Divyakant Tahlyan

selected publications

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

   Abs Bib HTML

   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

   Abs Bib HTML

   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 = {true},
     bibtex_show = {true},
     html = {https://doi.org/10.1016/j.tourman.2021.104421}
   }

3. 

   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

   Abs Bib HTML

   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 = {true},
     html = {https://doi.org/10.1177%2F03611981211035755},
     bibtex_show = {true}
   }