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Built environment and potential job accessibility effects of road pricing: A spatial econometric perspective

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  • Zhong, Shaopeng
  • Bushell, Max

Abstract

This paper analyzes the impacts of the built environment (BE) as it relates to the potential job accessibility (PJA) effects of road pricing. The relationships between the BE elements and PJA under a road charging policy are established using a spatial econometric approach, which uses an integrated land use and transportation model (TRANUS model) and a spatial lag model (SLM). With the intent of further analyzing the differences in the PJA effects of road pricing on traffic analysis zones (TAZs) that contain different combinations of BE elements, a quantitative classification method combining factor and cluster analysis is applied. This will quantitatively categorize TAZs inside and outside the tolled areas. In exploring the relationship between changes in PJA and the road pricing policy, we found the spatial autocorrelation coefficient to be negative. This result suggests that we are unable to increase the PJA of all the regions through road pricing, but rather affect a redistribution of PJA between different regions. Results also indicate that the impacts of road charging on PJA are associated with urban BE elements. Moreover, such effects are the common result of specific characteristics of the BE. The higher the number of jobs, the better the public transportation conditions, and the better the street design (high densities of street and intersections), the less the region will be negatively influenced by a road charging policy, and vice versa. To avoid the negative effects of road pricing on PJA prior to the launch of such a policy, cities should improve public transportation networks and enhance the street design of the road pricing policy areas, especially the toll ring periphery area.

Suggested Citation

  • Zhong, Shaopeng & Bushell, Max, 2017. "Built environment and potential job accessibility effects of road pricing: A spatial econometric perspective," Journal of Transport Geography, Elsevier, vol. 60(C), pages 98-109.
    • Handle: RePEc:eee:jotrge:v:60:y:2017:i:c:p:98-109
    DOI: 10.1016/j.jtrangeo.2017.02.014
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