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The key employer characteristics of the 82-program sample are as follows (size of sample sub-set
shown in parentheses):
· Employment Type:
Professional/Office (25)
Commercial/Service (8)
Manufacturing/Industrial (14)
Government (10)
Utility (8)
Medical Institution (6)
University (4)
Miscellaneous Research or Non-Profit Institution (7)
· Number of Employees:
10,000 or more (8)
5,000 to 9,999 (7)
1,000 to 4,999 (26)
500 to 999 (5)
100 to 499 (34)
less than 100 (2)
· Location:
Central Business District (CBD) (14)
CBD Fringe (9)
Suburban CBD (14)
Suburb (10)
Office Park (13)
Campus (12)
Exurban/Rural (10)
· Transit Availability:
High (24)
Medium (18)
Low (40)
· Parking Conditions:
Restricted Parking (34 with, 48 without)
Parking Fees (30 with, 52 without)
Inferences from the 82-program sample are presented together with results of synthesizing avail-
able TDM travel demand impact studies and research. In most instances the one is supportive of the
other, but in some cases disparate findings illustrate inability to draw definitive conclusions and
corresponding need for further research.
Response to Support Actions
Support actions are arguably the most basic initial strategies an employer can implement when
creating an employee TDM program. Frequently, low utilization of alternative modes for commut-
ing or of alternative work arrangements such as telecommuting or CWW is a result of low aware-
ness and poor information. Several studies have shown that even in an employment setting where
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the employer is offering a wide array of transportation options and benefits, a substantial percent-
age of employees are unaware or under-informed regarding the nature and availability of these
options. This aspect of awareness is covered in more detail in the "Individual Behavioral and
Awareness Considerations"--"Awareness and Comprehension of Options" discussion within the
"Underlying Traveler Response Factors" section. A primary function of TDM support actions is to
increase knowledge and awareness, not only of reasons why changing commute habits is impor-
tant, but--most importantly--what means exist to make that change and what advantages may
come to the employee for changing.
However, as important as support actions are for directing attention to an employer TDM pro-
gram, many programs rely too heavily--or even exclusively--on support actions while ignoring
measures shown to produce more substantive behavioral change. Support actions are perhaps best
viewed as a catalyst--important in stimulating the reaction, but generally with a minimum role in
the reaction itself. Regardless, many employers or institutions have tried to use a rigorous program
of marketing and promotion to raise employee consciousness levels, hoping to change the "cul-
ture" in accepting alternative choices.
Support Action Insights from the 82-Program Sample
Because there are so many TDM strategies that fall in the category of support actions, and with
countless combinations and renditions of those strategies, a typology has been used to examine the
relative effectiveness of different levels of employer support. The 82-program sample has been cat-
egorized into levels of high, medium, and low support, based on the range of strategies employed
and the level of intensity with which they are applied.
In general, a low-support program is one in which the employer shows little or no active effort in
promoting alternative commuting habits to employees. For example, such employers may allow
employees to participate in rideshare matching or allow the transit agency to drop off literature,
but will not themselves get involved in the process. In a medium-support program, by the defini-
tion used here, the employer makes a conscious effort to get involved. There seems to be good spirit
behind providing information about commute options and programs (inside and outside the orga-
nization), an employee transportation coordinator is appointed (even if only part time), and there
is an openness to assisting with ridesharing (matching), transit (pass sales), and promoting the use
of these programs. In a high-support program, the employer appears to be applying just about
every strategy possible, even though in some cases the applicability or objective may not be clear.
Table 19-1 provides an employer trip reduction performance comparison of programs that incor-
porate high, medium, and low levels of support actions. This is the first of a number of tables of
this genre. In these tables, vehicle trip reduction strategies are cross-classified, either with each
other or with ambient conditions such as transit availability. Drawing from the 82-program sam-
ple, the VTRs of programs that match each of the strategy/strategy or strategy/condition combi-
nations defined by the table's columns and rows are averaged using unweighted computations.
