Table III

The most important and highest-quality articles using regression models for tourism and passenger demand forecasting

AuthorsPurposeDemand type and periodDeterminantsModeling
Varagouli et al. (2005) Forecasting the travel demandNumber of passengers traveling by carGDP of both origin and destination zones/Population of the both origin and destination zones/Number of cars per thousand inhabitants of the origin zone/Trip time by car or trip length/Trip price by carMultiple linear regression
Wu et al. (2012) Forecasting the tourism demand based on the external effective factorsMonthly international tourist arrivalsTravel demand by each origin country/Income of origins/Prices in destination/Transportation costs/Foreign exchange rate/Population of the origin country/…Sparse Gaussian process regression/ARIMA/v-SVM/g-SVM
Sivrikaya and Tunç (2013) Predicting the domestic air transport demandNumber of passengers carried per city pairUrban population/Bedding capacity/Distance/Transit/Price/Airline count/Travel match/Schedule consistency/Travel timeSemi-logarithmic regression model
Chu (2014) Predicting the tourism demandMonthly tourist arrivalsHistoric monthly tourist arrival dataLogistic growth regression/SARIMA/Naïve 1
Semeida (2014) Predicting the taxi passenger demandNumber of trips per person per yearDistance/Population/Area/Income/Travel time/Travel cost/Trip frequencyMultiple linear Regression/Generalized linear modeling
Chinnakum and Boonyasana (2017) Modeling the tourism demand for ThailandAnnual tourist arrivalsGross domestic product per capita/Relative price of tourism in Thailand/Exchange rate/PopulationPanel data regression models

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