publications

2023

1. 

   In-Person, Pick Up or Delivery? Evolving Patterns of Household Spending Behavior Through the Early Reopening Phase of the COVID-19 Pandemic

   Said, Maher, Tahlyan, Divyakant, Stathopoulos, Amanda, Mahmassani, Hani, Shaheen, Susan, and Walker, Joan

   Travel Behaviour and Society 2023

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   Consumer reactions to COVID-19 pandemic disruptions have been varied, including modifications in spending frequency, amount, product categories and delivery channels. This study analyzes spending data from a sample of 720 U.S. households during the start of deconfinement and early vaccine rollout to understand changes in spending and behavior one year into the pandemic. This paper finds that overall spending is similar to pre-pandemic levels, except for a 28% decline in prepared food spending. More educated and higher income households with children have shifted away from in-person spending, whereas politically conservative respondents are more likely to shop in-person and via pickup.

   @article{said2023person,
     abbr = {spendingcovid},
     title = {In-Person, Pick Up or Delivery? Evolving Patterns of Household Spending Behavior Through the Early Reopening Phase of the COVID-19 Pandemic},
     author = {Said, Maher and Tahlyan, Divyakant and Stathopoulos, Amanda and Mahmassani, Hani and Shaheen, Susan and Walker, Joan},
     journal = {Travel Behaviour and Society},
     year = {2023},
     publisher = {Elsevier},
     selected = {true},
     html = {https://doi.org/10.1016/j.tbs.2023.01.003},
     bibtex_show = {true}
   }

2022

1. 

   For whom did telework not work during the Pandemic? understanding the factors impacting telework satisfaction in the US using a multiple indicator multiple cause (MIMIC) model

   Tahlyan, Divyakant, Said, Maher, Mahmassani, Hani, Stathopoulos, Amanda, Walker, Joan, and Shaheen, Susan

   Transportation Research Part A: Policy and Practice 2022

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   The COVID-19 pandemic required employees and businesses across the world to rapidly transition to work from home over extended periods, reaching what is likely the upper bound of telework in many sectors. Past studies have identified both advantages and disadvantages of teleworking. The pandemic experience offers a unique opportunity to examine employees’ experiences and perceptions of telework given the broad participation duration and extent. While employer strategies will play a major role in defining the future forms and adoption of telework, employee preferences and constraints, such as access to appropriate technology to work from home or the home environment, are also going to be important factors. Using data from a U.S. representative sample of 318 working adults, this study uses a Multiple Indicator Multiple Cause Model (MIMIC) to understand employee satisfaction with telework. The presented model links telework satisfaction with experienced and perceived benefits and barriers related to telework, and hence provide a causal structure to our understanding of telework satisfaction. We also present an ordered probit model without latent variables that help us understand the systematic heterogeneity in telework satisfaction across various socio-demographic groups. The results suggest younger and older aged individuals experienced/perceived lower benefits and higher barriers to teleworking compared to middle aged individuals. The results also suggest a disproportionate impact on Hispanic or Latino and Black respondents as well as on those with children attending online school from home. Accordingly, this study highlights important factors impacting telework adoption that employers and policy makers should consider in planning future work arrangements and policies in a post-pandemic world.

   @article{TAHLYAN2022387,
     abbr = {telework},
     title = {For whom did telework not work during the Pandemic? understanding the factors impacting telework satisfaction in the US using a multiple indicator multiple cause (MIMIC) model},
     author = {Tahlyan, Divyakant and Said, Maher and Mahmassani, Hani and Stathopoulos, Amanda and Walker, Joan and Shaheen, Susan},
     journal = {Transportation Research Part A: Policy and Practice},
     year = {2022},
     selected = {true},
     html = {https://doi.org/10.1016/j.tra.2021.11.025},
     bibtex_show = {true}
   }

2. 

   Characterizing visitor engagement behavior at large-scale events: Activity sequence clustering and ranking using GPS tracking data

   Abkarian, Hoseb, Tahlyan, Divyakant, Mahmassani, Hani, and Smilowitz, Karen

   Tourism Management 2022

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   This study uses GPS data of 1461 participants at a planned special event organized in Oshkosh, Wisconsin named AirVenture to characterize their spatio-temporal activity participation behavior. The GPS data is used to derive activity sequences for participants and study the attractiveness of various activities at the event site. A validation procedure is proposed using aerial photos, from which crowd density is estimated and compared to heatmaps of GPS data. A machine learning clustering approach is used to group participants into market segments on the basis of their activity sequences. The results show a prevalence of 6 behavioral groups with statistical tests confirming significant differences related to movement and time use. Finally, a multinomial logit model is formulated, demonstrating that age, prior visitation, and attendance plan (daily vs. weekly) affect the typological behavior. The results reveal valuable insights that can help special event organizers with related marketing and planning strategies.

