[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121083-en":3,"doc-seo-121083-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121083,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","Who do we choose to spend our leisure time with? - Insights from discrete choice and machine learning models","This thesis investigates the determinants of social contact selection in leisure activities, integrating traditional discrete choice models with machine learning techniques to improve model specification and explanatory power. A dataset collected in Switzerland via snowball sampling captures a broad range of participants and contexts relevant to leisure choices. The work focuses on identifying how preferences and factors shape with whom individuals spend leisure time, using the combined modelling framework to strengthen interpretation of social influence and decision drivers.","Who do we choose to spend our leisure time with? Insights from discrete choice and machine learning  \nmodels  \nShuwei Lin  \nInstitute for Transport Studies (ITS) University of Leeds  \nSubmitted in accordance with the requirements for the degree of Master of Philosophy  \nOctober 2024  \nAcknowledgements  \nI would like to extend my heartfelt gratitude to my supervisors, Chiara and Stephane, for welcoming me into this research programme and providing me with the opportunity to explore my passion for research. I am also deeply grateful to Aravinda for joining the supervisory team and offering his valuable expertise.  \nOriginally, this research was intended as a PhD programme with publication expectations. However, I had to switch to an MPhil as it was not working out for me. I am particularly thankful to my supervisors for their unwavering support during this difficult transition and for their willingness to continue guiding me to complete my degree. Special thanks are also due to Zia and Rachel for their assistance during this period. Zia was always available to offer coaching and help me evaluate my circumstances, while Rachel reminded me to take care of my mental health, providing timely and comforting support.  \nThe COVID-19 pandemic was one of many challenges that made this research journey difficult. I often wonder how things might have been different had I deferred my start date to post-pandemic times. Nonetheless, I am immensely grateful to Chiara for arranging countless online meetings to support my progress.  \nOne of my dreams has been to gain experience as a demonstrator and teaching assistant at a university. I am thankful to Chiara for giving me the opportunity to fulfil this dream through her Transport Data Collection and Analysis module for master’s students.  \nI would like to thank Charisma Choudhury and Ed Manley for serving as my examiners during my transfer process and for their invaluable feedback, which greatly improved my transfer report by enhancing its positioning in the literature and clarifying my ideas. Although some parts of the transfer report were no longer relevant to this thesis, the lessons learned from that process were invaluable.  \nThis research would not have been possible without the data provided by Matthias Kowald. I am grateful not only for the access to the data but also for his patience in answering my questions. I regret that this work did not result in any publications during my MPhil, but I hope to repay his kindness in the future.  \nI am thankful to the committee of the International Choice Modelling Conference 2022 in Reykjavik, Iceland, for the opportunity to attend and present at my first academic conference. It was exciting to meet scholars I had only encountered through their work, particularly Michael Maness, whose review paper on social influence was one of the starting points in my literature review. I appreciate Michael’s invitation for a potential collaboration, although it was unfortunate that it did not materialise.  \nI am grateful to my colleagues, friends, and fellow research students at this institute. Special thanks to Panos Tsoleridis, David Palma and Thomas Hancock for their assistance with coding in Apollo and discussions, Maximiliano Lizana Maldonado and Zannat for their companionship and research tips, Zihao An for his advice on academic writing and literature review, Alexandra-Elena Vitel for her tips on organising supervisory meetings and progress reviews, and Chen Peng and Zhuoqian Yang for their kindness and support during challenging times. Oguz Tengilimoglu and Pinar Bilgin also deserve thanks for their constant greetings and snacks.  \nAlthough Sijin Wu and I never managed to co-author a paper, our discussionson modelling the mobility changes caused by the perceived risk of the pandemic were really enjoyable and enlightening.  \nSports have been a cherished part of my life, and I am glad to have found companions at ITS as well. 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