Cross country relations in European tourist arrivals

Silva, Emmanuel Sirimal, Ghodsi, Zara, Ghosdi, Mansi, Heravi, Saeed ORCID: https://orcid.org/0000-0002-0198-764X and Hassani, Hossein 2017. Cross country relations in European tourist arrivals. Annals of Tourism Research 63 , pp. 151-168. 10.1016/j.annals.2017.01.012

Preview

PDF - Accepted Post-Print Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (654kB) | Preview

Abstract

This paper introduces an optimized Multivariate Singular Spectrum Analysis (MSSA) algorithm for identifying leading indicators. Exploiting European tourist arrivals data, we analyse cross country relations for European tourism demand. Cross country relations have the potential to aid in planning and resource allocations for future tourism demand by taking into consideration the variation in tourist arrivals across other countries in Europe. Our findings indicate with statistically significant evidence that there exists cross country relations between European tourist arrivals which can help in improving the predictive accuracy of tourism demand. We also find that MSSA has the capability of not only identifying leading indicators, but also forecasting tourism demand with far better accuracy in comparison to its univariate counterpart, Singular Spectrum Analysis.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > H Social Sciences (General)
Uncontrolled Keywords:	Multivariate Singular Spectrum Analysis; leading indicators;tourist arrivals; demand; Europe.
Publisher:	Elsevier
ISSN:	0160-7383
Date of First Compliant Deposit:	31 January 2017
Date of Acceptance:	24 January 2017
Last Modified:	17 Nov 2023 10:56
URI:	https://orca.cardiff.ac.uk/id/eprint/97888

Citation Data

Cited 23 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item