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, Bert Zwart

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)28-51
Number of pages24
JournalInternational Journal of Revenue Management
Volume10
Issue number1
DOIs
Publication statusPublished - 1 Jan 2017

Keywords

  • Data analysis
  • Forecasting
  • Hotel
  • Independent
  • Revenue management
  • Small
  • Small and medium enterprises
  • SME

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