These program average VTRs are the percentage values displayed in each cell of the table defined
by the column and row strategies/conditions.
Just below each VTR, in parentheses, is the number of programs out of the 82-program sample that
have met the combination criteria and have been used in calculating the average. In the tables these
counts are identified as sample size. It is crucial to remember that the VTR convention is to show
vehicle trip reductions (or the degree to which vehicle trips are less than in baseline sites) as posi-
tive numbers, reflecting that vehicle trip reduction is the TDM objective. The occasional negative
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VTR implies that the average in question reflects vehicle trip rates actually greater than the aver-
age baseline values with which they were originally compared.
As an example, take the "28.4%" value near the upper left-hand corner of the table. It is in the high
employer support level column and the high transit availability row. Below it is the sample size of
"(10)." This indicates that out of the 82-program sample, 10 programs have been found to be char-
acterized both by a high level of employer support actions in their TDM programs and location
in areas of high transit availability. The simple average VTR of these 10 programs has been calcu-
lated to be 28.4 percent. The fact that it is positive suggests success in trip reduction in connection
with the high-transit-availability location of the 10 sites, the high level of support actions applied,
and also (importantly), whatever other TDM actions these particular 10 programs may have also
included. The VTR value may be compared with others in the table to begin to infer the effect of
different combinations of TDM actions and situations.
In the "All" row, Table 19-1 first compares VTR performance with reference to the level of employer
support actions included in the programs. The table then connects the support program levels with
other important characteristics of the sites or of the TDM programs. Looking only from the perspec-
tive of level of support, the data suggest that employers or institutions offering high levels of sup-
port in their programs, with a 19.0 percent average VTR, performed better than medium-level
support (15.9 percent VTR) and low-level support (15.0 percent VTR) programs.
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Table 19-1 Vehicle Trip Reduction Percentages Related to Support Actions and Levels
VTR by Level of Overall Employer Support (Sample Size)
Other Conditions High Medium Low All
All 19.0% 15.9% 15.0% 16.9%
(32) (33) (17) (82)
Transit Availability
High 28.4% 28.2% 24.3% 26.0%
(10) (6) (8) (24)
Medium 10.1% 15.3% 3.2% 11.9%
(5) (10) (3) (18)
Low 15.9% 13.6% 8.6% 12.3%
(17) (17) (6) (40)
Restricted Parking
Yes 29.9% 23.8% 18.0% 24.1%
(12) (11) (11) (34)
No 12.5% 12.0% 9.6% 11.9%
(20) (22) (6) (48)
Parking Fees
Yes 24.4% 27.3% 22.8% 24.1%
(14) (7) (9) (30)
No 12.5% 12.0% 9.6% 11.9%
(18) (26) (8) (52)
Transportation Services
Yes 26.5% 15.5% 24.2% 21.6%
(15) (14) (5) (34)
No 12.4% 16.2% 11.2% 13.6%
(17) (19) (12) (48)
Modal Subsidies
Yes 20.5% 19.8% 16.9% 19.5%
(26) (25) (13) (64)
No 12.7% 3.7% 9.1% 7.9%
(6) (8) (4) (18)
Telecommuting
Yes 16.6% 14.6% 28.2% 16.5%
(10) (6) (1) (17)
No 20.1% 16.2% 14.2% 17.1%
(22) (27) (16) (65)
Compressed Work Week
Yes 19.7% 21.5% 8.3% 19.5%
(15) (10) (3) (28)
No 18.4% 13.5% 16.5% 15.8%
(17) (23) (14) (54)
Sources: Derived (see Appendix Table 19-A) from Comsis (1994), Comsis and ITE (1993), Rutherford et al.
(1994), and Comsis et al. (1996).
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What is not reflected in this simple comparison, however, is the extent to which the performance
of high-level programs is influenced by packaging with other high-impact strategies, such as park-
ing fees or modal subsidies. This question is further explored in the following discussion, in par-
allel with Table 19-1. It will be shown that support actions have less effect than either ambient area
transit service levels or programs involving parking management/pricing, transportation service
provisions, or modal subsidies.
