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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2018
عنوان انگلیسی مقاله:
Big Data analytics for forecasting tourism destination arrivals with the applied Vector Autoregression model
ترجمه فارسی عنوان مقاله:
تحلیل داده های بزرگ برای پیش بینی مقصد گردشگران مقصد با بکارگیری مدل بردار Autoregression
منبع:
Sciencedirect - Elsevier - Technological Forecasting & Social Change, 130 (2018) 123-134: doi:10:1016/j:techfore:2018:01:018
نویسنده:
Yuan-Yuan Liua,b, Fang-Mei Tsengc,⁎, Yi-Heng Tsengc
چکیده انگلیسی:
The prediction of tourist numbers is important for Destination Management and Marketing. While most existing
methods rely on well-structured statistical data, using web search queries of the destination to forecast its tourist
arrivals is a new way to apply Big Data analytics. However, there are no studies exploring correlation of weather,
temperatures, weekends and public holidays with tourism destination arrivals and web search queries of the
destination, respectively. This study uses the Vector Autoregressive modeling to examine the Granger causality
between actual arrivals of the studied cultural tourism destination and its web search queries, and to explore the
correlation mentioned above. The striking result is that weather has no correlation either with actual arrivals of
the studied cultural tourism destination, or with its web search queries. Meanwhile, unlike previous researchers
who discuss the predictive power of web queries on actual tourism flows, this study emphasizes their reciprocal
predictive powers upon each other. The originality of this study is exemplifying the utilization of Big Data
analytics in the tourism domain with Big Data datasets, data capture techniques, analytical tools, and analysis
results. This study further digs possible reasons for an identified short time lag length (p = 2), to provide insights
for Destination Management and Marketing.
Keywords: Big Data analytics ، Vector Autoregression model ، Granger causality ، Destination Management and Marketing
قیمت: رایگان
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