Can Money Buy Green? Demographic and Socioeconomic Predictors of Lawn-Care Expenditures and Lawn Greenness in Urban Residential Areas
Can Money Buy Green? Demographic and Socioeconomic Predictors of Lawn-Care Expenditures and Lawn Greenness in Urban Residential Areas
复制标题
有钱能买到绿色吗？
DOI：
10.1080/08941920802074330
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发表时间：
2009
影响因子：
2.5
通讯作者：
J. Jenkins
中科院分区：
文献类型：
--
作者：
Weiqi Zhou;A. Troy;J. Morgan grove;J. Jenkins
了解家庭特征如何影响草坪特征变得越来越重要，因为草坪在人类主导的景观中发挥着重要的生态作用。本文调查了家庭和邻里的社会经济特征作为住宅草坪护理支出和草坪绿化的预测因子。研究区域是格温斯福尔斯流域，其中包括马里兰州巴尔的摩市和巴尔的摩县的部分地区。我们研究了人口、社会分层（收入、教育和种族）、生活方式行为和住房年龄等指标，作为草坪护理支出和草坪绿化的预测因子。我们还测试了PRIZM市场集群数据作为这两个因变量预测因子的潜力。草坪绿度被发现与草坪护理支出显着相关，但相对较弱的正相关。我们还发现生活方式行为指标是两个因变量的最佳预测因子。PRIZM数据，特别是生活方式细分，也被证明是两者的有用预测因素。
It is increasingly important to understand how household characteristics influence lawn characteristics, as lawns play an important ecological role in human-dominated landscapes. This article investigates household and neighborhood socioeconomic characteristics as predictors of residential lawn-care expenditures and lawn greenness. The study area is the Gwynns Falls watershed, which includes portions of Baltimore City and Baltimore County, MD. We examined indicators of population, social stratification (income, education and race), lifestyle behavior, and housing age as predictors of lawn-care expenditures and lawn greenness. We also tested the potential of PRIZM market cluster data as predictors for these two dependent variables. Lawn greenness was found to be significantly associated with lawn-care expenditures, but with a relatively weak positive correlation. We also found lifestyle behavior indicators to be the best predictors for both dependent variables. PRIZM data, especially the lifestyle segmentation, also proved to be useful predictors for both.