26,140 research outputs found

    Web 2.0 and destination marketing: current trends and future directions

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    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

    Destination image analytics through traveller-generated content

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    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

    Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceThis thesis aims to perform a holistic investigation concerning how Airbnb accommodation features and hosts’ attributes influence guest’s reviews and how are the main topics distributed. A dataset containing almost 4 million reviews from major touristic cities in the world (Milan, Lisbon, Amsterdam, Toronto, San-Francisco, and Sydney) was used for the text mining analysis to uncover the reviews’ social and market norms, as well as the guests’ sentiments and topics distribution. This research uses both Mallet LDA (Latent Dirichlet Allocation) and Word2Vec methods to unveil the semantic structure and similarity between data in this study. This approach will allow hospitality providers to understand the impact of underlying factors on reviewers’ opinions for further improvement of their services. Finally, this study develops a predictive unbiased model to forecast the review’s scores, with an accuracy of 90.70%

    Word of Mouth, the Importance of Reviews and Ratings in Tourism Marketing

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    The Internet and social media have given place to what is commonly known as the democratization of content and this phenomenon is changing the way that consumers and companies interact. Business strategies are shifting from influencing consumers directly and induce sales to mediating the influence that Internet users have on each other. A consumer review is “a mixture of fact and opinion, impression and sentiment, found and unfound tidbits, experiences, and even rumor” (Blackshaw & Nazarro, 2006). Consumers' comments are seen as honest and transparent, but it is their subjective perception what shapes the behavior of other potential consumers. With the emergence of the Internet, tourists search for information and reviews of destinations, hotels or services. Several studies have highlighted the great influence of online reputation through reviews and ratings and how it affects purchasing decisions by others (Schuckert, Liu, & Law, 2015). These reviews are seen as unbiased and trustworthy, and considered to reduce uncertainty and perceived risks (Gretzel & Yoo, 2008; Park & Nicolau, 2015). Before choosing a destination, tourists are likely to spend a significant amount of time searching for information including reviews of other tourists posted on the Internet. The average traveler browses 38 websites prior to purchasing vacation packages (Schaal, 2013), which may include tourism forums, online reviews in booking sites and other generic social media websites such as Facebook and Twitter.Peer reviewedFinal Accepted Versio

    Selling Rooms Online: The Use of Social Media and Online Travel Agents

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    Purpose – This paper aims to focus on the reason why hoteliers choose to be present in online travel agent (OTA) and social media web sites for sales purposes. It also investigates the technological and human factors related to these two practices. Design/methodology/approach – The research is based on a survey sent to a wide range of hotels in a Swiss touristic region. The empirical analysis involves the specification of two ordered logit models exploring the importance (in terms of online sales) of both social media and the online travel agent, Booking.com. Findings – Findings highlight the constant tension between visibility and online sales in the web arena, as well as a clear distinction in social media and OTA web site adoption between hospitality structures using online management tools and employing personnel with specific skills. Practical implications – The research highlights the need for the hospitality industry to maintain an effective presence on social media and OTAs in order to move towards the creation of a new form of social booking technologies to increase their visibility and sales. Originality/value – This research contributes to understanding the major role played by OTAs and social media in the hospitality industry while underlining the possibility of a major interplay between the two

    Improving the resident-tourist relationship in urban hotspots

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    High volumes of tourists often pose a threat to tourism and decrease the quality of life for local residents, particularly in attractive urban tourism places. Yet, to date only a few solution-oriented studies have attempted to alleviate the overtourism problems and to improve the resident-tourist relationship. This study aims to present potential solutions, based on data analytics. Combining venue-referenced social media data with topic modelling from a case study in Paris, this research reveals both similarities and differences in the temporal and spatial activity patterns of tourists and residents. Results offer strategic support to tourism planners on how to manage over-crowded urban tourism hotspots, which consequently facilitate the improvement of the resident-tourist relationship and improve destination attractiveness in the long run. Results further indicate that the exchange of social media-based information for residents and tourists are part of the practice-based solution for better sustainable tourism planning

    Referencial para a caracterização de websites de hotéis de acordo com as necessidades dos consumidores

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    Online presence is essential for tourism organisations, and the quality of websites can influence customers. In the case of hotels, there are many studies to evaluate website performance based on functionality, usability and other factors, much less on the amount of different information available to the consumer. In the near future by using Big Data it is expected that hotel websites will be dynamic, they will adapt themselves on-the-fly, showing personalized information to each consumer. Different consumers will have different websites (information? available) from the same hotel. This paper presents a framework for the characterisation of hotel websites, focusing on the amount of information available to the consumer in each website, which was applied in a case study during the last months of 2013 to the websites of five-star hotels that operate in the tourist region of the Algarve, Portugal. The framework allowed to identify a set of exhaustive indicators for hotel website characterisation, which were then grouped into ten fundamental information dimensions. These dimensions further fell into four dimension groups. Finally, it is presented and discussed quantitative and qualitative evaluations, that illustrates which indicators and dimensions are more often considered on hotel websites to satisfy the consumer?s information needs

