Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

This study reviews 211 key papers published between 1968 and 2018, for a better
understanding of how the methods of tourism demand forecasting have evolved over time …

Time series prediction with neural networks has been the focus of much research in the past
few decades. Given the recent deep learning revolution, there has been much attention in …

The global economic outlook is more uncertain than ever before and sensitive to
uncertainties related to a variety of economic policies decisions of all stakeholders and …

Personal security is a major concern for tourists. Most tourists will seek safe and secure
destinations and avoid those that have been plagued by terrorism. This research quantifies …

The tourism sector, with its perishable nature of products, requires precise estimation of
demand. To this effect, we propose a deep learning methodology, namely Bayesian …

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 …

In recent years, machine-learning techniques, particularly deep learning, have outperformed
traditional time-series forecasting approaches in many contexts, including univariate and …

Looking at the current political turmoil across the globe, this study aims to analyze the effects
of interaction between political instability and terrorism on tourism development using panel …

This paper aims to provide the most up-to-date survey of tourism economics research and to
summarise the key trends in its recent development. Particular attention is paid to the …