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 winter term 2021/2022 at our chair, please note the application period: 27.09.2021 – 11.10.2021

  • Announcement of the topics expected as of 09.09.2021
  • Selection interviews: 18.10.2021 – 24.10.2021
  • Seminar for the Bachelor thesis: see bachelor thesis seminar

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

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 attended module B24, B25 or B26 at the chair
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

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

To capitalize on artificial intelligence (AI) and machine learning (ML) techniques and create value, companies must approach their application strategically. The first and central element of any AI strategy is the AI vision and AI mission. They describe how a company wants to use AI. The first step is to analyze whether existing companies already have an AI vision and mission. In the second step, industrial manufacturing companies should be asked about their strategy in a qualitative or quantitative survey. The questions could be, for example:
– Is there an AI/ML strategy? If not, why not? What are the factors that influence the strategy? What factors make for a successful strategy?
– Which business units are affected and why?
– What is the AI budget?
– Is there an in-house AI/ML team?
– Are there partnerships with other companies or is the implementation completely independent?
GER + ENG Daniel Schömer

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, having made extensive use of previous waves of digitalization 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 shop floor. As a result, 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 doing so, industrial autonomous and intelligent systems raise some important questions: What are the key characteristics of these autonomous systems? Which technologies (esp. AI and machine learning) play a role? How do they differ from other forms (e.g., automation) or how can the degree of autonomy be distinguished? What are the implications for research and practice? The questions will be answered with the help of a literature review.
GER + ENG Daniel Schömer

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? 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

How can I manage to exercise regularly and eat healthy? Many people ask themselves this question. Health technologies such as wearables or fitness and nutrition apps promise their users to drive them to healthy everyday behaviors. In doing so, the technologies use different techniques (e.g. reminder push messages, social influence, etc.) to move a behavior change in your users. In the context of this thesis, different questions can be answered on how to use digital nudging or persuasive technology to drive people to healthy everyday behaviors. Alternatively, a systematic literature review can be conducted to review the current state of research on digital health intervention techniques.
GER + ENG David Horneber

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

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

In this thesis, the negative effects of data-driven human resources management (HRM) in various areas will be analyzed. In particular, students will explore the question of what risks can arise from data-driven technologies in different areas and tasks of HRM for the affected stakeholders. Methodological approach of the work can be an empirical study, a literature analysis or an unsupervised machine learning approach.
GER + ENG Florian Meier

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 analytics method using exemplary data, e.g., from the field of finance. For this purpose, a suitable data set is to be found and analyzed with the help of the statistical language R in order to extract context-relevant entrepreneurial knowledge from the data and to prepare it visually. Subsequently, the steps carried out are to be documented and the feasibility and quality of the results of the procedure carried out are to be evaluated.
GER + ENG Kian Schmalenbach

The students deal with various questions on the topic of “digital books and publication processes”. For this purpose, usage scenarios for different contexts can be examined, a literature research can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed.
GER + ENG Prof. Sven Laumer

A literature review should be conducted that summarizes the published literature on the use of machine learning (and similar approaches) in recruitment. The idea is to summarize the status quo, explain the basic principles, and derive a research agenda for the use of machine learning in recruitment.
GER + ENG Prof. Sven Laumer

Students focus on different questions regarding Data Science. In this context, different Data Science and Data Management approaches can be reviewed, prototypes for the application of these approaches can be implemented and concepts for the use of these approaches in (online) tutorials can be developed. The idea is to use R and related frameworks to focus on one of the phases of the data management lifecycle.
GER + ENG Prof. Sven Laumer

The (further) development of innovative technologies and the changed communication behavior caused by social media can lead to new forms of work in the long term and thus also have a lasting influence on the recruitment of talents. The aim of this paper is to review the state of research on automated recruiting approaches by means of a systematic literature analysis.
GER + ENG Jessica Ochmann

Automated recruitment approaches and the use of social media are leading to efficiency gains in HR management. But how do candidates perceive these developments? Which innovations are accepted by candidates and which factors promote or inhibit acceptance?
Within the scope of the bachelor thesis, interviews or quantitative methods will be used to discuss and analyze how data-driven approaches as well as automated dialog systems in recruitment are also accepted by society in general.
GER + ENG Jessica Ochmann

