A new geodemographic classification of commuting flows for England and Wales

This paper aims to contribute to the area of geodemographic research through the development of a new and novel flow-based classification of commuting for England and Wales. In doing so, it applies an approach to the analysis of commuting in which origin-destination flow-data, collected as part of the 2011 census of England and Wales, are segmented into groups based on shared similarities across multiple demographic and socioeconomic attributes. k-Means clustering was applied to 49 flow-based commuter variables for 513,892 interactions that captured 18.4 million of the 26.5 million workers recorded as part of the 2011 census of England and Wales. The final classification resulted in an upper-tier of nine ‘Supergroups’ which were subsequently partitioned to derive a lower-tier of 40 ‘Groups’. A nomenclature was developed and associated pen portraits derived to provide basic signposting to the dominant characteristics of each cluster. Analysis of a selection of patterns underlying the ninefold Supergroup configuration revealed a highly variegated structure of commuting in England and Wales. The classification has potentially wide-ranging descriptive and analytical applications within research and policy domains and the approach would be equally transferable to other countries and contexts where origin-destination data are disaggregated based on commuter characteristics.本研究旨在通过构建面向英格兰与威尔士地区的、基于通勤流的新型分类体系，为地理人口统计学（geodemographic）研究领域贡献新的研究范式。研究采用的通勤分析方法，以2011年英格兰与威尔士人口普查采集的起讫点（origin-destination）通勤流数据为基础，依据多维度人口统计与社会经济属性的共同特征将数据划分为不同组别。本研究针对513892条起讫点通勤交互记录展开K均值聚类（k-Means clustering）分析，这些记录覆盖了2011年英格兰与威尔士人口普查记录的2650万通勤者中的1840万，共涉及49项基于通勤流的通勤特征变量。最终的分类体系形成了包含9个上层‘超级群组（Supergroups）’的层级结构，随后对超级群组进一步细分，得到40个下层‘群组（Groups）’。研究团队构建了配套的命名体系，并为每个聚类簇生成对应的简要特征画像，用以清晰指引各聚类簇的核心特征。对9个超级群组的潜在分布模式进行分析后发现，英格兰与威尔士地区的通勤结构呈现出高度多元化的特征。该分类体系在学术研究与政策制定领域具备广泛的描述性与分析性应用潜力，且这一研究方法可迁移至其他以通勤者特征为依据对起讫点数据进行细分的国家与场景中。