Weekly Hotel Occupancy Forecasting of a Tourism Destination

Muzi Zhang, Junyi Li, Bing Pan and Gaojun Zhang
Additional contact information
Muzi Zhang: School of Geography and Tourism, Shaanxi Normal University, Xi’an 710062, China
Junyi Li: School of Geography and Tourism, Shaanxi Normal University, Xi’an 710062, China
Bing Pan: Department of Recreation, Park, and Tourism Management, College of Health and Human Development, Penn State University, University Park, PA 16801, USA
Gaojun Zhang: Shenzhen Tourism College, Jinan University, Shenzhen 518055, China

Sustainability, 2018, vol. 10, issue 12, 1-17

Abstract: The accurate forecasting of tourism demand is complicated by the dynamic tourism marketplace and its intricate causal relationships with economic factors. In order to enhance forecasting accuracy, we present a modified ensemble empirical mode decomposition (EEMD)–autoregressive integrated moving average (ARIMA) model, which dissects a time series into three intrinsic model functions (IMFs): high-frequency fluctuation, low-frequency fluctuation, and a trend; these three signals were then modeled using ARIMA methods. We used weekly hotel occupancy data from Charleston, South Carolina, USA as an empirical test case. The results showed that for medium-term forecasting (26 weeks) of hotel occupancy of a tourism destination, the modified EEMD–ARIMA model provides more accurate forecasting results with smaller standard deviations than the EEMD–ARIMA model, but further research is needed for validation.

Keywords: time series; ensemble empirical model decomposition; demand forecasting; signal decomposition; spectral analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/2071-1050/10/12/4351/pdf (application/pdf)
https://www.mdpi.com/2071-1050/10/12/4351/ (text/html)

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:gam:jsusta:v:10:y:2018:i:12:p:4351-:d:184796

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().