Bibliography and Technical Appendices to Intercity Passenger Rail in the Context of Dynamic Travel Markets (2016) / Chapter Skim
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From page 97... ...
Technical Appendix: The Scenario Analysis Tool 97 TECHNICAL APPENDIX: MODEL APPLICATION FOR SCENARIO ANALYSIS This technical appendix to NCRRP Report 4 now presents the full description of the scenario testing tool, which takes the form of a Workbook of spreadsheets in Microsoft® Excel format. Chapter Six presented a shortened, edited version of this full description of the scenario testing tool.
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Technical Appendix: The Scenario Analysis Tool 98 - Psize: travel party size for actual reference trip, including the respondent - Mode: the mode used for the actual reference trip (car, bus, rail or air) All other variables on the sheet are variables used directly in the models that are derived from the variables above.
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Technical Appendix: The Scenario Analysis Tool 99 Coeffs: This worksheet has all model coefficients for each person in the sample. These were copied from the "original coefficient table" sheet, using the coefficients corresponding to each person's reference trip purpose.
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Technical Appendix: The Scenario Analysis Tool 100 3. Sample expansion and initial model calibration Because we are using only a partial sample of trips in the Northeast and Cascade Corridors, it was useful to first check the numbers of trips by mode and corridor against similar numbers from other corridors.
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From page 101... ...
Technical Appendix: The Scenario Analysis Tool 101 4. Changing the demographic distributions One way that the user can define future scenarios is to adjust the population distribution by gender, age group, education level, employment status and/or income level.
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Technical Appendix: The Scenario Analysis Tool 102 Under $25,000 5.6% 6.3% 6.9% 8.9% $25,000 to $49,999 10.4% 15.3% 14.0% 12.9% $50,000 to $74,999 12.3% 16.9% 16.2% 15.3% $75,000 to $99,999 19.0% 20.5% 20.5% 21.3% $100,000 to $149,999 (base, no ed) 23.7% 24.3% 22.3% 21.6% $150,000 to $199,999 12.7% 9.0% 9.3% 10.3% $200,000 and up 16.3% 7.7% 10.8% 9.7% Total 100.0% 100.0% 100.0% 100.0% Table 3: Change in rail trips by purpose for selected changes in demographic distributions Business Vacation Visit Other Total Female share up 10%, male share down to compensate -0.6% -1.2% -0.5% -2.2% -0.9% Age over 65 share up 10%, under 35% down 5% -0.1% 1.1% -0.1% -0.9% 0.1% Not college grad share down 10%, college grad share up to compensate 1.4% 1.0% 1.5% 1.9% 1.4% Not employed share down 10%, employed share up to compensate 0.4% -0.6% 0.5% 1.5% 0.3% Income shares below 50k up 10%, income shares above 150k up 10%, incomes 50-100 k down 10% -0.4% -0.5% 0.4% 0.7% -0.1%
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Technical Appendix: The Scenario Analysis Tool 103 5. Changing the mode travel times and costs Table 4 shows how the user can adjust the travel times or costs for specific scenarios.
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Technical Appendix: The Scenario Analysis Tool 104 6. Changing the attitudinal variables The spreadsheet also allows the user to simulate predefined shifts in the four latent attitudinal variables, where one or more groups defined by age, gender, education and/or employment status take on the attitudes of another group along that demographic dimension.
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From page 105... ...
Technical Appendix: The Scenario Analysis Tool 105 trips would decrease by almost 6%, due to opposite offsetting effects as described for the shift to "younger" attitudes. The most realistic future trend in attitudes by age may be the "shift all ages one group younger".
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From page 106... ...
Technical Appendix: The Scenario Analysis Tool 106 Table 9: Change in rail trips under the four scenarios, relative to the Base scenario Name Change in Rail Trips 1 Pessimistic for Rail 2 Mixed A 3 Mixed B 4 Optimistic for Rail Business -5% 13% 3% 22% Vacation -4% 8% 2% 14% Visit Friends/relatives -2% 9% 4% 15% Other -11% 14% 9% 35% Total -4% 10% 4% 18% The results are that the pessimistic scenario results in a 4% drop in total rail trips, while the optimistic scenario results in an 18% increase. The mixed scenarios result in a 10% and 4% increase in rail trips respectively.
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