Use/Demand

• Concepts/units

• Methods

• Use in Planning– Management/operations– Evaluation– Needs assessment– Forecasts

Why Measure Use

• Operational decisions– maintenance, staffing, budget allocations

• Needs

• Performance measure/evaluation

What to measure

• Use units – individual, groups…visit, visitor, trip, day, RVD, vehicle entry,…

• Level of detail/aggregation– Temporal– Spatial– By activity– By user characteristics

Use estimation questions

• Measure or estimate use at existing site

• Forecast use at existing site

• Forecast changes in use– New sites/products– Change at site or within the environment

Key determinants of use• Population size & characteristics• Distances to markets• Tastes & preferences• Prices• Substitutes• Quality/quantity of supply• Promotion/information• Weather/climate

Methods for estimating use

• On-site techniques– Counting devices– Observation– Surveys (sample or census)

• Off-site– Use prediction Models – e.g. Gravity model

• Trip generation

• Trip distribution

Double Sampling Technique

• 1. Select a variable that is easily measured• E.g. water meter - W

• 2. Establish a relationship with use• U = a * W + c

• Calibration via “double sampling” /linear regression

• U = 1/3 * W - 2

• 3. Regularly measure W and apply equation

• 4. Periodically recalibrate

See page 21 of lecture handouts for details

Sampling to estimate use

• Stratify time periods into H, M, L use• E.g. weekend, weekday, am, pm, eve

• Sample representative periods within each stratum

• Measure use during each sampled period, compute averages

• Expand from sample to population

Lansing Trail Strata: Use counts for one hour

Day Am (8-12) Pm (12-4) Eve (4-8)Weekday 7,8,18

Avg =11

3,8,8,8, 101

Avg= 25

78,59,139,13,72

Avg=72

Weekend 11, 21, 9

Avg= 14

8, 6, 116

Avg =43

8,104,123

Avg =135

Overall avg = 42,Total use = 42 *12 hours*31 days = 15,624

Gravity Model

• Ti,j = K* Pi *Aj / D2ij

• Where

– Ti,j = trips from origin i to destination j

– Pi = population of origin I

– Aj = measure of attractiveness of destination j

– Dij = distance from i to j (or cost)

– K =calibration constant

Linear regression model

• V = a0 + a1 X1 + a2 X2 + a3 X3 +… an Xn

• Where

– a’s are coefficients to be estimated– X’s are independent variables/use predictors– E.g. V = participation rate

» Frequency of participation

» Visits in past year

– X’s : age, income, gender, location, weather…

Demography

• Forecast size, geographic distribution, and age-sex composition of the population

• Census 2000 data

• American Fact Finder

Participation by demographic characteristics

• Age

• Income

• Gender

• Rural/urban, location

• Racial/ethnic group