知行分离视角下郑州市居民低碳行为影响因素研究

居民低碳行为-认知研究受到学者们的广泛关注,而行为-认知分离却是困扰低碳城市建设和居民生活方式转变的关键问题。论文构建“空间-行为/认知”分析框架,采用2018年郑州市大规模实地调查和遥感影像数据,运用专家打分法从居家用能、日常出行与生活消费3个方面测算1485户家庭的低碳行为、认知水平,使用彩色编码法从行为-认知偏差视角将低碳行为分为绿色型、被迫型、易感型、红色型,使用多元Logistic回归模型分析不同低碳行为的影响因素。研究发现：① 郑州市居民低碳行为存在行为-认知偏差,4种低碳行为所占比例差异较大;② 绿色型低碳行为主要集聚在土地利用混合度高、基础设施便利的区域,被迫型、易感型、红色型低碳行为在空间上呈随机分布;③ 4种低碳行为影响因素差异较大。居住区步行指数较高、低碳认知水平高的居民趋于绿色型低碳行为,居民低碳行为与低碳认知水平均较高;居住区住房条件相对较差、居民学历水平低,居民趋于被迫型低碳行为,低碳认知水平低但低碳行为水平较高;高档住宅居民趋于易感型低碳行为,居民的低碳认知水平高但低碳行为水平较低;经济水平高的年轻居民趋于红色型低碳行为,低碳行为和低碳认知水平均较低。

Influencing factors of low-carbon behaviors of residents in Zhengzhou City from the perspective of cognition-behavior gaps

Residents' low-carbon behavior-cognition relationship has been widely concerned by scholars since cognition-behavior separation is a key factor that hinders the construction of low-carbon cities and the transformation of residents' lifestyle. This study constructed a spatial-behavioral/cognitive analysis framework and used large-scale field survey and remote sensing data of Zhengzhou City in 2018, as well as expert scoring method to estimate the low-carbon behavior level and low-carbon cognition level of 1485 families based on their daily travel and consumption of household energy. The color coding method was used to classify their behaviors into the green type, the forced type, the susceptible type, and the red type based on cognition-behavior gaps, and the multiple Logistic regression model was used to analyze the influencing factors of different low-carbon behaviors. The research findings show that: 1) There are large cognition-behavior gaps in low-carbon behaviors of residents in Zhengzhou City, and the proportions of the four low-carbon behaviors vary greatly. 2) Green low-carbon behaviors are mainly concentrated in areas with highly mixed land use and convenient infrastructure, and forced low-carbon behaviors, susceptible low-carbon behaviors, and red low-carbon behaviors are randomly distributed in space. 3) The influencing factors of the four types of low-carbon behaviors are very different. Residents living in areas with a high walking index score and a high level of low-carbon cognition tend to exhibit green low-carbon behaviors, and have a high level of low-carbon behavior and low-carbon cognition. In areas where housing conditions are relatively poor and residents have low levels of education, the residents tend to exhibit forced low-carbon behaviors, their low-carbon cognition level is low but low-carbon behavior level is high. Residents of high-end residential buildings tend to show susceptible low-carbon behaviors, they have a high level of low-carbon cognition but a low level of low-carbon behaviors. Young residents with high economic status tend to exhibit red low-carbon behaviors and have a low level of low-carbon behavior and low-carbon cognition.