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The Evolving Air Transport Industry

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xiv INTRODUCTION TO AIR TRANSPORT ECONOMICS<br />

7.3 Concentration of the top ten global airports by alliance in terms<br />

of ASMs 174<br />

8.1 Market continuum 180<br />

8.2 Total revenue, average revenue and marginal revenue 183<br />

8.3 Profit-maximizing price for various price elasticities 196<br />

9.1 Market continuum 206<br />

9.2 Large aircraft manufacturers' market share 213<br />

9.3 Cournot theory progression 218<br />

9.4 Market share of Internet browsers 226<br />

9.5 US airlines' available seat miles, 2005 227<br />

9.6 Four-firm concentration ratio 228<br />

9.7 US domestic Herfindahl Indices, 1998-2005 229<br />

9.8 Pre-merger market share 230<br />

9.9 Post-merger market share 230<br />

10.1 Advantages and limitations of qualitative forecasting 240<br />

10.2 Advantages and limitations of quantitative forecasting 243<br />

10.3 Variance calculation of class average (1) 244<br />

10.4 Variance calculation of class average (2) 245<br />

10.5 Time-series data of bookings for a DirectJet flight 248<br />

10.6 Three-day and five-day moving average forecasts 249<br />

10.7 Exponential smoothing forecasts, using two different smoothing<br />

constants 251<br />

10.8 Expanded data set for DirectJet 252<br />

10.9 Mean squared error calculation for moving average forecasts 255<br />

10.10 Mean squared error calculation for weighted moving average forecasts 256<br />

10.11 Mean squared error calculation for exponential smoothing forecasts 256<br />

10.12 Mean absolute deviation calculation for moving average forecasts 257<br />

10.13 Mean absolute deviation calculation for weighted moving average<br />

forecasts 258<br />

10.14 Mean absolute deviation calculation for exponential smoothing forecasts 258<br />

10.15 Data set for the relation between consumption and income (1) 259<br />

10.16 Data set for the relation between consumption and income (2) 261<br />

10.17 Residual values for forecasts of consumption 263<br />

10.18 Coefficient of determination calculation 264<br />

10.19 Data set for the relation between consumption and income (3) 265<br />

10.20 Data set for forecasting demand for the Orlando-Los Angeles flight 267<br />

10.21 Model summary of demand forecast for the Orlando-Los Angeles<br />

flight from SSPS 268<br />

10.22 ANOVA for the demand forecast for the Orlando-Los Angeles flight 270<br />

10.23 Coefficients' significance for the demand forecast for the Orlando-Los<br />

Angeles flight from SSPS 271<br />

10.24 Correlation matrix for independent variables from SSPS 272<br />

11.1 Load factor for People Express 281<br />

11.2 Consumer surplus 285<br />

11.3 Fare class advance purchase restrictions 290<br />

11.4 Fare class Saturday Night stay restrictions 290<br />

11.5 Fare class frequent-flyer mileage 291<br />

11.6 Fare class refundable restrictions 291

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