Transit Availability. Sites with high transit availability show a rather small difference between
high- and low-support programs (28.4 percent versus 24.3 percent VTR), but there is a marked dif-
ference between sites with high and low transit availability, regardless of the support program level.
The difference between high and low transit availability sites with high support is 28.4 percent ver-
sus 15.9 percent VTR, while the same comparison for medium-support sites is 28.2 percent versus
13.6 percent, and for low support it is 24.3 percent versus 8.6 percent. Interestingly, though, the
implementation of higher-level support programs when transit service is limited seems to have
more of a benefit--while the difference between low- and high-support programs when transit
availability is high is only 4.1 percentage points5 (24.3 percent versus 28.4 percent). The difference
is 7.9 percentage points (3.2 percent versus 10.1 percent) for medium transit availability and 7.3 per-
centage points (8.6 percent versus 15.9 percent) where transit availability is low.
Incentives and Disincentives. A similar result may be seen in relation to support actions in pro-
grams with incentive and disincentive characteristics such as restricted parking, priced parking
(parking fees), or where the employer provided transportation services or modal subsidies. In
each of these cases, the difference in VTR between employers who had any of these TDM program
elements and those who did not is significantly greater than the corresponding difference associ-
ated with different support levels. Clearly, higher support levels are associated with higher rates
of trip reduction in most of these cases (all cases if the comparison is restricted to high- versus
low-support levels), but the effects are small relative to the impacts of the other types of strate-
gies in the comparison.
Alternative Work Arrangements. Higher levels of support programs seem to enhance trip reduction
in combination with both telecommuting and CWW programs, as they do in cases without telecom-
muting or CWW, though the modest positive effect on trip reduction is not entirely consistent
between individual support levels. Note that, as previously cautioned, data from the 82-program
sample are not capable of reflecting the full range of telecommuting and CWW impacts. A full dis-
cussion of how these alternative work arrangements perform as strategies is provided in the subsec-
tion on "Response to Alternative Work Arrangements." It should be consulted before attempting
interpretation of the "Yes" versus "No" telecommuting and CWW comparisons in Table 19-1.
Additional Evidence of Individual Support Action Effects
Information, Marketing, and Promotion. As suggested earlier, for a TDM program to succeed,
several conditions must be present. In the case of persuading employees to switch modes or adopt
an alternative work schedule, they must: (1) be convinced of the inherent value of changing their
behavior; (2) have access to the type of information that allows them to understand their options,
which also means being made aware that their employer offers particular options; and (3) be moti-
vated to test and ultimately continue using the recommended options. This is rightly seen as the
role of marketing and promotion.
5 "Percentage points" refers to an absolute difference in percentages, rather than a relative difference.
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An example of the possible effects of active marketing, promotion, and information campaigns on
commute behavior is offered by a "Transportation Days" experiment in the Cross Westchester
Expressway Corridor of New York State in the early 1990s. Rapid employment growth in the cor-
ridor in the late 1980s was resulting in severe traffic congestion, causing the New York State Energy
Office to award a grant to the Westchester County Department of Transportation to develop and
implement transportation management programs to save energy, and reduce congestion and air
pollution. The resulting public-private effort included targeted transit service improvements cou-
pled with marketing of alternatives and information on their availability and use. The information
was presented throughout 1992 at 79 different employer locations in the corridor, representing
about 12,000 of the corridor's estimated 100,000 employees.
