کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7422236 1482637 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data
ترجمه فارسی عنوان
پیش بینی تقاضای جهانی گردشگری شهر برای پاریس: دقت مدل های یک و چند متغیر با استفاده از داده های ماهانه
کلمات کلیدی
پیش بینی تقاضای گردشگری، گردشگری شهر، داده های ماهانه، مدل های اقتصادسنجی،
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری استراتژی و مدیریت استراتژیک
چکیده انگلیسی
The purpose of this study is to compare the predictive accuracy of various uni- and multivariate models in forecasting international city tourism demand for Paris from its five most important foreign source markets (Germany, Italy, Japan, UK and US). In order to achieve this, seven different forecast models are applied: EC-ADLM, classical and Bayesian VAR, TVP, ARMA, and ETS, as well as the naïve-1 model serving as a benchmark. The accuracy of the forecast models is evaluated in terms of the RMSE and the MAE. The results indicate that for the US and UK source markets, univariate models of ARMA(1,1) and ETS are more accurate, but that multivariate models are better predictors for the German and Italian source markets, in particular (Bayesian) VAR. For the Japanese source market, the results vary according to the forecast horizon. Overall, the naïve-1 benchmark is significantly outperformed across nearly all source markets and forecast horizons.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tourism Management - Volume 46, February 2015, Pages 123-135
نویسندگان
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