Bachelor/Project Thesis

General Information

The supervision of bachelor/project theses at our chair is based on a sequentially structured process that is repeated every six months. Deviations from the deadlines are not possible. The application period begins three weeks before the beginning of the lecture period of the respective semester and lasts two weeks. During the first week of lectures, the selection interviews take place, following which you will receive either an acceptance or a rejection.

Application process

If you want to write your thesis in the summer term 2022 at our chair, please note the application period: 04.04.2022 – 18.04.2022

  • Announcement of the topics expected as of 14.03.2022
  • Interviews: 25.04.2022 – 02.05.2022
  • Seminar for the Bachelor thesis: see bachelor thesis seminar
  • Latest date for registration of the thesis: 22.07.2022 (Please coordinate the exact registration date with your supervisor).

It is essential that you stay in regular contact with your supervisor in order to coordinate your work.

Seminar for Bachelor Thesis

Our chair offers a bachelor thesis seminar, which is especially aimed at students of business informatics and those interested in other courses of study who would like to write a bachelor thesis at the Schöller Endowed Chair for Business Informatics. The seminar is mandatory for students that write their bachelor thesis at our chair.

Prerequisites

Prerequisites

Course of study Conditions
International Business Studies attended in-depth module at the chair or application for exemption
International Production Engineering and Management attended module at the chair
Sozialökonomik attended in-depth module at the chair or application for exemption
Wirtschaftsinformatik none
Wirtschaftsingenieurwesen Module successfully taken at the chair
(Module is listed in your valid module handbook)
Wirtschaftswissenschaften mit Schwerpunkt Wirtschaftsinformatik none
Wirtschaftswissenschaften mit anderen Schwerpunkten attended in-depth module at the chair or application for exemption

Open Topics

If you are interested, please apply using the application form and attach your curriculum vitae, a current transcript of grades, and any graduation certificates you may already have. In the case of initiative applications, we also ask you to describe your intention briefly but meaningfully in the text of your e-mail.

For the application, please use solely your FAU e-mail address!

Please send the complete application documents to wiwi-wi-dwg@fau.de.

Thema Sprache Betreuer

From Data to Knowledge: Design, Implementation and Evaluation of a Data Analytics Project

More and more companies are using AI-based data analytics methods to optimize their product portfolio, their human resource management or their operational processes. The goal of this thesis is to implement and evaluate such an analysis procedure using exemplary data, e.g., from the field of finance. For this purpose, a suitable data set is to be found and analyzed using the statistical language R in order to extract context-relevant business knowledge from the data and to prepare it visually. Subsequently, the steps carried out are to be documented and the feasibility and quality of results of the procedure carried out are to be evaluated.
GER + ENG Kian Schmalenbach

eXplainable Artificial Intelligence in Information Systems - a systematic literature review

In this thesis, students deal with eXplainable Artificial Intelligence (XAI) in the discipline of business informatics. The aim is to investigate how XAI is perceived and understood, which characteristics and design principles XAI entails, and how these can be unified. In this way, a general understanding is to be built up of what implications XAI has for practice and research and where future research needs lie.
GER + ENG Florian Meier

Functional and non-functional requirements for artificial intelligence systems in industrial manufacturing.

The use of artificial intelligence (AI) and machine learning (ML) has become increasingly important in various fields, especially in the manufacturing industry.In addition to pure technical performance, there are a number of functional and non-functional requirements that are necessary and/or desirable for the development and use of AI systems. By means of qualitative expert interviews, general and industry-specific requirements and for the development and use of AI are to be determined and optimization potentials identified.
GER + ENG Daniel Schömer

Explainable and trustworthy artificial intelligence - Systematic literature review and/or expert interviews.

Despite the enormous potential of artificial intelligence (AI), many companies are hesitant to use it productively. A fundamental problem here is the understanding of and trust in AI technology, which is primarily hampered and inhibited by increasingly complex machine learning models.
The aim of this paper is to create a unified understanding of the terms and their characteristics in research and practice with the help of existing literature and expert interviews (here: manufacturing industry).
GER + ENG Daniel Schömer

Transparency through unrestricted openness? - Quality and Acceptance of Open Data

While large parts of the web are dominated by large commercial groups, some platforms such as Wikipedia or OpenStreetMap, whose content was created without commercial interests and is freely accessible (“Open Data”), also enjoy great popularity. However, recent cases (e.g., https://www.brianckeegan.com/2018/03/implications-of-the-bulgarian-national-anthem-for-information-security/) show that problems with the data quality of Open Data can have intransparent effects on the behavior of end applications. Thus, the question arises which factors are significant for the use of Open Data platforms and which measures are taken to ensure the quality of the data and thus the trust of users in corresponding services. In the context of this bachelor thesis, answers to one of these questions are to be found by means of a systematic literature analysis and/or an empirical investigation.
GER + ENG Kian Schmalenbach

(In)fairness through algorithms? - Causes and effects of algorithmic bias

Data-driven applications such as recommender systems or decision support systems are becoming increasingly popular in both corporate and private applications. However, this can be problematic if the algorithms have learned their behavior by evaluating training datasets that contain discriminatory or otherwise misleading biases. This phenomenon is referred to in the literature as “algorithmic bias” and can have negative ethical or economic implications if, for example, personnel decisions are made based on such algorithms. Therefore, the goal of this thesis is to use a structured literature review and/or empirical data analysis to identify cases of algorithmic bias and its effects, or to develop and review measures to address problems related to algorithmic bias.
GER + ENG Kian Schmalenbach

