Analysis of Hotel Bookings in Terms of Occupancy and Sales across Seasons and Events, and the Development of a Proposed Smart-Pricing Mechanism
Article Sidebar
Main Article Content
The hospitality sector increasingly relies on operational data to guide pricing, yet many operators still raise or lower prices uniformly across all units. This paper analyses hotel bookings in terms of occupancy and sales across seasons and events, and develops a proposed unit-level smart-pricing and selective-marketing mechanism. The study follows a descriptive–analytical approach using actual operational data for 95 residential hotel units operated by a hospitality company in Riyadh and Al-Madinah, Saudi Arabia, covering January to June 2026 (181 days, 9,028 occupied nights, SAR 4.22 million in confirmed sales), organised through an interactive web dashboard that is publicly accessible online. Independent-samples (Welch) t-tests were used to test the significance of the observed differences. The results show clear monthly variation, a dominant Airbnb channel, and — most importantly — that the occupancy–sales relationship is not directly proportional but is mediated by the average daily rate (ADR): some units combine low occupancy with high sales, while others show the opposite. The effect of Ramadan differs sharply by city, with occupancy and rate rising in Al-Madinah but falling in Riyadh; weekends significantly outperform weekdays; and the cancellation rate reaches 10.3%. The study concludes with a set of quantified, calibratable pricing rules that link each pricing decision to the event, season, city, day type, channel, and the actual performance of the individual unit.
Downloads
References
R. G. Cross, J. A. Higbie, and D. Q. Cross, "Revenue management's renaissance: A rebirth of the art and science of profitable revenue generation," Cornell Hospitality Quarterly, vol. 50, no. 1, pp. 56–81, 2009.
S. Ivanov and V. Zhechev, "Hotel revenue management – a critical literature review," Tourism, vol. 60, no. 2, pp. 175–197, 2012.
Yeoman, "Hospitality revenue management research," Journal of Revenue and Pricing Management, vol. 23, 2024.
Ampountolas and M. Legg, "Predicting daily hotel occupancy: A practical application for independent hotels," Journal of Revenue and Pricing Management, vol. 23, no. 3, pp. 197–205, 2024.
Blengini and C. Y. Heo, "The role of exchange rate on hotelier's pricing decision and business performance: The case of Switzerland, a small open economy," Journal of Revenue and Pricing Management, vol. 23, pp. 206–216, 2024.
R. Qi, D. Jin, H. Chen, X. Mou, and F. Ali, "Strategic-level perceived fairness of hotel dynamic pricing: The role of cues and the asymmetric moderating effect of inflation attribution," Journal of Revenue and Pricing Management, 2024.
S.-H. Chiu, T.-Y. Lin, and W.-C. Wang, "Investigating the spatial effect of operational performance in China's regional tourism system," Humanities and Social Sciences Communications, vol. 11, art. 242, 2024.
M. D. Flecha-Barrio, F. E. García-Muiña, L. González-Serrano, and P. Talón-Ballestero, "How to overcome a worldwide lockdown in the hospitality sector? Lessons from revenue managers," Journal of Revenue and Pricing Management, vol. 23, pp. 217–237, 2024.
W. M. Alhag, "Hotel bookings analytics dashboard." [Online]. Available: https://wadahzx.github.io/hotel-bookings-dashboard/
S. E. Kimes, "The basics of yield management," Cornell Hotel and Restaurant Administration Quarterly, vol. 30, no. 3, pp. 14–19, 1989.
G. Abrate, G. Fraquelli, and G. Viglia, "Dynamic pricing strategies: Evidence from European hotels," International Journal of Hospitality Management, vol. 31, no. 1, pp. 160–168, 2012.
G. Abrate and G. Viglia, "Strategic and tactical price decisions in hotel revenue management," Tourism Management, vol. 55, pp. 123–132, 2016.
H. S. Moula, S. H. Yaghoubyan, R. Malekhosseini, and K. Bagherifard, "Customer type discovery in hotel revenue management: A data mining approach," Journal of Revenue and Pricing Management, vol. 23, no. 3, pp. 238–248, 2024.

This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in our journal are licensed under CC-BY 4.0, which permits authors to retain copyright of their work. This license allows for unrestricted use, sharing, and reproduction of the articles, provided that proper credit is given to the original authors and the source.