Abschlussarbeiten

Informationen zu Abschlussarbeiten am Lehrstuhl Digital Communication and Transformation

We have summarized all the relevant information about registering and writing theses in a Moodle course. It is imperative that you study the information carefully before contacting us.

Click here for the Moodle course for theses

Among other things, we supervise theses in the fields mentioned below. In the following you will find advertised topics as well as open topics for theses . You can also make your own suggestions for topics. In principle, it is also possible to write theses in cooperation with companies.

It is expected that you think about a possible focus of your work in advance of your first meeting.

Ausgeschriebene Themen für Abschlussarbeiten

Performing Knowledge Work in the Metaverse

Zielgruppe:

Master

Anforderungen:

Experimental Design/Qualitative Methods

Inhalte:

The "Metaverse" is a computer-generated, three-dimensional, fully immersive environment (Drucker, 1994). The term was first coined by Neal Stephenson in his 1992 novel Snow Crash. Today, companies such as META aka Facebook invest hundreds of millions of dollars in building the leading metaverse. Apart from that, the Metaverse promises interesting opportunities for knowledge workers to collaborate and overcome spatial constraints of remote work. The aim of this thesis is to investigate the boundary conditions of performing knowledge in virtual environments such as a Metaverse. To do this, you will get a pair of VR-Goggles (Oculus Quest I) for conducting qualitative experiments at the University. Moreover, it is required to work with an accompanying theory such as conflict-distraction theory.

Literatur:

  • Park, S. -M. and Kim, Y. -G. (2022) "A Metaverse: Taxonomy, Components, Applications, and Open Challenges," in IEEE Access, 10, 4209-4251.
  • Robinson, S. and Mendelson, A. L. (2012) “A Qualitative Experiment: Research on Mediated Meaning Construction Using a Hybrid Approach”, Journal of Mixed Methods Research, 6(4), pp. 332–347.
  • Baron, R. S. (1986). “Distraction-Conflict Theory: Progress and Problems”. Advances in Experimental Social Psychology, 1–40.
  • Davenport, T. (2005). “Thinking for A Living: How to Get Better Performance and Results from Knowledge Workers”. Harvard Business School Press.

Kontakt:

Julian Marx

The Morality Game: Designing a Test for Identifying Ethical Principles in Machines

Target Group:

Master

Requirements:

Qualitative content analysis, conducting interviews

Contents:

While organizations and researchers have repeatedly shown the advantages of Artificial Intelligence (AI)-based systems for humanity (such as self-driving cars, AI-based conversational agents, and process automation), serious AI-related abuses and incidents have raised pressing ethical concerns. While unethical behavior can be intended in some cases (Stieglitz et al., 2019) due to the company’s or some manager’s values (e.g. during the VW diesel scandal), many unintended ethical challenges and moral issues can occur when applying AI (Boddington, 2017). For instance, Amazon’s discriminatory human resources (HR) software and Microsoft’s racist chatbot provide a strong case for the dangerous and unethical sides of AI that were inadvertent (Dastin, 2018; Horton, 2016; Yampolskiy, 2016). One the one hand, this is due to biased man-made algorithms used, for instance, in hiring, which cannot be absolutely non-discriminatory (Mann & O’Neil, 2016). On the other hand, this is due to the predictive nature of AI, resulting in a non-transparent derivation of outputs (Boddington, 2017). We consider AI as a group of technologies that rely on techniques such as machine learning, natural language processing, and knowledge representation (Carvalho et al., 2019).

To prevent harm from AI-based systems, researchers identified a variety of principles such as fairness (Teodorescu et al., 2021), explicability or justice (Floridi et al., 2018) and guidelines for designing a trustworthy AI (EU HLEG, 2019; Shneiderman, 2020). One challenge for practitioners is to implement such principles in an AI-based system. However, another challenge is to verify those implemented principles.

This is where this master thesis aims to start. First, suitable ethical principles shall be selected and defined. Second, expert interviews with researchers should be conducted to find out how AI-based systems can be tested with respect to their compliance with moral principles. The focus can be either holistically on AI-based systems, or specifically on anthropomorphic machines.

