2009
DOI: 10.1016/j.jtrangeo.2008.08.004
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Spatial evolution of airport traffic and air transport liberalisation: the case of Greece

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Cited by 62 publications
(40 citation statements)
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References 20 publications
(18 reference statements)
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“…This dataset provides information about estimated population density for the EU27, Croatia and Moldova at a pixel size of one hectare. This is a level of detail much higher than the NUTS 3 level used in previous analyses (e.g., Redondi et al, 2013;Scotti et al, 2012;Lieshout, 2012;Papatheodorou and Arvanitis, 2009;Grosche et al, 2007). Table 1 shows the substantial improvement in terms of data disaggregation that CORINE represents over the NUTS units.…”
Section: Datamentioning
confidence: 87%
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“…This dataset provides information about estimated population density for the EU27, Croatia and Moldova at a pixel size of one hectare. This is a level of detail much higher than the NUTS 3 level used in previous analyses (e.g., Redondi et al, 2013;Scotti et al, 2012;Lieshout, 2012;Papatheodorou and Arvanitis, 2009;Grosche et al, 2007). Table 1 shows the substantial improvement in terms of data disaggregation that CORINE represents over the NUTS units.…”
Section: Datamentioning
confidence: 87%
“…European studies considering population in the catchment area usually take the NUTS 3 level 1 to aggregate population values around the airport (e.g., Papatheodorou and Arvanitis, 2009;Grosche et al, 2007). Two recent studies use lower levels of data aggregation than NUTS 3, Redondi et al (2013) use municipality level units and Scotti et al (2012) use zip codes, both represent an advance.…”
Section: Introduction: the Modifiable Area Unit Problemmentioning
confidence: 99%
“…Lipczynski et al, 2009) argue that the Herfindahl-Hirschman Index (HHI) is one of the best candidate indices to measure concentration because it meets all the above criteria. The HHI is defined as the sum of squared market shares and ranges between zero (in case of a market with infinitesimal firms) and 10,000 (in case of a monopoly); values over 1,800 are usually indicative of a concentrated market (Papatheodorou and Arvanitis, 2009). Hannah and Kay (1977: 50-52) also stress that measures of inequality (such as the Gini coefficient to be discussed below) violate some of the axioms stated above and hence should not be used to measure seller concentration.…”
Section: Methodology and Operationalisation Of The Adimentioning
confidence: 99%
“…One method is to normalise the Gini index by fixing 'n' across time (e.g. Papatheodorou and Arvanitis, 2009). In this way, the confounding effects on Gini, of changes in airline network size (in terms of nodes connected), and the changes in the pattern of capacity distribution across the network, can be separated enabling the analyst to focus on the latter.…”
Section: Methodology and Operationalisation Of The Adimentioning
confidence: 99%
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