Before-and-after employee surveys showed that about 17 percent of the targeted employees attended
the promotional events. Of these, about 32 percent changed mode in the subsequent year, although
the changes were not uniformly from drive-alone to alternative modes. However, among promo-
tional event attendees, single occupancy vehicle (SOV) use fell from 68.6 percent to 63.7 percent--
an almost 5 percentage point reduction--while among those who did not attend, SOV use increased
from 68.9 percent to 70.8 percent, an increase of almost 2 percentage points. What is unclear from
these results is whether the people who attended the promotion were different in some way, such as
more in need of a transportation alternative, and how stable these choices were over time, given that
the follow-up survey was conducted within 1 year of the promotion (SG Associates and Howard/
Stein-Hudson Associates, 1993; Spielberg et al., 1993). This program is covered in more detail later
in the "Case Studies" section (see " `Transportation Days' Marketing and Outreach Programs--Cross
Westchester Expressway Corridor").
In a 1993 study for the California Air Resources Board (CARB), it was found that a surprising per-
centage of employees were unaware that their employer offered a particular type of TDM strategy.
While 1/2 to 2/3 of employees were aware of employer-offered measures such as preferential
parking (77 percent), rideshare matching (70 percent), company vanpool vehicles (67 percent),
and rideshare prizes (64 percent), much smaller numbers were aware that their employer con-
ducted transportation fairs (15 percent), or offered bus pass discounts (17 percent), on-site pass
sales (41 percent), or guaranteed ride home (36 percent). These findings were a revelation to CARB
and to the participating employers, and argued strongly for more aggressive information and mar-
keting efforts as part of the programs (Comsis, 1993a). For tabulation and further discussion of these
awareness level findings see "Individual Behavioral and Awareness Considerations"--"Awareness
and Comprehension of Options" within the "Underlying Traveler Response Factors" section.
Employee Transportation Coordinators (ETCs) are a popular strategy for performing this informa-
tion and promotional function. Most of the example programs in the 82-program sample incorpo-
rate ETCs, either on a part-time or full-time basis. The time investment required for an ETC is a
function of the size of the employer, the complexity of the given program and local travel alterna-
tives, and the pressure felt by the employer to have its program succeed. In addition to interacting
with employees, ETCs are also the point of contact with outside programs and agencies, such as
regional ridematching, transit, or a Transportation Management Association.
CUTR's National Center for Transit Research performed a study to try to determine the importance
of an ETC in the success of an employer TDM program, while at the same time accounting for dif-
ferences in management support and factors like transit availability. Based on a review of 13 work
sites in the Puget Sound area, the study reached an interesting, almost dichotomous conclusion:
ETCs are necessary for a successful work site trip reduction program if the work site is not located
in an area with access to high quality public transportation, but are not necessary if the work site is
located in an area with good public transportation and the employment base consists of lower-
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income staff who must choose transportation cost savings over time savings and convenience. The
study further concluded that, in a successful program, top management backs up these factors
through support such as the provision of meaningful incentives (Hendricks and Joshi, 2004).
Guaranteed Ride Home. A strategy appearing to address an important concern of employees con-
sidering use of an alternative commute mode to reach a work site is Guaranteed Ride Home (GRH).
Numerous surveys have suggested that having the assurance of a back-up mode that can be used
in the event of a personal emergency or unplanned schedule change can be the "deal clincher" in
getting an employee to switch from driving alone. The issue from an evaluation perspective is deter-
mining just how important a "supporting" strategy like GRH is in the overall trip-making decision
process, and what portion of vehicle trip reductions can be directly attributed to this strategy.
An examination of 11 GRH programs throughout the United States, representing many different
program types, scales, and settings, found--in general--strong intuitive support for GRH among
the program managers. The evaluation was, however, unable to statistically support or reject the
contention that GRH services actually encourage ridesharing. This situation was attributed to a
frequent lack of adequate before-and-after data and the fact that GRH was usually implemented
concurrently with other incentive programs, making it difficult to attribute changes in alternative
mode use exclusively to the GRH service (Polena and Glazer, 1991).