Literature:

  • Boddington, P. (2017). Towards a Code of Ethics for Artificial Intelligence. Springer International Publishing.
  • Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G
  • EU HLEG. (2019). Ethics Guidelines for Trustworthy AI. European Commission.
  • Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689–707.
  • Horton, H. (2016, March 24). Microsoft deletes “teen girl” AI after it became a Hitler-loving sex robot within 24 hours. The Telegraph. https://www.telegraph.co.uk/technology/2016/03/24/microsofts-teen-girl-ai-turns-into-a-hitler-loving-sex-robot-wit/
  • Mann, G., & O’Neil, C. (2016). Hiring Algorithms Are Not Neutral. Harward Business Review.
  • Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy. International Journal of Human–Computer Interaction, 36(6), 495–504. https://doi.org/10.1080/10447318.2020.1741118
  • Stieglitz, S., Mirbabaie, M., Kroll, T., & Marx, J. (2019). “Silence” as a strategy during a corporate crisis – the case of Volkswagen’s “Dieselgate.” Internet Research, 29(4), 921–939. https://doi.org/10.1108/INTR-05-2018-0197
  • Teodorescu, M., Morse, L., West Virginia University, Awwad, Y., Center for Complex Systems, King Abdulaziz City for Science & Technology, Massachusetts Institute of Technology, Kane, G., & Boston College. (2021). Failures of Fairness in Automation Require a Deeper Understanding of Human-ML Augmentation. MIS Quarterly, 45(3), 1483–1500. https://doi.org/10.25300/MISQ/2021/16535
  • Yampolskiy, R. V. (2016). Taxonomy of pathways to dangerous artificial intelligence. Workshops at the Thirtieth AAAI Conference on Artificial Intelligence.

Contact:

Lennart Hofeditz

One Cloud to Rule Them All - sciebo Research Data Services

Zielgruppe:

Bachelor/Master

Anforderungen:

Qualitative Forschung / Design Science Research

Inhalte:

Die campuscloud.nrw oder auch kurz sciebo (hergeleitet aus den beiden Wörtern „science“ und „box“) ist eine nicht-kommerzielle Cloud-Lösung, die speziell für Studium, Forschung und Lehre an Hochschulen entwickelt wurde (Vogl et al., 2015; Vogl et al., 2016). Sie stellt allen Studierenden und Mitarbeiter*innen aller Hochschulen in NRW mindestens 30 Gigabyte Speicherplatz zur Verfügung, um dort nicht nur die Archivierung von Daten zu ermöglichen, sondern auch die ortsunabhängige Zusammenarbeit in Forschungs- und Studierendenprojekten zu fördern (Vogl et al., 2016). sciebo wird von den Universitäten Duisburg-Essen und Münster stetig weiterentwickelt um den wachsenden Anforderungen der Nutzer*innen gerecht zu werden und mit kommerziellen Cloud-Lösungen mithalten zu können (Wilms et al., 2017). Vor dem Hintergrund der zunehmenden Digitalisierung der Forschung kann die Bedeutung eines strukturierten Forschungsdatenmanagements (FDM), wie es z.B. in den Leitlinien zum Umgang mit Forschungsdaten der DFG gefordert wird, kaum überschätzt werden. In der Praxis werden diese Vorgaben jedoch bisher nur unbefriedigend umgesetzt, wie verschiedene Studien zeigen (s. Sayogo & Pardo, 2013; Savage & Vickers, 2009). Auch eine Bestandsaufnahme des Status Quo des FDM in NRW zeigt, dass im Hinblick auf ein professionelles, den Empfehlungen der DFG entsprechendes FDM noch große Lücken existieren (DV-ISA, 2016). Dies liegt insbesondere am Fehlen von einfach zu nutzenden Tools (Hofeditz et al., 2020). Daher entwickelten wir in einem Projekt zusammen mit der Universität Münster eine umfangreiche Erweiterung für sciebo, die es Forschenden ermöglichen soll, weitere Services zum Managen und Teilen ihrer Forschungsdaten an sciebo anzubinden. Damit erhoffen wir uns nicht nur Forschenden ihre Arbeit mit Daten zu erleichtern, sondern auch die allgemeine Zugänglichkeit von Forschungsdaten gemäß der FAIR-Prinzipien der EU zu verbessern.

