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A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago
Distance to the CBD and neighboring commercial employment (land-use) have been the core determinants of spatial-related production externalities for firms. In these models, travel time to work (firms) is the single most important factor for residential land-use allocation. New theories of complex ur...
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Published in: | Regional science and urban economics 2018-05, Vol.70, p.215-228 |
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description | Distance to the CBD and neighboring commercial employment (land-use) have been the core determinants of spatial-related production externalities for firms. In these models, travel time to work (firms) is the single most important factor for residential land-use allocation. New theories of complex urban systems (CUS), however, have begun to cast some doubt on the efficacy of the “distance to CBD” model. There is some evidence for example, that large urban systems might evolve with scale-free transportation networks. In this paper, we examine urban land-use data from the Chicago Metropolitan Statistical Area (MSA) to argue for a theoretical shift from a “distance to CBD” based prototype to one that considers the complexity inherent in urban systems structure. We use a Stochastic Greedy Algorithm to quantify connectivity and attractions to every land cell (30 × 30 m) to existing population and employment centers, Points of Interests (POIs), and highway and major roads. We measure the frequency of commercial and resident land-uses relative to these found attraction levels and develop algorithms that help explain the relations. Using these methods, we find that both CBD-driven and network-driven approaches are empirically valid for explaining current urban structures. We also find, however, that these relations change when temporal variables are considered. For example, we found that the land-use change in Chicago from 2001 to 2011 is an obvious deviation from the “distance to CBD” based urban growth assumption. Our results suggest that we should re-examine the core urban structure assumptions of spatial equilibrium models.
•Residential and commercial land-uses in Chicago are distributed along networks.•Amenities are the most important determinants in household location choices.•Existing commercial activity shows spatial externalities to other commercial.•New commercial developments have different spatial externalities to existing ones.•Distance-based and trip-to-work based economic policies need reconsideration. |
doi_str_mv | 10.1016/j.regsciurbeco.2018.04.009 |
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•Residential and commercial land-uses in Chicago are distributed along networks.•Amenities are the most important determinants in household location choices.•Existing commercial activity shows spatial externalities to other commercial.•New commercial developments have different spatial externalities to existing ones.•Distance-based and trip-to-work based economic policies need reconsideration.</description><identifier>ISSN: 0166-0462</identifier><identifier>EISSN: 1879-2308</identifier><identifier>DOI: 10.1016/j.regsciurbeco.2018.04.009</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithms ; CBD ; Central business districts ; Complex urban system ; Deviation ; Efficacy ; Employment ; Equilibrium ; Externality ; Greedy algorithm ; Land ; Land use ; Metropolitan statistical areas ; Production externalities ; Scale-free networks ; Stochastic models ; Stochasticity ; Transportation ; Transportation networks ; Urban areas ; Urban growth ; Urban sprawl ; Urban structure ; Urban structures</subject><ispartof>Regional science and urban economics, 2018-05, Vol.70, p.215-228</ispartof><rights>2018 Elsevier B.V.</rights><rights>Copyright Elsevier Sequoia S.A. May 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c417t-ca0540a9e3483e8c7df924ccb738b931cd1aefe70b7160a9615580461a6f68993</citedby><cites>FETCH-LOGICAL-c417t-ca0540a9e3483e8c7df924ccb738b931cd1aefe70b7160a9615580461a6f68993</cites><orcidid>0000-0002-9981-5474 ; 0000-0002-0709-632X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925,33223</link.rule.ids></links><search><creatorcontrib>Pan, Haozhi</creatorcontrib><creatorcontrib>Deal, Brian</creatorcontrib><creatorcontrib>Chen, Yan</creatorcontrib><creatorcontrib>Hewings, Geoffrey</creatorcontrib><title>A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago</title><title>Regional science and urban economics</title><description>Distance to the CBD and neighboring commercial employment (land-use) have been the core determinants of spatial-related production externalities for firms. In these models, travel time to work (firms) is the single most important factor for residential land-use allocation. New theories of complex urban systems (CUS), however, have begun to cast some doubt on the efficacy of the “distance to CBD” model. There is some evidence for example, that large urban systems might evolve with scale-free transportation networks. In this paper, we examine urban land-use data from the Chicago Metropolitan Statistical Area (MSA) to argue for a theoretical shift from a “distance to CBD” based prototype to one that considers the complexity inherent in urban systems structure. We use a Stochastic Greedy Algorithm to quantify connectivity and attractions to every land cell (30 × 30 m) to existing population and employment centers, Points of Interests (POIs), and highway and major roads. We measure the frequency of commercial and resident land-uses relative to these found attraction levels and develop algorithms that help explain the relations. Using these methods, we find that both CBD-driven and network-driven approaches are empirically valid for explaining current urban structures. We also find, however, that these relations change when temporal variables are considered. For example, we found that the land-use change in Chicago from 2001 to 2011 is an obvious deviation from the “distance to CBD” based urban growth assumption. Our results suggest that we should re-examine the core urban structure assumptions of spatial equilibrium models.
