The Changes of Urban Structure and Commuting: An Application to Metropolitan Statistical Areas in the United States

Abstract

While urban structures have been delineated at the regional level, few works have explored the impact of urban structures on commuting at this same level. This article studies how urban structures affect commuting from 2000 to 2010. It applies a spatial statistical tool, standard deviation ellipses, to capture spatial patterns of jobs and residential workers for metropolitan statistical areas (MSAs). Two urban structure indexes are constructed to illustrate different decentralization levels of employment with reference to the distribution of residential workers; one illustrates the spatial decentralization of high job density nodes, while the other shows the spatial decentralization of moderate job density nodes. Commuting times of two modes by private cars and public transit are analyzed along with the number of commuters. The results highlight three findings: (1) MSAs become more compact in terms of employment distribution, (2) more decentralized high-density nodes lead to less total commuting times, and on the other hand, more decentralized moderate job density nodes contribute to longer commuting times, and (3) the decentralization of high job density nodes is associated with less commuting time of private cars, while they have insignificant effect on commuting time of public transit.

Assessment and Determinants of the Quality of Life in Portuguese Cities

“…As cities increase their size, they tend to meet the economic and social conditions necessary to support certain amenities required to guarantee a good way of life (Puga 2010), favoring, in this way, the QoL of their inhabitants. However, as cities increase in size, a certain number of disamenities also appear such as crowding and pollution, which are detrimental to the cities' QoL (Baldassare and Wilson 1995;Frank and Engelke 2005;Yao and Kim 2019). Leknes (2015) also sustains that the appeal of a city increases with the quantity and quality of amenities, which are related to the number of inhabitants, thus contributing to higher QoL, if those benefits are not offset by congestion.…”

“…This implies that the QoL of cities may not only be affected by their size (number of inhabitants) but also by their population density. Big cities tend to be more crowded, polluted and oppressive as they aggregate too many individuals and businesses (Yao and Kim 2019). In this sense, small cities can offer higher QoL opportunities.…”

Employment deconcentration and spatial dispersion in metropolitan areas: Consequences for commuting patterns

“…Another challenge is the choice of spatial unit of analysis when measuring urban spatial structure. While some studies use census tracts or block groups (Hajrasouliha and Hamidi 2017;Yao and Kim 2019) or traffic analysis zones (Vandersmissen, Villeneuve, and Thériault 2003), other studies use smaller units of analysis such as 1 sq. km grid cells (Hipp, Kim, and Forthun 2021;Kane, Hipp, and Kim 2018;Krehl and Siedentop 2019).…”

Proposing new measures of employment deconcentration and spatial dispersion across metropolitan areas in the US

“…While some studies, such as Arribas‐Bel et al (2015) and Hajrasouliha and Hamidi (2017), have sought a better appraoch to identifying employment centres using local indicators of spatial clustering, others have avoided focusing on employment centres in their analysis of metropolitan spatial structure. Yao and Kim (2019), for instance, employed standard deviation elipeses to measure the degree to which jobs are decentralized in each of the largest US metropolitan areas with more than 500,000 commuters. Also, although the focus is not specifically on employment concentration, there is a body of research concerning the measurement of sprawl vs. compactness.…”