Quantitatively Measuring Customer Experience (CX) in the Rail Industry

尽管铁路旅行的需求在过去20年里翻了一番还多(Munro，2021)，但英国的铁路旅行目前正面临着从新冠肺炎中复苏的挑战(哈灵顿，2022)。铁路行业正在做的一项工作是专注于鼓励人们再次乘坐火车出行。因此，铁路行业有必要变得更加以乘客为中心(Camacho，2016)，并更错综复杂地理解乘客体验(PX)。目前收集CX数据的方法是每年进行一次，因此无法提供最新的分析(Focus，2020)。该博士学位旨在创建一种工具，用于捕获和评估铁路行业的客户反馈，以帮助更深入地了解乘客体验(PX)。该工具还应设计为向行业提供改善PX的建议。本博士学位旨在创建一种识别和评估PX因素的新方法。这项工作的结果不会特定于任何场景，但将适用于以更以客户为中心的方式评估客户体验(CX)的其他场景。这种方法将不同于其他更加定量的数据驱动的方法，因为它将把主观的定性数据转化为定量的解决方案。本研究将首先使用定性的方法来确定影响PX的因素，然后尝试用定量的方法来分析这些数据。此外，可以使用机器学习算法对数据进行分类，以便在接收到更多数据时该工具可以自动运行。研究问题如何开发工具来识别和加权PX中的最新因素？如何使用机器学习方法来识别乘客提出的关键问题？该工具如何被行业使用以提供有效的PX问题解决方案？

Although demand for rail travel has more than doubled over the last 20 years (Munro, 2021), rail travel in the UK is currently facing the challenge of recovering from COVID-19 (Harrington, 2022). One part of the work being done in the rail industry is focusing on encouraging people to travel by rail again. Consequently, there is a need for the rail industry to become more passenger-centric (Camacho, 2016) and to more intricately understand passenger experience (PX). Current methods of collecting CX data are conducted annually, therefore cannot offer up-to-date analysis (Focus, 2020). This PhD aims to create a tool for capturing and assessing customer feedback in the rail industry to help understand passenger experience (PX) in greater depth. The tool should also be designed to provide recommendations to industry for improving PX.This PhD aims to create a new methodology for identifying and assessing factors of PX. The findings of this work will not be specific to any scenario but will be adaptable to other scenarios in which customer experience (CX) is to be assessed in a more customer-centric way. This methodology will be different to other, more quantitative data-driven, methods because it will turn subjective, qualitative data, into quantitative solutions. This research will initially employ qualitative methods to identify factors affecting PX, then attempt to analyse this data using quantitative methods. Furthermore, machine learning algorithms could be employed to categorise data so that the tool could run automatically as more data is received.Research QuestionsHow can a tool be developed to identify and weight up-to-date factors in PX?How can machine learning methods be used to identify key issues raised by passengers?How could the tool be used by industry to provide effective solutions to PX problems?