Hybrid geodemographics and creation of the 2021 Output Area Classification (ONS Collab)

地理人口学是小范围的邻里状况指标，通常用于描绘城镇杂乱无章的居住地理。尽管这种方法源于20世纪20年代芝加哥城市社会学家帕克和伯吉斯的原始数据收集，但将社区归类为社会、经济和人口类型的程序依赖于直到20世纪80年代的人口普查的次要数据。随着商业和公共服务提供应用的出现，数据得到了补充，部分由商业和开放来源取代，这些来源提供了更多的更新和深度(特别是在确定收入和支出偏好方面)。在过去十年中，人口普查机会的改善和开放数据运动的创新导致增加了开放的地理人口分类，从而提高了数据和方法的透明度。最后一项创新是人口普查数据的重新配置和重新使用，以提供夜间居住以外的小范围活动分类，特别是工作场所或其扩展，以探索不同的时间地理。在第一项工作中，将评估用于根据传统人口普查数据开发2011和2001年产出区域分类(OAC)的方法，并将对英国城市和区域系统的不同部分的社区变化统计数据进行比较和对比。在第二项工作中，学生将制定定期(例如每年)更新产出地区分类的方法。研究的第三部分将使用消费者数据来描述与社区相关的整体活动模式，以及它们与工作场所区域地理位置的相互关系。这将是一个影响很大的项目。2001年和2011年的OAC产品已通过国家统计局网站提供，并吸引了地方当局、商业和工业部门的广泛用户基础。此外，这项研究产生的分类将使用非常受欢迎和高度互动的maps.cdrc.ac.uk网站绘制，英国国家统计局将考虑恢复OAC 2011年的用户群体，该用户群体吸引了英国各地地方当局和政府的成员。此外，我们预计，根据2017年《数字经济法》的条款或通过相关的自愿活动向国家统计局提供数据的企业将对活动指标感兴趣。这里提出的议程对零售商和有兴趣进行门店选址规划和提供便利设施以改善多渠道零售客户体验的企业也具有明显的相关性。

Geodemographics are small area indicators of neighbourhood conditions, conventionally used to depict the variegated residential geographies of towns and cities. Although the approach has its roots in the primary data collection of urban sociologists Park and Burgess in 1920s Chicago, procedures of ascribing neighbourhoods to social, economic and demographic types relied upon secondary data from population censuses until the 1980s. With the advent of applications in commerce and public service delivery, data have been supplemented and partially replaced by commercial and open sources that offered greater frequency of update and depth (particularly in ascertaining income and spending preferences). Over the last ten years, improved access to censuses and the innovation of the Open Data movement has led to the addition of open geodemographic classifications that present greater transparency of data and methods. A final innovation has been the reconfiguration and re-use of census data to provide small area classification of activities other than night-time residence, specifically workplaces or their extension to explore varying temporal geographies.In the first work strand, the methodologies used to develop the 2011 and 2001 Output Area Classifications (OACs) from conventional Census data will be evaluated, and neighbourhood change statistics will be compared and contrasted for different parts of the UK's urban and regional system. In the second work strand, the student will develop methods for regularly (e.g. annually) updating Output Area Classifications. A third strand of the research will use consumer data to characterise the overall activity patterns associated with neighbourhoods, and their interrelatedness with workplace zone geographies. This will be a high impact project. The 2001 and 2011 OAC products have been made available through the ONS website and have attracted a wide user base from within the local authority, business and industry sectors. In addition, the classification arising from this research will be mapped using the very popular and highly interactive maps.cdrc.ac.uk website and ONS will consider rejuvenating the OAC 2011 User group which attracted membership from local authorities and government across the UK. Additionally, we anticipate that the activity indicators will be of interest to the businesses that supply data to ONS under the terms of the 2017 Digital Economies Act or through associated voluntary activities. The agenda that is proposed here also has clear relevance to retailers and businesses with interests in store location planning and the provision offacilities to improve customer experience of multi-channel retailing.