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60 Table 14. Comparison of general airport and airport-specific models with implementing a $10 drop-off fee. Portland International Airport Mode Share Policy Scenario Representative General Airport Airport-Specific Policy Scenario Access Mode Share Base Case Model Model Difference Park and Walk to Terminal 10% 12% 13% 1% Park and Ride Shuttle to Terminal 15% 19% 20% 1% Taxicab to Terminal 10% 12% 12% 0% Dropped Off at Terminal 45% 35% 31% 4% Transit to Airport 10% 11% 12% 1% Shared Van to Airport 5% 6% 6% 0% Scheduled Bus to Airport 5% 6% 7% 1% Total 100% 100% 100% Note: Totals may not add to 100% due to rounding. Source: Resource Systems Group, Inc., August 2009. volume and emissions) can be used to determine the changes rience. An example of a scenario analysis used to evaluate a from implementing a strategy, as long as the other input data strategy to address constrained parking would be estimating are available (such as vehicle occupancy by mode). However, demand and revenue at different parking rates. some of the strategies may result in a change in the vehicle Formal tools allow the user to look at a variety of outcomes occupancy rate by mode, which is not predicted by the model. related to passenger parking behavior and overall mode-share Parking facility exits (transactions) can be estimated for the distribution, which is in many cases based on relationships two parking mode categories (i.e., "park and walk to terminal" established from underlying data. The user can compare strate- and "parking and ride shuttle to terminal"), since exits are gies and understand the differences in outcomes at a certain equivalent to private automobile trips in each category, with level of reliability. The analysis results also may reveal outcomes the qualification that a change in the vehicle occupancy rate that were unanticipated by the user. Informal tools are not as by mode will influence the number of parking exits. It is not useful in comparing strategies because it is difficult to compare recommended that an airport operator use the model to esti- a range of potential results. In addition, changes in mode share mate parking revenue because the model allows for only two will not be possible to predict because the relationships between parking categories (meaning two rates) and does not consider mode preferences would not have been established. the average length of stay for parking customers (meaning that Benchmarks with the results from other airports also may it does not consider changes to the average length of stay result- provide some insights into the reasons for parking constraints ing from different strategies). Some strategies will result in a and strategies that may relieve constraints and for making change in the length of stay distribution by facility, which will generalized comparisons with other airports. However, a wide affect revenues received. range of variability typically can be found in these ratio-based benchmarks given the unique characteristics of each airport. Differing characteristics that may influence the ratio-based Informal Tools benchmarks include the percentage of airline passengers park- An airport operator may also use informal tools to estimate ing at an airport, the strength and availability of privately oper- the effects of strategies being considered to address constrained ated off-airport parking, and, most importantly, whether the airport parking. One approach is scenario analysis, which is existing parking supply is adequate or is currently constrained, the process of predicting, analyzing, and preparing for a range among other factors. Therefore, when airport operators con- of effects associated with implementation of a variety of strate- sider which airports to benchmark, they should consider those gies to address constrained parking. The effects evaluated will with similar characteristics and benchmark against some with be based on the airport operator's goals and objectives related constrained parking and some without constrained parking. to the parking program. Based on estimates of changes in park- Benchmarks related to parking supply include the following: ing behavior at varying levels, effects evaluated may include revenues, vehicle trips generated by airline O&D passengers, Public parking spaces per O&D passenger--Because the and changes in vehicle emissions. The analysis may be based majority of parking activity is generated by resident airline on experience, operational intuition, or benchmarks obtained passengers, the ratio of parking spaces available per resident from airports with similar operating environments and expe- O&D passenger is a meaningful benchmark that attempts

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61 Table 15. Comparison of rates: relationship of daily parking rates to rates for other parking products. Comparison to Daily Rates of Other Parking Daily Parking Rate Products Hub (Long-Term or Daily Short-Term or Economy Airport Classification1 Parking Facility) Hourly Parking Valet Parking Parking Boston Logan International (BOS) Large $24 75% Chicago O'Hare International (ORD) Large $30 167% 150% 30%53% McCarran International (LAS) Large $14 150% 57% Miami International (MIA) Large $15 200% 200% 53% San Diego International (SAN) Large $21 124% 143% 48%76% Seattle-Tacoma International (SEA) Large $26 135% Tampa International (TPA) Large $15 133% 167% 60% Washington Dulles International (IAD) Large $17 212% 112% 59% Bob Hope (BUR) Medium $20 150% 100% 45%55% Oakland International (OAK) Medium $22 145% 177% 68% Port Columbus International (CMH) Medium $17 159% 118% 35%53% Portland International (PDX) Medium $14 171% 214% 57% San Antonio International (SAT) Medium $10 220% 60% Huntsville International (HSV) Small $8 150% 75% Tulsa International (TUL) Small $10 100% 180% 60% Notes: means data are not applicable. 1 Hub size is defined by the FAA for commercial service airports based on the community's share of total U.S. passenger boardings accommodated. Large-hub airports accommodate 1% or more of annual passenger boardings; medium-hub airports accommodate at least 0.25%, but less than 1% of passenger boardings; and small-hub airports accommodate at least 0.05%, but less than 0.25% of passenger boardings in the United States and its territorial possessions. Source: Ricondo & Associates, Inc. and DMR Consulting, based on airport case studies and representing conditions for different time periods (case studies collected from November 2008 through February 2009). (115) to normalize the parking supply to potential customers. Relationship between rates--The relationship between This information can be used to consider the supply needed rates for different parking products may assist airport oper- in the future compared to forecast growth in number of air- ators in adopting rates that are different from rate changes line passengers. Other public parking ratios that may be con- made in the past. sidered for different purposes include (1) airport-operated Mode share--The nature of the airline passenger customer spaces per O&D passenger, (2) airport-operated spaces per base, as well as the viable modes available to airline passen- resident O&D passenger, (3) total public parking spaces gers based on service area, levels of service, and prices in (airport operated plus privately operated) per O&D passen- relation to other modes will all influence the mode-share ger, and (4) total public parking spaces (airport operated distribution at an airport. There may be value in compar- plus privately operated) per resident O&D passenger. ing the airport's mode share to mode shares at similar air- Composition of parking supply--Types of parking by ports, but it is likely that the comparison will have less value O&D passenger or resident O&D passenger, or the per- than the other benchmarks listed. centage of supply of a variety of parking products, such as long-term parking, short-term parking, or satellite park- Table 15 presents a comparison of daily parking rates to other ing, may provide insight. parking rates at the airports included in ACRP Project 10-06.