کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7421268 | 1482626 | 2016 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A dynamic linear model to forecast hotel registrations in Puerto Rico using Google Trends data
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
مدیریت، کسب و کار و حسابداری
استراتژی و مدیریت استراتژیک
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Recently, studies have used search query volume (SQV) data to forecast a given process of interest. However, Google Trends SQV data comes from a periodic sample of queries. As a result, Google Trends data is different every week. We propose a Dynamic Linear Model that treats SQV data as a representation of an unobservable process. We apply our model to forecast the number of hotel nonresident registrations in Puerto Rico using SQV data downloaded in 11 different occasions. The model provides better inference on the association between the number of hotel nonresident registrations and Google Trends SQV than using Google Trends data retrieved only on one occasion. Furthermore, our model results in more realistic prediction intervals of forecasts. However, compared to simpler models we only find evidence of better performance for our model when making forecasts on a horizon of over 6 months.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tourism Management - Volume 57, December 2016, Pages 12-20
Journal: Tourism Management - Volume 57, December 2016, Pages 12-20
نویسندگان
Roberto Rivera,