Impacts of telecommuting, and related aspects of intelligent transportation systems on residential location choice: A combined revealed and stated preference approach

Telecommuting and Intelligent Transportation Systems (ITS) have already demonstrated transportation-related benefits such as reduced vehicle kilometres of travel, and reduction of fuel consumption and emissions. However, the long-term effects of ITS and telecommuting on land use are subject to uncertainty. Considering the relationship between land use and transportation, the question is what will be the impacts of telecommuting and ITS on urban development pattern, which in turn will effect travel demand structure. The purpose of this study was to investigate the impacts of telecommuting and ITS on land use patterns, specifically on households' residential location choice decisions. To study these effects, discrete choice analysis within the well-developed random utility theory framework was adopted. Within this framework, combined revealed preference (RP) and stated preference (SP) logit analysis was performed to estimate the parameters of the utility function. Using the sequential maximum likelihood estimation procedure, taste parameters of the combined RP and SP multinomial logit model were obtained. Statistical inferences on the estimated parameters were made and measures of goodness-of-fit were also calculated and discussed.; The main conclusion of this research was that telecommuting and ITS measures were found to be highly significant factors in the residential choice model. The effects of these measures were in the direction of supporting the decentralization of land use pattern.; The SP model provided useful information on tradeoffs among attributes. It also produced more robust parameter estimates than the RP model due to wider range of attributes in the SP data as well as the well-designed SP matrix. The combined model produced a much better data fit than the RP and SP models, separately. This indicates that the combined model was a stronger model than either of those models alone.; Also, the comparison of telecommuters and non-telecommuters in terms of their residential location behaviour showed that the coefficient of telecommuting factor was much larger for the former group than the latter. In addition, the magnitude of this factor was higher in the second- and third-tier locations than in the central city. This further reinforced the perspective that urban areas would experience sub-urbanization trend as a result of telecommuting.