An integrated model to explain online review helpfulness in hospitality

Purpose: This study aims to propose a model to explain online review helpfulness grounded on both previously identified constructs (e.g. review length) and new ones, which have been analyzed in other online reviews’ contexts but not to explain helpfulness. Design/methodology/approach: A total of 112,856 reviews published in TripAdvisor about 21 Las Vegas hotels were collected and a random forest model was trained to assess if a review has received a helpful vote or not. Findings: After confirming the validity of the proposed model, each of the constructs was evaluated to assess its contribution to explaining helpfulness. Specifically, a newly proposed construct, the response lag of the manager’s replies to reviews, was among the most relevant constructs. Originality/value: The achieved results suggest that hoteliers should invest not only in responding to the most interesting reviews from the hotel’s perspective but also that they should do it quickly to increase the likeliness of the review being considered helpful to others.info:eu-repo/semantics/acceptedVersio

A different shape grammar approach for automatic design generation

This paper proposes a different approach for shape grammars where designs are exclusively generated through computations of symbols. This option has the advantage of supporting declarative knowledge and thus facilitates shape reasoning capabilities. Our approach also detached procedural knowledge from shape knowledge using procedural notions that capture sequences, alternatives and tests that should be applied during design process. This decision provides good modular specifications. Moreover, we follow a non-deterministic procedural perspective in the characterization of design processes. Its implementation supports exploratory automatic design generation. Differences between this approach and the conventional approach are discussed and a case study is explored.info:eu-repo/semantics/publishedVersio

A different shape grammar approach for automatic design generation

This paper proposes a different approach for shape grammars where designs are exclusively generated through computations of symbols. This option has the advantage of supporting declarative knowledge and thus facilitates shape reasoning capabilities. Our approach also detached procedural knowledge from shape knowledge using procedural notions that capture sequences, alternatives and tests that should be applied during design process. This decision provides good modular specifications. Moreover, we follow a non-deterministic procedural perspective in the characterization of design processes. Its implementation supports exploratory automatic design generation. Differences between this approach and the conventional approach are discussed and a case study is explored.info:eu-repo/semantics/publishedVersio

Service quality in airport hotel chains through the lens of online reviewers

Airport hotel chains target the specific and important segment of accommodation near airports, thus benefiting from travelers seeking to stay near an airport. This study addresses service quality by analyzing TripAdvisor online reviews over units from both a high-end and a low-end chain in five European cities (Amsterdam, Brussels, Frankfurt, London, Paris). Using text mining and topic modeling, ten heat matrices were drawn (one per unit) to summarize the main services characterizing the computed topics. Seven hypotheses grounded on existing literature were tested, from which some interesting findings emerged (e.g., related to transfer services, staff, food and beverage, cleanliness, and punctuality). This study contributes to the standardization versus adaptation debate by unveiling a globalized strategy in staff management and breakfast services, while bar services adopt a localized strategy. Transportation services, while not offered by the hotels, are frequently mentioned, which signals hoteliers to interact with local authorities to improve accessibilities.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

Research trends in CISTI's unveiled through text mining

CISTI (Iberian Conference on Information Systems and Technologies) is a technical and scientific annual event dating back to 2006, whose purpose is to present and discuss knowledge, new perspectives, experiences and innovations in the Information Systems and Technologies domain (IST). The dynamics associated with IST together with the growing interest of the global community in CISTI have resulted in many topics and articles published in each conference, justifying a comprehensive analysis of the literature published. In this study, we present such analysis encompassing the last four editions, between 2013 and 2016, and a total of 677 articles. To accomplish such challenge more efficiently, we adopted text mining. We assessed through topic modeling how the unveiled research trends are aligned with the main conference themes. Data-driven empirical research has proven it is still a hot subject for researchers. Likewise, education and learning are also playing a significant role in CISTI's contributions. Notwithstanding, Internet and social media are highly relevant topics for the conference, although not figuring as major themes. On the other side, health is receiving less attention. Thus, this study can lead to recommendations for future CISTI's themes, in addition to providing an overview of current research trends.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

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

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

Constructed response or multiple-choice questions for assessing declarative programming knowledge? That is the question!

Aim/Purpose This paper presents a data mining approach for analyzing responses to advanced declarative programming questions. The goal of this research is to find a model that can explain the results obtained by students when they perform exams with Constructed Response questions and with equivalent Multiple-Choice Questions. Background The assessment of acquired knowledge is a fundamental role in the teachinglearning process. It helps to identify the factors that can contribute to the teacher in the developing of pedagogical methods and evaluation tools and it also contributes to the self-regulation process of learning. However, better format of questions to assess declarative programming knowledge is still a subject of ongoing debate. While some research advocates the use of constructed responses, others emphasize the potential of multiple-choice questions. Methodology A sensitivity analysis was applied to extract useful knowledge from the relevance of the characteristics (i.e., the input variables) used for the data mining process to compute the score. Contribution Such knowledge helps the teachers to decide which format they must consider with respect to the objectives and expected students results. Findings The results shown a set of factors that influence the discrepancy between answers in both formats. Recommendationsfor Practitioners Teachers can make an informed decision about whether to choose multiplechoice questions or constructed-response taking into account the results of this study. Recommendations for Researchers In this study a block of exams with CR questions is verified to complement the area of learning, returning greater performance in the evaluation of students and improving the teaching-learning process. Impact on Society The results of this research confirm the findings of several other researchers that the use of ICT and the application of MCQ is an added value in the evaluation process. In most cases the student is more likely to succeed with MCQ, however if the teacher prefers to evaluate with CR other research approaches are needed. Future Research Future research must include other question formats.info:eu-repo/semantics/publishedVersio