NEW31"A
Taxonomy of Leisure Activities: The Role of ICT",
by Patricia L. Mokhtarian, Ilan Salomon, and Susan L. Handy. Research
Report UCD-ITS-RR-04-44, Institute of Transportation Studies, University of
California, Davis, April 2004.
A number of
studies have examined the adoption of information and communication technology (ICT)
and its impacts on personal travel, both at a general level and in the context
of a particular kind of activity. While it is not surprising that initial
attention has focused on the effects of ICT on travel for mandatory and
maintenance activities, discretionary or leisure activities have received
relatively little attention from this perspective. This report offers a
conceptual exploration of the potential impacts of ICTs on leisure activities
and the associated travel. We start by discussing some ideas about what leisure
is and is not. We point out that one reason for the nebulous nature of the
concept of leisure is that the boundaries between leisure, mandatory, and
maintenance activities are permeable, for three reasons: the multi-attribute
nature of a single activity, the sequential interleaving of activity fragments,
and the simultaneous conduct of multiple activities (multitasking).
With respect to
the relationship of ICT to leisure activities, we discuss four kinds of ways by
which ICT can affect leisure activities and travel: the replacement of a
traditional activity with an ICT counterpart, the generation of new ICT
activities (that displace other activities), the ICTenabled reallocation of time
to other activities, and ICT as a facilitator of leisure activities. We then
present 13 dimensions of leisure activities that are especially relevant to the
issue of ICT impacts: location (in)dependence, mobility-based v. stationary,
time (in)dependence, planning horizon, temporal structure and fragmentation,
possible multitasking, solitary v. social activity, active v. passive
participation, physical v. mental, equipment/media (in)dependence, informal v.
formal arrangements required, motivation, and cost.
The primary impact of ICT on leisure is to expand an individual’s choice set;
however whether or not the new options will be chosen depends on the attributes
of the activity (such as the 13 identified dimensions), as well as those of the
individual. The potential transportation impacts when the new options are chosen
are ambiguous. A number of directions for further research are identified.
NEW30“Tradeoffs between Time Allocations to Maintenance Activities/Travel
and Discretionary Activities/Travel”, by Cynthia Chen and Patricia L.
Mokhtarian. Forthcoming, Transportation.
This paper focuses on the tradeoff in time allocation between maintenance
activities/travel and discretionary activities/travel. We recognize that people
generally must travel a minimum amount of time in order to allocate one unit of
time to the activity. This minimum amount of travel is represented by the travel
time price, a ratio obtained by dividing the total amount of time traveling to
maintenance or discretionary activities by the total amount of time spent on
activities of the same type; it is the time equivalent of the monetary price for
performing an activity. Using the San Francisco Bay Area 1996 Household Travel
Survey data and applying the Almost Ideal Demand System (AIDS) of demand
equations, we found that with respect to the time equivalent of income
elasticities of maintenance and discretionary activities, the former is less
than unity and the latter is greater than unity. In other words, maintenance
activities are a necessity and discretionary activities are a luxury.
With
respect to the own travel time price elasticities, if the travel time price of
performing a certain type of activity increases (for reasons such as traffic
congestion), one would reduce the time allocated to that type of activity. Time
spent on maintenance activities is less elastic than the time spent on
discretionary activities. As for the cross travel time price elasticities
(changes in time allocated to activity type i in responses to changes in the
time price for activity type j), we found that
edm
> 0 and emd
> 0, suggesting a substitution effect between maintenance and discretionary
activities.
NEW29“Qualitative Subjective Assessments of Personal Mobility: What Makes
the Difference between a Little and a Lot?”, by Gustavo O. Collantes and Patricia L. Mokhtarian.
Available from the authors.
Using
survey data collected from 1,358 commuting workers in the San Francisco Bay Area
in 1998, this paper empirically explores the determinants of the subjective
assessment of individuals’ mobility (measured on a five-point ordinal scale, for
ten different categories of travel). Linear regression was used to identify the
relative importance of reported mobility in explaining the variance of the
dependent variables. A variety of personal factors were also found to
significantly influence such assessments: personality traits, travel-related
attitudes, lifestyle characteristics, and affinity for travel. The study
provides insight into the way individuals mentally process the amount of travel
they do, which will increase our understanding of travel behavior and its
motivations.
NEW28“Wanting to Travel, More or Less: Exploring the Determinants of
the Deficit and Surfeit of Personal Travel”, by Sangho Choo, Gustavo O. Collantes, and Patricia L. Mokhtarian.
Transportation 32(2), 2005, 135-164.
This study investigates the determinants of
people’s desire to increase or decrease the amount of travel they do. We use
data from 1,357 working commuters, residents of three different neighborhoods
in the San Francisco Bay Area, California. The dependent variables are
indicators of Relative Desired Mobility for ten categories of travel (short- and
long-distance overall and by several mode- and purpose-specific categories).
These variables are measured on a five-point ordinal scale ranging from “much
less” to “much more”, through which the respondents indicated the amount of
travel they want to do (in the category in question) compared to what they are
doing now. Censored ordered-probit models were developed for these variables,
with explanatory variables including general travel attitudes, specific liking
for travel in each of the same separate categories, objective and subjective
measures of the amount currently traveled in each category, and personality,
lifestyle, and demographic characteristics. The results support the hypotheses
that the liking for travel has a strong positive impact, and subjective
qualitative assessments of mobility have a strong negative impact, on the desire
to increase one’s travel. Finally, a number of general types of effects on
Relative Desired Mobility were identified, among them complementarity and
substitution effects. The results of this study can provide policy makers and
researchers with new and valuable insight into key principles that affect
individual travel demand.
NEW27“When
is Commuting Desirable to the Individual?”, by David T. Ory, Patricia L.
Mokhtarian, Lothlorien Redmond, Ilan Salomon, Gustavo Collantes, and Sangho Choo.
Special issue on Advances in Commuting Studies, eds. Peter Nijkamp and Jan
Rouwendal, Growth and Change 35(3) (summer), 2004, 334-359.
Commuting is
popularly viewed as a stressful, costly, time-wasting experience from the
individual perspective, with the attendant congestion imposing major social
costs as well. However, several authors have noted that commuting can also offer
benefits to the individual, serving as a valued transition between the home and
work realms of personal life. Using survey data collected from about 1,300
commuting workers in three San Francisco Bay Area neighborhoods, we develop
empirical models for four key variables measured for commute travel, namely:
Objective Mobility, Subjective Mobility, Travel Liking, and Relative Desired
Mobility. Explanatory variables include measures of general travel-related
attitudes, personality traits, lifestyle priorities, and sociodemographic
characteristics. Both descriptive statistics and analytical models indicate that
commuting is not the unmitigated burden that it is widely perceived to be. About
half our sample was relatively satisfied with the amount they commute, with a
small segment actually wanting to increase that amount. Both the psychological
impact of commuting, and the amounts people want to commute relative to what
they are doing now, are strongly influenced by their liking for commuting. An
implication for policy is that some people may be more resistant than expected
toward approaches intended to induce reductions in commuting (including, for
example, telecommuting). New creativity may be needed to devise policies that
recognize the inherent positive utility of travel, while trying to find socially
beneficial ways to fulfill desires to maintain or increase travel.
NEW26“When is Getting there Half the Fun? Modeling the Liking for
Travel”, by David T. Ory and
Patricia L. Mokhtarian. Transportation Research A 39(2&3), 2005,
97-124.
This paper
analyzes empirically measured values of Travel Liking – how much individuals
like to travel, in various overall, mode-, and purpose-based categories. The
study addresses two questions: what types of people enjoy travel, and under what
circumstances is travel enjoyed? We first review and augment some previously
hypothesized reasons why individuals may enjoy travel. Then, using data from
1,358 commuting residents of three San Francisco Bay Area neighborhoods, a total
of 13 ordinary least-squares linear regression models are presented: eight
models of short-distance Travel Liking and five models of long-distance Travel
Liking. The results indicate that travelers’ attitudes and personality
(representing motivations) are more important determinants of Travel Liking than
objective travel amounts. For example, while those who commute long distances do
tend to dislike commute travel (as expected), the variables entering the models
that hold the most importance relate to the personality and attitudes of the
traveler. Most of the hypothesized reasons for liking travel are empirically
supported here.
NEW25“Driving by Choice or Necessity?”, by Susan L. Handy, Lisa Weston, and Patricia L. Mokhtarian.
Transportation Research A 39(2&3), 2005, 183-204.
From just about all accounts, Americans are driving
more than ever, not just to work but to shopping, to school, to soccer practice
and band practice, to visit family and friends, and so on. Americans also seem
to be complaining more than ever about how much they drive – or, more
accurately, how much everyone else drives. However, the available evidence
suggests that a notable share of their driving is by choice rather than
necessity. Although the distinction between choice and necessity is not always
so clear, it is important for policy makers. For necessary trips, planners can
explore ways of reducing the need for or length of the trip or ways of enhancing
alternatives to driving. For travel by choice, the policy implications are much
trickier and touch on basic concepts of freedom of choice. This paper first
develops a framework for exploring the boundary between choice and necessity
based on a categorization of potential reasons for and sources of “excess
driving”, and then uses in-depth one-on-one interviews guided by this framework
to characterize patterns of excess driving. This research contributes to a
deeper understanding of travel behavior and provides a basis for developing
policy proposals directed at reducing the growth in driving.
NEW24“Personal Travel Management: The
Adoption and Consideration of Travel-Related Strategies”, by Michael J. Clay
and Patricia L. Mokhtarian. Journal of Transportation Planning and Technology
27(3) (June), 2004, 181-209.
