Consumer Data Research Support Service (CDRSS)

消费者数据研究支持服务 (CDRSS)

• 批准号: ES/L011891/1
• 负责人: Mark Birkin
• 金额: $ 1124.78万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FL011891%2F1
• 关键词: Consumer; Data; Research; Support; Service

This project will establish a unique Consumer Data Research Support Service (CDRSS) for the supply and provision of new forms of 'Big Data' which are emerging in consumer markets. Big Data are frequently characterised as being high in volume, variety and velocity. In other words the data are continually changing (for example traffic sensors may capture the position of individual vehicles which are rarely stationary); the data are diverse (for example relating to the demographic characteristics of people, their movement patterns, their lifestyles and attitudes, social networks); and simply large, so that for example it is possible to retain data over long time periods as computer storage has also expanded sufficiently to permit this in many situations.Retail and consumer organisations have been leading the way in the creation and extraction of value from Big Data. For example Tesco has used data from its Clubcard scheme to profile its customers based on their shopping habits and expenditure patterns. This in turn has allowed the company to maintain a long-term competitive advantage in product development, promotion and store formatting and network development. Telecommunications providers are now processing billions of transactions each day as callers interact with mobile telephone cells and wireless devices. The CDRSS will capitalise on the growing realisation that Big Consumer Data can provide unique insights into social science questions, for example relating to prosperity, deprivation and exclusion; physical movement and behaviour patterns; healthy living, crime, family activities and social networks. The CDRSS will:* bring together diverse sources of consumer data for the first time within a secure environment;* produce tools for the anonymisation, aggregation and analysis of big consumer data;* develop flagship research projects which demonstrate the value of consumer data in research studies; * create the means for widespread access to these data amongst academic research users; * explore mechanisms for extending this engagement to business, government and the general public;* make an important contribution to training and capacity-building in consumer data analytics, and in this way it will therefore have a significant positive effect on the quantitative skills gap in UK social science;The CDRSS will interact with existing and proposed investments, for example in Administrative Data, Research Methods, and Social Media; but at the same time it will create unique resources and its own distinctive community of users.

该项目将建立一个独特的消费者数据研究支持服务（CDRSS），以供应和提供消费者市场中出现的新形式的“大数据”。大数据的特点通常是数量大、种类多、速度快。换句话说，数据是不断变化的（例如，交通传感器可以捕获很少静止的单个车辆的位置）;数据是多样的（例如，与人口特征、行动模式、生活方式和态度、社交网络有关的信息）;而且很大，因此，例如，由于计算机存储器也已充分扩展到允许在许多情况下长时间地保留数据，因此可以长时间地保留数据。组织一直在从大数据中创造和提取价值方面处于领先地位。例如，乐购利用其俱乐部卡计划的数据，根据客户的购物习惯和支出模式对其进行分析。这反过来又使公司在产品开发、促销和商店布局以及网络开发方面保持了长期的竞争优势。电信提供商现在每天处理数十亿笔交易，因为呼叫者与移动的电话单元和无线设备交互。CDRSS将充分利用日益增长的认识，即大消费者数据可以为社会科学问题提供独特的见解，例如与繁荣，贫困和排斥;身体运动和行为模式;健康生活，犯罪，家庭活动和社交网络。CDRSS将：* 首次在安全的环境中汇集不同来源的消费者数据;* 为匿名化、汇总和分析大量消费者数据提供工具;* 开发旗舰研究项目，展示消费者数据在研究中的价值; * 为学术研究用户广泛获取这些数据创造手段; * 探索将这种参与扩大到企业、政府和公众的机制;* 为消费者数据分析的培训和能力建设做出重要贡献，因此，它将对英国社会科学的定量技能差距产生重大积极影响; CDRSS将与现有和拟议的投资互动，例如在行政数据，研究方法和社交媒体方面;但同时它也将创造独特的资源和自己独特的用户群体。

项目成果

Exploring the practices of steal-to-order burglars: a different brand of offender?

• DOI: 10.1057/s41284-019-00174-w
• 发表时间: 2019-12-01
• 期刊: SECURITY JOURNAL
• 影响因子: 1.2
• 作者: Addis, Nicholas;Evans, Andrew;Malleson, Nicolas
• 通讯作者: Malleson, Nicolas

Crime at Places and Spatial Concentrations: Exploring the Spatial Stability of Property Crime in Vancouver BC, 2003-2013

• DOI: 10.1007/s10940-016-9295-8
• 发表时间: 2017-06-01
• 期刊: JOURNAL OF QUANTITATIVE CRIMINOLOGY
• 影响因子: 3.6
• 作者: Andresen, Martin A.;Linning, Shannon J.;Malleson, Nick
• 通讯作者: Malleson, Nick

A comparison of time to event analysis methods, using weight status and breast cancer as a case study.

• DOI: 10.1038/s41598-021-92944-z
• 发表时间: 2021-07-07
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Aivaliotis G;Palczewski J;Atkinson R;Cade JE;Morris MA
• 通讯作者: Morris MA

How big data and The Sims are helping us to build the cities of the future

大数据和模拟人生如何帮助我们建设未来的城市

• 发表时间: 2015
• 期刊: The Conversation
• 作者: A. Heppenstall

AirBNB Property Rentals and Reviews: Data Profile

爱彼迎 (AirBNB) 房产租赁和评论：数据简介

• 发表时间: 2019
• 作者: A Keeley