In dieser Abschlussarbeit soll angelehnt an Design Science Research (Peffers et al., 2018) der entwickelte Prototyp nun zusammen mit Forschenden evaluiert werden. Dazu sollen Workshops und/oder Interviews mit Forschenden durchgeführt werden, denen der entwickelte Prototyp präsentiert wird. Auf Grundlage der Workshops/Interviews und unter Einbeziehung neuester Kenntnisse aus der Literatur (z.B. Hofeditz et al., 2020; Kim et al., 2015; Stieglitz et al., 2020), sollen Gestaltungsprinzipien zur Verbesserung des Prototypen und somit zur Unterstützung einer offenen und vernetzten Wissenschaft abgeleitet werden.

Literatur:

  • DV-ISA NRW (2016). Umgang mit digitalen Daten in der Wissenschaft: Forschungsda-tenmanagement in NRW. Umgang mit digitalen Daten in der Wissenschaft: Forschungs-datenmanagement in NRW- Eine erste Bestandsaufnahme.https://www.dvisa-nrw.de/veroeffentlichungen/veroeffentlichungen-container-oeffentlich/dv-isa-vorstudie-bestandsaufnahme-forschungsdatenmanagement
  • Hofeditz, L., Ross, B., Wilms, K., Rother, M., Rehwald, S. et al. (2020). How to Design a Research Data Management Platform? Technical, Organizational and Individual Perspectives and Their Relations. In: Yamamoto S., Mori H. (eds) Human Interface and the Management of Information. Interacting with Information. HCII 2020. Lecture Notes in Computer Science, vol 12185. Springer, Cham.
  • Kim, Y., and Zhang, P. 2015. “Understanding data sharing behaviors of STEM researchers: The roles of attitudes, norms, and data repositories,” Library & Information Science Research, (37:3), pp. 189–200 (doi: 10.1016/J.LISR.2015.04.006).
  • Peffers, K., Tuunanen, T., & Niehaves, B. (2018). Design science research genres: introduction to the special issue on exemplars and criteria for applicable design science research. European Journal of Information Systems, 27(2), 129–139. https://doi.org/10.1080/0960085X.2018.1458066.
  • Vogl R., Angenent H., Rudolph D., Thoring A., Schild C., Stieglitz S. and Meske C. 2015. „sciebo – the Campuscloud for NRW”, European Journal of Higher Education IT (EJHEIT) (2:3), pp. 1-12. (Winner of the Elite Award for Excellence).
  • Savage, C. J., & Vickers, A. J. (2009). Empirical study of data sharing by authors pub-lishing in PLoS journals.In: PloS one, 4(9), e7078.
  • Sayogo, D. S., & Pardo, T. A. (2013). Exploring the determinants of scientific data shar-ing: Understanding the motivation to publish research data. In: Government Information Quarterly, 30 (1), pp. 19-31.
  • Stieglitz, S., Wilms, K., Mirbabaie, M., Hofeditz, L., Brenger, B., Lopez, A. & Rehwald, S. (2020). When are researchers willing to share their data? – Impacts of values and uncertainty on open data in academia. PLOS ONE, 15(7).
  • Vogl, R., Rudolph, D., Thoring, A., Angenent, H., Stieglitz, S., & Meske, C. (2016). How to build a cloud storage service for half a million users in higher education: Challenges met and solutions found. Proceedings of the Annual Hawaii International Conference on System Sciences, 2016–March, 5328–5337. https://doi.org/10.1109/HICSS.2016.658
  • Wilms, K., Brenger, B., López, A., Rehwald, S. (2018). Open Data in Higher Education – What Prevents Researchers from Sharing Research Data?. In: Proceedings of the 39th International Conference on Information Systems (ICIS).
  • Wilms, K., Meske, C., Stieglitz, S., Decker, H., Fröhlich, L., Jendrosch, N., Schaulies, S., Vogl, R. and Rudolph, D. (2017). Digital Transformation in Higher Education – New Cohorts, New Requirements?. In: Proceedings of the 23rd Americas Conference on Information Systems (AMCIS)

