Patricia Mokhtarian
Professor, Civil Engineering Georgia Tech College of Engineering
- Atlanta GA
Patricia Mokhtarian has specialized in the application of quantitative methods to the study of travel behavior for more than 30 years.
Georgia Tech College of Engineering
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Media
Biography
Areas of Expertise
Selected Accomplishments
Sustained Research Award, School of Civil and Environmental Engineering, Georgia Institute of Technology
2015
Education
Florida State University
B.A.
Mathematics
1975
Northwestern University
M.S.
Industrial Engineering/Management Sciences
1977
Northwestern University
Ph.D.
Industrial Engineering/Management Sciences
1981
Links
Selected Media Appearances
How Will the Growing Popularity of Telecommuting Impact Public Transit?
Government Technology online
2017-11-01
Patricia Mokhtarian, a Georgia Tech professor who studies travel behavior and telecommuting, warns of other negative potential consequences. Given the option to work from home, some may opt to live further away from their jobs, leading to longer commutes when they do drive to the office. Telecommuting might also result in more air travel and its high carbon footprint. “I would advocate promotion of telecommuting,” Mokhtarian says, “but I would be clear-eyed on the likely transportation impacts.”
Selected Articles
Examining the impacts of residential self‐selection on travel behaviour: a focus on empirical findings
Transport ReviewsXinyu Cao, Patricia L Mokhtarian, Susan L Handy
2009
Numerous studies have found that suburban residents drive more and walk less than residents in traditional neighbourhoods. What is less well understood is the extent to which the observed patterns of travel behaviour can be attributed to the residential built environment (BE) itself, as opposed to attitude‐induced residential self‐selection. To date, most studies addressing this self‐selection issue fall into nine methodological categories: direct questioning, statistical control, instrumental variables, sample selection, propensity score, joint discrete choice models, structural equations models, mutually dependent discrete choice models and longitudinal designs. This paper reviews 38 empirical studies using these approaches. Virtually all of the studies reviewed found a statistically significant influence of the BE remaining after self‐selection was accounted for. However, the practical importance of that influence was seldom assessed. Although time and resource limitations are recognized, we recommend usage of longitudinal structural equations modelling with control groups, a design which is strong with respect to all causality requisites.
A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area
TransportationRyuichi Kitamura, Patricia L Mokhtarian, Laura Laidet
1997
This study examined the effects of land use and attitudinal characteristics on travel behavior for five diverse San Francisco Bay Area neighborhoods. First, socio-economic and neighborhood characteristics were regressed against number and proportion of trips by various modes. The best models for each measure of travel behavior confirmed that neighborhood characteristics add significant explanatory power when socio-economic differences are controlled for. Specifically, measures of residential density, public transit accessibility, mixed land use, and the presence of sidewalks are significantly associated with trip generation by mode and modal split. Second, 39 attitude statements relating to urban life were factor analyzed into eight factors: pro-environment, pro-transit, suburbanite, automotive mobility, time pressure, urban villager, TCM, and workaholic. Scores on these factors were introduced into the six best models discussed above. The relative contributions of the socio-economic, neighborhood, and attitudinal blocks of variables were assessed. While each block of variables offers some significant explanatory power to the models, the attitudinal variables explained the highest proportion of the variation in the data. The finding that attitudes are more strongly associated with travel than are land use characteristics suggests that land use policies promoting higher densities and mixtures may not alter travel demand materially unless residents' attitudes are also changed.