•Residential and commercial land-uses in Chicago are distributed along networks.•Amenities are the most important determinants in household location choices.•Existing commercial activity shows spatial externalities to other commercial.•New commercial developments have different spatial externalities to existing ones.•Distance-based and trip-to-work based economic policies need reconsideration.</description><subject>Algorithms</subject><subject>CBD</subject><subject>Central business districts</subject><subject>Complex urban system</subject><subject>Deviation</subject><subject>Efficacy</subject><subject>Employment</subject><subject>Equilibrium</subject><subject>Externality</subject><subject>Greedy algorithm</subject><subject>Land</subject><subject>Land use</subject><subject>Metropolitan statistical areas</subject><subject>Production externalities</subject><subject>Scale-free networks</subject><subject>Stochastic models</subject><subject>Stochasticity</subject><subject>Transportation</subject><subject>Transportation networks</subject><subject>Urban areas</subject><subject>Urban growth</subject><subject>Urban sprawl</subject><subject>Urban structure</subject><subject>Urban structures</subject><issn>0166-0462</issn><issn>1879-2308</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><recordid>eNqNkE1OwzAQhS0EEqVwBwvWCXZ-HLsbVNryI1VCQrC2HGdSEtq42E4ROw7BCTkJjsqCJZsZafS9N3oPoXNKYkoou2xjCyunm96WoE2cEMpjksWEiAM0orwQUZISfohGAWYRyVhyjE6cawkJhyQdIT_Fj6CcA-c20Hlsahy8VIedt732vQWsugqvw4h6B3irvAfbuQmuGudVpwF7g2fXc2ws7sC_G_salcpBdYW_P7_wYtdUMFC1NRs8e2m0WplTdFSrtYOz3z1GzzeLp9ldtHy4vZ9Nl5HOaOEjrUieESUgzXgKXBdVLZJM67JIeSlSqiuqoIaClAVlgWM0z3nISBWrGRciHaOLve_WmrcenJet6W0XXsqEcFEkTOQsUJM9pa1xzkItt7bZKPshKZFDy7KVf1uWQ8uSZDK0HMTzvRhCjl0DVgZuCFw1FrSXlWn-Y_MDfIuN8w</recordid><startdate>20180501</startdate><enddate>20180501</enddate><creator>Pan, Haozhi</creator><creator>Deal, Brian</creator><creator>Chen, Yan</creator><creator>Hewings, Geoffrey</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><orcidid>https://orcid.org/0000-0002-9981-5474</orcidid><orcidid>https://orcid.org/0000-0002-0709-632X</orcidid></search><sort><creationdate>20180501</creationdate><title>A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago</title><author>Pan, Haozhi ; Deal, Brian ; Chen, Yan ; Hewings, Geoffrey</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c417t-ca0540a9e3483e8c7df924ccb738b931cd1aefe70b7160a9615580461a6f68993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>CBD</topic><topic>Central business districts</topic><topic>Complex urban system</topic><topic>Deviation</topic><topic>Efficacy</topic><topic>Employment</topic><topic>Equilibrium</topic><topic>Externality</topic><topic>Greedy algorithm</topic><topic>Land</topic><topic>Land use</topic><topic>Metropolitan statistical areas</topic><topic>Production externalities</topic><topic>Scale-free networks</topic><topic>Stochastic models</topic><topic>Stochasticity</topic><topic>Transportation</topic><topic>Transportation networks</topic><topic>Urban areas</topic><topic>Urban growth</topic><topic>Urban sprawl</topic><topic>Urban structure</topic><topic>Urban structures</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pan, Haozhi</creatorcontrib><creatorcontrib>Deal, Brian</creatorcontrib><creatorcontrib>Chen, Yan</creatorcontrib><creatorcontrib>Hewings, Geoffrey</creatorcontrib><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Regional science and urban economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pan, Haozhi</au><au>Deal, Brian</au><au>Chen, Yan</au><au>Hewings, Geoffrey</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago</atitle><jtitle>Regional science and urban economics</jtitle><date>2018-05-01</date><risdate>2018</risdate><volume>70</volume><spage>215</spage><epage>228</epage><pages>215-228</pages><issn>0166-0462</issn><eissn>1879-2308</eissn><abstract>Distance to the CBD and neighboring commercial employment (land-use) have been the core determinants of spatial-related production externalities for firms. In these models, travel time to work (firms) is the single most important factor for residential land-use allocation. New theories of complex urban systems (CUS), however, have begun to cast some doubt on the efficacy of the “distance to CBD” model. There is some evidence for example, that large urban systems might evolve with scale-free transportation networks. In this paper, we examine urban land-use data from the Chicago Metropolitan Statistical Area (MSA) to argue for a theoretical shift from a “distance to CBD” based prototype to one that considers the complexity inherent in urban systems structure. We use a Stochastic Greedy Algorithm to quantify connectivity and attractions to every land cell (30 × 30 m) to existing population and employment centers, Points of Interests (POIs), and highway and major roads. We measure the frequency of commercial and resident land-uses relative to these found attraction levels and develop algorithms that help explain the relations. Using these methods, we find that both CBD-driven and network-driven approaches are empirically valid for explaining current urban structures. We also find, however, that these relations change when temporal variables are considered. For example, we found that the land-use change in Chicago from 2001 to 2011 is an obvious deviation from the “distance to CBD” based urban growth assumption. Our results suggest that we should re-examine the core urban structure assumptions of spatial equilibrium models.
•Residential and commercial land-uses in Chicago are distributed along networks.•Amenities are the most important determinants in household location choices.•Existing commercial activity shows spatial externalities to other commercial.•New commercial developments have different spatial externalities to existing ones.•Distance-based and trip-to-work based economic policies need reconsideration.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.regsciurbeco.2018.04.009</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-9981-5474</orcidid><orcidid>https://orcid.org/0000-0002-0709-632X</orcidid></addata></record> |
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subjects | Algorithms CBD Central business districts Complex urban system Deviation Efficacy Employment Equilibrium Externality Greedy algorithm Land Land use Metropolitan statistical areas Production externalities Scale-free networks Stochastic models Stochasticity Transportation Transportation networks Urban areas Urban growth Urban sprawl Urban structure Urban structures |
title | A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago |
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