Kontakt:

Lennart Hofeditz

Exploring the Identity of Knowledge Workers in a Digital World

Zielgruppe:

Master

Anforderungen:

Qualitative Methods/Quantitative Methods

Inhalte:

The ongoing development of information technology (IT) enables organizations to introduce digital work as the new normal. Therefore, employees face new forms of work that might decrease personal interaction and increase interaction with IT. Nevertheless, these new ways of work entail that individuals cannot do their jobs with the same values and convictions as they are used to. Furthermore, location-independent work such as home office or digital (corporate) nomadism is on the rise in the digital landscape.

However, there is a constant change that might impact self- beliefs constituting professional identity at work, i.e., the perception of one's role in the workplace. Experiencing a new work situation that contradicts one's identity might lead to a loss of self-esteem and a threat to identity. As emerging technologies have changed the landscape and experiences of various professions, various touchpoints correlate with the identification at work. The digitization of the workplace emphasizes the demand for digital work as the new normal in organizations.

Thus, this thesis aims to explore novel factors that might influence a digital knowledge worker's identity at the workplace. To this end, several methods could be applied. Students may choose or connect qualitative and quantitative methods such as a systematic literature review, (Expert) Interviews, or online experiments with (digital) knowledge workers.

This thesis will need a solid theoretical foundation considering an identity perspective. To this end, possible theoretical foundations are (1) IT-Identity, (2) Organizational Identity, (3) Social Identity Theory, or (4) Sociomateriality.

Literatur:

  • Prester, J., D. Cecez-Kecmanovic, and D. Schlagwein, “Becoming a digital nomad: Identity emergence in the flow of practice”, 40th International Conference on Information Systems, ICIS 2019, (2019)
  • RMirbabaie, M., Stieglitz, S., Brünker, F., Hofeditz, L., Ross, B., & Frick, N. R. J. (2021). Understanding Collaboration with Virtual Assistants – The Role of Social Identity and the Extended Self. Business & Information Systems Engineering, 63, 21-37
  • Carter, M., Grover, V., & Clemson University. (2015). Me, My Self, and I(T): Conceptualizing Information Technology Identity and its Implications. MISQuarterly, 39(4), 931–957. https://doi.org/10/gf5sg7
  • Carter, M., Petter, S., & Compeau, D. (2019). Identifying with IT in a Digital World. In ICIS 2019 Proceedings (p. 10). Presented at the International Conference on Information Systems, Munich.
  • Burke, P. J., & Stryker, S. (2016). Identity Theory: Progress in Relating the Two Strands. In New Directions in Identity Theory and Research (pp. 657–810). New York, NY: Oxford University Press.

Kontakt:

Felix Brünker

Digital Nudging to overcome hierarchy in organizations

Zielgruppe:

Master

Anforderungen:

Mixed Methods

Inhalte:

Hierarchies are omnipresent in organizations. They form the chain-of-command and sometimes provide the required stability in complex enterprise environments (Knight and Mehta 2017). (Hogg 2010) point out that given hierarchical power can alter people’s behavior. Despite positive intentions, it can easily lead to negative effects that hinder innovation (R. A. M. Mudambi 2011) and an organization's performance in general (Leavitt 2005; Meske et al. 2020). Digital nudging was suggested as a new way of guiding users towards to optimal decision. It seeks to optimize formerly negative decision-making processes and persuade the user towards the better decision (Weinmann et al. 2016). In the discipline of information systems, digital nudging was found to positively influence the user adoption (Gregor and Lee-Archer 2016; Thaler and Sunstein 2009) and effectiveness of application usage (Hummel and Maedche 2019). Nudging was applied in various contexts to verify positive influence on behavior (Meske and Potthoff 2017; Stieglitz et al. 2017). Yet, the application in the context of organizational hierarchy is missing. Research currently lacks the link between digital nudging in information systems and hierarchy in an organizational context. Thus, overcoming these hierarchical distances is both key and potentially benefiting from the new and subtle form of persuasion, digital nudging. First studies identified an accelerated effect of nudges when influenced by hierarchical power (Kretzer and Maedche 2018), however the opposite has not been elaborated on yet.
The study is a mixed-method study and has two parts. First, interviews with experts are conducted to find out what burdens exist with hierarchy. This will allow the validation of findings in literature that hierarchy forms an obstacle in the way towards an increased productivity in the digital age. In addition, the interviews should reveal what the examples and use cases are that hierarchy is impacting. This will contribute to the study by (1) verifying the hypothesis that hierarchy can be an inhibitor for productivity, (2) detailing out where the obstacles are (including their relative strength so prioritization is possible) and (3) what intentions of the interviewees are to overcome those obstacles. The interviews should be done with a target number of 12 participants conducted in an organization of at least around 100 employees. The second part is an experiment that will test a designed digital nudge, which was derived from the interviews. Depending on the interview outcomes, the strongest inhibitor for productivity should be chosen, preferably with backing from previous literature. This will allow the design based on the input from the interviews as well as previous research background and results. The nudge then should be tested at the same or another company in an automated way.