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 thesis is to review the state of research on this refusing behavior by means of a systematic literature review.
GER + ENG Jessica Ochmann

The HR industry is faced with the challenging task of filling vacancies on the labour market with increasingly complex candidate profiles and highly competitive, scarce talent. Within the framework of the bachelor thesis, the requirements of the candidates as well as the individual acceptance of innovative technologies in personnel management (e.g. chatbots, data-driven recruiting) are to be examined on the basis of explorative interviews.
GER + ENG Jessica Ochmann

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

Students focus on digital student advisory, which subsumes the use of artificial intelligence and data analytics regarding the support of students during their studies. The idea is to develop an early warning system that enable students and student advisor to identify challenges during the student lifecycle early on. For this purpose, use scenarios for different contexts known from one’s own study (for example, applying for a degree program, basic studies, advances studies) can be studied, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed.
GER + ENG Prof. Sven Laumer

Students focus on different questions regarding „digital learning“. For this purpose, use scenarios for different contexts known from one’s own study (for example, online tutorials, online tests, online exams, chatbots for Q&A) can be studied, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed.
GER + ENG Prof. Sven Laumer

“Digital nudging is the use of user-interface design elements to guide people’s behavior in digital choice environments.” (Weimann et al. 2016). Students can focus on different questions regarding digital nudging in different contexts (learning, advisory, sports, health, etc.). For this purpose, a literature review can be conducted, concrete challenges can be solved by prototypes or questions of acceptance can be analyzed.
GER + ENG Prof. Sven Laumer

In their work, students focus on the question of how apps can be used for communication in research projects and with students. The goal is to develop a communication platform that supports app-based communication to specific target groups.
GER + ENG Prof. Sven Laumer

The goal is to explore how digital technologies can be used in change management using different methodological approaches. Thus, the focus is not on the digital transformation, but on the question of how this transformation can be digitally designed.
GER + ENG Prof. Sven Laumer

In their work, students focus on different questions in the field of “People Analytics”. For this purpose, different methodological approaches could be chosen.
GER + ENG Prof. Sven Laumer

Society increasingly relies on data-driven models for automated decision-making processes. The algorithms, behind these models, and the data they work with are often biased due to the nature of historical data and fuzziness in observations. As a result, practitioners and researchers are increasingly looking for ways to mitigate the biases in algorithms and data. This paper will focus on two different research questions, “What is discrimination and how can it be identified?”; “How can discrimination be measured and mitigated?”. The methodology to be chosen is systematic literature review.
GER + ENG Florian Meier

The use of artificial intelligence (AI) and machine learning (ML) techniques has gained much importance in various fields, especially in the manufacturing industry. The objective of this paper is to highlight one or more of the following based on the existing literature:
– Application domains: what are the use cases/problems in industrial manufacturing. What AI/ML models are used to solve them. How are the models (ins. algorithms) differentiated?
– Challenges/problems/obstacles: What are challenges/problems/obstacles in implementing and operating AI/ML models.
– Metrics/KPIs: What (primarily non-technical) metrics are used to measure the success of AI/ML.
GER + ENG Daniel Schömer

Despite the enormous potential of artificial intelligence (AI), many companies are hesitant to use it productively. A fundamental problem here is understanding and trust in AI technology, which is hampered and inhibited primarily by increasingly complex machine learning models. The goal of this paper is to (1) analyze and present causes and factors that inhibit explainability, transparency, and lack of trust in these technologies. It also aims to (2) identify strategies/methods from the literature that can improve explainability and transparency and promote trust. Alternatively to (2), the market can be analyzed for existing products/services.
GER + ENG Daniel Schömer

Artificial intelligence (AI) is currently on everyone’s lips and holds enormous potential for new and improved products and services. The aim of this thesis is to analyze business models in industrial manufacturing with the help of AI and machine learning methods on the basis of existing literature or through a market analysis.
GER + ENG Daniel Schömer

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

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

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 hindering for the establishment of digital trust and by which measures these can be favored or hammered.
GER + ENG Kian Schmalenbach