    Electronic word of mouth in social media: The common characteristics of retweeted and favourited marketer-generated content posted on Twitter

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    Marketers desire to utilise electronic word of mouth (eWOM) marketing on social media sites. However, not all online content generated by marketers has the same effect on consumers; some of them are effective while others are not. This paper aims to examine different characteristics of marketer-generated content (MGC) that of which one lead users to eWOM. Twitter was chosen as one of the leading social media sites and a content analysis approach was employed to identify the common characteristics of retweeted and favourited tweets. 2,780 tweets from six companies (Booking, Hostelworld, Hotels, Lastminute, Laterooms and Priceline) operating in the tourism sector are analysed. Results indicate that the posts which contain pictures, hyperlinks, product or service information, direct answers to customers and brand centrality are more likely to be retweeted and favourited by users. The findings present the main eWOM drivers for MGC in social media.Abdulaziz Elwalda and Mohammed Alsagga

    How TripAdvisor’s reviewers level of expertise influence their online rating behaviour and the usefulness of reviews

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    The internet has improved the buying behaviour of customers. The development of technologies has led to the dissemination of opinions on social networks where customers buy goods and services. These comments on social networks started to be a part of the purchasing process. Until a few years ago, customers used to choose their itineraries based on tourist guides or brochures. Nowadays, customers’ reviews have changed the way a destination is portrayed, enhancing the description of a product or a service to a level that not even the supplier was able to reach before. There are different types of reviewers. The aim of this study is to identify both reviews, experts and non-expert reviewers and analyse the way they write their reviews. Reviews of five hotels taken from the TripAdvisor website were used in order to conduct this study. After analyzing a great set of variables, the results show that there is not much different on the amount of positive/negative reviews written by a reviewer, however, there is a difference in the deeper meaning of a review when it is positive than when it is negative. The expert reviewer tends to be more emotional when writing positive reviews than negative reviews. Regarding the usefulness of the reviews, there is no significant difference in usefulness of a review whether is an written by an expert reviewer or by a non-expert reviewer. The results also indicate that being an expert does not influence the rating a reviewer gives to a hotel stay either. The study was conducted by using Lexalytics program to analyze a Natural Language Processing (NLP) used to classify reviews according to their polarity. With this study, a new research in study was filled. This study gives insights on the polarity of a review depending on the type of reviewer. The results of this study are also important for hotel managers in order for them to understand the type of guest in house.O desenvolvimento da tecnologia, com ênfase na internet e nos seus desenvolvimentos ao longo dos anos, melhorou o comportamento dos clientes e levou à disseminação de opiniões em redes sociais onde os clientes compram productos e serviços. Os comentários feitos a um produto ou serviço nas redes sociais começaram a fazer parte do processo da compra. Até há uns anos atrás, os clientes escolhiam os itinerários para as suas viagens com base em guias turísticos e brochuras. Recentemente, os comentários de clientes mudaram a maneira que um destino é explicado e ilustrado, melhorando, desta forma, a descrição de um produto/serviço a um nível que nem mesmo os fornecedores destes tinham alcançado ainda. Há diferentes tipos de reviewers. O objectivo deste estudo é identificar ambos tipos, expert e non-expert e analisar o estilo de reviews escrita por estes. Experts são assim denominados se tiverem escrito mais de dez reviews; por outro lado os non-expert reviewers são assim denominados se tiverem escrito menos de 10 reviews. Para este estudo, foi utilizada informação de cinco hotéis de Orlando, Florida, retirada do TripAdvisor. Depois de uma análise das variáveis, os resultados mostram que não há grande diferença no que toca ao volume de comentários positivos/negativos escritos por um utilizador. Por outro lado, existe uma diferença na emoção dada a cada comentário, entre os utilizadores. O expert reviewer tende a ser mais emocional quando escreve comentários positivos do que quando escreve comentários negativos. Relativamente a utilidade de cada comentário, não há grande diferença no que toca a ser um expert reviewer ou um non-expert a escrever um comentário. Os resultados indicam, também, que ser um expert não tem qualquer influência na avaliação que um utilizador dá a sua estadia num hotel. Este estudo foi feito com base no programa Lexalytics, com objectivo de analisar a Natural Language Processing (NLP) usada para classificar os comentários de acordo com a sua polaridade
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