Traveler behavior plays a role in the
effectiveness of travel demand management (TDM) policies. Personal travel
management is explored in this paper by analyzing individuals’ adoption and
consideration of 17 travel-related alternatives in relation to
socio-demographic, mobility, travel-related attitude, personality and lifestyle
preference variables. The sample comprises 1282 commuters living in urban and
suburban neighborhoods of the San Francisco Bay Area. Among the findings:
females were more likely to have adopted/considered the more ‘costly’
strategies; those with higher mobility were more likely to have
adopted/considered travel-maintaining as well as travel-reducing strategies; and
those who like travel and want to do more are less likely to consider
travel-reducing strategies. These findings, when combined with those of earlier
work on this subject, present a compelling argument for the need to further
understand traveler behavior -- particularly in response to congestion and TDM
policies.
NEW23“How do Individuals Adapt their Personal
Travel? Objective and Subjective Influences on the Consideration of
Travel-related Strategies for San Francisco Bay Area Commuters”, by Xinyu
Cao and Patricia L. Mokhtarian. Transport Policy 12(4), 2005.
Preparatory to an empirical analysis, this study
conceptually discusses the influences of objective and subjective variables on
the consideration of 16 travel-related strategies, reflecting a range of options
individuals have to adapt to congestion. The variables considered here were
measured by a 1998 survey conducted in the San Francisco Bay Area. The
conceptual exploration shows that the consideration of travel-related strategies
may be affected by the amounts of travel that individuals actually do, their
subjective assessments, desires, affinities, and constraints with respect to
travel. Individuals’ travel attitudes, personality, lifestyle and prior
experience are also likely to affect their current consideration. Socio-economic
and demographic characteristics may exhibit distributional effects with respect
to the options individuals consider. These potential influences indicate that
the individual adaptation process may be influenced by a wide range of
qualitative and experiential variables, which are often ignored or omitted by
policy makers and planners. A companion paper develops binary logit models of
the consideration of each strategy.
NEW22“How do Individuals Adapt their Personal
Travel? A Conceptual Exploration of the Consideration of Travel-related
Strategies”, by Xinyu Cao and Patricia L. Mokhtarian. Transport Policy 12(3),
2005, 199-206. doi:10.1016/j.tranpol.2005.03.002.
Preparatory to an empirical analysis, this study
conceptually discusses the influences of objective and subjective variables on
the consideration of 16 travel-related strategies, reflecting a range of options
individuals have to adapt to congestion. The variables considered here were
measured by a 1998 survey conducted in the San Francisco Bay Area. The
conceptual exploration shows that the consideration of travel-related strategies
may be affected by the amounts of travel that individuals actually do, their
subjective assessments, desires, affinities, and constraints with respect to
travel. Individuals’ travel attitudes, personality, lifestyle and prior
experience are also likely to affect their current consideration. Socio-economic
and demographic characteristics may exhibit distributional effects with respect
to the options individuals consider. These potential influences indicate that
the individual adaptation process may be influenced by a wide range of
qualitative and experiential variables, which are often ignored or omitted by
policy makers and planners. A companion paper develops binary logit models of
the consideration of each strategy.
NEW21“How do People Respond
to Congestion Policies? Exploring the Individual Consideration of
Travel-Related Strategy Bundles”, by Sangho Choo and Patricia L. Mokhtarian.
Paper presented at the 84th Annual Meeting of the Transportation Research Board,
Washington DC, January, 2005.
This study
explores the relationships between adoption and consideration of three
travel-related strategy bundles (travel maintaining/increasing, travel reducing,
and major location/lifestyle change), linking them to Mobility-related, Travel
Attitude, Personality, Lifestyle, Travel Liking, Socio-demographic, and other
variables. The data for this study are the responses to a fourteen-page survey
returned by nearly 1,300 commuting workers living in three distinct San
Francisco Bay area neighborhoods in May 1998. We first identified patterns of
adoption and consideration among the bundles, using pairwise correlation tests.
The test results indicate that those who have adopted coping strategies continue
to seek for improvements across the spectrum of generalized cost, but perhaps
most often repeating the consideration of a previously-adopted bundle.
Furthermore, we developed a multivariate probit model for individuals’
simultaneous consideration of the three bundles. It is found that in addition to
the previous adoption of the bundles, qualitative and quantitative
Mobility-related variables, Travel Attitudes, Personality, Lifestyle, and Travel
Liking significantly affect individual consideration of the strategy bundles.
Overall, the results of this study give policy makers and planners insight into
understanding the dynamic nature of individuals’ responses to travel-related
strategies as well as differences between the responses to congestion that are
assumed by policy makers and those that are actually adopted by individuals.
NEW20“Specification
of a Tour-Based Model for Well-Mixed Neighborhoods”, by Thirayoot Limanond,
Debbie A. Niemeier, and Patricia L. Mokhtarian. Transportation 32(2),
2005, 105-134.
This paper presents a state-of-the practice
neighborhood shopping travel demand model. The model structure is designed to
incorporate decisions across five dimensions of shopping travel, including
decisions of: (1) household tour frequency; (2) participating party; (3)
shopping tour type; (4) mode, and (5) destination choices using a tour-based
nested-logit model. As a neighborhood model, we have also captured the
interrelated effects of three main factors associated with shopping travel
decisions both within and outside of the neighborhood, including the residential
location within the neighborhood, the neighborhood regional setting and the
household structure. The model was validated using the travel data collected in
three neighborhoods located in the Puget Sound region, WA. Results show that
household socio-demographics have significant effects on the decisions for
household tour frequency, mode and destination choices, while the
characteristics of the traveling party have considerable impacts on the
decisions for tour type. The level of service and the zone attractions influence
decisions about mode and destination choices. The day of week variable (weekday
versus weekend) is statistically significant in all models, indicating that
weekday shopping travel decisions differ from weekend, across all five
dimensions of interest. The paper concludes with a discussion about how the
model can be used to examine policy-related neighborhood issues (e.g.
accessibility).
NEW19“What Affects Commute Mode Choice: Neighborhood Physical Structure or
Preferences toward Neighborhoods?”, by Tim Schwanen and Patricia L.
Mokhtarian. Journal of Transport Geography 13,
2005,
83-99.
The academic literature on the impact of urban form
on travel behavior has increasingly recognized that residential location choice
and travel choices may be interconnected. We contribute to the understanding of
this interrelation by studying to what extent commute mode choice differs by
residential neighborhood and by neighborhood type dissonance—the mismatch
between a commuter _s current neighborhood type and her preferences regarding
physical attributes of the residential neighborhood. Using data from the San
Francisco Bay Area, we find that neighborhood type dissonance is statistically
significantly associated with commute mode choice: dissonant urban residents are
more likely to commute by private vehicle than consonant urbanites but not quite
as likely as true suburbanites. However, differences between neighborhoods tend
to be larger than between consonant and dissonant residents within a
neighborhood. Physical neighborhood structure thus appears to have an autonomous
impact on commute mode choice. The analysis also shows that the impact of
neighborhood type dissonance interacts with that of commuters’ beliefs about
automobile use, suggesting that these are to be reckoned with when studying the
joint choices of residential location and commute mode.
NEW18“The Role of Attitudes
toward Travel and Land Use in Residential Location Behavior: Some Empirical
Evidence from the San Francisco Bay Area”, by Tim Schwanen and Patricia L.
Mokhtarian.
Available from the authors.
While more and more neo-traditional or compact neighborhoods are being developed
as an alternative to the low-density, sprawling, auto-dependent developments of
the recent past in the USA, limited empirical evidence regarding individuals’
willingness to live in such neighborhoods is available. This study aims to
contribute to the knowledge about the factors that drive residential
neighborhood choice by studying the decision to reside in a traditional or
different types of suburban neighborhoods in the San Francisco Bay Area. Rather
than using objective travel factors, we analyze the impact of attitudes toward
travel and land use on neighborhood choice, while also considering the impact of
sociodemographic, personality, and lifestyle variables. Discrete choice models
indicate that attitudes toward travel and land use are clearly related to the
residential neighborhood decision process. Their discriminatory power is
particularly large when the choice between an urban or a suburban neighborhood
is considered. The variables available are, however, not effective at
distinguishing the factors that influence the choice between the suburban
communities of Concord and Pleasant Hill.
NEW17“The Extent and
Determinants of Dissonance between Actual and Preferred Residential Neighborhood
Type”, by Tim Schwanen and Patricia L. Mokhtarian. Environment and
Planning B 31, 2004, 759-784.
While
households’ general preference for low-density residential environments is well
documented in the literature, little research in geography and urban planning
has explicitly investigated how many and which households experience a state of
mismatch in terms of land use patterns between their preferred residential
neighborhood type and the type of neighborhood where they currently reside.
Using data from 1,358 commuters living in three communities in the San
Francisco Bay Area, this study finds that nearly a quarter of the residents live
in a neighborhood type that does not match their land-use related preferences.
The results of an investigation of the determinants of such dissonance are
consistent with existing knowledge about residential preferences. It is shown
that single suburban dwellers and large households and families in the city are
more likely to be mismatched, or experience higher levels of mismatch in terms
of neighborhood type. Further, the extent of mismatch is clearly related to
automobile orientation, as well as to lifestyles and personality traits. The
results suggest that policies aiming to attract a diverse market to
neo-traditional, high-density neighborhoods may not be as effective as
decision-makers and planners hope. If a broad range of households is
artificially attracted to such new developments, e.g. through providing
financial advantages or other policy incentives, this might on average result in
lower levels of residential satisfaction, higher residential mobility, lower
sense of community, and enduring auto dependency. On the other hand, it is
encouraging to see that there is also a substantial proportion of suburban
dwellers preferring high-density environments. Relaxation of land use laws in
existing suburban communities might be successful in reducing residential
neighborhood type dissonance for these types of suburban dwellers, but perhaps
at the cost of increasing dissonance for the suburbanites preferring lower
densities. It would be valuable to investigate whether there is a mix of
densities and uses that would optimally satisfy both types of preferences.
NEW16“Does Dissonance between
Desired and Current Neighborhood Type Affect Individual Travel Behavior? An
Empirical Assessment from the San Francisco Bay Area", by Tim Schwanen and
Patricia L. Mokhtarian. Proceedings of the European Transport Conference (ETC),
October 8-10, 2003, Strasbourg, France.