Literatur:

  • Gregor, S., and Lee-Archer, B. 2016. “The Digital Nudge in Social Security Administration,” International Social Security Review (69:3–4), pp. 63–83. (https://doi.org/10.1111/issr.12111).
  • Hogg, M. A. 2010. “Influence and Leadership,” in Handbook of Social Psychology, John Wiley & Sons, Inc. (https://doi.org/10.1002/9780470561119.socpsy002031).
  • Meske, C., Kissmer, T., and Stieglitz, S. 2020. “Bridging Formal Barriers in Digital Work Environments – Investigating Technology-Enabled Interactions across Organizational Hierarchies,” Telematics and Informatics (48), Elsevier Ltd. (https://doi.org/10.1016/j.tele.2020.101342).
  • Stieglitz, S., Potthoff, T., and Kißmer, T. 2017. “Digital Nudging Am Arbeitsplatz,” HMD Praxis Der Wirtschaftsinformatik, Springer Fachmedien Wiesbaden, pp. 1–12. (https://doi.org/10.1365/s40702-017-0367-5).

Kontakt:

Tobias Kissmer

Giving advice on cyber threats

Target Group:

Master

Requirements:

Online Experiment / Online study

Contents:

Nowadays we have adopted a variety of technological devices into our lives that we use on a daily basis. Among these technologies are numerous devices that are connected to the internet. This makes them vulnerable to cyber-attacks from individuals with malicious intent.

In order for end-users of these technologies to handle such threats, they need to be informed about current cyber threats and how to handle them in case they become a victim of such an attack.

Therefore, it is important to understand the behavior of the end user in seeking out such information and the factors that influence the end-users behavioral intention to follow or ignore warnings in regard to cyber threats when they are presented with information about current threats.

Thus, this work aims at identifying such factors and their information-seeking behaviors through an (online) experiment where participants are surveyed in regard to their behavioral intention when presented with such information and how they seek out such information.

The aim of this work is to acquire insights into factors that might influence the end-user to act appropriately when experts provide them with information about cyber threats and how to handle them.

Literature:

  • Kovačević, A., Putnik, N., & Tošković, O. (2020). Factors Related to Cyber Security Behavior. IEEE Access, 8, 125140-125148.
  • Nicholson, J., Coventry, L., & Briggs, P. (2019, May). " If It's Important It Will Be A Headline" Cybersecurity Information Seeking in Older Adults. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-11).
  • Gratian, M., Bandi, S., Cukier, M., Dykstra, J., & Ginther, A. (2018). Correlating human traits and cyber security behavior intentions. computers & security, 73, 345-358.

