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Analytical Considerations
A variety of considerations need to be weighed when using or interpreting the findings reported in
this chapter. These considerations include the size and nature of the samples surveyed or
investigated, the use of control groups, the definition of TOD, and the difficulty of isolating causality
of the effects under study. When working with the findings, their significance should be assessed in
the context of these considerations.
Key TOD travel characteristics studies have had difficulty achieving adequately large and reliably
representative samples of survey respondents. Low survey response rates introduce a greater
potential for self-selection bias among the individuals from whom survey responses are obtained.
As the response rate declines, the confidence that one can place in the results and their transferability
declines as well. Regrettably, the phenomenon of low response rates has become more common
among travel behavior surveys as sampling costs have increased and subject willingness has
decreased. TOD resident and visitor/worker surveys have been particularly affected. Sample rates
are reported here, where available, to enable the reader to make an informed evaluation of likely
findings reliability.
Several studies rely on Census data as the source of baseline comparisons in lieu of having
collected study-specific control group data. Although this approach can save on data collection
costs, it yields a data set in which baseline (Census) survey procedures are likely not fully
comparable to the TOD survey procedures, rendering survey process effects and differential
sample biases more likely and harder to assess. Moreover, it builds any limitations in the Census
survey instrument into the study findings, including the fact that the Census has only asked travel
questions about the Journey to Work. The 2000 Census survey instrument asked about the "usual"
mode of travel to work rather than the mode used on a specific day, which leads to under-reporting
of transit use by occasional users and over-representation of transit use by not-quite full-time
users.
Caution should be exercised in directly transferring the results from one application or experience
to another situation. This may be especially critical in the case of TOD, where few before-and-after
data-driven studies exist, and a large proportion of the quantitative findings derive solely from
California and Portland, Oregon, data. The notable differences illustrated by the relatively stronger
LRT-based TOD travel demand effects encountered in Portland compared to weaker LRT-based
TOD effects assayed in certain California locations, and the stronger HRT-based TOD effects in the
San Francisco Bay Area compared to Los Angeles, deserve attention. It is helpful that these
differences mark out broad ranges within which many potential TOD applications nation-
wide should fall.
As is evident in the "Types of Transit Oriented Development" discussion it is impossible to develop
a simple litmus test for what is or isn't TOD. As a result, many studies look at adjacency to transit as
a surrogate measure. Survey and study results for residents or workers located proximate to transit
within various manifestations of TODs and other transit-adjacent development may be lumped
together. Inconclusive findings regarding TOD travel impacts or TOD success may in part derive
from including travel behavior and related outcomes observed in transit-adjacent constructs that do
not possess critical elements generally perceived as being essential characteristics of good TOD
(Hendricks, 2005).
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Researchers have noted the interactive nature of various factors, not all transportation-related, that
influence the effectiveness of TOD in altering travel behavior. Different characteristics of the travel
experience may relate to urban form, urban design, and transit service variables in a synergistic man-
ner. In isolation they may not have the same effect as they do together (Hendricks, 2006). These
dynamics, in combination with the huge variety of TODs and other forms of transit-adjacent devel-
opment, make it quite difficult to sort out the details of causality: What is it exactly that produces
observed phenomena such as higher transit use in proximity to transit stations? High-density, mixed-
use development and high levels of transit service are often present together at sites exhibiting a high
transit commute mode share and a high midday non-motorized mode share. Unknowns involving
causality make it difficult to separate the contribution of each site element to the resulting transit and
pedestrian activity (Douglas and Evans, 1997).
Involved is not only the question of what factors are at play, but also the issue of direction of causal-
ity. For example, is observed lower auto ownership within TODs the result of TOD characteristics
leading residents to own fewer autos or the result of families with lower auto ownership actively
choosing to live in TODs? The following additional examples are only a small sampling of causality-
related analytical problems from among the many that make TOD travel-demand effects analysis
particularly challenging.
External factors may in part be the cause of observed travel demand changes. Much of the TOD
research cited in this chapter was carried out in recent years. The mid-years of this period coincided
with an economic downturn across the United States that resulted in somewhat less commuting in
most markets. Ridership on many transit systems dropped during the period. These events followed
an earlier period of growing transit ridership which coincided with an economic boom and height-
ened gas prices. As a result, the findings from some studies may be clouded by external economic
influences (Pucher, 2002). There is always the possibility of various unreported confounding factors.
A few of the cited studies used survey questions asking respondents to isolate the significance of ele-
ments responsible for the experience they report. The value of this approach to probing causality is
open to question. Sometimes, the combination of factors responsible is difficult for respondents to
isolate. For example, respondents may underreport the significance of elements that may be taken
for granted but are in fact quite important. Sidewalks are a case in point. They may be taken for
granted, but were they not present in a high-density TOD context, the pedestrian friendliness of a
street would be dramatically degraded.
Likewise open to question are the importance and effects of attitudes relative to TOD attributes in
shaping TOD travel behavior outcomes. Resident self-selection and associated attitudinal
influences have been a particular concern to some investigators. For further discussion of this
particular consideration, see "Underlying Traveler Response Factors"--"Self-Selection of
Residents." Still other concerns, in addition to those highlighted above, are relevant in assessment
of TOD effects as well as evaluation of any traveler response findings. Chapter 1, "Introduction,"
offers additional perspectives under "Use of the Handbook." See especially the subsections
"Handbook Application," "Degree-of-Confidence Issues," "Impact Assessment Considerations,"
and "Demographic Considerations."
In view of the uncertainties inherent in traveler response research in general and TOD
research in particular, notes are included where appropriate in the main body of the chapter
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