Neto-Bradley André P, Rangarajan Rishika, Choudhary Ruchi, Bazaz Amir B
Department of Engineering, University of Cambridge, UK.
Indian Institute for Human Settlements, India.
MethodsX. 2021 Aug 14;8:101491. doi: 10.1016/j.mex.2021.101491. eCollection 2021.
Studies on clean energy transition amongst low-income urban households in the Global South use an array of qualitative and quantitative methods. However, attempts to combine qualitative and quantitative methods are rare and there are a lack of systematic approaches to this. This paper demonstrates a two stage approach using clustering methods to analyse a mixed dataset containing quantitative household survey data and qualitative interview data. By clustering the quantitative and qualitative data separately, latent groups with common characteristics and narratives arising from each of the two analyses are identified. A second stage of clustering identifies links between these qualitative and quantitative clusters and enables inference of energy transition pathways followed by low-income urban households defined by both quantitative characteristics and qualitative narratives. This approach can support interdisciplinary collaboration in energy research, providing a systematic approach to comparing and identifying links between quantitative and qualitative findings.•A mixed dataset comprising of quantitative survey data and qualitative interview data on low-income household energy use is analysed using hierarchical clustering to detect communities within each dataset.•Interviewees are matched to quantitative survey clusters and a second stage of clustering is performed using cluster membership as variables.•Second stage clusters identify common pairs of survey and interview clusters which define energy transition pathways based on socio-economic characteristics, energy use patterns, and narratives for decision making and practices.
对全球南方低收入城市家庭的清洁能源转型研究采用了一系列定性和定量方法。然而,将定性和定量方法结合起来的尝试很少,而且缺乏系统的方法。本文展示了一种两阶段方法,即使用聚类方法来分析一个包含定量家庭调查数据和定性访谈数据的混合数据集。通过分别对定量和定性数据进行聚类,识别出两个分析中各自产生的具有共同特征和叙述的潜在群体。聚类的第二阶段识别这些定性和定量聚类之间的联系,并能够推断出由定量特征和定性叙述所定义的低收入城市家庭所遵循的能源转型路径。这种方法可以支持能源研究中的跨学科合作,提供一种系统的方法来比较和识别定量和定性研究结果之间的联系。
使用层次聚类分析包含低收入家庭能源使用的定量调查数据和定性访谈数据的混合数据集,以检测每个数据集中的群体。
将受访者与定量调查聚类进行匹配,并使用聚类成员身份作为变量进行第二阶段的聚类。
第二阶段的聚类识别出调查和访谈聚类的常见配对,这些配对基于社会经济特征、能源使用模式以及决策和实践的叙述来定义能源转型路径。