A naive Bayes strategy for classifying customer satisfaction: A study based on online reviews of hospitality services

This research assesses whether terms related to guest experience can be used to identify ways to enhance hospitality services. A study was conducted to empirically identify relevant features to classify customer satisfaction based on 47,172 reviews of 33 Las Vegas hotels registered with Yelp, a social networking site. The resulting model can help hotel managers understand guests' satisfaction. In particular, it can help managers process vast amounts of review data by using a supervised machine learning approach. The naive algorithm classifies reviews of hotels with high precision and recall and with a low computational cost. These results are more reliable and accurate than prior statistical results based on limited sample data and provide insights into how hotels can improve their services based on, for example, staff experience, professionalism, tangible and experiential factors, and gambling-based attractions.Junta de Andalucía SEJ49

When some negative feedback increases profits: the experience gift industry case

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Online Travel Agencies (OTAs) and Hoteliers’ Relationships: Do Social and Cognitive Relationships Matter?

This study aims to discover if social relationship as measured by shared value, duration and non-economic satisfaction and cognitive relationship as measured by task performance and economic satisfaction affect OTAs-hoteliers’ relationship, which is measured through trust and commitment. Data was collected from hotels’ operation managers, senior managers, financial executives, business owners, and partners through online surveys. A total of 208 usable questionnaires were returned from 577, resulting in a response rate of 36.04 per cent. The hypotheses were tested using SEM and mediation effects were tested and translated using Hair et al. (2014) nested structural model concept.  The results indicate partial mediation for cognitive domain - relationship commitment and full mediation for social domain - relationship commitment affects. Trust forms as the mediating variable

Digital Business Strategies for Incumbent Firms. How a Scandinavian hotel chain competes with the internet giants

The rise of digital platform companies has shaken many business sectors and led to the emergence of new competition arenas, digital business ecosystems. Incumbent firms realize they need to change how they do business, and that conventional business strategies are no longer fit for competing in these new digital arenas. Our research questions are (i) how can incumbent service firms develop and leverage a digital business strategy, and (ii) how can hotels and hotel chains compete with online travel agencies (OTAs) in digital hospitality ecosystems? We chose a longitudinal case study to explore how a large Scandinavian hotel chain implemented a digital business strategy to compete with OTAs in a digital hospitality ecosystem. Our approach was to stay close to the practices and actual behaviours of the company and the individuals engaged in fulfilling the strategy. We contribute to theory and practice by proposing that (i) incumbent firms need two strategies, one for the digital ecosystem and one for the traditional competition arena, (ii) that the two strategies should be implemented ambidextrously but also integrated and (iii) that to succeed, it is essential to establish self-reinforcing interactions between the digital and the physical

Propuesta de un nuevo índice para la gestión de la reputación online de hoteles

Aim: To develop a procedure for the calculation of a new online reputation index, inrelation to TripAdvisor user ratings, which helps create a hotel ranking, and improvestrategic marketing guidelines.Methods and techniques: Analysis and synthesis, induction-deduction, and historical-logic. The second group of methods included expert opinion, survey, Spearmancorrelation coefficient, and Kendall Tau-b coefficient. SPSS, 22 was used for statisticaldata processing.Main results: The new procedure proposal is based on calculation of the onlinereputation index during the period studied, which overcomes previously existinglimitations, and assigns a value to every hotel scoring received according to hotel size.The methodological proposal makes the establishment of a hotel ranking possible,according to hotel typology, and also permits to enhance strategic marketing guidelines.Conclusions: The procedure meets the objectives set, by implementing its phasesproperly, which shows the capacity of responding to the characteristics needed in thisscenario. The new ranking is regarded as valid, based on the analysis of statistical data.The findings of this study will permit to make decisions in order to improve strategicprocesses, and implement policies to optimize critical processes in the hotel sector.Objetivo: Desarrollar un procedimiento para el cálculo de un nuevo índice de reputación online asociado a las puntuaciones de los usuarios en TripAdvisor, que permita la confección del ranking de hoteles así como la mejora de las directrices estratégicas de la comercialización. Métodos y técnicas: Análisis-síntesis, inducción-deducción y el histórico lógico; además del criterio de expertos, la encuesta, el coeficiente de correlación de Spearman y el coeficiente Tau-b de Kendall. Para el procesamiento de los datos se utilizó el software estadístico SPSS vs- 22. Principales resultados: El procedimiento propone calcular un nuevo Índice de reputación online del período, que supera las limitaciones existentes y asigna valor a cada puntuación recibida por un hotel, tomando en consideración su tamaño. La propuesta metodológica permite comprobar que es posible la confección del ranking de hoteles según su tipología y perfeccionar las directrices estratégicas de la comercialización. Conclusiones: El procedimiento cumple con los objetivos propuestos, implementa de forma adecuada las fases que lo componen y tiene la capacidad de responder a las características necesarias para el contexto. El nuevo ranking es considerado válido según los datos estadísticos alcanzados. Los resultados obtenidos permitirán tomar decisiones en función de mejorar los procesos estratégicos y desarrollar políticas para perfeccionar procesos claves de la empresa hotelera

