Purpose: The purpose of this paper is to know which hotels mostly rely on Booking.com, investigating the level of presence on Booking.com around the world by country, hotel size, hotel category and managerial form. Neither the company nor the hotels provide this information, so the authors use the number of reviews as an indicator of estimated sales. Design/methodology/approach: Data from 33,996 hotels worldwide are downloaded from Booking.com using a Web browser automatically controlled, developed in Python, that simulated a user navigation (clicks and selections). The comparison between independent hotels and hotels belonging to a chain is performed by a Student’s t distribution test and the comparison of hotel categories and hotel size is analyzed by a one-way ANOVA test. Findings: The results show that three factors clearly influence the usage level of Booking.com: independent vs chain hotels, small vs large hotels and low vs high category hotels worldwide. The authors also observe that hotels from Europe are the ones that rely more on Booking.com. Originality/value: The originality of this research is to identify the factors that make hotels to have a greater (lesser) dependence on Booking.com within each destination and geographical area. Moreover, the use of big data from hotels worldwide allows the authors to know the level of use of Booking.com in dozens of countries, especially those with the highest tourist activity. This work expands the capabilities of big data in the hospitality industry research, and with a simple ratio, this study counteracts the lack of public data on hotel sales through Booking.com. This new approach could be extended to the analysis of other online travel agencies (OTAs), which use similar review systems.

Social media and mobile technologies have revolutionised communication and particular attention has been given to user-generated content (UGC) and the formation of online communities; however, little attention has been given to tourist events entirely generated by users through social media. This paper aims to define and characterise the phenomenon of tourism user-generated events (UGEs) through social media around the user’s new empowered role and to assess user-generated social media events’ online socialness. It is also our aim to provide a useful mixed-methodology analysis framework for UGEs in relation to social media and to highlight their interest for organisations. The methodological approach includes a quantitative model to store, analyse and compare events’ online socialness, which is combined with qualitative, participant observation at the events. This approach is applied to the analysis of three Instagram meetups organised by a specific online community at Catalan ski resorts. The paper’s results show the differential characteristic of tourism UGEs: user initiative and empowerment, full organisation and structure, great social media use and UGC production, brand dissemination, attraction capacity, strong online community bond and faithfulness. With UGEs, an event management paradigm shift occurs as organisations are no longer the main initiators and controllers of the event.

The aim of this research is to confirm whether there is a relationship between the number of reviews and the hotel’s score on Booking.com and TripAdvisor and whether the relationship is different depending on the geographical area. Moreover, the study endeavors to confirm whether the number of reviews influences the score on each website. With the analysis of about 13,899 hotels in 146 cities, our findings suggest that there is some lineal relationship between the amount of reviews and the score on TripAdvisor but not on Booking.com. Moreover, by regions on TripAdvisor hotels from Middle East and Africa and Asia and Pacific have a stronger relationship between reviews and score than those from Europe and America.