey. Furthermore, within SMA, photo and metadata are compared to offer additional awareness of social media data’s underlying complexity. The results showed the limitations of text-based image questions in surveys. The findings provide meaningful insights for tourism marketers by having a more holistic understanding of TDI through multiple data sources.

A big data approach to examining social bots on Twitter

2019 ◽  
Vol 33 (4) ◽  
pp. 369-379 ◽  
Author(s):  
Xia Liu
Keyword(s):  
Big Data ◽  
Fixed Effects ◽  
Latent Dirichlet Allocation ◽  
User Generated Content ◽  
Fixed Effects Model ◽  
Data Set ◽  
Information Distortion ◽  
Content Type ◽  
Related Information ◽  
Brand Reputation

Purpose Social bots are prevalent on social media. Malicious bots can severely distort the true voices of customers. This paper aims to examine social bots in the context of big data of user-generated content. In particular, the author investigates the scope of information distortion for 24 brands across seven industries. Furthermore, the author studies the mechanisms that make social bots viral. Last, approaches to detecting and preventing malicious bots are recommended. Design/methodology/approach A Twitter data set of 29 million tweets was collected. Latent Dirichlet allocation and word cloud were used to visualize unstructured big data of textual content. Sentiment analysis was used to automatically classify 29 million tweets. A fixed-effects model was run on the final panel data. Findings The findings demonstrate that social bots significantly distort brand-related information across all industries and among all brands under study. Moreover, Twitter social bots are significantly more effective at spreading word of mouth. In addition, social bots use volumes and emotions as major effective mechanisms to influence and manipulate the spread of information about brands. Finally, the bot detection approaches are effective at identifying bots. Research limitations/implications As brand companies use social networks to monitor brand reputation and engage customers, it is critical for them to distinguish true consumer opinions from fake ones which are artificially created by social bots. Originality/value This is the first big data examination of social bots in the context of brand-related user-generated content.

The surveillance of a supreme audit institution on related party transactions

2020 ◽  
Vol 32 (4) ◽  
pp. 577-603
Author(s):  
Gustavo Cesário ◽  
Ricardo Lopes Cardoso ◽  
Renato Santos Aranha
Keyword(s):  
Public Sector ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Conflicts Of Interest ◽  
International Standards ◽  
Content Type ◽  
Related Party Transactions ◽  
The Public ◽  
Audit Reports ◽  
Dirichlet Allocation

PurposeThis paper aims to analyse how the supreme audit institution (SAI) monitors related party transactions (RPTs) in the Brazilian public sector. It considers definitions and disclosure policies of RPTs by international accounting and auditing standards and their evolution since 1980.Design/methodology/approachBased on archival research on international standards and using an interpretive approach, the authors investigated definitions and disclosure policies. Using a topic model based on latent Dirichlet allocation, the authors performed a content analysis on over 59,000 SAI decisions to assess how the SAI monitors RPTs.FindingsThe SAI investigates nepotism (a kind of RPT) and conflicts of interest up to eight times more frequently than related parties. Brazilian laws prevent nepotism and conflicts of interest, but not RPTs in general. Indeed, Brazilian public-sector accounting standards have not converged towards IPSAS 20, and ISSAI 1550 does not adjust auditing procedures to suit the public sector.Research limitations/implicationsThe SAI follows a legalistic auditing approach, indicating a need for regulation of related public-sector parties to improve surveillance. In addition to Brazil, other code law countries might face similar circumstances.Originality/valuePublic-sector RPTs are an under-investigated field, calling for attention by academics and standard-setters. Text mining and latent Dirichlet allocation, while mature techniques, are underexplored in accounting and auditing studies. Additionally, the Python script created to analyse the audit reports is available at Mendeley Data and may be used to perform similar analyses with minor adaptations.

Factors influencing the tourists’ intention to select sustainable tourism destination: a case study of Penang, Malaysia

2017 ◽  
Vol 3 (4) ◽  
pp. 442-465 ◽  
Author(s):  
Zurina Mohaidin ◽  
Koay Tze Wei ◽  
Mohsen Ali Murshid
Keyword(s):  
Service Quality ◽  
Word Of Mouth ◽  
Sustainable Tourism ◽  
Destination Image ◽  
Tourism Destination ◽  
Environmental Attitude ◽  
Tourist Destination ◽  
Content Type ◽  
Perceived Service Quality ◽  
The Relationship

Purpose The purpose of this paper is to examine the factors of environmental attitude, motivation, destination image, word-of-mouth, and perceived service quality to predict the tourists’ intention to select sustainable tourist destination. It also aims to investigate the moderating effect of knowledge on the relationship between environmental attitude and the tourists’ intention to select sustainable tourist destination. Design/methodology/approach Using survey design, 300 self-administrated questionnaires (both online/hard copy) were distributed to both local and international tourists at different tourism locations in Penang state in Malaysia. A total of 161 questionnaires were returned and analysed by using SPSS and smart PLS software. Findings The findings found that environmental attitude, motivation, and word-of-mouth significantly influenced the tourists’ intention to select sustainable tourism destination, while destination image and perceived service quality have not a significant influence in this study. Furthermore, this study proved that knowledge negatively moderates the positive effect of the environmental attitude on tourists’ intention to select sustainable tourism destination. Research limitations/implications The findings offer important managerial implications for managers of tourism destinations and decision makers in understanding what motivates influence tourists’ intention in selecting sustainable tourism destination. The research scope was limited to convenient sampling and one city (Penang). Thus, the results could not be generalised to all Malaysia or other countries. Originality/value This research contributes to extending knowledge in sustainable tourism destination in the context of emerging markets, especially Malaysia. Moreover, this study found a way to examine the relationship between the environmental attitude and tourists’ intention to select sustainable tourism destination.