How do activities conducted while commuting influence mode choice? Using revealed preference models to inform public transportation advantage and autonomous vehicle scenarios
Transportation Research Part A: Policy and PracticeAliaksandr Malokin, Giovanni Circella, Patricia L. Mokhtarian
2019
From early studies of time allocation onward, it has been acknowledged that the “productive” nature of travel could affect its utility. Currently, at the margin an individual may choose transit over a shorter automobile trip, if thereby she is able to use the travel time more productively. On the other hand, recent advancements toward partly/fully automated vehicles are poised to revolutionize the perception and utilization of travel time in cars, and are further blurring the role of travel as a crisp transition between location-based activities. To quantify these effects, we created and administered a survey to measure travel multitasking attitudes and behaviors, together with general attitudes, mode-specific perceptions, and standard socioeconomic traits (N = 2229 Northern California commuters). In this paper, we present a revealed preference mode choice model that accounts for the impact of multitasking attitudes and behavior on the utility of various alternatives. We find that the propensity to engage in productive activities on the commute, operationalized as using a laptop/tablet, significantly influences utility and accounts for a small but non-trivial portion of the current mode shares. For example, the model estimates that commuter rail, transit, and car/vanpool shares would respectively be 0.11, 0.23, and 1.18 percentage points lower, and the drive-alone share 1.49 percentage points higher, if the option to use a laptop or tablet while commuting were not available. Conversely, in a hypothetical autonomous vehicles scenario, where the car would allow a high level of engagement in productive activities, the drive-alone share would increase by 1.48 percentage points. The results empirically demonstrate the potential of a multitasking propensity to reduce the disutility of travel time. Further, the methodology can be generalized to account for other properties of autonomous vehicles, among other applications.
User Preferences for Bicycle Infrastructure in Communities with Emerging Cycling Cultures
Transportation Research RecordCalvin Clark, Patricia Mokhtarian, Giovanni Circella, Kari Watkins
2019
Non-motorized travel modes, particularly cycling, are experiencing a resurgence in many United States (U.S.) states as well as in other countries. Still, most studies focus on bicyclists’ behaviors in areas with strong bicycling cultures. This paper discusses the findings of a survey (N = 1,178) deployed in six communities in Alabama and Tennessee, U.S., where cycling is not (yet) popular nor widely adopted. The analysis includes linear regression models built on respondents’ reactions to images of bicycling infrastructure and their perceptions of being comfortable, safe, and willing to try cycling on the displayed roadway type. Findings indicate a preference for more separated bicycle infrastructure types along with options that exclude on-street parking. Segmented models indicate that, compared with potential cyclists, the preferences of regular utilitarian cyclists can vary more than those of recreational/occasional cyclists. Results from this study provide useful insights into ways to maximize the return on investments, and design bike infrastructure that can attract patronage and be most successful in areas lacking a substantial bicycling population.
It’s not all fun and games: An investigation of the reported benefits and disadvantages of conducting activities while commuting
Travel Behaviour and SocietyF. Atiyya Shaw, Aliaksandr Malokin, Patricia L. Mokhtarian, Giovanni Circella
2019
Travel-based multitasking, or the performance of activities while traveling, is more feasible than ever before, as the expanding availability of shared ride services and increasing vehicle automation coincide with the ubiquity of portable information and communication technology devices. However, the question of whether, and if so, how these increasingly blurred boundaries between activities are truly helping rather than hurting us is not presently well-understood. Using an attitudinally-rich travel survey of Northern California commuters (N ≈ 2500), we develop a conceptual and empirically-based framework for studying benefits and disadvantages of travel-based multitasking. Through latent variable models of reported benefits and disadvantages of activities conducted on a recent commute, we identify constructs associated with hedonic and productive benefits, and with affective and cognitive disadvantages. This empirically-developed framework informs the definition of binary variables indicating the presence/absence of each construct for a given traveler on the commute in question. We then present two bivariate binary probit models that examine the effects of person and trip attributes such as personality traits, chosen mode, commute preferences, and activities conducted while traveling on the presence of those benefits and disadvantages, respectively. Notably, we find evidence that conditions/activities that may facilitate multitasking benefits can also simultaneously yield disadvantages; for example, several activities – conspicuously including talking on or otherwise using a phone – increase the probability of receiving benefits while also increasing the probability of experiencing cognitive disadvantages. This finding resonates with the general multitasking literature, and empirically corroborates the suggestion that travel-based multitasking may not uniformly increase trip utility.
