Theses

Description

For companies such as Facebook, Netflix, Tinder, etc., users who then stop using their services pose a challenge. Currently, little research has been done on this topic. For example, it is unclear why people stop using these services, whether users and ex-users differ in terms of personality structure, or how ex-users can be won back.
All of these are topics that can be addressed in this thesis.

Methodological approach

Empirical work

Level

Bachelor's/Master's

Language

German/English

Literature

• Maier, C; Laumer, S; Weinert, C; and Weitzel, T. The effects of technostress and switching stress on discontinued use of social networking services: a study of Facebook use. Info Systems J, 25, 3 (2015), 275–308.
• Turel, O. Quitting the use of a habituated hedonic information system: A theoretical model and empirical examination of Facebook users. Eur J Inf Syst, 24, 4 (2015), 431–446.

Description

Alongside its advantages, ongoing digitalization also poses new challenges for individuals and companies. For example, the use of information technology (IT) can lead to feelings of stress. However, the causes of this phenomenon, known as “technostress,” are as varied as its possible effects.

In companies, “technostress” arises among employees in particular as a result of management requirements to use new IT – possibly with reluctance. With the introduction of new IT, employees feel obliged to complete more complex (techno-complexity) tasks more quickly (techno-overload). But the constant learning of new skills in order to be able to use IT confidently and competently also causes stress for employees in the long term.

While in a corporate context the reaction described above can be explained by the use of a technology prescribed by company management, individuals can decide for themselves in their free time whether or not they want to use certain technologies. However, even here, situations arise in which people feel stressed by technologies (e.g., smartphones, social media). Well-known reasons for this include information overload or too many (e.g., trivial) interactions (interaction overload). 

Since technostress has a major social (e.g., burnout, reduced satisfaction) and organizational (e.g., lower work performance, increased resignations or sick days) impact, this topic will examine how technostress spreads.

Methodological approach

Empirical work (survey) or interviews

Level

This topic is assigned as a bachelor's thesis (interviews) and as a master's thesis (survey and possibly interviews).

Language

German/English

Description

At a time when data is considered the “new oil” and companies and governments are collecting and processing personal information on an unprecedented scale, questions about privacy and security inevitably arise. After all, the more data is collected, the greater the risk of misuse, data breaches, and unwanted surveillance. For example, smart home devices offer convenience, but at the same time create new risks for data theft and surveillance. Work on this topic develops an understanding of what risks exist, how users deal with them, and what measures can be taken to ensure privacy and security.

Methodological approach

Literature review/qualitative/quantitative

Level

Bachelor's/Master's

Language

German/English

Literature

Bélanger, F., & Crossler, R. E. (2011). Privacy in the digital age: A review of information privacy research in information systems. MIS Quarterly, 35(4), 1017–1041. doi.org/10.2307/41409971

Siponen, M., & Vance, A. (2010). Neutralization: New insights into the problem of employee information systems security policy violations. MIS Quarterly, 34(3), 487–502. doi.org/10.2307/25750688

Description

The psychological concept of inspiration describes a special form of intrinsic motivation that is stimulated by external sources and is closely linked to the development of new ideas (Thrash, Elliot 2003). The construct has since been further developed and divided into two components: an epistemic activation component (“inspired by”) and an intentional component (“inspired to”) (Böttger et al. 2019).

Proven scales are available for measurement, which are very well suited for empirical implementation in the form of a survey. For example, to answer the question of what inspires users of digital technologies – and what this inspiration motivates them to do.

The technologies that can be examined include social media, XR, and GenAI, although other digital contexts can also be included.

Start date: Immediately

Method: Literature review (BA) or survey (MA)

Level: BA or MA

Recommended reading:

Thrash, T. M., & Elliot, A. J. (2003). Inspiration as a psychological construct. Journal of Personality and Social Psychology, 84(4), 871–889. doi.org/10.1037/0022-3514.84.4.871.

Böttger, T., Rudolph, T., Evanschitzky, H., & Pfrang, T. (2017). Customer inspiration: Conceptualization, scale development, and validation. Journal of Marketing, 81(6), 116–131. doi.org/10.1509/jm.15.0007 

Description

Relationships between humans and various forms of artificial intelligence are becoming increasingly close and diverse as technologies become better at recognizing, understanding, and imitating emotions and aspects of the human psyche (Gur, Maaravi 2025).

Against this backdrop, it is important to gain a more detailed understanding of these newly emerging relationships. A thesis could examine the background to these relationships and their potential impact on users' experiences, behavior, and well-being.
Possible topics include attachment, trust, and companionship.

Start date: immediately

Method: interviews (BA) or survey (MA)

Level: BA or MA

Recommended reading:

Gur, T., & Maaravi, Y. (2025). The algorithm of friendship: literature review and integrative model of relationships between humans and artificial intelligence (AI). Behaviour & Information Technology, 44(14), 3446–3466. doi.org/10.1080/0144929X.2025.2502467 

Description

Many people now increasingly use social media and AI to find information. The topics are diverse: finance, politics, history, relationship advice, fashion, and health. Even small niches are now covered online by numerous people, be it special hobbies, food intolerances, or even specific skills. Influencers and journalists, but also private individuals and experts share their knowledge about their respective fields.

