Initially testing an improved extrapolative hotel room occupancy rate forecasting technique

Chun Hung Roberts Law

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

14 Citations (Scopus)


The existing time series forecasting models either capture the information of the last few data in the data series or the entire data series is used for projecting future values. In other words, the time series forecasting models are unable to take advantage of the last trend in the data series, which always have a direct influence on the estimated values. This paper proposes an improved extrapolative time series forecasting technique to compute future hotel occupancy rates. The performance of this new technique was tested with officially published room occupancy rates in Hong Kong. Forecasted room occupancy rates were compared with actual room occupancy rates in several accuracy performance dimensions. Empirical results indicate that the new technique is promising with reasonably good forecasting results.
Original languageEnglish
Title of host publicationManagement Science Applications in Tourism and Hospitality
PublisherTaylor and Francis
Number of pages7
ISBN (Print)9781315782478
Publication statusPublished - 1 Jan 2014


  • Forecasting accuracy
  • Room occupancy rates
  • Time series forecasting

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)


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