TY - JOUR
T1 - Google Trends and tourists’ arrivals
T2 - Emerging biases and proposed corrections
AU - Dergiades, Theologos
AU - Mavragani, Eleni
AU - Pan, Bing
N1 - Funding Information:
We would like to thank the Editor in Chief Chris Ryan, and two anonymous reviewers of this Journal for their most useful comments and suggestions. Dr. Bing Pan would like to acknowledge the grant support from the National Natural Science Foundation of China (Grant # 41428101 ).
Funding Information:
We would like to thank the Editor in Chief Chris Ryan, and two anonymous reviewers of this Journal for their most useful comments and suggestions. Dr. Bing Pan would like to acknowledge the grant support from the National Natural Science Foundation of China (Grant # 41428101).
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2018/6
Y1 - 2018/6
N2 - As search engines constitute a leading tool in planning vacations, researchers have adopted search engine query data to predict the consumption of tourism products. However, when the prevailing shares of visitors come from countries in different languages and with different dominating search engine platforms, the identification of the aggregate search intensity index to forecast overall international arrivals, becomes challenging since two critical sources of bias are involved. After defining the language bias and the platform bias, this study focuses on a destination with a multilingual set of source markets along with different dominating search engine platforms. We analyze monthly data (2004–2015) for Cyprus with two non-causality testing procedures. We find that the corrected aggregate search engine volume index, adjusted for different search languages and different search platforms, is preferable in forecasting international visitor volumes compared to the non-adjusted index.
AB - As search engines constitute a leading tool in planning vacations, researchers have adopted search engine query data to predict the consumption of tourism products. However, when the prevailing shares of visitors come from countries in different languages and with different dominating search engine platforms, the identification of the aggregate search intensity index to forecast overall international arrivals, becomes challenging since two critical sources of bias are involved. After defining the language bias and the platform bias, this study focuses on a destination with a multilingual set of source markets along with different dominating search engine platforms. We analyze monthly data (2004–2015) for Cyprus with two non-causality testing procedures. We find that the corrected aggregate search engine volume index, adjusted for different search languages and different search platforms, is preferable in forecasting international visitor volumes compared to the non-adjusted index.
UR - http://www.scopus.com/inward/record.url?scp=85040775595&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040775595&partnerID=8YFLogxK
U2 - 10.1016/j.tourman.2017.10.014
DO - 10.1016/j.tourman.2017.10.014
M3 - Article
AN - SCOPUS:85040775595
SN - 0261-5177
VL - 66
SP - 108
EP - 120
JO - Tourism Management
JF - Tourism Management
ER -