This paper investigates to what extent trip frequencies
differ not only by residential neighbourhood but also by the extent and level of
mismatch between a traveller’s current and preferred type of neighbourhood. The
analysis of data from residents of three communities in the San Francisco Bay
Area provides mixed results regarding the hypothesized systematic ordering in
terms of trip frequencies for discretionary and grocery shopping purposes, with
high frequencies for consonant urbanites, lower frequencies for dissonant
urban, even lower frequencies for suburban residents, to the lowest ones for
consonant suburbanites.
The ordered probit analysis indicates that variations in trip
frequencies for the suburban neighbourhoods are accounted for by factors
associated with sociodemographic position, personality, lifestyle, and
travel–related attitudes. Thus, for suburban neighborhoods we believe that, at
least for trip frequency by purpose, the conditioning influence of the
environment prevails over travellers’ preferences regarding the environment.
In the urban neighbourhood, on the other hand, the relative contributions
that preferences towards and constraints imposed by the physical structure of
the neighbourhood make to the explanation of travel patterns are more balanced:
the impact of dissonance persists for the frequency of grocery shopping, social/
recreation/ entertainment, and eat out trips of North San Francisco residents.
In this case, accordingly, we believe that residential self-selection processes
play a role in the explanation of travel patterns. In other words, residential
location choice is not completely exogenous to the relationship between travel
behaviour and land-use factors. Nevertheless, neighbourhood structure appears
to have an autonomous influence as well.
NEW15“What if You Live in the Wrong Neighborhood? The Impact of Residential
Neighborhood Type Dissonance on Distance Traveled”, by Tim Schwanen and
Patricia L. Mokhtarian. Transportation Research D 10, 2005,
127-151.
While urban form in general and density in
particular are believed by many to significantly influence travel
behavior, various recent studies have argued that
the true determinants of travel patterns are attitudes rather than land use
characteristics. This research builds on this notion and investigates to what
extent a
lack of congruence between physical neighborhood
structure and preferences regarding land use near one’s home location (termed
“residential neighborhood type dissonance” or mismatch) affect distance traveled
overall and by mode. A conceptual model is described in which the relationship
between neighborhood type dissonance and distance traveled is embedded in a
wider set of individual and household choices, and tobit models of the influence
of neighborhood type mismatch are presented. The results suggest that
neighborhood type mismatch should be taken into account in future research as
well as in policies attempting to modify travel behavior through land use
regulations.
NEW14“The Influences of the
Built Environment and Residential Self-selection on Pedestrian Behavior
in Austin, Texas”,
by Xinyu Cao, Susan L. Handy, and Patricia L. Mokhtarian.
Transportation
33(1) (February), 2006, 1-20.
Pedestrian
travel offers a wide range of benefits to both individuals and society.
Planners and public health officials alike have been promoting policies that
improve the quality of the built environment for pedestrians: mixed land uses,
interconnected street networks, sidewalks and other facilities. Whether such
policies will prove effective remains open to debate. Two issues in particular
need further attention. First, the impact of the built environment on
pedestrian behavior may depend on the purpose of the trip, whether for
utilitarian or recreational purposes. Second, the connection between the built
environment and pedestrian behavior may be more a matter of residential location
choice than of travel choice. This study aims to provide new evidence on both
questions. Using 1,368 respondents to a 1995 survey conducted in six
neighborhoods in Austin, TX, two separate negative binomial models were
estimated for the frequencies of strolling trips and pedestrian shopping trips
within neighborhoods. We found that although residential self-selection impacts
both types of trips, it is the most important factor explaining walking to a
destination (i.e. for shopping). After accounting for self-selection,
neighborhood characteristics, especially perceptions of these characteristics,
impact strolling frequency, while characteristics of local commercial areas are
important in facilitating shopping trips.
NEW13“Correlation or
Causality between the Built Environment and Travel Behavior? Evidence from
Northern California”, by Susan L. Handy, Xinyu Cao, and Patricia L.
Mokhtarian. Forthcoming, Transportation Research D, 10(6), 2005,
427-444.
The sprawling
patterns of land development common to metropolitan areas of the United States
have been blamed for high levels of automobile travel, and thus for air quality
problems. In response, “smart growth” programs--designed to counter
sprawl--have gained popularity in the United States. Studies show that, all
else equal, residents of neighborhoods with higher levels of density, land-use
mix, transit accessibility, and pedestrian friendliness drive less than
residents of neighborhoods with lower levels of these characteristics. These
studies have not shed much light, however, on the underlying direction of
causality--in particular, whether neighborhood design influences travel behavior
or whether travel preferences influence the choice of neighborhood. The
available evidence thus leaves a key question largely unanswered: If cities
use land use policies to bring residents closer to
destinations and provide viable alternatives to driving, will people drive
less, thereby reducing emissions? This paper provides new evidence that helps
to answer this question. The study presented here uses a quasi-longitudinal
design to investigate the relationship between neighborhood characteristics and
travel behavior while taking into account the role of travel preferences and
neighborhood preferences in explaining this relationship. A multivariate
analysis of cross-sectional data shows that differences in travel behavior
between suburban and traditional neighborhoods are largely explained by
attitudes. However, a quasi-longitudinal analysis of changes in travel
behavior and changes in the built environment shows significant associations,
even when attitudes have been accounted for, providing support for a causal
relationship. The results presented here thus provide some encouragement that
land-use policies designed to increase the opportunities to drive less will
actually lead to less driving.
NEW12“Cross-sectional and
Quasi-panel Explorations of the Connection between the Built Environment and
Auto Ownership”, by Xinyu Cao, Patricia L. Mokhtarian, and Susan L. Handy.
Forthcoming, Environment and Planning A.
Auto ownership
is a critical mediating link in the connection between the built environment and
travel behavior: the built environment presumably influences auto ownership,
which in turn impacts travel behavior. However, the way in which individual
elements of the built environment affect auto ownership choices is far from
understood. Further, residential self-selection may confound the interaction
between the built environment and auto ownership. And the absence of panel data
impedes our understanding of the causal relationships. Using a survey of 1682
respondents in Northern California, this study applied ordered probit and
static-score modeling techniques to investigate the causal link from the built
environment to auto ownership in both cross-sectional and quasi-panel contexts.
Through variable selection in cross-sectional analysis, we found that
individuals’ attitudes regarding residential neighborhood and travel are more
strongly associated with their auto ownership decision than is the built
environment per se. Specifically, when general preferences for various
neighborhood traits were allowed to enter the model, they drove out from the
model the (perceived) measure of the same trait for the neighborhood of current
residence, a pattern suggesting that the observed correlation between
neighborhood characteristics and auto ownership is primarily a result of
self-selection. On the other hand, the quasi-panel results indicate that some
built environment elements such as outdoor spaciousness and mixed land use are
causes of auto ownership (remaining even after attitudes were allowed to enter
the model), but their effects are marginal. In contrast, the strong influence
of socio-demographics suggests that households’ auto ownership decisions are
fundamentally based on their mobility needs and purchasing power. Given the
mixed findings, this study does not definitively confirm a causal relationship
between the built environment and auto ownership. However, it provides
encouraging evidence that land-use policies designed to reduce auto ownership
and use will lead to a marginal reduction in auto ownership.
NEW11“Does Self-selection Explain the Relationship between Built
Environment and Walking Behavior? Empirical Evidence from Northern California”,
by Susan L. Handy, Xinyu Cao, and Patricia L. Mokhtarian.
Journal of the American Planning Association, 2006.
Suburban
sprawl is increasingly being blamed for growing levels of obesity in the U.S.
The logic is simple: low-density, segregated-use suburbs are designed for
driving rather than walking, leading people to drive more and walk less, thereby
contributing to a decline in physical activity and an increase in weight. The
available evidence is less than conclusive, however: studies have established
correlations between the built environment and walking but not a causal
relationship. Researchers are now debating the role of “self-selection” in
explaining the observed correlations: do residents who prefer to walk choose to
live in more walkable neighborhoods? Using data from a survey of residents of
eight neighborhoods in Northern California, this paper presents new evidence on
the possibility of a causal relationship between the built environment and
walking behavior. This work makes two improvements on most previous studies:
the incorporation of travel attitudes and neighborhood preferences into the
analysis of walking behavior, and the use of a quasi-longitudinal design to test
the relationship between changes in the built environment and changes in
walking. In both analyses, the results show that the built environment has an
impact on walking behavior even after attitudes and preferences have been
accounted for.
NEW10“Understanding
Commuters’ Evening Stop-making Behavior: The Effects of the Built Environment
and Attitudes”, by Xinyu Cao, Patricia L. Mokhtarian, and Susan L. Handy.
Submitted to Environment and Planning B, March 2005.
Understanding
commuters’ stop-making behavior is important for planners and policy makers in
their efforts to improve travel demand models and develop transportation demand
management strategies. Previous studies have identified various determinants of
commuters’ stop generation. However, the way in which the built environment
affects stop-making decisions is not clear. In addition, given the extensive
influences of attitudes on travel behavior, individuals’ attitudes and
predispositions are expected to affect their stop-making decisions, but few
studies have considered their impacts. Using 1256 commuters in Northern
California, this study investigates the influences of the built environment and
attitudes on evening commute stop-making behavior. Based on the results from a
Tobit model and a bivariate selection model, we found that workers’ propensity
to make stops during their evening commutes is largely dependent on their
attitudes, work-related attributes, and socio-demographic characteristics,
whereas the frequency of stopping is primarily determined by personal needs and
facilitated/discouraged by time and spatial constraints. Interestingly, both
individuals who like travel and those who tend to minimize their travel are more
likely to stop, possibly due to trip generation in the first instance and
consolidation of trips in the second. Individuals preferring high accessibility
are also more likely to stop. After controlling for attitudes, some residential
neighborhood characteristics were found to be significantly associated with stop
frequency. Accordingly, if we offer commuters opportunities to stop through
land use and transportation policies, they may do so more frequently. However,
whether a stop consolidates trips or represents new travel depends on whether it
is for necessary or discretionary purposes, and remains unclear. Further, this
study corroborates a previous finding that the variation in travel demand is
heteroscedastic across spatial dimensions, which is commonly ignored in travel
demand analysis.