How does this information influence us? How do modern possibilities influence our research behavior? What is the significance of information that we did not specifically seek out? We absorb things, implement them (or not), and perhaps even share them with others. This gives rise to many topics that business informatics and psychology address, such as fake news, behavioral change, trust, parasocial relationships, learning behavior, marketing, and much more.

Social media and AI have become indispensable as central sources of information, whether in our private or professional lives.

The example of health information shows that platforms offer both opportunities and risks: in addition to the early detection of serious illnesses and the empowerment of recipients, misdiagnoses and fear can also be consequences. However, misinformation and trivialization can also play a role here. The so-called digital health paradox can also play a role here, as it does with health apps and wearables. It describes the contradiction that technologies can promote healthier lifestyles on the one hand, but on the other hand can themselves create health risks (e.g., addiction, poor posture, etc.).

The sample literature below refers to the topic of health. However, as mentioned above, exciting questions arise in relation to many fields and can be freely selected.

Start date: Immediately

Methods: Interviews, content analysis, discourse analysis, survey, literature review

Level: Bachelor's and Master's

Sample questions:

• What role do media and health literacy or AI literacy play in self-diagnosis?
• To what extent does self-diagnosis support or hinder the use of professional healthcare services?
• What positive and negative effects do users of health communities on social media report?

Sample literature:

Naslund, J. A., Bondre, A., Torous, J., & Aschbrenner, K. A. (2020). Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. Journal of Technology in Behavioral Science, 5(3), 245–257. doi.org/10.1007/s41347-020-00134-x

Neely, S., Eldredge, C., & Sanders, R. (2021). Health Information Seeking Behaviors on Social Media During the COVID-19 Pandemic Among American Social Networking Site Users: Survey Study. Journal of Medical Internet Research, 23(6), e29802. doi.org/10.2196/29802

Children and adolescents are increasingly coming into contact with AI technologies. This issue is particularly relevant in the school setting. While AI can help explain content more clearly or personalize learning processes, it also creates new challenges. For example, students may practice problem-solving skills less often or accept unverified or incorrect information.

Schools, teachers, and parents are therefore faced with the question of how AI can be used in a meaningful, fair, and safe way. This involves not only technical proficiency but also issues of responsibility, dependence, and motivation to learn.

The topic is particularly well-suited for literature reviews but can also be explored empirically through interviews (for example, with teachers or parents). Analyses of public educational discourses are also possible. Direct interviews with children or minor students are theoretically feasible but are more methodologically and ethically challenging, as informed consent forms and special protective measures are required. The questions can also be extended to include young adults (such as undergraduate students).

Start date: immediately

Methods: Literature review, interviews, discourse analysis

Level: Undergraduate and graduate

Sample questions:

• How is AI changing the culture of homework?
• How do teachers deal with the use of AI in the classroom and with homework?

Description

As a broad psychosocial construct, identity is influenced by many parameters and events: experiences, roles, and social belonging. Today, digital technologies can become part of this self-concept. Devices and platforms, especially when used regularly, are part of our personal identity. They shape our existence, our interests, and our social interactions. So-called IT identity thus expands the context in which social identity is formed (social identity theory).

AI technologies open up new dimensions with regard to the question of identity. With its unique characteristics, AI brings new opportunities and challenges. In many cases, it is not just a tool, but a creative partner. This raises questions about the extent to which AI use shapes identity in the context of study and work, both in terms of professional life and issues such as self-efficacy, social perception, and the meaning of work.

Start date: Immediately

Methods: Interviews, survey, literature review

Level: Bachelor's and Master's

Sample questions:

• What factors promote or inhibit the development of AI identity (e.g., benefits, trust, perceived control, ethical concerns)?
• Does frequent AI use lead to higher self-efficacy (because you get more done) or lower self-efficacy (because you feel dependent) in terms of professional identity?
• How does transparent use of AI affect recognition, trust, and belonging in a professional context?
• What identity signals does AI use send within a team?

Sample literature:

Carter, M., & Grover, V. (2015). Me, My Self, And I(T): Conceptualizing Information Technology Identity and Its Implications. MIS Quarterly, 39(4), 931–958.

Carter, M., Petter, S., & Compeau, D. (2019). Identifying with IT in a Digital World. ICIS 2019 Proceedings, 32.

Mirbabaie, M., Brünker, F., Möllmann Frick, N. R. J., & Stieglitz, S. (2022). The rise of artificial intelligence – understanding the AI identity threat at the workplace. Electronic Markets, 32(1), 73–99. doi.org/10.1007/s12525-021-00496-x

Description

The rapid development and spread of artificial intelligence (AI) is opening up not only innovative applications, but also new forms of technology abuse. These range from the creation of deceptively real deepfakes for defamation and disinformation, to academic misconduct through AI-generated texts, to the automation of social engineering attacks. These abusive applications raise serious ethical, social, and legal questions and threaten trust in digital technologies as well as the reputation of individuals and organizations. Work on this topic develops an understanding of the causes and mechanisms underlying this behavior, analyzes its consequences, or investigates possible technical and regulatory countermeasures.

