A revenue-maximizing strategy is an important part of yield management to maximize the service capacity. Specifically, determining hotel room pricing plays a crucial role in maximizing revenue in a highly competitive environment. Therefore, this study proposed an approach based on full factorial experimental design to analyze the effects of qualitative design factors
on hotel room pricing. The aim of this paper is three-fold. First, a factorial design was selected to analyze the effects of the four important qualitative design factors (the customer’s evaluation, the number of stars, disabled-friendly, and the free cancellation) on hotel room pricing. Second, an estimated regression function was obtained to determine the estimated hotel pricing. Additionally, a pure integer programming model was proposed to obtain the optimum settings of the four qualitative design factors using the desirability function. Further more, a nonlinear integer programming model was presented based on a 2n factorial design for comparison purposes. Third, a case study was presented to determine hotel room pricing in Antalya, Türkiye. According to the results obtained from the case study, the most important qualitative design factor, among others, is the number of stars. The qualitative factors used in the study explain 60.97% of the variation in hotel room prices. In the presented models, it has been determined that the minimum and maximum room prices should be 35 $ and 404 $, respectively. Also, the minimum and maximum room prices determined in both models were
consistent, and the optimum results were confirmed. The findings obtained in the study can guide hotel managers in determining appropriate hotel room prices.