Unpacking the impact of social media analytics on customer satisfaction : do external stakeholder characteristics matter?

Purpose Underpinned by the lens of Contingency Theory (CT), the purpose of this paper is to empirically evaluate whether the impact of social media analytics (SMA) on customer satisfaction (CS) is contingent on the characteristics of different external stakeholders, including business partners (i.e. partner diversity), competitors (i.e. localised competition) and customers (i.e. customer engagement). Design/methodology/approach Using both subjective and objective measures from multiple sources, we collected primary data from 141 hotels operating in Greece and their archival data from TripAdvisor and the Hellenic Chamber of Hotels (HCH) database to test the hypothesised relationships. Data were analysed through structural equation modelling. Findings This study confirms the positive association between SMA and CS, but it remains subject to the varied characteristics of external stakeholders. We find that an increase in CS due to the implementation of SMA is more pronounced for firms that (1) adopt a selective distribution strategy where a limited number of business partners are chosen for collaboration or (2) operate in a highly competitive local environment. The results further indicate that high level of customer engagement amplifies the moderating effect of partner diversity (when it is low) and localised competition (when it is high) on the SMA–CS relationship. Originality/value The study provides novel insights for managers on the need to consider external stakeholder characteristics when implementing SMA to enhance firms' CS, and for researchers on the value of studying SMA implementation from the CT perspective

Tourism in the Digital Age: E-booking Perspective

Digitization in the tourism sector beside hospitality information systems application as its integral part has also led to the application of on-line booking systems, which enable the booking of the desired tourist arrangement via the Internet. Consequently, the emergence of the e-booking concept has made it possible reducing administrative and operational costs, since the e-booking system is also used on smartphones with appropriate applicative support. This paper aims to point out the importance of e-booking in the digital age of tourism, especially from monitoring the most common destinations, customer preferences and performing predictive analytics by collecting large amounts of data. In this way, the implementation of big data and cloud computing concept enhances tourism services, since it is possible to analyse destination history and tourist potential of the client via the Internet. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

Understanding relationship quality in hospitality services : A study based on text analytics and partial least squares

Purpose – The purpose of this paper is to analyze the occurrence of terms to identify the relevant topics and then to investigate the area (based on topics) of hospitality services that is highly associated with relationship quality. This research represents an opportunity to fill the gap in the current literature, and clarify the understanding of guests’ affective states by evaluating all aspects of their relationship with a hotel. Design/methodology/approach – This research focuses on natural opinions upon which machine-learning algorithms can be executed: text summarization, sentiment analysis and latent Dirichlet allocation (LDA). Our data set contains 47,172 reviews of 33 hotels located in Las Vegas, and registered with Yelp. A component- based structural equation modeling (partial least squares (PLS)) is applied, with a dual – exploratory and predictive – purpose. Findings – To maintain a truly loyal relationship and to achieve competitive success, hospitality managers must take into account both tangible and intangible features when allocating their marketing efforts to satisfaction-, trust- and commitment-based cues. On the other hand, the application of the PLS predict algorithm demonstrates the predictive performance (out-of-sample prediction) of our model that supports its ability to predict new and accurate values for individual cases when further samples are added. Originality/value – LDA and PLS produce relevant informative summaries of corpora, and confirm and address more specifically the results of the previous literature concerning relationship quality. Our results are more reliable and accurate (providing insights not indicated in guests’ ratings into how hotels can improve their services) than prior statistical results based on limited sample data and on numerical satisfaction ratings alone

