Behavioural Modelling of Space and Time in the City Context: Implications for Urban Wellbeing

目前的经济学和心理学研究表明，不同年龄的人对时间和空间的感知是不同的。该项目将系统地测量这些差异，并将其与城市福祉联系起来。该研究将使用数据推理和机器学习算法来开发最终用户（公民、家庭、政策制定者和企业）可以改变其行为的方法，以便在城市环境中达到更高水平的城市福祉。设计并进行实验室和现场实验，然后用于测试如何将健康数据和行为见解呈现给市民，以“推动”他们做出更优化的决策并增加城市福祉。该角色的职责是集中注意设计和发展：(i)反馈协议和（ii）奖励机制，参照项目小组在人机和人-数据相互作用方面的工作；（iii）评估指定幸福要求的机制，以及确定团队、合作伙伴（SunBath和Databox）和外部应用程序使用的平台之间的数据流。在整个项目中，一个独立的研究项目将被开发出来，我将探索如何“推动”公民和家庭对他们的城市环境和生活方式做出更好的决定，以增加他们的福祉。

Current research in economics and psychology shows that people of different ages perceive time and space differently. This project will systematically measure those differences and relate them to urban wellbeing. The research will use data inference and machine learning algorithms to develop ways in which end users (citizens, households, policy-makers, and businesses) can change their behaviour in order to reach higher levels of urban wellbeing in the city context. Design and conduct laboratory and field experiment will then be used to test how wellbeing data and behavioural insights should be presented to citizens in order to 'nudge' them to make more optimal decisions and to increase urban wellbeing. The responsibilities of the role are to focus on the design and development of: (i) feedback protocols and (ii) incentive mechanisms, informed by the work of the project team on human-computer and human-data interactions; and (iii) evaluation of mechanisms for specifying happiness requirements as well as determining the data flow between the platforms used by the team, partners (SunBath and Databox), and external applications.Throughout this project an independent programme of research will be developed and I will explore how individual citizens and households could be 'nudged' to make better decisions about their urban environment and lifestyle, in order to increase their wellbeing.