NEW9“Neighborhood Design and Vehicle Type Choice: Evidence from Northern
California”, by Xinyu Cao, Patricia L. Mokhtarian, and Susan L. Handy. Transportation Research D,
2006.
Previous studies
found that suburban development is associated with the unbalanced choice of
light duty trucks (LDTs). However, what aspects of the built environment
influence vehicle choice are far from being revealed. Further, these studies
have not shed much light on the underlying direction of causality – whether
neighborhood designs as opposed to attitudes towards vehicle choice more
strongly influence individuals’ decisions on vehicle type choice. Using a sample
from Northern California, this study investigated the relationship between the
built environment and vehicle type choice, controlling for residential
self-selection. The results from correlational analyses showed that the built
environment has a strong association with vehicle type choice. Specifically,
traditional designs (exhibiting high accessibility) are correlated with the
choice of passenger automobiles, while suburban designs (including large yards
and off-street parking) are associated with the choice of LDTs. The multinomial
logit model suggests that attitudinal factors play an important role, and that
the built environment impacts vehicle type choice after controlling for
residential and travel preferences. Therefore, this study supports that smart
growth strategies have the potential to reduce the choice of LDTs, thereby
reducing emissions.
NEW8“A Monte Carlo Simulation Model Incorporating Telecommuter,
Employer, and Public Sector Perspectives”, by Kevan Shafizadeh, Debbie A.
Niemeier, Patricia L. Mokhtarian, and Ilan Salomon. Forthcoming, ASCE
Journal of Infrastructure Systems.
This paper reviews and utilizes the current body of
telecommuting related research to study the costs and benefits of home-based
telecommuting. Monte Carlo simulation methods were utilized to help account for
costs or benefits that remain highly variable or have not been well documented
by past research. This study illustrates the conditions under which the
business case for telecommuting is supported or weakened. Conditions for the
employee (the telecommuter) are generally most favorable when: (1) the employer
bears the equipment cost, (2) commute distances are above average, (3) the
commute vehicle has below-average fuel economy, (4) travel time is highly
valued, and (5) telecommuting is frequent, while conditions for the employer are
most favorable when: (1) the telecommuter bears the equipment cost, (2) there is
low telecommuter attrition, (3) the employee is highly productive on
telecommuting days, (4) the employee’s time is highly valued, and (5)
telecommuting is frequent. For the employer, telecommuting is also favorable if
parking and office space savings are realized. While public sector benefits are
conceivable, they remain insignificant in most situations because the impacts on
the transportation network are probably not concentrated enough over a specific
transportation corridor to realize infrastructure benefits and not quantified or
valued enough within a regional air district to realize significant air quality
benefits. Further, the public sector loses fuel tax revenue. Altogether, this
paper provides insight on the potential public sector impacts of telecommuting,
as well as the federal, state, regional, and local public policy implications
that arise when telecommuting is considered among other transportation demand
management alternatives.
NEW7 “Telecommuting, Residential
Location, and Commute Distance Traveled: Evidence from State of California
Employees”, by Patricia L. Mokhtarian, Gustavo O. Collantes, and Carsten
Gertz. Environment and Planning A 36, 2004, 1877-1897. An
abridged version appears in Dieter Hassenpflug and Gudrun Tegeder, eds.,
City.net: Cities in the Age of Telecommunications. Marburg, Germany:
Tectum Verlag, pp. 127-148.
This study
analyzes retrospective data on telecommuting engagement and residential and job
location changes over a ten-year period, from 218 employees (62 current
telecommuters, 35 former telecommuters, and 121 people who had never
telecommuted) of six California state government agencies that had actively
participated in the well-known pilot program of 1988-90. We compare estimates of
the total commute person-miles traveled of telecommuters and non-telecommuters,
on a quarterly basis.
Key
findings include: (a) One-way commute distances are higher for telecommuters
than for non-telecommuters, consistent with prior empirical evidence and with
expectation. (b) Average telecommuting frequency declines over time. Several
explanations are proposed, but cannot be properly tested with these data.
(c) The first two findings notwithstanding, the average quarterly per-capita
total commute distances are generally lower for telecommuters than for
non-telecommuters, indicating that they telecommute often enough to more than
compensate for their longer one-way commutes.
We
cannot say from these results whether the ability to telecommute is itself
prompting individuals to move farther away, or whether telecommuting is simply
more attractive to people who already live farther from work for other
reasons. Even if the first case is true, however, and telecommuting is the
"problem", it also appears to be the solution, i.e. enabling people to achieve a
desired but more distant residential location without a net increase in commute
travel.
NEW6“Which Came First, the Telecommuting
or the Residential/Job Relocation? An Empirical Analysis of Causality”, by
David T. Ory and Patricia L. Mokhtarian. Submitted to Urban Geography,
March 2005.
Researchers
have questioned whether the ability to telecommute is encouraging workers to
relocate to more desirable residences farther from work, and in doing so,
exacerbate sprawl and increase their net vehicle-miles traveled. The research
presented here directly asks, is telecommuting a “friend or foe” of
travel-reducing policies? Given that telecommuters tend to have longer commutes
than non-telecommuters, is the ability to telecommute prompting workers to move
farther away from work? Or, does the ability to telecommute allow those who for
other reasons have already chosen, or would in any case choose, to live in more
distant locations to commute less frequently? These questions are addressed
using data collected from more than 200 State of California workers, including
current, former, and non-telecommuters. The survey inquired retrospectively
about their residential relocations, as well as their telecommuting engagements,
over a ten-year period. The results indicate that, as expected, residential
moves that are temporally associated with telecommuting episodes tend to
increase commute time and length compared to other moves – though the
differences are not statistically significant. Analyzing the temporal order of
telecommuting engagement and residential relocation, the data show that those
who are telecommuting and then move actually tend to relocate closer to
their workplace, whereas those who begin telecommuting following a residential
relocation tended to have moved much farther from their workplace. Analysis of
the stated importance of telecommuting to specific residential relocations did
not show a convincing effect toward more distant moves. Thus, the evidence more
strongly supports the positive view of telecommuting, that it is ameliorating
the negative transportation impacts of moves that occur for other reasons.
NEW5“Measuring the Measurable: Why Can’t
We Agree on the Number of Telecommuters in the US?”, by Patricia L.
Mokhtarian, Ilan Salomon, and Sangho Choo. Quality and Quantity 39,
423-452.
Using telecommuting as a case study, we demonstrate that definitions,
measurement instruments, sampling and sometimes vested interests affect the
quality and utility even of seemingly objective and “measurable” data. Little
consensus exists with respect to the definition of telecommuting, or to
possible distinctions from related terms such as teleworking. Such a consensus
is unlikely, since the “best” definition of telecommuting depends on one’s point
of reference and purpose. However, differing definitions confound efforts to
measure the amount of telecommuting and how it is changing over time. This
paper evaluates estimates of the amounts of telecommuting occurring in the
U. S. obtained from several different sources: the U. S. Census, the American
Housing Survey, several Work at Home supplements to the Current Population
Survey, a series of market research surveys, and the trade association-sponsored
Telework America surveys. Many of the issues raised here are transferable to
other contexts, and indirectly serve as suggestions for improving data
collection in the future.
NEW4“Modeling the Joint Labor-Commute
Engagement Decisions of San Francisco Bay Area Residents”, by David T. Ory
and Patricia L. Mokhtarian. Hani S. Mahmassani, ed., Transportation and
Traffic Theory: Flow, Dynamics, and Human Interaction. Oxford, UK:
Elsevier Ltd., pp. 487-506.
Using
socio-demographic, personality, and attitudinal data from 1,680 residents of the
San Francisco Bay Area, we develop and estimate binary, multinomial, and nested
logit models of the choice to work or not, whether or not to work at home, and
whether to commute all of the time or some of the time (either by only working
part time, or by working a compressed work week, or by telecommuting some of the
time). To our knowledge, these are the first models of all these choices
simultaneously. This work is relevant both to travel demand modeling, which
usually bases trip or activity generation models on a given set of employment
status inputs, and to labor force engagement modeling, which typically ignores
the impact of travel-related variables. The model results indicate that the
typical predictors of labor force engagement (gender, household income, and
education) play an important role here, with family variables having an
especially complex effect. Other interesting findings are that telecommuters
tend to be adventure-seekers and home-based workers tend to be workaholics;
those who like travel tend to commute five or more times per week; and mobility
constraints are significant in the decisions to work part-time and to commute
full-time.
NEW3“The
Impacts of ICT on Leisure Activities and Travel: A Conceptual Exploration”,
by Patricia L. Mokhtarian, Ilan Salomon, and Susan L. Handy. Forthcoming
Transportation.
This paper
offers a conceptual exploration of the potential impacts of ICTs on leisure
activities and the associated travel. We start by discussing what leisure is
and is not. We point out that the boundaries between leisure, mandatory, and
maintenance activities are permeable, for three reasons: the multi-attribute
nature of a single activity, the sequential interleaving of activity fragments,
and the simultaneous conduct of multiple activities (multitasking).
We then discuss four kinds of ways by which ICT can
affect leisure activities and travel: the replacement of a traditional activity
with an ICT counterpart, the generation of new ICT activities (that displace
other activities), the ICT-enabled reallocation of time to other activities, and
ICT as a facilitator of leisure activities. We suggest 13 dimensions of leisure
activities that are especially relevant to the issue of ICT impacts: location (in)dependence,
mobility-based v. stationary, time (in)dependence, planning horizon, temporal
structure and fragmentation, possible multitasking, solitary v. social activity,
active v. passive participation, physical v. mental, equipment/media (in)dependence,
informal v. formal arrangements required, motivation, and cost.
