African Journal of Hospitality, Tourism and Leisure (May 2019)
Social big data analysis of Five Star hotels: A case study of hotel guest experience and satisfaction in Marrakech.
Abstract
The fast progress of the Internet and mobile devices facilitated the introduction of travel and hospitality review sites, producing a high number (big data) of customer opinion posts. While such comments may manipulate future demand of the specific hotels, they can also be used by hotel managers for bettering customer experience. In order to understand the hotel guest experience and satisfaction in Morocco, especially in Marrakech city during the period from 2015 to 2018, we collected data from “TripAdvisor.com”, the online customer textual reviews, and rating of 7 five star hotels. A Hadoop cluster was configured to handle the social big data extracted, as the method we employed big data analytics and sentiment analysis for handling the sentiment-detection algorithms using tidytext package, as well as bing lexicon. The used techniques were reliable to analyze and identify different characteristics of hotel guest such as “types” of hotel guests; we found that the highest rated type of hotel guests was 'with family'. Concerning the “behavioral”, the type of guest 'with family' seems to comment and expresses his satisfaction or dissatisfaction every month, except in January, September, and December. Moreover, concerning the “nationality” of hotel guests, France represented the highest rate by 70.07%. On the other hand for satisfaction, the “rating” of the field 'service' was decreased in the last two years. Finally, the “sentiment-experience” and the words 'limitations' and 'excellent' were clearly the main hotel attributes mentioned by the customers. The present study showed that big social data analytics and sentiment analysis could be good solutions to help the tourism and hospitality industry to gain insights into the characteristics, satisfaction, and sentiments of the guests to hotels during their experiences at the hotels. However, knowing more elements relevant to the hotel guest would be even more beneficial for hotels in order to enable them to improve their products/services ratio.
