In this study, we investigate the spatial agglomeration of the Meetings, Incentives, Conferences, and Exhibitions (MICE) industry. We use detailed information on the convention venues characteristics and their spatial distribution to identify clusters by using the spatially constrained...

In this paper we enhance the literature exploring the forecasting capability of six alternatives GARCH-type models to predict volatility of four of the most traded cryptocurrencies: Bitcoin, Ethereum, Ripple and Litecoin. The analysis is performed on daily data from 1st March 2016 to 28th...

What happens when high-frequency and high spatial detailed characteristics of data encounter long publication delays in forecasting problems? This paper emphasises the predictive power of Google Trends (GT) data, only strongly assessed, but not in the investigations of high-frequency tourism...

Exploring the main determinants of tourism participation at national and international level, the paper investigates if there are differences in tourism consumption behavior among Italian families which reflect disparities in their standard of living. To achieve this a Heckman model has been...