   @article{abkarian2022characterizing,
     abbr = {seqclus},
     title = {Characterizing visitor engagement behavior at large-scale events: Activity sequence clustering and ranking using GPS tracking data},
     author = {Abkarian, Hoseb and Tahlyan, Divyakant and Mahmassani, Hani and Smilowitz, Karen},
     journal = {Tourism Management},
     year = {2022},
     selected = {false},
     bibtex_show = {true},
     html = {https://doi.org/10.1016/j.tourman.2021.104421}
   }

3. 

   [Open Access] Disentangling social capital – Understanding the effect of bonding and bridging on urban activity participation

   Tahlyan, Divyakant, Stathopoulos, Amanda, and Maness, Michael

   Transportation Research Interdisciplinary Perspectives 2022

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   Social capital is a critical glue for economic and social development in urban areas. Yet, to effectively guide research and practice, there is a need for careful measurement of social capital and how it links to important aspects of urban system functions. This study is aimed at examining the multi-dimensional nature of social capital and the relationship between these dimensions and travel behavior. Prior research has shown connections between stand-alone social capital concepts, such as resources gathered via social networks, with specific aspects of travel behavior. In this work, we expand the definition of social capital to cover separate dimensions, modeled via multiple indicators. Specifically, we make use of over 1400 observations from the Pew Internet Networks and Community Survey dataset to build a Structural Equation Model dividing social capital into two latent dimensions: bonding and bridging to examine the relationship of both these dimensions with discretionary urban activity participation diversity and frequency. Moreover, broader measures of neighborhood and community engagement are included in the model to explain how such engagement can help with the accumulation of social capital. Our results indicate a positive but differential relationship between both social capital dimensions and activity participation. Further, the results also suggest an absence of correlation between bonding and bridging capital, strengthening the hypothesis that social capital is multi-dimensional. In terms of explaining the social capital accrual, we find that while community engagement is positively correlated to bridging capital, no evidence was found for a relationship between community engagement and bonding capital. Further, neighborhood engagement was not found to be associated with any of the social capital dimensions. This suggests that individuals predominantly rely on close-knit and stronger relationships for social/emotional support, while instead, community engagement significantly helps in the accumulation of bridging capital. The result from the study can be used by policy makers to improve transportation planning, management, and community well-being.

   @article{tahlyan2022socialcapital,
     abbr = {socialcapital},
     title = {[Open Access] Disentangling social capital – Understanding the effect of bonding and bridging on urban activity participation},
     author = {Tahlyan, Divyakant and Stathopoulos, Amanda and Maness, Michael},
     journal = {Transportation Research Interdisciplinary Perspectives},
     year = {2022},
     selected = {true},
     html = {https://doi.org/10.1016/j.trip.2022.100629},
     bibtex_show = {true}
   }

2021

1. 

   The influence of activities and socio-economic/demographic factors on the acceptable distance in an Indian scenario

   Rahul, TM, Manoj, M, Tahlyan, Divyakant, and Verma, Ashish

   Transportation in Developing Economies 2021

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   Type of activity is an important aspect that influences the travel behavior of the trip makers. The present study uses the concept of an acceptable trip distance to compare the walking characteristics across subgroups of various socio-demographic factors and the type of activity. It further formulates a multiple linear regression model to investigate the relative influence of various socio-demographic factors and the type of activity on the walking distance; and develops a standalone formula, which reduces the effort of acceptable distance determination, for helping decision-makers to determine the acceptable distance easily. The regression model in the study found that the type of activity had a statistically significant effect on the walking distance. The acceptable distance for the work trips was found to be 996 m and for the ‘personal/household business’ trips was found to be 263 m. The results of this study were used to devise various policy guidelines including a zonal priority criterion for the development of pedestrian infrastructures and a stratified urban space where individuals would have an option of walking. Further, in the study, the standalone formula for calculating the acceptable distance was determined by equating the third derivative of the theoretical distribution (log-normal) to zero.

   @article{rahul2021influence,
     abbr = {walking},
     title = {The influence of activities and socio-economic/demographic factors on the acceptable distance in an Indian scenario},
     author = {Rahul, TM and Manoj, M and Tahlyan, Divyakant and Verma, Ashish},
     journal = {Transportation in Developing Economies},
     year = {2021},
     selected = {false},
     html = {https://link.springer.com/article/10.1007%2Fs40890-020-00110-3},
     bibtex_show = {true}
   }

2. 

   Simulating Large-Scale Events as a Network of Heterogeneous Queues: Framework and Application

   Cummings, Christopher, Abkarian, Hoseb, Zhou, Yuhan, Tahlyan, Divyakant, Smilowitz, Karen, and Mahmassani, Hani S.