Contact:

Ali Sercan Basyurt

Effektive Nutzung der Virtual Reality App Spatial für Kollaboration im Unternehmenskontext

Zielgruppe:

Master

Anforderungen:

Interviews (evtl. auch in englischer Sprache), hohes Engagement während der Rekrutierung von Interviewpartnern

Inhalte:

Plattformen für die Zusammenarbeit in virtueller Realität (VR) ermöglichen es Teammitgliedern, ein natürliches Gespräch zu führen, nonverbale Hinweise wahrzunehmen und in einer ablenkungsfreien Umgebung zusammenzuarbeiten. Die VR-Kollaborationsplattform Spatial hat sich als äußerst erfolgreich erwiesen, insbesondere seit der weit verbreiteten Home-Office-Regelung während der COVID-19-Pandemie. Viele große Unternehmen wie LARVOL, Mattel, Pfizer, BNP Paribas, Ford, Nestlé Purina und Enel SpA nutzen Spatial für die Zusammenarbeit und interaktive Meetings. So hat beispielsweise das Unternehmen LARVOL seinen Hauptsitz nach Spatial verlegt, während Unternehmen wie Mattel und Ford interdisziplinäre Teams aus der ganzen Welt in Spatial-Projekträume bringen, um gemeinsam neue Produkte zu entwerfen.

Nichtsdestotrotz sind kollaborative Meetings in VR immer noch eher die Ausnahme als die Regel, und es bleibt die offene Frage, wie VR effektiv genutzt werden kann, vor allem angesichts des breiten Spektrums anderer verfügbarer Meeting-Optionen wie Face-to-Face-Meetings, Telefonate und Videokonferenz-Tools. Ziel dieser Arbeit ist es daher, zu verstehen, was effektives Nutzungsverhalten in Bezug auf VR für die Zusammenarbeit im Unternehmenskontext ausmacht. Die Literatur zur Theorie der effektiven Nutzung und des Affordance-Netzwerk-Ansatzes als methodischer Schritt-für-Schritt-Ansatz zum Verständnis von effektivem Nutzungsverhalten dient dabei als guter Ausgangspunkt für die Auseinandersetzung mit dem Thema.

Um Erkenntnisse zu den Forschungsfragen zu gewinnen, sollen Interviews mit Beschäftigten geführt werden, die Spatial für die Zusammenarbeit nutzen. Da die Zielgruppe nicht einfach für Interviews zu rekrutieren ist, ist eine hohe Begeisterung für das Thema und Engagement während des Rekrutierungsprozesses erforderlich. Außerdem ist eine gewisse Sicherheit in der englischen Sprache erforderlich, um Interviews mit Beschäftigen aus internationalen Unternehmen führen zu können. Ein guter Anfang könnte die Kontaktaufnahme mit der Firma Spatial selbst und den oben genannten Unternehmen sein, die Spatial bereits einsetzen. Während der Bearbeitung besteht die Möglichkeit, ein Oculus-Quest-Headset vom Lehrstuhl auszuleihen, um Spatial (und andere Apps) selbst auszuprobieren und sich mit Interviewpartnern in ihrer Spatial-Umgebung zu treffen, um einen besseren Eindruck davon zu bekommen, wie Unternehmen diese Umgebung nutzen.

Literatur:

  • Spatial (2020). LARVOL Uses Spatial As Their Virtual Headquarters. https://spatial.io/blog/larvol-vr-office
  • Burton-Jones, A., & Grange, C. (2013). From Use to Effective Use: A Representation Theory Perspective. Information Systems Research, 24(3), 632–658.
  • Burton-Jones, A., & Volkoff, O. (2017). How can we develop contextualized theories of effective use? A demonstration in the context of community-care electronic health records. Information Systems Research, 28(3), 468–489.
  • Fromm, J., Mirbabaie, M. & Stieglitz, S. (2020). The Effects of Virtual Reality Affordances and Constraints on Negative Group Effects during Brainstorming Sessions. In Proceedings of the 15th International Conference on Wirtschaftsinformatik (WI), Potsdam, Germany.

Kontakt:

Jennifer Fromm

Themenfelder für Abschlussarbeiten

Social media analytics

  • Misinformation in social media -  contact
  • Automated communication in social media - contact
  • (Digital) science communication -  contact
  • Echo chambers and filter bubbles in social networks - contact

Communication and Collaboration

  • Conversational agents in virtual collaboration -  contact  &  contact
  • Deployment and use of artificial intelligence (in companies) -  contact 
  • Digital ethics -  contact  &  contact
  • Research data management and open science in the cloud - contact