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90 I N N O VAT I O N S I N T R AV E L D E M A N D M O D E L I N G , V O L U M E 2
underreporting rate to vary greatly (in Austin the rate dures to reduce the magnitude of trip underreporting in
was 12% or 31%, depending on the time threshold). future travel surveys.
· The actual data collection methods and instruc-
tions to respondents can also influence the calculation of
trip underreporting rates. In most studies, respondents GPS AND TRAVEL SURVEY DATA
are instructed not to report trips out of the geographi-
cally defined study area and trips for commercial pur- The empirical analysis in the current paper uses data
poses. However, most early trip-detection algorithms did extracted from the Kansas City Regional Household
not distinguish between these types of trips and those Travel Survey conducted in spring 2004 under the spon-
reported by respondents, resulting in overreported trip- sorship of the Mid-America Regional Council and the
underreporting rates. In addition, as determined in the Kansas and Missouri Departments of Transportation. As
Laredo study, the survey process does not directly collect part of the Kansas City survey, complete demographic
information about trips made by nonhousehold mem- and travel behavior characteristics of 3,049 randomly
bers driving the GPS-equipped vehicles. sampled households were obtained, including details
about 32,011 trips for 7,570 household members. The
On the basis of a review of literature on trip underre- GPS component of the study involved equipping the vehi-
porting in regional household travel surveys and the cles of 294 households with GPS equipment to record all
development of associated correction factors, most trip vehicle travel during the assigned travel period. Of the
underreporting is associated with households that own 294 households, both computer-assisted telephone inter-
three or more vehicles, households with incomes of less view (CATI) and GPS data are available for 228 house-
than $50,000, and respondents under the age of 25. holds. All subsequent analyses in the current paper focus
From a travel behavior perspective, respondents who on these 228 households, corresponding to 377 drivers
travel substantially make several short trips (less than 5 and 2,359 vehicle trips. (For more details on the charac-
min) and make trips of a discretionary nature are most teristics of these GPS households compared with the gen-
likely to "forget" to record this travel (as has been sug- eral survey participants as a whole, see NuStats.)
gested on parallel literature about trip chaining). Of the 377 drivers, 269 (or 71%) accurately reported
The studies to date have clearly aided in identifying all travel in their CATI survey, while 108 (or 29%) had
factors associated with trip underreporting in regional at least one instance of a trip that was not reported. [A
travel surveys. In this paper, the authors contribute to subtle, but important, point is that, for the underreport-
this existing literature and continuing discussion about ing analysis, the authors focused on the CATI-reported
GPS technology in travel surveys in several ways. First, vehicle trips across all individuals in the household who
in the current study (and unlike earlier studies), both the drove each GPS-equipped vehicle. This focus allows a
presence of trip underreporting by an individual and the fair comparison between the CATI-reported vehicle trips
level of trip underreporting by the individual are mod- and the GPS-detected vehicle trips. However, rather than
eled. The separation of the presence of trip underreport- confine the analysis of the determinants of underreport-
ing from the level of trip underreporting recognizes that ing to household-level characteristics, also included were
different explanatory variables may affect these out- person-level characteristics to accommodate person-
comes, that the same explanatory variable may affect specific tendencies to underreport. To accomplish this,
these outcomes differently, or both. Second, the joint the authors identified a primary driver for each GPS-
model also recognizes that the likelihood of trip under- equipped vehicle on the basis of information provided by
reporting and the level of trip underreporting may be respondents and used these primary-driver characteris-
related to one another. For example, it is conceivable (if tics as explanatory variables in the analysis (along with
not likely) that individuals who are, by nature, less likely household demographics). This approach is reasonable
to be responsive to surveys are the ones who underreport because each vehicle in this study was predominantly
and underreport substantially. Similarly, individuals who used by only one primary driver in the household (espe-
are, by nature, interested in the survey would be the ones cially within a short period of time, such as a survey day).
less likely to underreport at all, and even if they did Specifically, in the sample used for our analysis, there
underreport, would do so only marginally. Third, in was car sharing of some form among household mem-
addition to jointly modeling trip underreporting and the bers in 6% of all households.] Among the 108 respon-
level of trip underreporting, the empirical analysis in the dents who underreported, 53 (49%) missed one trip, 22
current study considers a comprehensive set of variables (20%) missed two trips, 11 (10%) missed three trips, six
related to driver demographics, driver travel characteris- (5.5%) missed four trips, and 16 (14.5%) missed five or
tics, and driver adherence to survey protocol. Finally, more trips. There was a narrow, long tail in the 5
this work translates the empirical analysis results to rec- missed-trips category, with one individual underreport-
ommendations about household travel survey proce- ing 17 trips.
