Conceptual Models of the Effect of Information and Communications Technology on Long-Distance Travel Demand

Erhardt, Gregory D.

doi:10.3141/2658-04

Cited by 4 publications

(1 citation statement)

References 18 publications

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“…Therefore, communication technologies may not save us much travel. As Larsen et al (70) and Erhardt (71) have noted, modern social networks are becoming more and more dispersed, aided by technology advances as well as greater mobility choice. Not only does the presence of such communication technologies result in a limited substitution effect (away from in-person travel), they enable people and businesses to stay connected at a distance.…”

Section: Modeling Resultsmentioning

confidence: 99%

Reducing Greenhouse Gas Emissions from Long-Distance Travel Business: How Far Can We Go?

Kockelman

Lee

2021

Transportation Research Record

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Long-distance (LD) travel accounts for over 30% of person-trip miles, with important energy and emissions impact. LD business travel can often be replaced by remote participation, so targeting such trips for cost, time, and emissions savings may be a wise strategy for protection of the climate, budgets, and human health. To appreciate Americans’ LD travel choices better, a 73-question online survey was conducted in 2019 that captured 2,327 LD (over 100 mi each way) trips made by 929 respondents during the previous 12 months, of which 490 round trips were for business purposes. Predictive models for LD trips per adult per year, overnights, LD travel times, and willingness to participate remotely and/or purchase carbon offsets for those trips were developed using respondents in Austin only. As expected, those educated to degree level tend to travel more often, for both business and nonbusiness purposes; everything else is constant. People who undertake LD travel more frequently are more likely to spend less time in transit/en route. Single people or those from large households educated to degree level are more likely to be willing to pay for the carbon emissions produced by their flights. Out of the 298 LD business trips made by Austinites, remote participation is possible for approximately a quarter, and the respondents involved are willing to participate remotely in 44% of those trips. In other words, Austinites appeared willing to participate remotely in slightly over 10% of their business trips overall, at least before the COVID-19 pandemic. This is definitely not enough to address climate change concerns as a result of carbon emissions from LD travel.

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Section: Modeling Resultsmentioning

confidence: 99%

Reducing Greenhouse Gas Emissions from Long-Distance Travel Business: How Far Can We Go?

Kockelman

Lee

2021

Transportation Research Record

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Understanding ICT’s impacts on urban spaces: a qualitative content analysis of literature

Kazem

Nourian

2020

GeoJournal

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The changing accuracy of traffic forecasts

et al. 2021

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Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road projects in the United States and Europe. We compared measured versus forecast traffic and identified the factors associated with accuracy. We found measured traffic is on average 6% lower than forecast volumes, with a mean absolute deviation of 17% from the forecast. Higher volume roads, higher functional classes, shorter time spans, and the use of travel models all improved accuracy. Unemployment rates also affected accuracy-traffic would be 1% greater than forecast on average, rather than 6% lower, if we adjust for higher unemployment during the post-recession years (2008 to 2014). Forecast accuracy was not consistent over time: more recent forecasts were more accurate, and the mean deviation changed direction. Traffic on projects that opened from the 1980s through early 2000s was higher on average than forecast, while traffic on more recent projects was lower on average than forecast. This research provides insight into the degree of confidence that planners and policy makers can expect from traffic forecasts and suggests that we should view forecasts as a range of possible outcomes rather than a single expected outcome.

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Conceptual Models of the Effect of Information and Communications Technology on Long-Distance Travel Demand

Cited by 4 publications

References 18 publications

Reducing Greenhouse Gas Emissions from Long-Distance Travel Business: How Far Can We Go?

Reducing Greenhouse Gas Emissions from Long-Distance Travel Business: How Far Can We Go?

Understanding ICT’s impacts on urban spaces: a qualitative content analysis of literature

The changing accuracy of traffic forecasts

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