Topic Trends in Sustainability Disclosure of German DAX 40 Companies : A Text Mining-Based Analysis

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00008373
URN to cite this document: urn:nbn:de:bvb:703-epub-8373-3

Title data

Contala, Tobias ; Gerk, Alexander-Michael ; Höttler, Johannes ; Büttner, Ricardo:
Topic Trends in Sustainability Disclosure of German DAX 40 Companies : A Text Mining-Based Analysis.
In: IEEE Access. Vol. 12 (2024) . - pp. 77300-77335.
ISSN 2169-3536
DOI der Verlagsversion: https://doi.org/10.1109/ACCESS.2024.3404368

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Abstract

Given the increasing importance of sustainability in the business world, there has been growing interest in using topic modeling approaches to identify reported topics in corporate sustainability reports (CSR). Due to the inconsistent legal foundation and different sustainability standards, the content of individual reports can vary greatly. In this paper, the corporate social responsibility reports of DAX 40 companies from 2017 to 2021 are therefore analyzed using Latent Dirichlet Allocation (LDA). In particular, we attempt to identify topics that are suggested by the Global Reporting Initiative (GRI) Sustainability Standard for large public companies. In addition, a comparison is made throughout the years. The study shows that specific guidelines of the GRI can only be identified to a certain degree using LDA. Although some topics that partly reflect the content of the GRI can be found by the model, the overall structure of the GRI can’t be replicated. Overall, this study shows that an evaluation of the content of sustainability reports can be successful in terms of the relevance of the reported topics, although the results depend heavily on the respective pre-processing steps.

Further data

Item Type:	Article in a journal
Keywords:	Companies; Standards; Sustainable development; Text mining; Resource management; ISO Standards; Guidelines; Organizational aspects; Social factors; Corporate social responsibility reporting (CSR); global reporting initiative (GRI); latent dirichlet allocation (LDA); topic modeling
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Institutions of the University:	Faculties Faculties > Faculty of Law, Business and Economics Faculties > Faculty of Law, Business and Economics > Department of Business Administration Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration I - Finance and Banking Management > Chair Business Administration I - Finance and Banking Management - Univ.-Prof. Dr. Klaus Schäfer Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors > Chair Business Administration XVIII - Information Systems Management and Data Science - Univ.-Prof. Dr. Ricardo Büttner Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration I - Finance and Banking Management
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-8373-3
Date Deposited:	31 Mar 2025 05:24
Last Modified:	11 Aug 2025 06:34
URI:	https://epub.uni-bayreuth.de/id/eprint/8373

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