Modelling the cancellation behaviour of hotel guests
Markku Vieru2018, International Journal of Contemporary Hospitality Management
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Abstract
Purpose The purpose of this study is to provide new insights into the factors that influence cancellation behaviour with respect to hotel bookings. The data are based on individual bookings drawn from a hotel reservation system database comprising nine hotels. Design/methodology/approach The determinants of cancellation probability are estimated using a probit model with cluster adjusted standard errors at the hotel level. Separate estimates are provided for rooms booked offline, through online travel agencies and through traditional travel agencies. Findings Evidence based on 233,000 bookings shows that the overall cancellation rate is 8 per cent. Cancellation rates are highest for online bookings (17 per cent), followed by offline bookings (12 per cent) and travel agency bookings (4 per cent). Probit estimations show that the probability of cancelling a booking is significantly higher for early bookings, large groups that book offline, offline bookings during high seasons, booking...
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