In its 2001 State of the Commute Survey, the Metropolitan Washington Council of Governments
(MWCOG) found that 31 percent of commuters who decided to use a non-drive-alone mode felt
that GRH was very important to their decision, while 33 percent said it was somewhat important
and 36 percent said that it was not at all important. Asked another way, 20 percent said that they
would be 100 percent likely to use an alternative mode even if GRH were not available, 48 percent
said they would be very likely, 23 percent said they would be somewhat likely, and 8 percent said
they would be not at all likely (MWCOG, 2002).
A 1994 review of a GRH program demonstration conducted in the Baltimore/Washington Inter-
national Airport Business District reached a similar set of conclusions. These responses suggest
that despite a highly favorable view of GRH, evaluation of its importance in actually determining
a shift in mode must consider that only a small percentage of employees making a shift (8 percent)
would be unlikely to make the change without GRH.
Under the 12-month Airport Business District experiment, a registered program participant would
notify his/her supervisor of the emergency or overtime requirement and directly call one of the par-
ticipating service providers (a taxi company and a rental car company). The service, which was
available 24 hours a day, was provided within 30 minutes, with the user permitted to make en route
stops related to the emergency. The fare was passed directly on to the administrating agency (BWI
Partnership). The number of participants grew steadily from 241 to 732 over the course of the pro-
gram, amounting to roughly 25 percent of eligible employees. In all, 114 participants (15 percent of
all participants) used the GRH program for a total of 287 trips. The majority of users made only one
GRH trip, with the average number of trips per user being 2.5. Forty-five percent of the GRH trips
were for unexpected overtime, while the remainder were for personal or family emergencies.
The evaluation of the program concluded that there was no reliable evidence that the GRH pro-
gram directly increased alternative mode use in the study area, although it may have helped retain
existing alternative mode users. Analysis of commute behavior before and after the demonstration
indicated that overall it remained virtually unchanged. Surveys revealed a decrease of less than
1 percent in SOV use and a 1 percent increase in High Occupancy Vehicle (HOV) and transit use
over the course of the project. Some 58 percent of those respondents who changed their mode during
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this time period said that the GRH program was not an important factor in their choice (Jewell and
Schwenk, 1994).
An evaluation of the impact of trip reduction requirements for the City of Sacramento suggests a
different result. Looking at annual employer and employee travel survey data compiled by the city,
covering 58 employers and roughly 26,000 employees, vehicle trip rates were compared for the
38 employers who offered GRH with the rates of the 20 employers who did not. An increase in
carpool mode share by an average of 4.6 percent was found at the employers offering GRH as
compared to only 1.6 percent at those where it was not offered. Similarly, an increase in vanpool
share of 1.7 percent was found in the presence of GRH versus a decline of 0.2 percent otherwise,
along with an increase in transit share of 1.2 percent when GRH was offered versus a no-GRH
decline of 0.1 percent. These findings correspond to an average VTR of 7.3 percent in the programs
where GRH was offered versus only 1.7 percent in those where it was not, suggesting a net VTR
effect of 5.6 percentage points for GRH (Schreffler, 1997). Of course, as with the Handbook authors'
own pairwise analysis of the 82-program sample, other characteristics of program or setting that
may have influenced this result are not known.
Support Action Combinations. A National Center for Transit Research study aimed at developing a
"Worksite Trip Reduction Model and Manual" provides an overview of the types of employer support
strategies that are most commonly employed, and roughly what role they have in TDM program effec-
tiveness. Using data from major publicly mandated employer trip reduction programs in Los Angeles,
Tucson, and Washington State, the researchers first identified the 50 most common types of program
combinations that were offered by employers. They then calculated the average VTR associated with
each combination of strategies. The most common support measures observed were marketing,
rideshare matching, guaranteed ride home, and facilities and amenities such as bike racks, showers,
and changing areas (CUTR, 2004). What was evident in comparing the different programs with regard
to their composition and VTR is that while the support strategies occurred in virtually all of the pro-
gram packages, the programs with the higher impacts were clearly those which also implemented
financial and other incentives. This provides further support for the premise that support strategies are
a necessary, but not sufficient, ingredient for a successful TDM program.
