Analysis of telecommuting behavior and impacts on travel demand and the environment
Open accessAbstract
Abstract The discussion of whether, and to what extent, telecommuting can curb congestion in urban areas has spanned more than three decades. This study develops an integrated framework to provide the empirical evidence of the potential impacts of home-based telecommuting on travel behavior, network congestion, and air quality. In the first step, we estimate a telecommuting adoption model using a zero-inflated hierarchical ordered probit model to determine the factors associated with workers’ propensity to adopt telecommuting. Second, we implement the estimated model in the POLARIS activity-based framework to simulate the potential changes in workers’ activity-travel patterns and network congestion. Third, the MOVES mobile source emission simulator and Autonomie vehicle energy simulator are used to estimate the potential changes in vehicular emissions and fuel use in the network as a result of this policy. Different policy adoption scenarios are then tested in the proposed integrated platform. We found that compared to the current baseline situation where almost 12% of workers in Chicago region have flexible working time schedule, in the case when 50% of workers have flexible working time, telecommuting can reduce total daily vehicle miles traveled (VMT) and vehicle hours traveled (VHT) up to 0.69% and 2.09%, respectively. Considering the same comparison settings, this policy has the potential to reduce greenhouse gas and particulate matter emissions by up to 0.71% and 1.14%, respectively. In summary, our results endorse the fact that telecommuting policy has the potential to reduce network congestion and vehicular emissions specifically during rush hours.
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Telecommuting total emission savings are estimated at no more than 1% of total land transport GHG emissions.
“Key avoid strategies involve telecommuting, although total emission savings are estimated at no more than 1% of total land transport GHG emissions 31 .”
From Demand-side solutions to climate change mitigation consistent with high levels of well-being (2022) · cites this paper as [31]
Cites
Activity-based models of travel demand: promises, progress and prospects
Rasouli, S., & Timmermans, H. (2014) · International Journal of Urban Sciences · doi:10.1080/12265934.2013.835118 · Cited by 321 · see citing works
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- Authors
- Shabanpour, R., Golshani, N., Tayarani, M., Auld, J., & Mohammadian, A. (.
- Affiliations
- University of Illinois Chicago (US)
- University of New Mexico (US)
- Argonne National Laboratory (US)
- Corresponding author
- Shabanpour, Ramin
- Venue
- Transportation Research Part D: Transport and Environment
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 62
- Pages
- 563-576
- ISSN
- 1361-9209 (ISSN-L)
- OpenAlex
- W2804943360
- Semantic Scholar
- 89dc9e4fd007de3a6b7e366159f3e836e057746f
- Cited by
- 167
- References
- 1
- Citations by year
- 2026: 17 · 2025: 21 · 2024: 33 · 2023: 27 · 2022: 27 · 2021: 17 · 2020: 18 · 2019: 5 · 2018: 2
- FWCI
- 12.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 285 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Transportation Research Part D Transport and Environment (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- U.S. Department of Energy
- Topics
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
- Keywords
- remote work, travel demand, network congestion, air quality, vehicle miles traveled, vehicle emissions, flexible working hours, activity-based travel demand modeling, greenhouse gas emissions, particulate matter, peak hours, Chicago metropolitan area
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