Year: 2023
Type: dissertation
Abstract: This dissertation consists of 6 papers. The papers investigate the areas of application of semantically structured data in company analysis. The first paper examines the extent to which alternative data can support tax audits. It is also important to understand how alternative data can be used in the first place. This includes the generation and further the processing of the data. Different meth-ods are presented for this purpose. The second paper deals with the quality of inline eXtensible Business Reporting Language (iXBRL) annual reports from the UK. Small and medium-sized enterpris-es (SMEs) have been required to make their annual reports available in iXBRL since 2011. These reports are both machine and human readable. This offers the possibil-ity to evaluate the annual reports of SMEs by machine. The study examines various dimensions of quality such as the structure of the tags. The analysis is important because the use of XBRL and iXBRL will still play an important role in the future, especially regarding the new European Single Electronic Format (ESEF) and the EU taxonomy for sustainable activities. The third paper analyzes iXBRL company accounts of SMEs in the UK. The infor-mation from the annual reports is processed automatically and linked to other data sources with the help of a knowledge graph. In this way, further information can be generated and processed. Other data sources are, for example, another database of the UK Companies House, but also other alternative data. Linking the data sources using the knowledge graph then enables the data to be queried, evaluated and visu-alized. The fourth paper deals with the question how connections between supervisory boards, management boards and auditors can be visualized with the help of the graph database Neo4j. Basically, the problem is that networks are difficult to ana-lyze and display. For this reason, this paper deals with the use of a graph database to close this gap. The database includes supervisory board members, management board members and auditors of DAX30 companies in 2019. With the help of Neo4j, the Curricula Vitae (CVs) are matched and the persons with common activities are analyzed. Among other things, multiple mandates, joint professional activities and joint training are examined. The fifth paper examines the collapse of the German financial services company Wirecard AG. The focus here is particularly on the people behind the scandal. For this purpose, the CV of the members of the supervisory board and the management board of the DAX30 companies are collected. The information is taken from the respective company websites. In addition, publicly available data sources are used to expand the database. The data is analyzed and visualized with the aid of a knowledge graph. In particular, the special features of the members of the supervi-sory board and the management board of Wirecard is addressed and the paper exam-ines the differences to other DAX30 companies in detail. The sixth paper is dedicated to teaching the basics of Resource Description Frame-work (RDF) and the RDF query language SPARQL. It has already been shown in the previous studies that the use of Knowledge Graphs can bring great benefits. In this paper, the concept of the WireGraph learning game is presented, which is used to teach business students how to work with knowledge graphs in order to work through the Wirecard scandal. For this purpose, a prosumer environment is provid-ed, with which the competence area of digital content creation of the reference model is taught completely and across all performance levels. In doing so, students not only learn the basics of RDF and SPARQL but can also apply them specifically to their ideas and further expertise. The conception of the learning game WireGraph is the first stage of a multi-stage project. The following steps are the development of the learning game and afterwards the application and the measurement of the di-dactic success.
Author: Grümmer, Julian
Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg
Language: German
Topic: Financial Reporting and XBRL
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7065495505