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贫民窟改造如何影响家电拥有情况?非收入驱动因素的结构模型。

How does slum rehabilitation influence appliance ownership? A structural model of non-income drivers.

作者信息

Debnath Ramit, Bardhan Ronita, Sunikka-Blank Minna

机构信息

Behaviour and Building Performance Group, Department of Architecture, University of Cambridge, CB21PX, UK.

Centre for Research in Arts, Social Sciences and Humanities, University of Cambridge, CB39DT, UK.

出版信息

Energy Policy. 2019 Sep;132:418-428. doi: 10.1016/j.enpol.2019.06.005.

DOI:10.1016/j.enpol.2019.06.005
PMID:31481823
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6703188/
Abstract

This study explores the effect of slum rehabilitation on appliance ownership and its implications on residential electricity demand. The low-income scenario makes it unique because the entire proposition is based on the importance of non-income drivers of appliance ownership that includes effects of changing the built environment (BE), household practices (HP) and appliances characteristics (AC). This study demonstrates quantitatively that non-income factors around energy practices influence appliance ownership, and therefore electricity consumption. The methodology consists of questionnaire design across the dimension of BE, HP and AC based on social practice theory, surveying of 1224 households and empirical analysis using covariance-based structural equation modelling. Results show that higher appliance ownership in the slum rehabilitation housing is due to change in household practice, built environment and affordability criteria of the appliances. Change in HP shifts necessary activities like cooking, washing and cleaning from outdoor to indoor spaces that positively and significantly influences higher appliance ownership. Poor BE conditions about indoor air quality, thermal comfort and hygiene; and product cost, discounts and ease of use of the appliances also triggers higher appliance ownership. The findings of this study can aid in designing better regulatory and energy efficiency policies for low-income settlements.

摘要

本研究探讨贫民窟改造对家电拥有情况的影响及其对居民用电需求的影响。低收入情景使其具有独特性,因为整个命题基于家电拥有情况的非收入驱动因素的重要性,这些因素包括建成环境(BE)变化、家庭行为(HP)和家电特性(AC)的影响。本研究定量表明,围绕能源使用行为的非收入因素会影响家电拥有情况,进而影响电力消耗。该方法包括基于社会实践理论设计涵盖BE、HP和AC维度的问卷,对1224户家庭进行调查,并使用基于协方差的结构方程模型进行实证分析。结果表明,贫民窟改造住房中较高的家电拥有率归因于家庭行为、建成环境的变化以及家电的可承受性标准。HP的变化将烹饪、洗涤和清洁等必要活动从室外转移到室内空间,这对更高的家电拥有率产生了积极且显著的影响。室内空气质量、热舒适度和卫生方面的不良BE条件,以及家电的产品成本、折扣和易用性也促使了更高的家电拥有率。本研究的结果有助于为低收入住区设计更好的监管和能源效率政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/31f491339d4f/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/3d66720f5f8f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/16bcf80aba11/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/5f544dcb1179/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/77813952f268/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/24e419ff2c9a/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/31f491339d4f/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/3d66720f5f8f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/16bcf80aba11/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/5f544dcb1179/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/77813952f268/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/24e419ff2c9a/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac26/6703188/31f491339d4f/gr6.jpg

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Grounded reality meets machine learning: A deep-narrative analysis framework for energy policy research.扎根现实与机器学习相遇:能源政策研究的深度叙事分析框架。
Energy Res Soc Sci. 2020 Nov;69:101704. doi: 10.1016/j.erss.2020.101704.