Propuesta de un nuevo índice para la gestión de la reputación online de hoteles

Objetivo:  Desarrollar  un  procedimiento  para  el  cálculo  de  un  nuevo  índice  de reputación online asociado a las puntuaciones de los usuarios en TripAdvisor, que permita la confección del ranking de hoteles así como la mejora de las directrices estratégicas de la comercialización. Métodos y técnicas: Análisis-síntesis, inducción-deducción y el histórico lógico; además del criterio de expertos, la encuesta, el coeficiente de correlación de Spearman y el coeficiente Tau-b de Kendall. Para el procesamiento de los datos se utilizó el software estadístico SPSS vs- 22. Principales resultados: El procedimiento propone calcular un nuevo Índice de reputación online del período, que supera las limitaciones existentes y asigna valor a cada puntuación recibida por un hotel, tomando en consideración su tamaño. La propuesta metodológica permite comprobar que es posible la confección del ranking de hoteles según su tipología y perfeccionar las directrices estratégicas de la comercialización. Conclusiones: El procedimiento cumple con los objetivos propuestos, implementa de forma adecuada las fases que lo componen y tiene la capacidad de responder a las características necesarias para el contexto. El nuevo ranking es considerado válido según los datos estadísticos alcanzados. Los resultados obtenidos permitirán tomar decisiones en función de mejorar los procesos estratégicos y desarrollar políticas para perfeccionar procesos claves de la empresa hotelera.

Evaluación de entidades hoteleras de Cabo Verde a través de Tripadvisor

Este trabajo consiste en un estudio preliminar o exploratorio cuyo objetivo principal es obtener información, a través de la plataforma Tripadvisor, de hoteles de Cabo Verde de 3 a 5 estrellas. Para ello, se usa una serie de métodos cuantitativos, como el análisis descriptivo, el análisis de correlación, el análisis de regresión simple y el análisis discriminante doble, utilizando una muestra de 62 hoteles. Después de analizar los resultados, se puede concluir que los hoteles del grupo 1 de las islas (Barlovento) se destacan más por el servicio y los precios más altos que los hoteles del grupo 2 (Sotavento), destacando este último por la limpieza. Se encontró que la categoría del hotel mantiene una relación positiva con la evaluación general del cliente y con el precio. Los dos análisis de regresión realizados nos permiten concluir que es posible predecir con éxito la Evaluación general del cliente y el Ranking de hoteles, utilizando un pequeño número de variables. En general, los resultados muestran que los hoteles de Cabo Verde son altamente calificados por los usuarios, aunque, por supuesto, reciben críticas y comentarios negativos en varias ocasiones.This work consists of a preliminary or exploratory study in which the main objective is to obtain information about Cape Verde hotels from 3 to 5 stars through the Tripadvisor platform. For this, a series of quantitative methods are used, such as descriptive analysis, correlation analysis, simple regression analysis, and double-discriminant analysis using a sample of 62 hotels. After obtaining the results it allows us to conclude that the hotels of group 1 of islands (Barlovento) stand out more for the service and higher prices than the hotels of group 2 (Sotavento), the second standing out for cleanliness. It was found that the category of the hotel maintains a positive and close relationship with the general evaluation of the customer and with the price. The two regression analyzes carried out allow us to conclude that it is possible to successfully predict the General Customer Assessment and the Ranking of Hotels, using a small number of variables. In general, the results show that Cape Verde hotels are highly rated by users, although, they receive criticism and negative comments on several occasion