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DC FieldValueLanguage
dc.contributorFaculty of Businessen_US
dc.contributor.advisorLu, Haitian (AF)en_US
dc.creatorLin, Lie-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/12859-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleA comparative analysis of ESG reporting practices among listed companies in Hong Kong and Chinaen_US
dcterms.abstractAs the importance of ESG issues continues to rise, the quality of ESG reporting has garnered significant attention among scholars. However, the current literature on ESG report quality measurement methods are either overly simplistic or excessively complex. This study presents a comprehensive, computationally feasible, and programmatic approach to evaluate the quality of ESG reports based on natural language processing techniques. I comprehensively analyze the quality of ESG reports for A-share and A+H­-share companies from five aspects: Materiality, Quantitative, Balance, Consistency, and Readability, using web scraping, ESG report processing, and text analysis techniques. Through panel regression and Difference-in-Differences (DiD) research design, I find that dual-listing enhances the quality of ESG reports, providing further support for the Bonding hypothesis. Then, the results support that enhanced regulatory can effectively improve the quality of ESG reports. Finally, I discover that the improvement in ESG report quality reduces stock price synchronicity and increases the information content in stock prices.en_US
dcterms.extentiii, 219 pages : illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2024en_US
dcterms.educationalLevelD.B.A.en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHInvestments -- Environmental aspectsen_US
dcterms.LCSHInvestments -- Social aspectsen_US
dcterms.LCSHSustainable development reporting -- China -- Hong Kongen_US
dcterms.LCSHCorporation reports -- Chinaen_US
dcterms.LCSHCorporation reports -- China -- Hong Kongen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/12859