Mountain landscapes and communities are highly sensitive and vulnerable to climate
change. Tourism in mountain regions is highly dependent on natural resources and …

Purpose The purpose of this paper is to review recent studies published from 2007 to 2015
on tourism and hotel demand modeling and forecasting with a view to identifying the …

A novel approach based on long short-term memory (LSTM) networks that can incorporate
multivariate time series data, including historical tourism volume data, search engine data …

Hospitality constituencies need accurate forecasting of future performance of hotels in
specific destinations to benchmark their properties and better optimize operations. As …

Tourists from different European regions have reacted heterogeneously during the Global
Economic Crisis. Such variability is due to different preferences and willingness to pay for …

Accurate forecasting of daily tourism demand is a meaningful and challenging task, but
studies on this issue are scarce. To address this issue, multisource time series data, relating …

Increasing temperatures and snow scarce winter seasons challenge the winter tourism
industry. In this study the impacts of+ 2° C global warming on winter tourism demand in …

A new model that links climate and seasonal tourism demand is developed to study the
effects of home climate, destination climate, and climate difference between destinations …

This study evaluated the impact of actual weather encountered and perceptions of the
comfort of the weather on tourist movements in Hong Kong. Data were collected using both …

This paper aims to investigate the effects of economic uncertainty on the Japanese tourists
who travelled to the United States (USA) over the period 1996Q1–2015Q1. To achieve this …