Effects of airbnb rental proliferations on revpar of star-rated hotels in Nairobi County

Abstract

Airbnb is one of the disruptive technologies that have grown exponentially since its inception in 2008. It has raised concerns among hoteliers in the hospitality industry worldwide due to its perceived effect on hotel performance. Nairobi County has seen a surge in the number of Airbnb rentals over the years while at the same time a declining financial performance of star-rated hotels. As a result, there has been a proliferation of studies aimed at understanding the nature of these effects. However, most of these studies have been conducted mainly in the developed economies with reported contrasting results. On the same note, very limited studies have considered Airbnb listings and Airbnb price related factors such as price dispersion and price differentials effects on performance of hotels in Nairobi County, Kenya. This study therefore aimed to investigate the effects of Airbnb proliferations on RevPAR of star-rated hotels in Nairobi County. Specifically, the study set to determine the effect of Airbnb listings on RevPAR of star-rated hotels in Nairobi County; assess the effect of price differentials on RevPAR of star-rated hotels in Nairobi County; identify the effect of Airbnb price dispersion on RevPAR of star-rated hotels in Nairobi, County. The study was anchored on disruptive innovation theory and adopted a quantitative research approach. Correlational research design was used to collect and analyse pooled panel data relating to ADR, occupancy and listings from Airbnb and 54 star-rated hotels in Nairobi County. The study used monthly secondary data for the period between April 2012 to March 2023. Data was subjected to descriptive analysis in Excel and pooled regression analysis in STATA v 13. Descriptive analysis indicates that Airbnb in its initial stage may not be a concern to hoteliers but in the long run does affect the hotel performance. The regression analysis results indicate that Airbnb listings, price differentials and Airbnb price dispersions jointly accounted for 22.4% of the variation in RevPAR of star-rated hotels in Nairobi County (F [3, 127] = 10.34, p < .05, R2 = .224). The results indicate that a percentage increase in Airbnb listing, price differentials and Airbnb price dispersions would result to a decrease in RevPAR of star-rated hotels in Nairobi County by 0.017%, .13% and .12% respectively. This implies that with Airbnb rentals proliferation in Nairobi County, clients would prefer them to hotels as they charge lower rates and offer convenience. With lower rates, hoteliers would be forced to lower their room rates too and suffer low occupancy rate which in turn affects hotel RevPAR. The findings suggest that hoteliers should closely monitor Airbnb listings and prices and where possible also list some of their rooms on Airbnb. The findings add to the existing body of knowledge by providing insights on the disruptive nature of Airbnb to the hotel industry.