Policy makers ask for spatially detailed statistical information in the assessment of the tourism impact, often asking for ad-hoc surveys for gathering additional information. To design marketing strategies and to foster the development of tourism destinations, these information should be provided with respect to the characteristics generally recognized as main determinants of individuals’ behaviour spending: socio-economic, demographic, psychographic and behavioural variables. In this chapter, we adopt data gathered from the National Frontier Survey and made available by Banca d’Italia to deliver estimates of average individual expenditure by tourist nationality, adjusting for trip-related variables, in small areas of the Emilia Romagna Region, with particular focus on Russian tourists. A Bayesian approach is adopted in order to manage estimation based on small sample sizes by borrowing strength in space and time. The approach appears promising in small area estimation for producing the spatially detailed information sought by policy makers.

Studying Russian individual consumption in small areas of the Emilia Romagna Region

GRECO, FEDELE PASQUALE;GUIZZARDI, ANDREA
2016

Abstract

Policy makers ask for spatially detailed statistical information in the assessment of the tourism impact, often asking for ad-hoc surveys for gathering additional information. To design marketing strategies and to foster the development of tourism destinations, these information should be provided with respect to the characteristics generally recognized as main determinants of individuals’ behaviour spending: socio-economic, demographic, psychographic and behavioural variables. In this chapter, we adopt data gathered from the National Frontier Survey and made available by Banca d’Italia to deliver estimates of average individual expenditure by tourist nationality, adjusting for trip-related variables, in small areas of the Emilia Romagna Region, with particular focus on Russian tourists. A Bayesian approach is adopted in order to manage estimation based on small sample sizes by borrowing strength in space and time. The approach appears promising in small area estimation for producing the spatially detailed information sought by policy makers.
2016
Russian tourism in Italy: features, dynamics, and opinions
129
152
Greco, Fedele; Guizzardi, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/585802
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