Impact of telecommuting and intelligent transportation systems on residential location choice

The impacts of telecommuting and intelligent transportation systems (ITS) on urban development patterns were investigated in terms of households' residential location choice decisions. A discrete choice modelling approach framework was used. A stated preference (SP) logit analysis was carried out to estimate the parameters of the utility function. An attitude survey of employees of selected public and private sector organizations in the Ottawa-Carleton Region (Canada) yielded the required data for model estimation. In addition to obtaining background information, the survey elicited SP responses by presenting a number of hypothetical residential choice scenarios defined according to the principles of SP experimental design. Results show that telecommuting and ITS measures are highly significant factors in the residential choice model. This leads to the conclusion that these reinforce dispersed residential patterns and encourage moves towards outlying sites. Implications of this conclusion for urban land development planning are noted.     

Analysis of telecommuting behavior and impacts on travel demand and the environment

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.     

Review: State of teleactivities

The investigation of teleactivities and their impacts on travel behavior received much attention in the transportation literature. Toward further teleactivity research, this paper reviews previous research and analyzes the findings regarding the role of Information and Communication Technologies (ICT) in personal activity and travel patterns. This review of about 100 studies of teleactivities impacts maps reviewed studies according to whether the type of personal activity is mandatory, maintenance, or leisure, the nature of the research is conceptual or empirical and, if empirical, tabulates the ICT impact and the modeling approaches. Telecommuting, enabling mandatory personal activities, has been the most investigated teleactivity (by more than 50% of reviewed articles). Teleshopping and several other teleservices (e.g., telebanking), enabling maintenance personal activities, have received less attention in the literature. Teleleisure, enabling discretionary personal activities, has been the least studied. Of the four major direct impacts of ICT on travel, i.e., substitution, complementarity, modification, and neutrality, substitution has been the most prevalent impact for telecommuting, with complementarity most prevalent impact for teleshopping and teleleisure. More recent empirical have applied more advanced modeling approaches.     

Does working from home reduce CO2 emissions? An analysis of travel patterns as dictated by workplaces

This research provides new evidence about the relationship between travel behavior, workplace diversification, and environmental impact in the United Kingdom using data from the National Travel Survey for the period between 2002 and 2017. The path analysis approach based on SEM handles both direct and indirect effects and allows for a comprehensive study of travel behavior, trade-off effects, and work and non-work trips. The results suggest that workplace diversification is often reflected by longer average distances for work trips, which are often associated with more remote residential locations. Findings also show that for some categories, such as teleworkers and home-based workers, trade-off effects are observed between work and non-work trips, which increase CO2 emission levels.     

Telecommuting and urban sprawl

This study examines what happens to city size when telecommuting occurs. It assumes that more telecommuting occurs when telecommuters’ labor cost share increases and/or workers adopt a more favorable attitude toward working from home. The study shows that telecommuting produces opposing forces that regulate the city size, one centralizing and the other decentralizing urban activities. These forces are examined in a city where workers and firms are given the option to freely mix working at the office and at home, and the city’s land use is endogenously determined. A rise in the productivity of an economy due to telecommunications technology could work to centralize urban activities, while urban contraction can occur with a fixed city population.     

Why do you care what other people think? A qualitative investigation of social influence and telecommuting

The effect of social interactions on decision-making is a topic of current interest in the travel behavior literature. These interactions have been investigated primarily from an intra-household perspective, but increasingly too in other types of social settings. In the case of interactions within a workplace, it has been suggested that the decision to telecommute may have some important social components. Previous research has concentrated on social isolation, and the effect on job satisfaction of qualitatively different (i.e., telecommunications-mediated) relationships with managers and colleagues. A topic that remains unexplored is the way social norms, in effect the influence of other people’s behavior, may influence the decision to adopt telecommuting. In this paper we set to investigate, within a qualitative framework, the role of social contact in the process of acquiring information on, and making decisions about, telecommuting. The results indicate that social contact does play a subtle but non-trivial role in the adoption and continuation process, and offer some insights about the importance of the social dimension, institutional set-up, and how they interact to influence the decision to telecommute.     

Understanding the role of the forecast-maker in overestimation forecasts of policy impacts: The case of Travel Demand Management policies

Forecasting the impacts of a proposed policy is an important component of the transportation planning and decision making process. Although scientific tools are often used in transportation forecasts, biases and, more specifically, overestimations of the expected impact are often observed. This study explores the correlations between forecast-maker’s characteristics and forecast bias creation and reduction. The study examines two transport-related policies aiming at the reduction of car use: telecommuting and carsharing. Both are Travel Demand Management (TDM) policies, which attract much attention from transport experts. We tested the extent to which the forecast-maker’s beliefs about the policy at stake affected the forecast bias. We found that attitudes and beliefs associates not only with overestimation bias but also with its reduction over time. We also tested the extent to which the forecast-maker’s affiliation, the performing institute and the publication type were correlated with the biases of the forecast and with the forecaster attitudes and beliefs. These characteristics are intuitively used by the forecast user as tools to assess the ‘objectivity’ of the forecast, but our analysis found no association between these characteristics and the forecast bias.