Consulting the 82-program sample once more, judgment has been used to identify those pro-
grams which were exclusively or substantially high-employer-support programs, with none or few
other meaningful strategies offered. There were 15 programs that fit this definition. The programs
are identified in Appendix Table 19-A as Childress Buick, K-Mart Valencia, Mercy Home Care,
Hillsborough County, Rosarita Foods, Shure Bros., California Franchise Tax Board, McClellan AFB,
Dean Witter, Kinko's Service Corp., Payroll One, Varian, UCLA, University of Central Florida, and
AT&T Pleasanton. The average VTR for this set of programs is 4.1 percent, substantially below the
average of 16.9 percent for the entire 82-program sample.
An analysis of information previously compiled by the legislatively-mandated employer trip
reduction program of Maricopa County, Arizona, was prepared in 1993 for the Chicago Area
Transportation Study (CATS) as an aid to developing guidelines for Employee Commute Options
(ECO) program implementation in Chicago. The Arizona program had required all employers
with 100 or more employees to develop a set of strategies aimed at reducing vehicle trips by 5 per-
cent annually. The analysis looked at data on TDM measures, employer characteristics, and travel
behavior changes taken from annual surveys covering the first 3 years of program operation--from
inception through year 3--for 556 work sites.
Maricopa County had identified approximately 55 distinct TDM measures, and those which had
been actually implemented were consolidated in the CATS analysis into 16 strategy categories. The
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first 10 were classified as "marketing and support" measures. Table 19-2 shows the change in
Average Passenger Occupancy (APO)6 for programs that--according to this classification system--
only employed support and marketing strategies. (It will be noted that several of these strategies
were not classified as employee support programs for purposes of this chapter's discussions.)
Where a particular strategy (e.g., Bike Incentives) was one of the strategies in a package, that pro-
gram is included in the tabulation under that strategy.
A percentage increase in APO may be roughly compared to a percentage increase in VTR. APO
increases were found to range from 3.4 percent to 9.0 percent depending on the included strategies,
with an average 4.6 percent for the group as a whole (Teal, 1993). This Maricopa County/CATS
analysis suggests that 4.6 percent may be taken as a reasonable estimate of the vehicle trip reduc-
tion potential for TDM programs that incorporate only "marketing and support" strategies, an esti-
mate very close to the 4.1 percent average VTR for the 15 support-strategy-only programs identified
in the 82-program sample.
Table 19-2 Association Between "Marketing and Support" Strategies and Average
Passenger Occupancy (APO) Changes in Maricopa County, Arizona
Included "Marketing and Support" Strategy APO Increase (Pct.) No. of Programs
Bike Incentives 5.4% 25
Bike/Walk Facilities 5.0 77
Preferential Parking 5.5 61
Carpool Matching 4.9 47
Carpool Incentives 4.3 23
Guaranteed Ride Home 5.8 74
Prizes, Rewards 5.5 75
Flexible Schedules for Alternative Mode Use 9.0 5
Transit Support Incentives 3.4 21
Information Measures 4.7 239
All (Programs with "Marketing and Support" 4.6% 240
Strategies Only)
Note: The typical program had more than one "Marketing and Support" strategy, thus the last column does
not add to the total number of programs.
Source: Teal (1993).
Still further corroborative evidence is provided by an analysis conducted by the Washington State
Commute Trip Reduction (CTR) program. With very high statistical correlation, it was estimated that
early employer TDM programs in both city and suburban locations achieved an average drive-alone
mode share reduction close to 5 percentage points in the first 2 years after program implementation.
6 Average Passenger Occupancy (APO) is the weekly total number of employee person trips divided by the
weekly total of employee vehicle trips (commute trips only). A percentage change in APO may be roughly
compared to a percentage change in vehicle trip rate. APO is essentially the same as AVR, except that legal
definitions of AVR may introduce slight differences, such as specification of covered commute hours instead
of having the computation cover full 24-hour periods.
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