Methodological approach

Literature review/qualitative/quantitative

Level

Bachelor's/Master's

Language

German/English

Literature

Menard, P., & Bott, G. J. (2024). Artificial intelligence misuse and concern for information privacy: New construct validation and future directions. Information Systems Journal, 35(1), 322–367. doi.org/10.1111/isj.12544

D’Arcy, J., Herath, T., & Shoss, M. K. (2014). Understanding employee responses to stressful information security requirements: A coping perspective. Journal of Management Information Systems, 31(2), 285–318. doi.org/10.2753/MIS0742-1222310210

D’Arcy, J., Hovav, A., & Galletta, D. (2009). User awareness of security countermeasures and its impact on information systems misuse: A deterrence approach. Information Systems Research, 20(1), 79–98. doi.org/10.1287/isre.1070.0160

Chatterjee, S., Sarker, S., & Valacich, J. S. (2015). The behavioral roots of information systems security: Exploring key factors related to unethical IT use. Journal of Management Information Systems, 31(4), 49–87. doi.org/10.1080/07421222.2014.1001257

Description

Research in information systems consistently shows that gender, among other factors, influences how information systems function, are used, and are perceived. Furthermore, systems may be designed differently or function differently depending on the user group.
As part of a thesis, you can investigate how such differences arise and what consequences they have for the development, use, and perception of information systems. The goal is to design information systems that are fairer, more inclusive, and more useful for all users.
Possible areas of focus include artificial intelligence, health information systems, and digital platforms.

• How do perceptions of and trust in AI systems differ among different gender groups?
• To what extent can digital health information and health information systems (Health-IS) address or disadvantage different gender groups in different ways?
• How do user participation, visibility, and influence on digital platforms differ by gender?

Start Date

Immediately

Methodological Approach

Literature review, interviews, or survey

Level

Bachelor's/Master's

Language

German/English

Literature

• Jaakola, Joni (2025) "Reassessing the Gender Script Concept. The case of feminised conversational agents," Scandinavian Journal of Information Systems: Vol. 37: Iss. 1, Article 3. DOI: 10.17705/3SJIS/037.03 Available at: https://aisel.aisnet.org/sjis/vol37/iss1/3
• O’Connor, M., & Carter, L. (2024). A Systematic Review of Gender in Information Systems Development — An Analysis of Information Systems, Software Engineering, and Human-Computer Interaction Literature. ECIS 2024 Proceedings, 13. https://aisel.aisnet.org/ecis2024/track01\_peoplefirst/track01\_peoplefirst/13/
• Serenko, Alexander and Turel, Ofir (2021) "Why Are Women Underrepresented in the American IT Industry? The Role of Explicit and Implicit Gender Identities," Journal of the Association for Information Systems, 22(1). Available at: https://aisel.aisnet.org/jais/vol22/iss1/8

Description

Information systems can not only reflect existing social inequalities but also reinforce or reduce them. Questions regarding inclusive design, bias in data-driven systems, and potential disadvantages for marginalized groups are therefore particularly relevant.

A thesis can explore how inequality and discrimination influence the development, use, and impact of information systems.

• Which groups—such as LGBTQIA+ individuals, people with disabilities, or ethnic minorities—are systematically disadvantaged by digital systems such as recruiting, healthcare, or administrative systems, and through which mechanisms?
• How can “inclusion by design” help prevent discrimination in information systems?

Start Date

Immediately

Methodological Approach

Literature review, interviews, or survey

Level

Bachelor's/Master's

Language

German/English

Literature

• Buzila, E., & Heinrich, K. (2025). Red Lights, Blind Spots: Sex Work and Stigma in Information Systems. Communications of the Association for Information Systems, 57, 577-602. https://doi.org/10.17705/1CAIS.05724
• Dilger, Philipp; Fetzer, Dominik Christian; and Zeller-Lanzl, Julia, "Designing Inclusive Generative Artificial Intelligence-Based Conversational Agents with and for Intellectually Disabled Individuals" (2025). ICIS 2025 Proceedings. 3.
• https://aisel.aisnet.org/icis2025/is_good/is_good/3
• Vimalan, Naveen; Zimmer, Markus P.; and Drews, Paul, "Fostering Inclusivity – Towards Principles for Inclusive Information Systems Design" (2024). Wirtschaftsinformatik 2024 Proceedings. 85. https://aisel.aisnet.org/wi2024/85 

Description

Students who have already completed a seminar or bachelor's thesis at the ISHANDS Chair can apply for this open thesis topic with a topic of their choice that fits the teaching and research content of the ISHANDS Chair. In this case, please indicate in the free text field below which academic work has already been written at the ISHANDS Chair (seminar paper or bachelor's thesis), which chair staff member supervised the work, in which year the work was written, and which topic the thesis should cover.

Methodological approach

Literature review/qualitative/quantitative

Level

Bachelor's/Master's

Language

German/English