Purpose–Based on more than 2.7 million online reviews (ORs) collected with big data analytical techniques from Booking.com and TripAdvisor.com, this study explores if and to what extent environmental discourse embedded in ORs has an impact on electronic Word-of-Mouth (e-WOM) helpfulness across 8 major destination cities in North America and Europe.
Design/methodology/approach–This study gathered, by means of Big Data techniques, 2.7 million online reviews (ORs) hosted on Booking and TripAdvisor, and covering hospitality services in 8 different destinations cities in North America (New York City, Miami, Orlando, and Las Vegas) and Europe (Barcelona, London, Paris, and Rome) over the period 2017-2018. The ORs were analysed by means of ad hoc content analytic dictionaries to identify the presence and depth of the environmental discourse included in each OR. A negative binomial regression analysis was used to measure the impact of the presence/depth of online environmental discourse in ORs on e-WOM helpfulness.
Findings–The findings indicate that the environmental discourse presence and depth influence positively e-WOM helpfulness. More specifically those travelers who write explicitly about environmental topics in their ORs are more likely to produce ORs that are voted as helpful by other consumers.
Research implications/limitations – Implications highlight that both hotel managers and platform developers/managers should become increasingly aware of the importance that customer attach to environmental practices and initiatives and therefore engage more assiduously in environmental initiatives, if their objective is to improve online review helpfulness for other customers reading the focal reviews. Future studies might include more destinations and other operationalizations of environmental discourse.
Originality/value – This study constitutes the first attempt to capture how the presence and depth of hospitality services consumers’ environmental discourse influence e-WOM helpfulness on multiple digital platforms, by means of a big data analysis on a large sample of online reviews across multiple countries and destinations. As such it makes a relevant contribution to the area at the intersection between big data analytics, e-WOM, and sustainable tourism research