The primary impact of ICT on leisure is to expand
an individual’s choice set; however whether or not the new options will be
chosen depends on the attributes of the activity (such as the 13 identified
dimensions), as well as those of the individual. The potential transportation
impacts when the new options are chosen are ambiguous.
NEW2“Communication Chains: A Methodology
for Assessing the Impacts of the Internet on Communication and Travel”, by
Colby Brown, Prashant Balepur, and Patricia L. Mokhtarian. Journal of Urban
Technology (April), 2005, 71-98.
This study
empirically investigates the relationship between Internet communications and
the use of other communications media, including travel, for 148 residents of
Davis, California. The data used derive from activity diaries collected in 1994
as part of the evaluation of the Davis Community Network, an experimental
Internet access project providing e-mail, World Wide Web, and other services to
Davis residents. Tabulation and cluster analyses of 636 Internet communications
indicate that: 1) A plurality of Internet activities bear a neutral relationship
to other types of communication (including travel); 2) Although 44% of surveyed
activities had no other alternative, the remainder were most likely (39% of 636)
to be replacing other electronic media (including phone calls), with only 22%
contemporaneously replacing travel or in-person communication; 3) Twice as many
Internet activities were expected to generate future travel or in-person
communication as to eliminate future travel or in-person communication; 4) Many
Internet activities may be “self-generating”—that is, engagement in Internet
activities tends to lead to more of such engagement. These results suggest that
neutrality, self-generation, and complementary with travel, rather than
substitution for travel, are likely to be the dominant communication impacts of
the Internet.
NEW1“Telecommunications and Travel Demand
and Supply: Aggregate Structural Equation Models for the U.S.”, by Sangho
Choo and Patricia L. Mokhtarian. Forthcoming Transportation Research A.
Disaggregate
studies of the impacts of telecommunications applications (e.g. telecommuting)
on travel have generally found a net substitution effect. However, such studies
have all been short-term and small-scale, and there is reason to believe that
when more indirect and longer-term effects are accounted for, complementarity is
the likely outcome. At least two aggregate studies have focused on the
relationships between telecommunications and travel from economic perspectives
(consumer and industry). However, both use the monetary value of consumption or
transactions rather than actual activity measures (e.g. miles, number of calls),
and neither fully explains the direct and indirect causal relationships between
the two. The purpose of this study is to develop a conceptual model in a
comprehensive framework, considering causal relationships among travel,
telecommunications, land use, economic activity, and socio-demographics, and to
explore the aggregate relationships between telecommunications and travel, using
structural equation modeling of national time series data spanning 1950-2000 in
the U.S. In this paper we focus on number of telephone calls as the measure of
telecommunications, and passenger vehicle-miles traveled as the measure of
transportation. Future research will investigate additional measures of these
two constructs. Our empirical results
strongly support the hypothesis that telecommunications and travel are
complementary. That is, as
telecommunications demand increases, travel demand increases, and vice versa.
These results offer a more realistic picture to policy makers and
transportation planners than has been available till now, and suggest useful
directions for them to develop transportation or telecommunications strategies
designed to reduce traffic congestion, air pollution, and energy consumption.
TRP44 “Does Telecommuting Reduce Vehicle-miles Traveled? An
Aggregate Time Series Analysis for the U.S.”,
by Sangho Choo, Patricia L. Mokhtarian, and Ilan Salomon.
Transportation 32(1), 2005, 37-64.
This
study examines the impact of telecommuting on passenger vehicle-miles traveled (VMT)
through a multivariate time series analysis of aggregate nationwide data
spanning 1966-1999 for all variables except telecommuting, and 1988-1998 for
telecommuting. The analysis was conducted in two stages. In the first stage,
VMT (1966-1999) was modeled as a function of conventional variables representing
economic activity, transportation price, transportation supply and
socio-demographics. In the second stage, the residuals of the first stage
(1988-1998) were modeled as a function of the number of telecommuters. We also
assessed the change in annual VMT per telecommuter as well as VMT per
telecommuting occasion. The models suggest that telecommuting reduces VMT,
with 94% confidence. Taken together, the evidence suggests a reduction in
annual VMT on the order of 0.8% or less.
TRP43
“A Conceptual Analysis of the Transportation Impacts of B2C E-Commerce”, by
Patricia L. Mokhtarian. Transportation 31(3) (August),
2004, 257-284.
This paper
discusses, at a conceptual level, a number of issues related to the evaluation
of the transportation and spatial impacts of e-shopping. We review the
comparative advantages of store shopping and e-shopping, and conclude that
neither type uniformly dominates the other. We identify the building blocks of
the shopping process, and note that information and communications
technologies are making possible the spatial and temporal fragmentation and
recombination of those elements. We examine some potential transportation
impacts of e-shopping, and note that some factors result in reduced travel while
others lead to increased travel. The combined outcome of all factors does not
appear to support any hope that e-shopping will reduce travel on net; to the
contrary there may be negative impacts due to increased travel, even if those
impacts are likely to be localized and/or small in magnitude for the most part.
Thus, on the whole, we are likely (with some exceptions) to see continued
adoption of both store shopping and e-shopping. Consumers will blend both
forms as they conduct a sequence of shopping activities, and retailers will
blend both in marketing to and serving customers. Assessing the transportation
impacts of e-shopping – even in the short term, let alone the long term –
presents some formidable measurement challenges. Nevertheless, those
challenges are worthy of our most creative efforts at solution.
TRP42
"Telecommunications and Travel:
The Case for Complementarity", by Patricia L. Mokhtarian. Journal
of Industrial Ecology 6(2), Special Issue on E-Commerce,
the Internet, and the Environment, 2003, 43-57.
This paper examines the conceptual, theoretical,
and empirical evidence with respect to the impact of telecommunications on
travel. The primary focus is on passenger travel, but goods movement is
addressed briefly. I argue that although direct, short-term studies focusing on
a single application (such as telecommuting) have often found substitution
effects, such studies are likely to miss the more subtle, indirect, and
longer-term complementarity effects that are typically observed in more
comprehensive analyses. Overall, substitution, complementarity, modification,
and neutrality within and across communication modes are all happening
simultaneously. The net outcome of these partially counteracting effects, if
current trends continue, is likely to be faster growth in telecommunications
than in travel, resulting in an increasing share of interactions falling to
telecommunications, but with continued growth in travel in absolute terms. The
empirical evidence to date is quite limited in its ability to assess the extent
of true causality between telecommunications and travel, and more research is
needed in that area. At this point, what we can say with confidence is: the
empirical evidence for net complementarity is substantial although not
definitive, and the empirical evidence for net substitution appears to be
virtually non-existent.
TRP41 "Patterns of Telecommuting Engagement and Frequency: A Cluster Analysis
of Telecenter Users", by Patricia L. Mokhtarian and Ravikumar Meenakshisundaram.
Prometheus 20(1), 2002, 21-37.
Cluster analysis of sign-in log
data for 115 users of California telecenters was conducted to identify patterns
of telecommuting engagement and frequency over a six-month window. Three
engagement clusters were identified: Persisters (45% of the sample,
telecommuting in 91% of the 13 two-week periods), Decliners (31% of the
sample, telecommuting in 72% of the periods with a decline over the six-month
window), and Dabblers (24% of the sample, telecommuting in 22% of the
periods). Four frequency clusters were identified, classified as Low
(63%, averaging 0.9 telecommuting occasions per two weeks), Medium (26%,
3.0 occasions), High (8%, 7.3 occasions), and Erratic (3%,
averaging 5 occasions with high variance). Nearly half of the Persisters
belonged to the Low Frequency cluster. There was also some evidence of
migration from higher to lower telecommuting frequencies over time. These
findings highlight the need to count not just telecommuters, but telecommuting
occasions, in analyzing and forecasting the impacts of telecommuting on other
areas such as transportation.
Two variables were
significantly associated (p-values
# 0.09) with telecommuting engagement: Persisters
had more positive perceptions of their professional development prospects at
both the regular and telecommuting workplaces than did Decliners, and
they also had one-third longer commutes on average. Perceptions of
productivity, job satisfaction, supervisor relationship, co-worker interaction,
and workplace-based personal benefits, autonomy, and work-effectiveness did not
differ significantly between these groups, nor did gender, age, education, or
income. Several variables were significantly associated with frequency: Low
Frequency telecommuters had higher job satisfaction scores, lower supervisor
relationship scores, were more likely to be female or younger, and had shorter
commutes compared to Medium Frequency telecommuters. Consistent with
other research, management-related issues seem to play a substantial role in
affecting both the engagement in, and frequency of, telecommuting.
TRP40
"Multicriteria Network Equilibrium Modeling with Variable Weights for
Decision-Making in the Information Age, with Applications to Telecommuting and
Teleshopping", by Anna Nagurney, June Dong, and Patricia L. Mokhtarian.
Journal of Economic Dynamics and Control 26(9-10), special issue in
honor of David Kendrick, 2002, 1629-1650.
In this paper, we develop a multicriteria network
equilibrium framework for modeling decision-making in the Information Age. We
consider distinct classes of decision-makers, each of whom has a set of criteria
associated with the decision along with weights which are variable and
criterion-dependent. The decisions take place on a network in which links can
be either physical, as in the case of transportation, or virtual, as in the case
of telecommunications. We derive the equilibrium conditions and establish
qualitative properties of the equilibrium pattern. The model enables the
prediction of the number of decision-makers that will select particular choices,
along with the incurred generalized costs. We then apply the modeling schema to
telecommuting versus commuting and to teleshopping versus shopping
decision-making.
TRP39
"Traffic Network Equilibrium and the
Environment: A Multicriteria Decision-Making Perspective", by Anna Nagurney, June Dong, and Patricia L. Mokhtarian. Chap. 25 in Erricos
Kontoghiorghes, Berc Rustem, and Stavros Siokos, eds., Computational
Methods in Decision-Making, Economics, and Finance. Kluwer Applied
Optimization Series. Dordrecht: Kluwer Academic Publishers,
2002, 501-523.
