[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127856-en":3,"doc-seo-127856-105":30,"detail-sidebar-cat-0-en-105":92},{"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":20,"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},127856,2336474466712,"Maeve","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Analysis of Bankruptcy Prediction of Shipping Industry - Machine Learning Approach","A thesis analyzing how machine learning can be applied to bankruptcy prediction in the shipping industry. The work focuses on building and evaluating predictive modeling approaches, using relevant inputs to estimate the likelihood of financial distress. It emphasizes research methodology aligned with academic repository requirements, including copyright and fair-dealing reuse terms, while presenting results intended to support more data-driven risk assessment for maritime firms.","Plymouth Business School Theses  \nFaculty of Arts, Humanities and Business Theses  \n2024  \nAnalysis of bankruptcy prediction of shipping industry-Machine Learning Approach  \nMinsu Kwon Plymouth Business School  \nLet us know how access to this document benefits you  \nGeneral rights  \nAll content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author.  \nTake down policy  \nIf you believe that this document breaches copyright please contact the library providing details, and we will remove access to the work immediately and investigate your claim.  \nFollow this and additional works at: [https://pearl.plymouth.ac.uk/pbs-theses](https://pearl.plymouth.ac.uk/pbs-theses)  \nRecommended Citation  \nKwon, M. (2024) Analysis of bankruptcy prediction of shipping industry-Machine Learning Approach. Thesis. University of Plymouth. Retrieved from [https://pearl.plymouth.ac.uk/pbs-theses/286](https://pearl.plymouth.ac.uk/pbs-theses/286)  \nThis Thesis is brought to you for free and open access by the Faculty of Arts, Humanities and Business Theses at PEARL. It has been accepted for inclusion in Plymouth Business School Theses by an authorized administrator of PEARL. For more information, please [contact](contact openresearch@plymouth.ac.uk)[ openresearch@plymouth.ac.uk](contact openresearch@plymouth.ac.uk).  \nPEARL  \nPHD  \nAnalysis of bankruptcy prediction of shipping industry-Machine Learning Approach  \nKwon, Minsu  \nAward date:  \n2024  \nAwarding institution: University of Plymouth  \nLink to publication in PEARL  \nAll content in PEARL is protected by copyright law.  \nThe author assigns certain rights to the University of Plymouth including the right to make the thesis accessible and discoverable via the British Library’s Electronic Thesis Online Service (EThOS) and the University research repository (PEARL), and to undertake activities to migrate, preserve and maintain the medium, format and integrity of the deposited file for future discovery and use.  \nCopyright and Moral rights arising from original work in this thesis and (where relevant), any accompanying data, rests with the Author unless stated otherwise* .  \nRe-use of the work is allowed under fair dealing exceptions outlined in the Copyright, Designs and Patents Act 1988 (amended), and the terms of the copyright licence assigned to the thesis by the Author.  \nIn practice, and unless the copyright licence assigned by the author allows for more permissive use, this means,  \nThat any content or accompanying data cannot be extensively quoted, reproduced or changed without the written permission of the author / rights holder  \nThat the work in whole or part may not be sold commercially in any format or medium without the written permission of the author / rights holder  \n* Any third-party copyright material in this thesis remains the property of the original owner. Such third-party copyright work included in the thesis will be clearly marked and attributed, and the original licence under which it was released will be specified . This material is not covered by the licence or terms assigned to the wider thesis and must be used in accordance with the original licence; or separate permission must be sought from the copyright holder.  \nDownload date: 28. Oct. 2024  \nUniversity of Plymouth  \nPEARL [https://pearl.plymouth.ac.uk](https://pearl.plymouth.ac.uk)  \n\n| 04 University of Plymouth Research Theses | 01 Research Theses Main Collection |\n| --- | --- |\n\n2024  \nAnalysis of bankruptcy prediction of shipping industry-Machine Learning Approach  \nKwon, Minsu  \n[https://pearl.plymouth.ac.uk/handle/10026.1/22583](https://pearl.plymouth.ac.uk/handle/10026.1/22583)  \n[http://dx.doi.org/10.24382/5216](","cbCaisbWo9rNcg62","https://ap.wps.com/l/cbCaisbWo9rNcg62","pdf",4255698,1,288,"English","en",105,"# Introduction\n# Research Context: Shipping Industry Bankruptcy\n# Machine Learning Approach\n## Model Development\n## Evaluation and Results\n# Ethical and Copyright Considerations","[{\"question\":\"What is the thesis topic?\",\"answer\":\"The thesis studies bankruptcy prediction in the shipping industry using machine learning approaches.\"},{\"question\":\"Which method is highlighted in the document?\",\"answer\":\"Machine learning is presented as the main approach for building predictive models and assessing bankruptcy risk.\"},{\"question\":\"How can the thesis content be reused?\",\"answer\":\"Reuse is allowed under fair dealing exceptions, following the Copyright, Designs and Patents Act 1988 and the copyright licence terms assigned by the author.\"}]","Analysis of Bankruptcy Prediction of Shipping Industry - 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