   Transportation Research Record 2021

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   Large-scale planned special events (PSEs) can pose unique transportation and logistics challenges. Data collection and simulation are important tools to address these challenges, although they are often difficult because of event size and complexity. This paper discusses methods to address the challenge of multimodal simulation at large PSEs through the context of AirVenture, a large week-long airshow organized by the Experimental Aircraft Association in Oshkosh, Wisconsin. Sampling and data collection techniques are discussed for a variety of modal processes like private vehicles, pedestrians, and shuttles, and for different situations like vehicle arrivals and departures, pedestrian queues, and shuttle systems. A flexible simulation framework for integrating these three modes and numerous activities is developed as a network of heterogeneous queues and queue-dependent choices. The simulation tested a variety of proposed policy changes around the site, including rerouting shuttle lines, and adjusting the system of vehicle arrivals to the site. Results of this study demonstrate the effectiveness and flexibility of the data collection and simulation methodologies. The techniques developed in this work can be used to improve planning and transportation systems at many other forms of PSE.

   @article{eaasim2021,
     abbr = {eaasim},
     author = {Cummings, Christopher and Abkarian, Hoseb and Zhou, Yuhan and Tahlyan, Divyakant and Smilowitz, Karen and Mahmassani, Hani S.},
     title = {Simulating Large-Scale Events as a Network of Heterogeneous Queues: Framework and Application},
     journal = {Transportation Research Record},
     year = {2021},
     selected = {false},
     html = {https://doi.org/10.1177%2F03611981211035755},
     bibtex_show = {true}
   }

2020

1. 

   Performance evaluation of choice set generation algorithms for analyzing truck route choice: insights from spatial aggregation for the breadth first search link elimination (BFS-LE) algorithm

   Tahlyan, Divyakant, and Pinjari, Abdul Rawoof

   Transportmetrica A: Transport Science 2020

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   A new approach is presented to evaluate route choice set generation algorithms, which is based on comparing algorithm-generated choice sets for an origin-destination (OD) location pair against the portfolio of observed routes for that OD pair. The approach offers the ability to evaluate both the generation of relevant routes that are considered by travelers and the generation of extraneous routes that are seldom chosen. The approach is used to evaluate the performance of a breadth-first search link elimination (BFS-LE) algorithm to generate route choice sets for freight trucks. Based on the evaluation, the paper offers guidance on effectively using BFS-LE to maximize generation of relevant routes. It is found that aggregating route choice sets across trips with spatially proximate trip ends can reduce the need to generate large choice sets for each trip. However, such spatial aggregation might yield greater benefits if extraneous routes are eliminated from the choice sets.

   @article{tahlyan2020performance,
     abbr = {routeset},
     title = {Performance evaluation of choice set generation algorithms for analyzing truck route choice: insights from spatial aggregation for the breadth first search link elimination (BFS-LE) algorithm},
     author = {Tahlyan, Divyakant and Pinjari, Abdul Rawoof},
     journal = {Transportmetrica A: Transport Science},
     year = {2020},
     selected = {false},
     html = {https://www.tandfonline.com/doi/abs/10.1080/23249935.2020.1725790},
     bibtex_show = {true}
   }

2. 

   An empirical assessment of the impact of incorporating attitudinal variables on model transferability (In. Mapping the Travel Behavior Genome)

   Tahlyan, Divyakant, Balusu, Suryaprasanna Kumar, Sheela, Parvathy Vinod, Maness, Michael, and Pinjari, Abdul Rawoof

   2020

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   This chapter focuses on assessing the benefits of incorporating attitudinal and perception variables for the spatial transferability of travel forecasting models. Specifically, this study compares the spatial transferability, in an empirical setting, for three model structures: 1) multinomial logit (MNL), 2) integrated choice and latent variable (ICLV) models and 3) MNL with factor scores. Transferability is assessed by applying the models estimated in one spatial context to another spatial context. The data utilized for assessing the spatial transferability in the three contexts comes from a survey conducted among 1148 respondents across the United States – primarily the Midwest and Southeast. In the survey, respondents were asked about their preferred intended use of autonomous vehicles, along with personal and household characteristics, current travel characteristics, and perceptions about benefits and concerns related to autonomous vehicles. The study found that the ICLV models estimated had similar transferability to fixed coefficient MNL models with no improvement in transferability observed. But it was found that additional information that could lead to improvement of transferability was found when factor scores were directly incorporated into a MNL model. The chapter concludes with a discussion of possible transferability implications for ICLV model use.

   @incollection{tahlyan2020empirical,
     abbr = {transfer},
     title = {An empirical assessment of the impact of incorporating attitudinal variables on model transferability (In. Mapping the Travel Behavior Genome)},
     author = {Tahlyan, Divyakant and Balusu, Suryaprasanna Kumar and Sheela, Parvathy Vinod and Maness, Michael and Pinjari, Abdul Rawoof},
     booktitle = {Mapping the Travel Behavior Genome},
     year = {2020},
     selected = {false},
     html = {https://www.sciencedirect.com/science/article/pii/B9780128173404000097},
     bibtex_show = {true}
   }

3. 

