Eugenio-Martin, J.L., J.M. Cazorla-Artiles, A. Moreda and J.M. Murguia (2023)

 

Adaptive nowcasting of arrivals during health crises

 

This paper develops a new methodology to nowcast the number of arrivals during

health-related crises such as Covid-19. The methodology is adaptive, so that the

relevance of different determinants vary over time by employing hurdles that work as

‘necessary travelling conditions’. It starts with a baseline series built upon a pre-Covid-

19 trend. This series is adjusted by each hurdle. The first hurdle is the market closure;

SIR epidemiological models are applied to anticipate the dates of re-opening. The

second hurdle deals with key travelling determinants such as the income effect. The

third hurdle is the lack of confidence; this depends on the length of the recovery, and

the expected path to follow.

 

Cazorla-Artiles, J.M. and J.L. Eugenio-Martin (2023)

 

Optimal targeting of latent tourism demand segments

 

This paper identifies for the first time the optimal target markets employing the latent

tourism demand expenditure, a novel concept in tourism literature. The study quantifies

latent tourism demand between each pair of origin-destination through distinguishing

by type of tourism and seasonality. It works with market shares that are estimated via a

fractional regression model. Moreover, latent demand is clustered using a market

segmentation approach based on a latent class regression. Finally, the optimal target

markets are chosen depending on the expected latent tourism expenditure. The result

has clear policy implications in terms of which markets are promoted, the optimal

channels of communication and the maximum budget for each marketing campaign. [Paper]