Keeping policy commitments: An organizational capability approach to local green housing equity.
Affordable housing that incorporates sustainability goals into its design has the potential to address both health and economic disparities via enhanced energy‐efficiency, structural durability and indoor environmental quality. Despite the potential for these win‐win advances, survey data of U.S. lo...
| Publicado en: | Review of Policy Research Vol. 41; no. 1; pp. 135 - 160 |
|---|---|
| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
Jan2024
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=174818596&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 174818596 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 1541132X MJJ jtl: Review of Policy Research issn: 1541132X maglogo: Y pubinfo: dt: Jan2024 vid: 41 iid: 1 pid: 480 pub: Wiley-Blackwell artinfo: ui: 174818596 10.1111/ropr.12499 ppf: 135 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P size: 1.1MB tig: atl: Keeping policy commitments: An organizational capability approach to local green housing equity. aug: au: Deslatte, Aaron Kim, Serena Hawkins, Christopher V. Stokan, Eric affil: O'Neill School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington Indiana,, USA College of Engineering, Design and Computing, University of Colorado Denver, Denver Colorado,, USA School of Public Administration, University of Central Florida, Orlando Florida,, USA Department of Political Science, University of Maryland Baltimore County, Baltimore Maryland,, USA su: Housing Organizational commitment Capabilities approach (Social sciences) Environmental policy Social sustainability Green movement Machine learning Knowledge management sug: subj: Housing Organizational commitment Capabilities approach (Social sciences) Environmental policy Social sustainability Green movement Administration of Air and Water Resource and Solid Waste Management Programs Other provincial and territorial public administration Other Community Housing Services Machine learning Knowledge management keyword: green housing machine learning process‐tracing social equity sustainability aprendizaje automático Igualdad Social seguimiento de procesos sustentabilidad vivienda verde 可持续性 机器学习 社会公平 绿色住房 过程追踪 green housing machine learning process‐tracing social equity sustainability aprendizaje automático Igualdad Social seguimiento de procesos sustentabilidad vivienda verde 可持续性 机器学习 社会公平 绿色住房 过程追踪 ab: Affordable housing that incorporates sustainability goals into its design has the potential to address both health and economic disparities via enhanced energy‐efficiency, structural durability and indoor environmental quality. Despite the potential for these win‐win advances, survey data of U.S. local governments indicate these types of equity investments remain rare. This study explores barriers and pathways to distributional equity via energy‐efficient housing. Using archival city sustainability survey data collected during a period of heightened U.S. federal investment in local government energy‐efficiency programs, we combine machine learning (ML) and process‐tracing approaches for modeling the complex drivers and barriers underlying these decisions. First, we ask, how do characteristics of a city's organizational learning methods—its administrative structure, past experience with housing programs, resources, stakeholder engagement and planning—predict policy commitments to green affordable housing? Using ensemble ML methods, we find that three specific modes of organizational learning—past experience with affordable housing programs, seeking assistance from neighborhood groups and the technical expertise of professional green organizations—are the most impactful features in determining city commitments to constructing green affordable housing. Our second stage uses process‐tracing within a specific case identified by the ML models to determine the ordering of these factors and to provide more nuance on green‐housing policy implementation. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|