DATA-DRIVEN INTEGRATED TRANSPORT SOLUTIONS - USING PERSONAS IN POLICY-MAKING

交通运输是我们社会所有日常活动的推动者，对国家经济发展至关重要。交通也直接或间接地影响福祉，包括使人们能够获得重要的生活必需品和活动，促进身体流动性，促进基础设施发展（Delbosc, 2012）。因此，改善交通系统不仅能促进社会和经济发展，还能增进福祉和平等（Chatterjee et al., 2019）。政府承诺向社会所有成员提供公共服务，并将投资和金融资本分配给最需要的项目、地方和社区（公务员制度，2022年；英国政府，2022年）。然而，由于几个原因，乘客之间表达的情绪、态度、偏好和行为各不相同（Mooradian & Swan, 2006）。为了开展这些公共活动，有必要了解不同人口群体的行为、需求和偏好，提供最适当的干预措施，并确定应优先考虑的最脆弱群体。人物角色是沟通和交互设计的强大工具（Caballero等人，2014），可以用作设计工具来创建以用户为中心的政策和服务（Gonzalez de Heredia等人，2018）。本研究旨在探讨如何操纵来自不同来源的数据，以了解不同人口群体的旅行行为，并为决策过程提供支持。两个主要的研究问题是：如何操纵来自多个来源的数据，以加深对不同角色的旅行行为的理解。如何利用人物角色来支持基于证据的政策制定。该研究将与运输部（DfT）的同事合作进行探索和开发，重点关注英国国内运输系统的背景。在调查政策与人物之间的关系时，政策将塑造交通系统。分析政策对人物角色的影响可以通过回到人的因素中的经典问题来完成：检查人物角色与政策设计的系统之间的相互作用。Davis等人（2014）设计的社会技术框架和Wilson & Sharples（2015）重新设计的“洋葱模型”将被应用于分析人物角色（人）与政策（技术、文化、流程、基础设施、目标）形成的相关元素之间的关系。本研究将分为两部分。第一部分致力于调查旅行者角色与交通系统中其他元素之间的相互作用。多种数据来源，包括国家调查数据源（2002 - 2021）、英国人口普查数据（至2022）和其他数字足迹数据，将用于扩大和深化DfT人物角色的叙述。在研究项目的第二阶段，将采用人因方法和政策分析的定性方法来研究人物角色在基于证据的政策制定中的应用。将创建一个衡量和比较不同政策选择对不同角色的影响的框架。这项研究将集中于改进决策技术，而不是建议一项特定的政策。因此，该研究可以填补关于在设计中使用人物角色的知识空白，特别是人物角色如何积极影响决策过程。

Transport is an enabler for all daily activities in our society and is essential to national economic development. Transport also influences wellbeing directly and indirectly, including enabling access to significant life necessities and activities, promoting physical mobility, and fostering infrastructure development (Delbosc, 2012). Thus, improving the transport system not only enables social and economic development but also enhances wellbeing and equality (Chatterjee et al., 2019). The Government committed to providing public services to all members of society and distributing investment and financial capital to the programmes, places and communities that require it most (Civil Service, 2022; HM Government, 2022). However, expressed sentiments, attitudes, preferences, and behaviour among passengers vary for several reasons (Mooradian & Swan, 2006). To conduct these public engagements, it is necessary to comprehend the behaviour, demands, and preferences of various population groups, to provide the most appropriate intervention, and to identify the most vulnerable groups that should be prioritised.Persona is a powerful tool for communication and interactive design (Caballero et al., 2014), which could be utilised as a design tool to create user-centric policies and services (Gonzalez de Heredia et al., 2018). The research aims to examine how data from different sources can be manipulated to comprehend the travel behaviour of distinct demographic groups and support the policy-making process. The two main research questions are:How can data combined from multiple sources be manipulated to deepen the understanding of travel behaviour of different personas.How can personas be used to support evidence-based policy making. The research will be explored and developed in partnership with colleagues from Department for Transport (DfT), focussing on the context of the UK domestic transport system. In investigating the relation between policies on personas, policies will shape the transportation system. Analysing the impacts of policies on personas could be accomplished by reverting to the classic problem in human factors: examining the interaction between the personas and the system designed by the policies. The social-technical framework designed by Davis et al.(2014) and the "onion model" revisited designed by Wilson & Sharples (2015) will be applied to analyse the relationship between personas (people) and related elements shaped by policy (technologies, culture, process, infrastructure, goals). The research will be divided into two parts. The first section is devoted to investigating the interaction between travellers' personas and other elements in transport system. Multiple data sources including national survey data source (2002 - 2021), the UK census data (to 2022), and other digital footprint data will be used to widen and deepen the narrative of DfT personas.In the second phase of the research project, a qualitative approach employing human factors methods and policy analysis will be used to examine the application of personas in evidence-based policy making. A framework that measures and compares the impacts of different policy options on different personas will be created. Instead of recommending a particular policy, the research will concentrate on improving decision-making techniques. Thus, the research can fill the gap in knowledge regarding the use of personas in design, particularly how personas can positively impact policy-making processes.