Can we trace back hotel online reviews’ characteristics using gamification features?

Gamification is here to stay, and tourism and hospitality online review platforms are taking advantage of it to attract travelers and motivate them to contribute to their websites. Yet, literature in tourism is scarce in studying how effectively is users’ behavior changing through gamification features. This research aims at filling such gap through a data-driven approach based on a large volume of online reviews (a total of 67,685) collected from TripAdvisor between 2016 and 2017. Four artificial neural networks were trained to model title and review's word length, and title and review's sentiment score, using as input 12 gamification features used in TripAdvisor including points and badges. After validating the accuracy of the model for extracting knowledge, the data-based sensitivity analysis was applied to understand how each of the 12 features contributed to explaining review length and its sentiment score. Three badge features were considered the most relevant ones, including the total number of badges, the passport badges, and the explorer badges, providing evidence of a relation between gamification features and traveler's behavior when writing reviews.info:eu-repo/semantics/acceptedVersio

Unfolding the drivers for sentiments generated by Airbnb experiences

Purpose Airbnb Experiences is a new type of service launched by Airbnb in November 2016 where users can offer travellers a wide range of activities. This study devotes attention to analysing customer feedback expressed in online reviews published in Airbnb to evaluate those experiences. Design/methodology/approach A total of 1,110 reviews were collected from twelve categories, including 111 experiences, thus ten reviews per experience. First, the sentiment score was computed based on the text of the reviews. Second, seventeen quantitative features encompassing user, experience, and review information were used to model the score through a support vector machine. Third, a sensitivity analysis was performed to extract knowledge on the most relevant features influencing the sentiment score. Findings Touristswriting online reviews are not only influenced by their tourist experience, but also by their own online experience with the booking and online review platform. The number of reviews made by the user accounted for more than 20% of relevance, while users with more reviews tend to grant more positive reviews. Originality/value Current literature is enhanced with a conceptual model grounded on existing studies that assess tourist satisfaction with tour services. Both services online visibility and user characteristics have shown significant importance to tourist satisfaction, adding to the existing body of knowledge.info:eu-repo/semantics/acceptedVersio

Are the States United? An analysis of US hotels’ offers through TripAdvisor’s eyes

This empirical data-driven research aims to unveil thought-provoking insights on the U.S. hotel offer across its 50 states. Information of more than 30,000 hotels was collected through web scraping from TripAdvisor. Using such data, 50 support vector machine models were trained to model the TripAdvisor score, one per state, to assess the convergent and divergent factors in customer satisfaction across all the U.S. states. A conceptual model is proposed and validated through the data-driven support vector machine models developed for each state to identify convergent features across the states to explain customer satisfaction (here represented by TripAdvisor score). Hotel size, price, and stars are not moderated by the location, expressed by the corresponding state, although these highly influence satisfaction, whereas both hotel number of published photos and the amenities are affected by the location. Thus, adaptation issues were found regarding amenities and published photos within each state’s offer.info:eu-repo/semantics/acceptedVersio

Analysing recent augmented and virtual reality developments in tourism

Purpose Virtual reality (VR) and augmented reality (AR) are two technological breakthroughs that stimulate reality perception. Both have been applied in tourism contexts to improve tourists’ experience. This paper aims to frame both AR and VR developments during the past 15 years from a scientific perspective. Design/methodology/approach This study adopts a text mining and topic modelling approach to analyse a total of 1,049 articles for VR and 406 for AR. The papers were selected from Scopus, with the title, abstract and keywords being extracted for the analysis. Formulated research hypotheses based on relevant publications are then evaluated to assess the current state of the broader scope of the large sets of literature. Findings Most of research using AR is based on mobile technology. Yet, wearable devices still show few publications, a gap that is expected to close in the near future. There is a lack of research adopting Big Data/machine learning approaches based on secondary data. Originality/value As both AR and VR technologies are becoming more mature, more applications to tourism emerge. Scholars need to keep pace and fill in the research gaps on both domains to move research forward.info:eu-repo/semantics/acceptedVersio

The role of badges to spur frequent travelers to write online reviews

Purpose: Online travel reviews platforms have become innovative information systems also due to the incorporation of sophisticated gamification elements such as visually appealing badges. This study aims to analyze three features of the review after leveling up a badge: review length (number of words), sentiment scoring, and period between two successive reviews (number of days until the next review is written). Design/methodology/approach: A total of 77k online TripAdvisor reviews written by 100 frequent travelers and contributors are analyzed using a data mining approach. A data-based sensitivity analysis (DSA) is then conducted to provide an understanding of the data mining trained models. Findings: The results show evidence that badges appealing for self-pride (“badge passport”) and for peer-recognition (“badge helpful”) have significant influence across the lifespan of online review, whereas badges simply awarded by counting the contributions have little effect. Originality: This study provides the first analysis of how an experienced traveler is influenced as the badges and points are being awarded. Intrinsic motivational factor to award badges for standard contributions scarcely influence user behavior. Badges need to be designed to reward accomplishments that are not so trivial to be achieved and that do not depend entirely on the user.info:eu-repo/semantics/acceptedVersio

