Understanding hotel location preference of customers: Comparing random utility and random regret decision rules

Abstract

During hotel selection, tourists compare alternative hotels based on hotel characteristics and process such information according to a specific decision rule. This study investigates customer preference toward various hotel location attributes through the implementation of a stated choice experiment and estimation of a discrete choice model. The study further aims to compare the well-established utility-based decision rule with a recently introduced regret-based decision rule. The study analyzes the stated preferences of 719 tourists in Hong Kong for different factors, including walking time to the nearest points of interest, hotel neighborhood, online rating, and price. The two decision rules investigated in the study provide similar estimation results with regard to the significance of the estimated coefficient of different factors, although the random regret minimization model performs significantly better than the random utility maximization model. The paper also compares and discusses the willingness to pay measures and implications.