Increasing response rates and improving research design: Learnings from the Smart Energy Research Lab in the United Kingdom
Increasing response rates and improving research design: Learnings from the Smart Energy Research Lab in the United Kingdom
复制标题
提高回复率并改进研究设计：英国智能能源研究实验室的经验教训
DOI：
10.1016/j.erss.2021.102312
复制
发表时间：
2022
影响因子：
6.7
通讯作者：
T. Oreszczyn
中科院分区：
文献类型：
--
作者：
E. Webborn;E. McKenna;S. Elam;B. Anderson;Adam B. Cooper;T. Oreszczyn
从大量具有代表性的家庭样本中获得高分辨率的能源消耗数据对研究至关重要，但低回复率、样本偏差和高招聘成本构成了实质性障碍。智能电表的广泛安装为获取此类数据提供了一种新的途径，但在英国等国家，需要得到每个家庭的同意；这是大规模抽样的真正障碍。在本文中，我们展示了某些研究设计选择如何影响能源研究请求访问半小时智能电表数据和（可选）调查完成的回复率。我们采用3×2×2因子设计的随机对照试验（RCT）；3个（包括无）激励组×2消息内容/结构×2“推送到网络”治疗组。多达4封邮件（信件）发送到18,000个地址，招募了1711名参与者（9.5%的回复率）在英格兰和威尔士。最有效的策略是提供有条件的5英镑代金券和多封邮件的邮政回复选项（相比之下，推送到网络的方式只有一次，尽管在线注册的人数要少得多）。激励标题和信息结构也被发现是有影响的。提醒增加了回应，但4次邮寄并不划算。我们的结果和建议可以用来帮助未来的能源研究获得更高的回复率和更好的代表性。英国的研究人员可以申请使用我们的纵向智能仪表和上下文数据集。
Obtaining high-resolution energy consumption data from a large, representative sample of homes is critical for research, but low response rates, sample bias and high recruitment costs form substantial barriers. The widespread installation of smart meters offers a novel route to access such data, but in countries like Great Britain (GB) consent is required from each household; a real barrier to large-scale sampling. In this paper we show how certain study design choices can impact the response rate for energy studies requesting access to half-hourly smart meter data and (optional) survey completion. We used a randomised control trial (RCT) with a 3×2×2 factorial design; 3 (including none) incentive groups ×2 message content/structures ×2 ‘push-to-web’ treatment groups. Up to 4 mailings (letters) were sent to 18,000 addresses, recruiting 1711 participants (9.5% response rate) in England and Wales. The most effective strategy offered a conditional £5 voucher and postal response options in multiple mailings (compared to only once in the push-to-web approach, although at the expense of far fewer online signups). Motivational headlines and message structure were also found to be influential. Reminders increased response but a 4thmailing was not cost effective. Our results and recommendations can be used to help future energy studies to achieve greater response rates and improved representation. UK-based researchers can apply to use our longitudinal smart meter and contextual datasets.
确保统计数据具有效力：减少电力需求和行为改变计划的设计、报告和行动指南
影响因子：
6.7
作者：
Anderson B
通讯作者：
Anderson B