The impact of the COVID-19 on the airline industry emerging from online comments

The aim of this research is to evaluate how the novel Coronavirus impact on the airline industry is reflected on the affected travelers’ concerns expressed in the comments they write online. In this study, a sample of 639 comments related to the airline industry, written on the website of the Italian National Consumer Union, has been assessed through an automated sentiment analysis. The achieved results showed that travelers’ attention was directed mainly towards compensations, cancellations, and COVID-19 and at the same time they had mixed and unpredictable feelings. This suggests that consumers may understood that airline companies are facing unsustainable cash-flow and revenue situations. Moreover, all the hypotheses, grounded on the existing literature were refuted. Accordingly, we argue that the actual context prevents assessments based on previous assumptions and studies related to the impact of COVID-19 need to be conducted anew.O objetivo deste estudo é avaliar como o impacto do novo Coronavírus no setor aéreo se reflete nas preocupações dos viajantes afetados através dos comentários que eles escrevem on-line. Neste estudo, uma amostra de 639 comentários relacionados com o setor aéreo, escritos no website da União Nacional dos Consumidores da Itália, foi avaliada através de uma análise de sentimentos automática. Os resultados alcançados mostraram que a atenção dos viajantes foi sobretudo focada nas compensações, cancelamentos e COVID-19 sendo que, ao mesmo tempo, os sentimentos revelados eram confusos e imprevisíveis. Tal sugere que os consumidores podem ter de certa maneira aceite que as empresas aéreas estão a enfrentar situações insustentáveis de tesouraria e receita. Adicionalmente, todas as hipóteses, baseadas na literatura existente, foram refutadas. Assim, argumentamos que o contexto real impedem análises baseadas em assunções anteriores, sendo que é necessário desenvolver de raiz estudos relacionados com o impacto da COVID-19

Evaluating a guest satisfaction model through data mining

Purpose: This paper aims to propose a data mining approach to evaluate a conceptual model in tourism, encompassing a large data set characterized by dimensions grounded on existing literature. Design/methodology/approach: The approach is tested using a guest satisfaction model encompassing nine dimensions. A large data set of 84 k online reviews and 31 features was collected from TripAdvisor. The review score granted was considered a proxy of guest satisfaction and was defined as the target feature to model. A sequence of data understanding and preparation tasks led to a tuned set of 60k reviews and 29 input features which were used for training the data mining model. Finally, the data-based sensitivity analysis was adopted to understand which dimensions most influence guest satisfaction. Findings: Previous user’s experience with the online platform, individual preferences, and hotel prestige were the most relevant dimensions concerning guests’ satisfaction. On the opposite, homogeneous characteristics among the Las Vegas hotels such as the hotel size were found of little relevance to satisfaction. Originality/value: This study intends to set a baseline for an easier adoption of data mining to evaluate conceptual models through a scalable approach, helping to bridge between theory and practice, especially relevant when dealing with Big Data sources such as the social media. Thus, the steps undertaken during the study are detailed to facilitate replication to other models.info:eu-repo/semantics/acceptedVersio

An Analysis on the Formation and Cultivation of Environmental Protection Norms in the Context of Green Gamification

Currently, individual green behaviors have attracted great attention from many countries for environmental degradation. It is particularly critical to identify useful strategies to motivate users’ green behaviors. Based on the goal framing theory, this paper considers three target motivations (hedonic goal, gain goal, and normative goal) of users’ behaviors, proposes the formation and cultivation mechanics of green behaviors in the green gamification platform, and builds a model considering the process of users’ engagement. By comparing users’ quality situation (high, general, low), this paper concludes that a lower involvement degree is required by high-quality individuals when forming and cultivating an environmental behavior habit. The result also benefits organizations that apply gamification designs in varieties of ways to engage and steer users like employees or consumers toward targeted goals

Using sentiment analysis in tourism research: A systematic, bibliometric, and integrative review

Purpose: Sentiment analysis is built from the information provided through text (reviews) to help understand the social sentiment toward their brand, product, or service. The main purpose of this paper is to draw an overview of the topics and the use of the sentiment analysis approach in tourism research. Methods: The study is a bibliometric analysis (VOSviewer), with a systematic and integrative review. The search occurred in March 2021 (Scopus) applying the search terms "sentiment analysis" and "tourism" in the title, abstract, or keywords, resulting in a final sample of 111 papers. Results: This analysis pointed out that China (35) and the United States (24) are the leading countries studying sentiment analysis with tourism. The first paper using sentiment analysis was published in 2012; there is a growing interest in this topic, presenting qualitative and quantitative approaches. The main results present four clusters to understand this subject. Cluster 1 discusses sentiment analysis and its application in tourism research, searching how online reviews can impact decision-making. Cluster 2 examines the resources used to make sentiment analysis, such as social media. Cluster 3 argues about methodological approaches in sentiment analysis and tourism, such as deep learning and sentiment classification, to understand the user-generated content. Cluster 4 highlights questions relating to the internet and tourism. Implications: The use of sentiment analysis in tourism research shows that government and entrepreneurship can draw and enhance communication strategies, reduce cost, and time, and mainly contribute to the decision-making process and understand consumer behavior

Gamification for Brand Value Co-Creation:A Systematic Literature Review

Gamification, commonly defined as the use of game elements in non-game contexts, is a relatively novel term, yet it has been gaining popularity across a wide range of academic and industrial disciplines. In the marketing field, companies are increasingly gamifying their mobile apps and online platforms to enrich their customers’ digital experiences. Whilst there has been a number of systematic studies examining the influence of gamification on user engagement across different fields, none has reviewed its role in brand value co-creation. Following a systematic literature review procedure via the online research platform EBSCOhost, this paper is the first to survey a set of empirical studies examining the role and impact of gamification on brand value co-creation. A final pool of 32 empirical studies implies the existence of four types of activities that are co-created by online users and positively influenced by gamification, namely: customer service, insights sharing, word-of-mouth, and random task. Moreover, this paper highlights the major game dynamics driving these activities, the key findings of each of the covered studies and their main theoretical underpinnings. Lastly, a set of noteworthy research directions for future related studies are suggested, comprising the exploration of novel game elements, and new co-creation activities related to corporate social responsibilities and physical commercial operations