A call for exploratory data analysis in revenue management forecasting: a case study of a small and independent hotel in The Netherlands

Dirk Sierag, Jean-Pierre Van Der Rest, Ger Koole, Rob Van Der Mei and Bert Zwart

International Journal of Revenue Management, 2017, vol. 10, issue 1, 28-51

Abstract: Using five years of data collected from a small and independent hotel this case study explores RMS data as a means to seek new insights into occupancy forecasting. The study provides empirical evidence on the random nature of group cancellations, an important but neglected aspect in hotel revenue management modelling. The empirical study also shows that in a local market context demand differs significantly per point of time during the day, in addition to seasonal monthly and weekly demand patterns. Moreover, the study presents evidence on the nonhomogeneous Poisson nature of the probability distribution that demand follows, a crucial characteristic for forecasting modelling that is generally assumed but not reported in the hotel forecasting literature. This implies that demand is more uncertain for smaller than for larger hotels. The paper concludes by drawing attention to the critical and often overlooked role of exploratory data analysis in hotel revenue management forecasting.

Keywords: hotel; revenue management; forecasting; data analysis; SME; small and medium enterprises; independent; small. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.inderscience.com/link.php?id=84147 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijrevm:v:10:y:2017:i:1:p:28-51

Access Statistics for this article

More articles in International Journal of Revenue Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().