A traffic network equilibrium model is developed in which the
users or travelers on the network are assumed to be multicriteria
decision-makers with an explicit environmental criterion. The members of a
class of traveler perceive their generalized cost on a route as a weighting of
travel time, travel cost, and the emissions generated. The model allows the
weights to be not only class-dependent but also link-dependent. The multiclass,
multicriteria network equilibrium conditions are shown to satisfy a
finite-dimensional variational inequality problem. Qualitative properties of
the solution are obtained. A special case of the model is then used to obtain
sharper results and to illustrate the relationship between the weights and the
attainment of a desired environmental quality standard. An algorithm is
proposed for the computation of the equilibrium pattern, along with convergence
results, and then applied to solve a numerical example. The multiclass,
multicriteria network equilibrium model is the first to incorporate an
environmental criterion.
TRP38
"A Space-Time Network for Telecommuting versus Commuting Decision-Making", by
Anna Nagurney, June Dong, and Patricia L. Mokhtarian. Available from the
authors. Papers in Regional Science 82, 2003,
451-473.
In this paper, we develop a theoretical framework for the study of telecommuting
versus commuting decision-making over a fixed time horizon, such as a work
week. We consider multiclass, multicriteria decision-makers who perceive the
criteria of travel cost, travel time, and opportunity cost in an individual
fashion. We introduce a space-time network to conceptualize the
decision-makers’ choices over space and time and propose a network equilibrium
model over the space-time network. The model allows for the prediction of the
equilibrium flows and, hence, the number of periods that members of each class
of decision-makers will telecommute or commute as well as the modes that they
will choose. In addition, we derive a tatonnement process whose set of
stationary points coincides with the set of equilibria. An algorithm is given,
along with convergence results, and applied to numerical examples.
TRP37
"Teleshopping versus Shopping: A Multicriteria Network Equilibrium Framework",
by Anna Nagurney, June Dong, and Patricia L. Mokhtarian. Mathematical and
Computer Modeling 34, 2001, 783-798.
This paper proposes a network equilibrium framework for the conceptualization,
modeling, and analysis of consumers’ selection of teleshopping versus shopping
for a frequently purchased product. The shoppers or consumers are assumed to be
multicriteria decision-makers with each class of consumer characterized by a
finite number of criteria which may include, for example, time, cost,
opportunity cost, as well as security/safety, among other criteria. We
construct the network structure of the consumers’ choices with an explicit
identification of the nodes, links, paths, and origin/destination pairs, and
allow each class of consumer or shopper to weight his criteria in an individual
manner on each link of the shopping network. The framework is the first to
capture teleshopping versus shopping alternatives with predictive equilibrium
flows.
TRP35
"Worker Telecommunication and Mobility in Transition: Consequences
for Planning", by Amy Helling and Patricia L. Mokhtarian. Journal of
Planning Literature 15(4) (May), 2001, 511-525.
Though planners have been interested in work-related telecommunication
and mobility arrangements chiefly as means of transportation demand management,
even telecommuting, the most promising in this regard, seems to have limited
long-run potential to reduce congestion. However, such work arrangements
do affect workers' travel needs, and thus the mix of travelers, destinations
and trip purposes as well as equitable access to housing, jobs and amenities.
They are also likely to further disperse residences in the long run, with
consequences for both land use and transportation, except where counterbalanced
by workers' rising time values and/or increased uncertainty about future
travel destinations or times. Thus, we recommend that academic researchers
and metropolitan planning organizations cooperate to identify effects of
telecommunication- and mobility-enabled work arrangements on travel and
location behavior in the long-run and at the detailed scale necessary for
truly forward-looking planning.
TRP33
"Modeling Employees' Perceptions and Proportional Preference of Work
Locations: The Regular Workplace and Telecommuting Alternatives", by
Patricia L. Mokhtarian and Michael N. Bagley. Transportation Research A
34(4), 2000, 223-242. To be reprinted in Transport and Information
Systems, eds. Roger Stough, Yoshiro Higano, Kenneth Button, and Peter
Nijkamp (Series on Classics in Transport Analysis, eds. Kenneth Button and Peter
Nijkamp), Cheltenham, UK, Edward Elgar Publishing Ltd.
This paper develops measures of job and workplace perceptions,
and examines the importance of those and other measures to the desired
proportions of work time at each of three locations: regular workplace,
home, and telecommuting center. Using data from 188 participants in the
Neighborhood Telecenters Project, four job context perception factors were
identified: productivity, job satisfaction, supervisor relationship, and
co-worker interaction. Four generic workplace perception factors were identified
(with measures for each of the work locations of interest): personal benefits,
work effectiveness, autonomy, and supervisor comfort. A multinomial logit
model of the desired work time allocation found the generic variables job
suitability, personal benefits, and work effectiveness to be significant
and positively related to greater desired proportions of time at the associated
location. These variables capture the major elements previously hypothesized
to influence telecommuting preference (including work, family, independence,
and commute stress reduction drives as well as manager and job suitability
constraints) in a parsimonious fashion. The model explained 55% of the
theoretical maximum amount of information in the data, and did not violate
IIA.
TRP32 "Beyond Tele-substitution: Disaggregate Longitudinal Structural
Equations Modeling of Communications Impacts",
by Patricia L. Mokhtarian and Ravikumar Meenakshisundaram. Transportation
Research C 7(1), 1999, 33-52. To be reprinted in Transport and
Information Systems, eds. Roger Stough, Yoshiro Higano, Kenneth Button, and
Peter Nijkamp (Series on Classics in Transport Analysis, eds. Kenneth Button and
Peter Nijkamp), Cheltenham, UK, Edward Elgar Publishing Ltd. Also to be
reprinted in Structural Change in Transportation and Communications in the
Knowledge Economy: New Questions and Analytical Approaches, ed. T. R.
Lakshmanan.
Information on the number and types of communication activities
(including travel) engaged in over a period of four consecutive days, at
two points in time about six months apart, was collected from 91 respondents.
A system of structural equations was developed and estimated, expressing
the quantity of each type of communication at time 2 as a function of quantities
of communication of each type at time 1, the elapsed time between measurements,
and exogenous sociodemographic variables. All "own" lagged effects (that
is, the effect of one communication type in wave 1 on the same type of
communication in wave 2) were found to be positive and (except for information
object delivery) highly significant. The "elapsed time" variable was always
positive and (except for personal meetings and, in one model, information
object delivery) significant; these effects indicate net generation of
communication activities over time. Significant "cross" lagged effects
(that is, the effect of one communication type in wave 1 on a different
type in wave 2) were mostly positive, indicating that the predominant effect
across modes is complementarity rather than substitution. Several exogenous
variables were also significant in logical ways.
TRP31 "The Tradeoff between Trips and Distance Traveled in Analyzing
the Emissions Impacts of Center-Based Telecommuting", by Patricia L.
Mokhtarian and Krishna V. Varma. Transportation Research D 3(6),
1998, 419-428.
In recent years telecommuting has attracted considerable attention
for its potential as an effective transportation control measure (TCM).
Most of the earlier studies of the travel and emissions impacts of telecommuting
have focused on the home-based form. Substantial reductions in distance
traveled, trips, and hence emissions have been found in these studies.
But the impacts of center-based telecommuting could be different: because
a commute trip is still made, the number of cold engine starts may not
be significantly affected even though distance traveled may still decrease.
Hence, the impacts on emissions may not be as strongly positive as for
home-based telecommuting, and if new trips are created, those impacts may
even be adverse.
This
paper describes one of the first studies of the travel and emissions impacts
particularly of center-based telecommuting, based on the largest sample
available to date. Travel diary data comprising 323 person-days and 1,442
person-trips were collected from 72 participants in a telecommuting center
demonstration project in California. Six fundamental travel indicators were
studied: number of person trips, personal vehicle trips, cold starts, hot
starts, person-miles traveled, and vehicle-miles traveled.
The per capita vehicle-miles traveled (VMT) were reduced significantly
as a result of center-based telecommuting (from 66.4 miles on non-telecommuting
days to 31.2 miles on telecommuting days, a 53% reduction). In contrast
to that, however, the number of commute personal vehicle trips increased
significantly (58%), from 1.2 to 1.9 trips per day (due to trips home for
lunch and back to the telecenter in the afternoon). On the other hand,
there was a significant decrease in the number of non-commute personal
vehicle trips, so that the total number of personal vehicle trips increased
slightly (from 3.0 to 3.3 trips) but not statistically significantly. Similarly,
there was a small but insignificant increase in the number of cold starts
(from 2.0 to 2.2).
What is the net impact of these partially counteracting effects on emissions?
As expected, the pollutants most-closely tied to distance traveled showed
the greatest reductions: a 51% decrease in particulate matter and a 35%
decrease in oxides of nitrogen for telecommuters on their telecommuting
days. The pleasant surprise is that reductions (albeit smaller ones) are
even found in the pollutants most closely tied to the number of cold starts:
a 15% decrease in total organic gases and a 21% decrease in carbon monoxide.
Even for those pollutants, a signi-ficant portion of the amount generated
is a function of distance traveled, and in this case it resulted that the
large decrease in distance traveled more than outweighed the slight increase
in trips in their respective effects on emissions.
TRP30 "Emerging Travel Patterns: Do Telecommunications Make a Difference?", by Patricia L. Mokhtarian and Ilan Salomon.
Invited resource paper for the 8th Meeting of the International Association for
Travel Behaviour Research, Austin,
TX, September 21-25, 1997.
Chapter 7 in: In Perpetual Motion: Travel Behaviour Research Opportunities
and Application Challenges, Hani S. Mahmassani, ed., Pergamon
Press/Elsevier, 2002, 143-182.