Tourism service quality and destination loyalty – the mediating role of destination image from international tourists’ perspectives

2016 ◽  
Vol 71 (1) ◽  
pp. 18-44 ◽  
Author(s):  
Mamoun N. Akroush ◽  
Luai E. Jraisat ◽  
Dina J. Kurdieh ◽  
Ruba N. AL-Faouri ◽  
Laila T. Qatu
Keyword(s):  
Service Quality ◽  
Brand Image ◽  
Dead Sea ◽  
Destination Image ◽  
Tourism Destination ◽  
Content Type ◽  
Destination Loyalty ◽  
The Dead ◽  
Tourism Service ◽  
The Relationship

Purpose The purpose of this paper is to examine the relationship between tourism service quality and destination loyalty through investigating the mediation effect of destination image in the Dead Sea tourism destination, Jordan, from international tourists perspectives. The paper also investigates the tourism service quality dimensions from international tourists’ viewpoints. Design/methodology/approach A structured and self-administered survey was used targeting international tourists who were visiting the Dead Sea tourism destination, Jordan. The authors delivered 300 questionnaires to international tourists from which 237 were retained and valid for the analysis. A series of exploratory and confirmatory factor analyses were performed to assess the research constructs dimensions, unidimensionality, validity and composite reliability. Structural path analysis was also used to test the hypothesised relationships of the research model. Findings The empirical findings indicate that tourism service quality is, in fact, a four-dimensional (4D) construct as opposed to five as proposed by the original hypothesised model. The 4D model consists of four facets: assurance-responsiveness, tangible facilities-empathy, reliability and reliability-quality of directions. Also, the results indicate that brand image loaded onto two dimensions named as “physical environment” and “people characteristics”. The structural findings indicate that the four dimensions of tourism service quality have positively and significantly affected destination image. Further, brand image has positively and significantly affected destination loyalty. Finally, destination image fully mediates the relationship between tourism service quality and destination loyalty. Research limitations/implications This paper has examined only five dimensions of tourism service quality that affected destination loyalty directly and indirectly; meanwhile, other service quality dimensions such as technical quality may affect both destination image and destination loyalty. Further, destination image is the only mediator investigated in this paper. Other consumer-based brand equity factors such as brand salience my act as another mediator. Also, this paper investigated international tourists’ perspectives in the Dead Sea tourism destination only, which means that its generalisation to other tourism destinations is limited. Therefore, comparative studies inside and outside Jordan’s tourism destinations are potential areas of future research. Other limitations and future research areas are also outlined. Practical implications The paper highlights the strategic importance of brand image on the relationship between tourism service quality and destination loyalty. Tourism service quality acts as an antecedent to brand image and the later is essential to destination loyalty. In other words, brand image of the physical environment and people friendless and kindness are the critical linkage that create destination loyalty. Further, an integrated model of tourism service quality, destination image and destination loyalty is required by tourism organisations operating in the Dead Sea destination to win international tourists again. Originality/value This paper represents one of the very few attempts that investigate tourism service quality and destination loyalty through understanding the mediating role of brand image in the Dead Sea destination. Accordingly, it should shed more light into the strategic role of brand image dimensions and how they affect destination loyalty. Further, the paper is the first of its kind to investigate an integrated model of tourism service quality and destination loyalty from international tourist perspectives in Jordan. The main issue here is that tourism organisations operating in the Dead Sea tourism destination have now valuable empirical evidence concerning the drivers of destination loyalty in an integrated manner.

Evaluation of the image of a coastal tourism destination in Brazil

2017 ◽  
Vol 3 (4) ◽  
pp. 324-338 ◽  
Author(s):  
Francisco Antonio dos Anjos ◽  
Melise de Lima Pereira ◽  
Florença Fiedler Pichler Von Tennenberg
Keyword(s):  
Structural Equation ◽  
Equation Model ◽  
Destination Image ◽  
Coastal Tourism ◽  
Tourism Destination ◽  
Santa Catarina ◽  
Content Type ◽  
Confirmatory Factor ◽  
Convenience Sampling ◽  
The Relationship

Purpose In order to offer a theoretical and empirical contribution to the theme, the purpose of this paper is to assess the tourist image of the destination Balneário Camboriú, Santa Catarina, Brazil, from the tourists’ perspective. The authors specify the latent dimensions involved in the formation of the cognitive, affective, and conative image of coastal tourism destination, through which the authors can analyze and measure the construct. Design/methodology/approach The research is exploratory, descriptive, and predominantly quantitative. It uses non-probability convenience sampling, consisting of a sample of 425 tourists. Data collection were conducted in the studied destination during the summer season – 2015/2016. Findings Through exploratory and confirmatory factor analysis, the authors identified and tested the factors that comprise the image. Structural equation model evaluated the relationship that theoretically exists between the components of the image and the weight of the various components (cognitive, affective, and conative) on the overall image of the destination. Originality/value This research contributes theoretically and empirically to the discussions on the components of the destination image, in as much as it analyzes and interprets the cognitive, affective, and conative components of the image of the tourism destination Balneário Camboriú, Santa Catarina, Brazil.

Sign in / Sign up

Export Citation Format

Share Document