   Agent based simulation model for improving passenger service time at Bangalore airport

   Verma, Ashish, Tahlyan, Divyakant, and Bhusari, Shubham

   Case Studies on Transport Policy 2020

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   This study presents a comprehensive exploratory analysis of truck route choice diversity in the state of Florida, for both long-haul and short-haul truck travel segments. It employs six metrics to measure three different dimensions of diversity in truck route choice between any given origin–destination (OD) pair. These dimensions are: (a) number of distinct routes used to travel between the OD pair, (b) the extent of overlap (or lack thereof) among the routes, and (c) the evenness (or dominance) in the usage of different unique routes. The diversity metrics were applied to a large database of 73,000 truck routes derived from 200 million GPS records. Descriptive analysis and statistical modeling of the diversity metrics offered insights into the determinants of various dimensions of truck route choice diversity between any OD pair. The results are useful for improving choice set generation algorithms for truck route choice modeling and in truck route policies and investments.

   @article{verma2020agent,
     abbr = {bnglrairport},
     title = {Agent based simulation model for improving passenger service time at Bangalore airport},
     author = {Verma, Ashish and Tahlyan, Divyakant and Bhusari, Shubham},
     journal = {Case Studies on Transport Policy},
     year = {2020},
     selected = {false},
     html = {https://doi.org/10.1016/j.cstp.2018.03.001},
     bibtex_show = {true}
   }

2018

1. 

   Comprehensive Exploratory Analysis of Truck Route Choice Diversity in Florida

   Luong, Trang D, Tahlyan, Divyakant, and Pinjari, Abdul R

   Transportation Research Record 2018

   Abs Bib HTML

   This study presents a comprehensive exploratory analysis of truck route choice diversity in the state of Florida, for both long-haul and short-haul truck travel segments. It employs six metrics to measure three different dimensions of diversity in truck route choice between any given origin–destination (OD) pair. These dimensions are: (a) number of distinct routes used to travel between the OD pair, (b) the extent of overlap (or lack thereof) among the routes, and (c) the evenness (or dominance) in the usage of different unique routes. The diversity metrics were applied to a large database of 73,000 truck routes derived from 200 million GPS records. Descriptive analysis and statistical modeling of the diversity metrics offered insights into the determinants of various dimensions of truck route choice diversity between any OD pair. The results are useful for improving choice set generation algorithms for truck route choice modeling and in truck route policies and investments.

   @article{luong2018comprehensive,
     abbr = {routediversity},
     title = {Comprehensive Exploratory Analysis of Truck Route Choice Diversity in Florida},
     author = {Luong, Trang D and Tahlyan, Divyakant and Pinjari, Abdul R},
     journal = {Transportation Research Record},
     year = {2018},
     selected = {false},
     html = {https://doi.org/10.1177%2F0361198118784175},
     bibtex_show = {true}
   }

2017

1. 

   Development of hub and spoke model for improving operational efficiency of bus transit network of Bangalore city

   Verma, Ashish, Kumari, Alpana, Tahlyan, Divyakant, and Hosapujari, Amalingayya B

   Case Studies on Transport Policy 2017

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   In a large city, operating a bus transit service on a route network based on destination-oriented or point-to-point approach, which considers all possible routes with the node set, is cumbersome and impractical. Alternatively, a Hub and Spoke network, which combine the destination-oriented and direction-oriented approaches, could be a more efficient choice. However, this model has only been applied to airline networks, whose influencing factors and variables could widely differ from those of an urban transit network. This paper proposes an approach to develop a hub and spoke network for an urban bus transit service in the Indian context. The proposed methodology consists of finding optimal locations for potential hubs, allocating non-hub nodes to hub nodes, and generating inter-hub and intra-hub routes and the frequencies of the bus service in those routes. For the case study, the proposed model is applied on the bus service operated by Bangalore Metropolitan Transport Corporation (BMTC) in Bangalore City, India. The results suggest noticeable savings in operator cost and CO2emissions compared with the existing point-to-point operational approach. This is significant considering that most of the urban bus transport corporations in India are currently under losses.

   @article{verma2017development,
     abbr = {hubspoke},
     title = {Development of hub and spoke model for improving operational efficiency of bus transit network of Bangalore city},
     author = {Verma, Ashish and Kumari, Alpana and Tahlyan, Divyakant and Hosapujari, Amalingayya B},
     journal = {Case Studies on Transport Policy},
     year = {2017},
     selected = {false},
     html = {https://doi.org/10.1016/j.cstp.2016.12.003},
     bibtex_show = {true}
   }