The importance of online tourism demand

In recent decades, the combination of tourism and Information and Communication Technologies (ICT), has originated considerable changes in tourists’ behaviour. The analysis of tourism demand resulting from the Internet is of growing importance, given the increasing number of online reservations observed in recent years. However, in order to analyse the new trends caused by online bookings, the availability of data enabling the measurement and characterization of this phenomenon is essential. This has, however, been a considerable limitation, given that either no data on key variables is available or the available data is sometimes of questionable quality. For professionals and researchers in the area of tourism, the high volume of tourists who use the Internet to make hotel and travel reservations is worth of consideration, given that it may potentiate the discovery of new source markets, the identification of clients with different characteristics and may help explain the dynamics between suppliers or countries. The existence of predictive studies to support decision-making and planning, by professionals of the tourism sector, is of great importance. Panel data models are a useful and appropriate method for the analysis and modelling of tourism demand. These models consider both the time series and the cross-sectional dimensions of the data and allow for the inclusion of social variables. The results of estimation of tourism demand, through panel data models, show that the Internet and the sharp technological development have encouraged the increasing demand for tourism. The growing number of tourism companies online will naturally promote or potentiate an increase of tourism demand.

Modelling health state preference data using fixed and random effects models

The use of preference-based measures of health in the measurement of Health Related Quality of Life has become widely used in health economics. Hence, the development of preference-based measures of health has been a major concern for researchers throughout the world. This study aims to model health state preference data using a new preference-based measure of health (the SF- 6D) and to suggest alternative models for predicting health state utilities using fixed and random effects models. It also seeks to investigate the problems found in the SF-6D and to suggest eventual changes to it.

Design and implementation of a real-time data acquisition system for the identification of dynamic temperature models in a hydroponic greenhouse

This text describes a real data acquisition and identification system implemented in a soilless greenhouse located at the University of Algarve (south of Portugal). Using the Real Time Workshop, Simulink, Matlab and the C programming language a system was developed to perform real-time data acquisition from a set of sensors.

Real-time data acquisition system for the Identification of dynamic temperature models in a hydroponic greenhouse

A real-time data acquisition and identification system implemented in a soil-less greenhouse located in the south of Portugal is described. The system performs real-time data acquisition from a set of sensors connected to a data logger.