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

目前经济学和心理学的研究表明，不同年龄的人对时间和空间的感知是不同的。这个项目将系统地衡量这些差异，并将它们与城市福祉联系起来。这项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，以便在城市背景下达到更高的城市福祉水平。设计和进行实验室和现场实验将被用来测试应该如何向公民展示幸福感数据和行为洞察力，以“推动”他们做出更优化的决定，并增加城市幸福感。该角色的职责是专注于设计和开发：(I)反馈协议和(Ii)激励机制，根据项目团队在人机和人-数据交互方面的工作提供信息；以及(Iii)评估指定幸福感要求的机制，以及确定团队、合作伙伴(太阳浴和数据库)和外部应用程序之间的数据流。通过这个项目，将制定一个独立的研究计划，我将探索如何才能“推动”个人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，以提高他们的幸福感。

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.