This paper reviews empirical studies of the relationships between
telecommunications and travel. The studies are classified into three
approaches: macro-scale, micro-scale application-specific, and micro-scale
comprehensive (activity-based). Within the second category we review
the literature on the applications of telecommuting, teleconferencing,
teleshopping, and the telephone. A diversity of relationships is
identified, with some studies finding complementarity and others finding
substitution. However, the preponderance of evidence suggests that
the net impact is complementarity, and continued growth in both telecommunications
and travel should be expected. Hypotheses and directions for future
research are discussed, including the need to further develop the comprehensive
activity-based approach and to synthesize accounting exercises with behavioral
modeling approaches to yield causal forecasts of the impacts of telecommunications
on travel.
TRP29 "The Impact of Gender, Occupation, and Presence of Children on
Telecommuting Motivations and Constraints", by Patricia L. Mokhtarian,
Michael N. Bagley, and Ilan Salomon. Journal of the American Society
for Information Science 49(12), Special Issue on Social Informatics,
1998, 1115-1134.
Accurate forecasts of the adoption and impacts of telecommuting
depend on an understanding of what motivates individuals to adopt telecommuting
and what constraints prevent them from doing so, since those motivations
and constraints offer insight into who is likely to telecommute under what
circumstances. Telecommuting motivations and constraints are likely to
differ by various segments of society. In this study, we analyze differences
in these variables due to gender, occupation, and presence of children
for 583 employees of the City of San Diego. Numerous differences are identified,
which can be used to inform policies (public or organizational) intended
to support telecommuting.
Most
broadly, women on average rated the advantages of telecommuting more highly than
men -- both overall and within each occupation group. Women were more likely
than men to have family, personal benefits, and stress reduction as potential
motivations for telecommuting, and more likely to possess the constraints of
supervisor unwillingness, risk aversion, and concern about lack of visibility to
management.
Clerical workers were more likely than managers or profes-sionals to
see the family, personal, and office stress-reduction benefits of telecommuting
as important, whereas managers and professionals were more likely to cite
getting more work done as the mo st important advantage of telecommuting.
Constraints present more strongly for clerical workers than for other occupations
included misunderstanding, supervisor unwillingness, job unsuitability,
risk aversion, and (together with professional workers) perceived reduced
social interaction. Constraints operating more strongly for professional
workers included fear of household distractions, reduced social and (together
with managers) professional interaction, the need for discipline, and lack
of visibility to management. Key constraints present for managers included
reduced professional interaction and household distractions.
Lack of awareness, cost, and lack of technology or other resources
did not differ significantly by gender or occupation.
Respondents with children rated the stress reduction and family benefits of
telecommuting more highly than did those with no children at home. Those with
children were more likely than those without children to be concerned about the
lack of visibility to management, and (especially managers) were more likely to
cite household distractions as a constraint.
TRP28 "A Synthetic Approach to Estimating the Impacts of Telecommuting
on Travel", by Patricia L. Mokhtarian. Urban Studies 35(2),
1998, 215-241.
A multiplicative model is proposed as a framework for examining
the current state of knowledge in forecasting the demand for telecommuting
and the resulting transportation impacts. A running illustrative example
(containing a base and a future case) is developed, using plausible values
for each factor in the model. The base case suggests that 6.1% of the workforce
may be currently telecommuting (at least in California), 1.2 days a week
on average, with the result that 1.5% of the workforce may be telecommuting
on any given day. It is estimated that the vehicle-miles eliminated by
this level of telecommuting constitute at most 1.1% of total household
vehicle travel. When the limited knowledge about potential stimulation
effects of telecommuting is inc orporated, it is estimated that the net
reduction falls to at most 0.6% of household travel. Reductions in the
future could be smaller as commute distances of telecommuters fall closer
to the average and as the stimulation effect grows. In any event it is
likely that, due to counteracting forces, the aggregate travel impacts
will remain relatively flat well into the future, even if the amount of
telecommuting increases considerably.
TRP27 "The Transportation Impacts of Center-Based Telecommuting: Interim
Findings from the Neighborhood Telecenters Project", by Prashant N.
Balepur, Krishna V. Varma, and Patricia L. Mokhtarian. Transportation
25(3), 1998, 287-306.
The transportation impacts of center-based telecommuting for
24 participants (representing 69 person-days of travel and 295 trips) in
the California Neighborhood Telecenters Project are analyzed. Comparing
non-telecommuting (NTC) day to telecommuting (TC ) day travel shows that
person-trips did not change significantly, whereas vehicle-trips increased
significantly (by about one trip) on TC days. Both PMT and VMT decline
significantly on TC days: by an average of 68 miles (74%) and 38 miles
(65%), respe ctively. When these savings are weighted by the frequency
of telecommuting, overall reductions in PMT and VMT come to 19% and 17%,
respectively, of total weekday travel. Commute trips increase slightly
(by 0.5 trips) but significantly, mainly due to lun ch-time trips made
home from the telecenter. Total non-commute travel does not increase, but
there is a significant shift from other modes to driving alone on TC days.
Commute mode split on NTC days is not affected by telecommuting. Travel
on TC days tends to be compressed into fewer hours. Higher numbers of return
home, eat meal, shopping, and social/recreational trips are made on TC
days, in exchange for a reduction (to zero) in the number of change mode
trips.
TRP26 "Analyzing
the Travel Behavior of Home-Based Workers in the 1991 Caltrans Statewide
Travel Survey", by Patricia L. Mokhtarian and Dennis K. Henderson.
Journal
of Transportation and Statistics 1(3), 1998, 25-41.
This study compares the travel patterns of three different groups
of workers identified from the 1991 Caltrans Statewide Travel Survey: home-based
business (HBB) workers, home-based telecommuters (HBT), and non-home-based
(NHB) workers. It constitutes the first known US study of HBB travel, and
the first representative-sample study of HBT travel. HBB workers have the
highest average daily trip rate of the three groups. In marked contrast
to previous specialized-sample studies of telecommuting, trip r ates for
HBTs and NHB workers are statistically equivalent. However, differences
between the two groups in distance traveled (as approximated by travel
time) appear to be similar to those of other studies, with HBTs traveling
46% less than NHB workers in this sample. Although HBB workers have the
highest work-related trip rate, the NHB group makes nearly twice as many
work and work-related trips combined as the HBB group, and more than three
times as many as HBTs. Telecommuters have more carpool trips and fewer
transit trips than the other two groups. The temporal distribution of HBB
trips is unimodal, in contrast to the traditional bi-modal distribution
for NHB trips and a flat distribution (from 9 a.m. to 6 p.m.) for HBTs.
The HBB group is quite he terogeneous, with distinct differences across
industry in overall trip rates, freeway use, and rates by purpose. Weaknesses
of the data set mean that these results should be viewed with some caution,
but they are suggestive of areas for further research.
TRP25 "The Duration and Frequency of Telecenter Use: Once a Telecommuter,
Always a Telecommuter?", by Krishna V. Varma, Chaang-Iuan Ho, David
M. Stanek, and Patricia L. Mokhtarian. Transportation Research C6(1/2),
1998, 47-68.
The study of temporal patterns of telecommuting is essential in understanding
the adoption of telecommuting and, hence, the impacts of telecommuting on the
demand for equipment and services as well as the demand for travel. This
research examines, in the context of center-based telecommuting, how often
individuals telecommute, the duration of their telecommuting participation, and
causes of attrition among telecommuters. It also presents related findings from
previous studies of home-based telecommuting.
Attrition at the telecenters studied was relatively high, with 50% of
all telecommuters quitting within the first nine months. The average telecommuting
frequency across the sample was 22% or about 1.1 days per week. Nearly
64% of the participants telecommuted less than one day per week on average.
The relationship between frequency and duration appears to be complex,
with partially counteracting trends. The results suggest that there is
a stable segment of the sample (stayers) who are committed higher-frequency
telecommuters, but that within the segment having a propensity to quit,
there is a slight but statistically significant tendency for higher-frequency
telecommuters to quit sooner.
The
motivations of participants for quitting the program were investigated. The most
frequent type of reason given was job-related (cited by more than a third of all
quitters). Other important reasons were supervisor-related (16%) and closure of
the center (12%). No one cited dissatisfaction with telecommuting as a reason
for quitting, and most quitters expressed a desire to continue telecommuting
from the center.
TRP24 "The Impact of Telecommuting on the Activity Spaces of Participants and
their Households", by Somitra Saxena and Patricia L. Mokhtarian.
Geographical
Analysis 29(2) (April), 1997, 124-144.
A spatial analysis of the activity space of telecommuters and their household
members is performed to analyze the impacts of telecommuting. The analysis is
based on the geo-coded travel diary data from the State of California
Telecommuting Pilot Project for State of California employees and their
household members. The study analyzes the spatial location, orientation and
extent of the activity locations within the "activity space" of individuals. To
be able to quantitatively compare and contrast the travel patterns and the
distribution of trip ends within the activity space, several spatial indicators
have been defined. Several hypotheses concerning the selection of activity
locations by individuals are presented and the impact of telecommuting on the
selection of locations for activity analyzed. Key findings include: on
telecommuting days, 86% of telecommuters' activities are performed closer to
home than to work, compared to 56% on normal commuting days; and destinations on
telecommuting days are more even distributed in all directions around the home,
whereas a majority of destinations on commuting days are oriented toward the
work location.
To be
able to understand the influence of the contributing factors towards the
selection of non-work activity locations, potential causal relationships between
the influencing factors and the activity location choice are investigated. Log-
linear models for cross-classified data are used to develop these relationships.
Key model estimation results include: interaction effects of activity location
with commute distance and with trip purpose are present in all the models,
confirming the importance of these two variables in the selection of activity
location; the interaction of activity location and income is also significant;
and day status (telecommuting or not) of the employee influences the trip
purpose, which in turn affects location. Several plausible model structures
provide a good fit, rather than having one unique model which represents the
activity location selection by individuals.
