Abstract
Business travel demand in official statistics is often measured by means of households/travellers survey. Such approach produces very little evidence about expenditure and demand structure because for that purpose others statistical units should be sampled. Enterprises - that actually buy business travels - are rarely interviewed. The application of CHAID technique to data from an explorative sampling survey on the Italian enterprises shows statistically significant relationships among business travel expenditure, enterprise size and economic sector. The multivariate analysis allows to derive the definition of the optimal strata design for survey on business travel through enterprises interviews.
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References
EUROSTAT (2000): Balance of Payments Working Party executive summary Technical group travel report. Kirchberg, Luxembourg.
KASS, G. V. (1980): An exploratory technique for investigating large quantities of categorical data. Applied Statistics, 29, 119–127.
OECD (2001): Measuring the Role of Tourism in OECD Economies The OECD manual on tourism satellite accounts and employement, enterprise, industry and service. OECD, Paris.
TASSINARI, F. (1994): Turismo culturale e turismo di studio, Rivista italiana di economia demografla e statistica, vol. XLVIII, 1–2.
WOOLLETT, G. and TOWSEND, J. and WATTS, G. (2002): Development of QGEM-T-a Computable General Equilibrium Model of Tourism, Office of Economic and Statistical Research working paper. Queensland Treasury, Australia.
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© 2005 Springer-Verlag Berlin · Heidelberg
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Guizzardi, A. (2005). A New Approach in Business Travel Survey: Multivariate Techniques for Strata Design. In: Bock, HH., et al. New Developments in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27373-5_37
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DOI: https://doi.org/10.1007/3-540-27373-5_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23809-6
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