Talking Freight:

Establishment Surveys

State and Local Experience

Johanna Zmud

Mia Zmud

Chris Simek

2 NuStats, Austin, Texas – 12/ 10/ 08

Purposes For modeling

For policy, decision-making

For improved understanding of freight movements

Sample Units Drivers / Carriers

Shippers / Receivers (firms and households)

Database Contents Vehicle characteristics, freight characteristics, driver characteristics, commodity

type and quantity

Origins, destinations, routes traveled, stops, mode shares, travel times and distance

Satisfaction, attitudes, opinions

State and Local Freight Surveys

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Defining the universe and survey population

Adequacy of sampling frames and coverage errors

Sample size calculation

Sampling Challenges

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Complexity and extent of data elements

Limitations to respondent knowledge

Specificity of data required

Instrument Development Challenges

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Data Collection Challenges

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Policy-making Value of Time Survey of Shippers, Georgia I-75

Modeling Commercial Vehicle Travel Diary Survey, Phoenix

Understanding Freight movements NYS DOT Commercial Vehicle Driver Survey

Example Projects

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Truck-only Toll (TOT) Lane Study Assess opinions of shippers and drivers

that use corridor regarding TOTs

Determine pricing structure for TOT

Universe Commercial Users of the I-75 Corridor

Data Descriptive and Preference (VOT)

#1 Value of Time Survey of Shippers

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Universe Trucking companies that contain transport vehicles with 4 or

more axles that operate on the corridor

Dual Sampling Frame FMCA Commercial database – subset of carriers in

Georgia, Alabama, Florida, South Carolina, Tennessee, and North Carolina (N=8409)

Database developed in-field during operator survey (N=215)

Instrument Screening (recruitment)

Attitude / opinion, Trips, Stated Preference

Data Collection CATI – 176 completed interviews Web – 156 completed interviews

Shipper Survey Methods

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Lack of statistical control Sample from unknown population

Time-consuming 47% Noncontacts

An average of 10.3 contact attempts per CATI complete

CATI length: 13.4 minutes

Web application after-the-fact to enable shippers to participate on their own time

Web length: 14.6 minutes

Overcoverage of sampling units in FMCA database 43% of sample records were not qualified to participate in survey

Nonresponse 32% response rate

40% refusal rate

Shipper Survey Challenges / Lessons

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Purpose Recalibrate Maricopa Association of Governments (MAG) truck model to

reflect emerging travel realities and address new planning challenges

Survey to provide data for the model update

Approaches

Trip Diaries

Operator Surveys

Service Truck Activity

#2 Commercial Vehicle Travel Diary Survey

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Universe Firms in modeled area that own and operate

trucks (FHWA Class 5 and larger; two axel-six wheels)

NAICS: mail/parcel, local pickup and delivery, construction, retail, for-hire

Sampling Frame MAG Employer Database (N=11,652)

Probability sample stratified by number of employees

Instrument Screening (eligibility & recruitment)

Diary: Driver information, Truck information, Trip information

Travel Diary Survey Methods

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Incidence Types and number of trucks, firms often performed distribution-related delivery

services (warehouse distribution)

Supplemental Frames: FleetSeek, ATA Fleet Directory, US Data Corp.

Non- Contacts / Qualified Sample Slowed Recruitment Research updated numbers; 15 call attempts

In-person visits used to boost recruitment

Multiplicity in-field sampling

Diary Retrievals Retraction of agreement to participate

Low participation by truck drivers (Spanish version necessary)

Extend data collection from 4 to 8 weeks to allow for temporal effects

Nonresponse 21% response rate, 66% refusal rate

Travel Diary Survey Challenges / Lessons

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Truck Drivers at NYSDOT Rest Areas, NYSTA Travel Plazas, Private Truck Stops

Strategic planning study

Supplement Transport Canada interviews at CA/NY border

Purposes: Facility locating, assess parking shortage, commercial vehicle routing, placement of NYSDOT traffic counters, etc.

#3 Commercial Vehicle Driver Survey

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Universe FHWA vehicle class 8-13

30-total sites, with two days of collection at each

Instrument Tablet PC with used to collect detailed information from over 1,000 truck drivers

Real-time geocoding and route verification

Data Elements Truck, freight, facility characteristics

Driver attitudes and opinions regarding parking availability

Reasons why they stopped at this facility

Route choice

Driver Survey Methods

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Driver Survey Instrumentation

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Logistical Sites spread out across the state and, at times, separated by more than 100-miles. Lots of travel costs.

Need to coordinate with interviewers, state police, NYSDOT and NYSTA personnel, facility operators and traffic count contractors to ensure everyone knows schedule and expectations.

Survey Participation Survey is long, and it can be difficult to keep drivers on track (participation rate high, but key was listening to

them “vent”)

Good field staff and proper training one of the key’s to success. The more they know, the better driver response you will have.

Data Collection Pilot is vital to success

Driver Survey Challenges/ Lessons

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Concluding Remarks

Overlap in challenges at national / state local levels

Solutions unique to information needs Vehicle activity (travel patterns) is most often primary focus Commodity flow has been less important

No single type (e.g., establishment, operator, distributor) or mode (e.g., intercept, telephone, web) meets needs at local level The value of each is leveraged when used together

Wide variation in response rates and factors impacting response

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Further Information

Johanna Zmudjzmud@nustats.com

Mia Zmudmzmud@nustats.com

Chris Simekcsimek@nustats.com