TRP23 "Analyzing the Preference for Non-Exclusive Forms of Telecommuting:
Modeling and Policy Implications", by Michael N. Bagley and Patricia
L. Mokhtarian. Transportation24(3), 1997, 203-226.
This paper examines the individual's preference to telecommute
from a center. Data obtained from 628 employees of the City of San Diego
were used in the development of three preference models based on a previously
developed conceptual model of the decision to telecommute. Two binary logit
models are presented, one on the preference to telecommute from a center
versus not telecommuting from a center (rho-squared = 0.28), and the other
on the preference to telecommute from a center over telecommuting from
home (rho-squared = 0.68). A multinomial logit model is also estimated
on the following four alternatives: preferring to telecommute from home,
preferring to telecommute from a center, preferring not to telecommute,
and preferring either form of telecommuting (rho-squared = 0.34). Tests
for the independence from irrelevant alternatives (IIA) property on the
third model showed that a multinomial logit structure was invalid, which
suggests that future research into other model structures such as multinomial
probit or nested logit should be conducted.
The results of the models illustrated the importance of attitudinal
measures in measuring an individual's preference to telecommute. Oblique
factor scores representing workplace interaction, stress, workaholism,
internal control, and commute stress were statistically significant in
some or all of the models. Other explanatory variables which were found
to be consistently significant were education, job suitability, and age.
TRP22 "Developing Models of Preference for Home-Based and Center-Based
Telecommuting: Findings and Forecasts", by David M. Stanek and Patricia
L. Mokhtarian. Technological Forecasting and Social Change 57(1/2),
1998, 53-74.
This paper investigates the preference to telecommute from
home and from a center. Survey data were collected from center-based telecommuters,
home-based telecommuters, and non-telecommuters, as part of a telecommuting
center demon- stration project in California. Factor analysis was performed
on questions relating to job satisfaction and attitudes about work characteristics.
Using these factor scores, as well as travel and sociodemographic variables,
the preferences to work from the telecommuting center and to work from
home were modeled. Logit models for center preference (rho-squared = 0.70),
home preference (rho-squared = 0.76), and center versus home preference
(rho-squared = 0.88) were estimated. The most frequently significant characteristics
were personal benefits at the center, work ethic at home, and age of the
respondent. Further research into multinomial logit models of preference
using the factor scores as generic and alternative-specific variables is
suggested.
TRP21 "Impacts of Center-Based Telecommuting on Travel and Emissions:
Analysis of the Puget Sound Demonstration Project", by Dennis K. Henderson
and Patricia L. Mokhtarian. Transportation Research D 1(1),
1996, 29-45.
Center-based telecommuting has many hypothesized benefits. To determine its
value as a transportation demand management strategy, however, its
travel-related benefits must be established quantitatively. This research
provides the first analysis of the impacts of center-based telecommuting on
individual travel behavior and emissions, using travel diary data from the Puget
Sound Telecommuting Demonstration Project.
An analysis of personal vehicle usage for this small sample of
workers showed that vehicle-miles traveled (VMT) were reduced significantly
as a result of center-based telecommuting (from 63.25 miles per person-day
on non-telecommuting days to 29.31 miles on telecommuting days). The reductions
in weekday VMT comprise significant reductions in commute-related VMT with
insignificant changes in non-commute-related VMT. The number of personal
vehicle trips did not change significantly. In essence, on telecommuting
days, center-based telecommuters behave as conventional commuters in terms
of their number of trips, but are more similar to home-based telecommuters
in terms of VMT reductions.
The significant reduction in VMT translates into a 49% decrease
in Oxides of Nitrogen (NOx) emissions and a 53% decrease in Particulate
Matter emissions comparing telecommuting days to non-telecommuting days
for the small sample. Because the number of daily trips was not impacted
by telecommuting, the levels of emissions associated with the cold start
process, Total Organic Gases (TOG) and Carbon Monoxide (CO), were essentially
unaffected. Of course, region-wide impacts will be much smaller when the
proportion of telecommuters in the work- force and the frequency of telecommuting
is considered.
TRP20 "The Travel and Emissions Impacts of Telecommuting for the State
of California Telecommuting Pilot Project", by Brett E. Koenig, Dennis
K. Henderson, and Patricia L. Mokhtarian. Transportation Research C
4(1),
1996, 13-32.
The impacts of home-based telecommuting on travel behavior
and personal vehicle emissions for participants in the State of California
Telecommuting Pilot Project are analyzed using the most advanced emissions
modeling tools currently available. A comparison of participants' telecommuting
day travel behavior with their before-telecommuting behavior shows a 27%
reduction in the number of personal vehicle trips, a 77% decrease in vehicle-miles
traveled (VMT), and 39% (and 4%) decreases in the number of cold (and hot)
engine starts. These decreases in travel translate into emissions reductions
of: 48% for Total Organic Gases (TOG), 64% for Carbon Monoxide (CO), 69%
for Nitrogen Oxides (NOx), and 78% for Particulate Matter (PM). Although
the authors developed the methodology to investigate the emissions impacts
of telecommuting, the analysis technique can be applied to any demand management
or other transportation strategy where all of the necessary model inputs
are available.
An analysis of the number of trips and VMT partitioned into commute-related
and non-commute-related purposes revealed that non-commute trips
increased
by 0.5 trips per person-day on average, whereas the non-commute VMT
decreased
by 5.3 miles. This important finding supports (for one indicator, the number
of trips) the hypothesis that non-commute travel generation is a potential
negative impact of telecommuting. This finding demonstrates the need to
monitor these changes as telecommuting moves into the mainstream. In this
study, however, the small increase in non-commute trips has a negligible
impact compared to the overall travel and emissions savings.
TRP19 "Using
Travel Diary Data to Estimate the Emissions Impacts of Transportation Strategies:
The Puget Sound Telecommuting Demonstration Project", by Dennis K.
Henderson, Brett E. Koenig, and Patricia L. Mokhtarian. Journal of the
Air and Waste Management Association 46 (January), 1996, 47-57.
Transportation control measures are often implemented for their environmental
benefits, but there is a need to quantify what benefits actually occur.
Telecommuting has the potential to reduce the number of daily trips and miles
traveled with personal vehicles and consequently, the overall emissions
resulting from vehicle activity. This research studies the emissions impacts of
telecommuting for the participants of the Puget Sound Telecommuting
Demonstration Project. The California Air Resources Board's emissions models,
EMFAC7F and BURDEN7F, are used to estimate the emissions on telecommuting days
and non-telecommuting days based on travel diaries completed by program
participants. This study, among the first of its kind, represents the most
sophisticated application to date of emissions models to travel diary data.
Analysis of the travel diary data and the emissions model output
supports the hypothesis that telecommuting has beneficial transportation
and air quality impacts. The most important results are that telecommuting
decreases the number of daily trips (by 30%), the vehicle miles traveled
(by 63%), and the number of cold starts (by 44%), especially those taking
place in early morning. These reductions are shown to have a large effect
on daily emissions with a 50 to 60% decrease in pollutants generated by
a telecommuter's personal vehicle use on a telecommuting day. Reductions
of this magnitude are observed because the telecommuters in this sample
are long-distance commuters, with commutes twice as long as the regional
average. However, even as telecommuting adoption moves into the mainstream,
its net impacts are still expected to be beneficial - a reduction in VMT
and emissions.
It is
important to note that when the level of telecommuting is considered, that is,
the percentage of work days that employees actually telecommute, the weekly
savings will be a much smaller proportion of total weekday travel. Also, these
findings represent average per-capita reductions; the aggregate (or overall,
region-wide) impacts are determined by scaling these reductions by the number of
program participants. Thus, the aggregate effectiveness of telecommuting must
take into account the number of people likely to participate as telecommuters
and how often they telecommute, not just the per-capita, per-occasion impacts.
TRP18 "The
Future of Telecommuting", by Susan L. Handy and Patricia L. Mokhtarian.
Futures
28(3),
1996, 227-240.
Interest in telecommuting is growing among transportation planners, workers,
employers, communities, the telecommunications industry, and others. But the
future of telecommuting depends on the choices and actions of these different
interest groups. This paper assesses that future by outlining and evaluating
important trends in a variety of factors and explores the need for new policies
and further research on telecommuting. For the most part the future of
telecommuting looks promising, but many questions remain about the nature of
telecommuting in the future.
TRP17 "Forecasting
Telecommuting: An Exploration of Methodologies and Research Needs",
by Susan L. Handy and Patricia L. Mokhtarian.
Transportation 23,
1996, 163-190.
Transportation planners increasingly recognize telecommuting as
an important trend. But while they often advocate telecommuting as a transportation
demand management strategy, transportation planners have made little progress
toward incorporating telecommuting into transportation forecasts, at least
partly because of the limited data available. In this paper we explore
four alternative methodologies for forecasting telecommuting and discuss
the kinds of data that must be collected before these methodologies can
be applied. The first approach is trend extrapolation, using curves of
technological substitution. Sufficient data are currently available to
produce forecasts, albeit highly uncertain forecasts, using this approach.
However, even with better data this approach does not address underlying
factors and trends that will affect the future of telecommuting. As a result,
we explore three additional approaches that should produce more reliable
forecasts but which require new data and knowledge about tel ecommuting:
analyzing the characteristics of telecommuters in contrast to nontelecommuters,
analyzing factors affecting the individual choice to telecommute, and incorporating
telecommuting into traditional transportation forecasting models.
TRP16
"Modeling the Choice of Telecommuting 3: Identifying the Choice Set and
Estimating Binary Choice Models for Technology-Based Alternatives",
by Patricia L. Mokhtarian and Ilan Salomon. Environment and Planning
A 28, 1996, 1877-1894.
Previous papers in this series have presented a conceptual model
of the individual decision to telecommute and explored relationships among
constraints, preference, and choice. A related paper has developed a binary
model of the preference for home-based telecommuting. Noting that there
is a wide gap between preferring to telecommute (88% of the sample) and
actually telecommuting (13%), this paper develops binary logit mode