Who can (still) be trusted? - Meaning and building digital trust

In an age where digital media and platforms are responsible for much of the information gathering and processing, the question of the trustworthiness of these media and platforms is becoming increasingly important (“digital trust”). For example, the question arises as to how it can be that in the development of technologies for pandemic control, there is often a great deal of skepticism with regard to questions of data protection and thus trustworthiness, while commercial social media applications are often used rather unreflectively in everyday life. Based on such observations, it becomes clear that companies must also attach importance to the trustworthiness of their digital applications if they want to ensure a high level of acceptance and thus effectiveness of the applications. The aim of this work is therefore to use a structured literature analysis and/or empirical surveys to identify factors that are causal or obstructive for the establishment of digital trust, and which measures can be used to promote or inhibit this.
GER + ENG Kian Schmalenbach

Human or Artificial Intelligence? A literature analysis on aversion to algorithms.

Algorithm aversion describes the phenomenon that individuals tend to reject recommendations based on complex algorithmic models. Although early research from the 1950s showed that even basic statistical algorithms (e.g., linear regression) outperform human experts in predicting suitable alternatives, individuals often hesitate or refuse to include AI-based recommendations in their decision making.
The aim of this paper is to review the state of research on this refusing behavior by means of a systematic literature review.
GER + ENG Jessica Ochmann

How fair can artificial intelligence be? A Literature Analysis on Ethical Implications of AI-Based Applications

The increasing use of AI in organizations raises numerous ethical questions. How do we deal with them if AI is to take over decisions in private and professional everyday life? Does AI actually act more fairly than humans? What effects does the involvement of AI in decision-making processes have on humans? The aim of this paper is to review the state of research on ethical issues in the context of artificial intelligence by means of a systematic literature analysis.
GER + ENG Jessica Ochmann

Theories of Digital Health Research - A Systematic Analysis

Research in the field of health technologies has increased tremendously in recent years. It has been shown that different theories from a variety of different scientific fields can make a meaningful contribution to explaining different phenomena related to the use of health technologies. The aim of this paper is to provide an overview of all the theories that have been used to explore health technologies in recent years through a systematic literature review.
GER + ENG David Horneber

Ethical aspects of digital health technologies

The increasing spread of digital health technologies such as wearables or apps raises a number of ethical and social questions. Can the technologies be used without barriers? What are the consequences for patients of collecting and storing their health data? Who is responsible for positive and negative consequences that arise from the use of health technologies? In the context of this bachelor thesis, these or other questions can be investigated empirically. Alternatively, a systematic literature analysis can be used to review the current state of research on ethical issues in the field of digital health technologies.
GER + ENG David Horneber

Digital health for older people

The increasing development and diffusion in the field of digital health technologies promises to give older people more options and autonomy in managing their daily lives. But what do older people think about such technologies anyway? Are they aware of their possibilities? Do they use them? How do they have to be designed to be used by older people? These and other questions can be answered empirically in this bachelor thesis. Alternatively, a systematic literature analysis can be conducted, which reviews the current state of research on digital health technologies for older people.
GER + ENG David Horneber

Autonomous systems in production

The waves of digital transformation have significantly impacted the way business is conducted and how value is created and captured. The manufacturing industry is no exception, as it has made extensive use of previous waves of digitization to automate both its physical manufacturing areas and other activities within the value chain.In this context, the ongoing steep development of artificial intelligence (AI) in particular has recently raised hopes in the manufacturing landscape that AI and related technologies will be able to automate not only physical but also cognitive tasks in the near future, which could lead to a whole new level of autonomy on the store floor. Therefore, AI is predicted to provide greater efficiency and flexibility, drive economic growth, and dramatically change existing work by transforming existing processes and systems into autonomous and intelligent systems.In this context, autonomous and intelligent systems raise some important questions for the manufacturing industry:
– What are the key characteristics of autonomous systems? Which technologies play a role?
– How can the degree of autonomy be distinguished?
– What is the state of automaization in practice?The questions will be elaborated and investigated with the help of a systematic literature review and/or qualitative surveys/expert interviews.
GER + ENG Daniel Schömer

Maturity, experience, challenge of artificial intelligence and machine learning in industrial manufacturing.

With AI’s rapid development, unprecedented applications, and increasing practical importance, research is gaining momentum and has created a vast and burgeoning field of study. Manufacturers recognize that AI is critical to their success and are defining it as a strategic priority. They are eager to launch large-scale initiatives to introduce AI into their organizations.This study aims to shed light on the issues by conducting a survey or expert interviews on AI maturity, AI experiences, and data-related, system-related, model-related, organizational, environmental/external, and ethical/trust challenges that have prevented them from introducing and using AI in their operations!
GER + ENG Daniel Schömer

Natural Language Processing in Human Resources Management

The machine processing of natural language in audio and text form is gaining increasing importance in various areas of business and society. In this thesis the application of Natural Language Processing (NLP) in the field of Human Resources Management (HRM) will be considered. Possible thematic orientations could be potential and risk analysis, or the development of suitable applications.
GER + ENG Florian Meier