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Das Hauptziel unserer Lehrveranstaltungen ist es, die Datenkompetenz der Studierenden zu erhöhen. Wir verfolgen einen problem-orientierten Fallstudienansatz, der es Studierenden ermöglicht, herausfordernde betriebswirtschaftliche Probleme in datenbezogene Fragestellungen zu übersetzen und diese mit Ansätzen aus den Bereichen Business Analytics, Data Science und Machine Learning zu lösen sowie die erzielten Ergebnisse kritisch zu hinterfragen.

Kurse FS23 & HS22

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Master
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Business Analytics und Data Science Applications

Ivo Blohm

Daten sind das neue Öl! Daten sind eine neue Asset-Klasse! Solche und ähnliche Aussagen sind heute allgegenwärtig und sollen das grosse wirtschaftliche Potenzial von Data Science und künstlicher Intelligenz veranschaulichen. "Smarte" Produkte und Dienstleistungen sind bereits heute allgegenwärtig und werden in Zukunft eine immer grössere Rolle in unserem Privat- und Arbeitsleben spielen. So galten beispielsweise selbstfahrende Autos vor 10 Jahren noch als technische Utopie; heute wartet man auf die flächendeckende Markteinführung. Übergeordnetes Ziel des Kurses ist es, Studierende in die Lage zu versetzen, mittels Big Data, Data Science, Machine Learning & Co betriebswirtschaftliche Probleme lösen zu können. Dafür verfolgt der Kurs ein Fallstudien-orientiertes Kursdesign. In jeder Fallstudie wird auf Basis einer konkreten betriebswirtschaftlichen Problemstellung eine prototypische Anwendung entwickelt, um z.B. die finanzielle Performance, operative Effizienz oder die Effektivität von betriebswirtschaftlichen Massnahmen zu verbessern. Im Rahmen der Fallstudien werden eine Vielzahl von unterschiedlichen Algorithmen und Analyse-Ansätzen besprochen und eingeübt. Die Fallstudien stammen dabei in der Regel aus dem Kontext von führenden Internet- und Technologie-Unternehmen, wie z.B. Facebook, Linkedin, Netflix, Orange oder Zalando. Diese Fallbeispiele umfassen dabei u.a. die Vorhersage von Weinqualität, Vorhersage von zukünftigen Kundenverhalten, das Erstellen von Kaufempfehlungen oder die automatisierte Identifikation von Fake News. Studierende lernen dabei den Umgang mit grossen unstrukturierten Datenmengen.

Abschlussarbeiten

Sind Sie am Ende Ihres Bachelor- oder Masterstudiums? Im Rahmen unserer Forschungsschwerpunkte suchen wir fortlaufend Studierende, die bei uns eine Abschlussarbeit schreiben wollen.

Level:
Bachelor or Master
Kontakt:
Alexander Meier

The Situation:
Are you interested in exploring the different types of biases that exist in AI systems and their impact on society? Do you want to learn how to mitigate these biases and contribute to the creation of better AI systems? If so, then this thesis on bias in AI is for you!

Objective of the Thesis:
The thesis could cover topics such as the definition of AI bias, types of AI bias, examples of AI bias, and debiasing strategies. Research fields could include analyzing datasets for bias, developing algorithms that are less prone to bias, exploring the role of bias in AI models such as ChatGPT, or investigate the role of bias in algorithms for the grant selection of scholarships. You’ll have the opportunity to work with experienced researchers in the field of AI and machine learning, and to contribute to cutting-edge research on this important topic. The thesis could focus on either technical bias or societal bias.
Your thesis could either entail qualitative (expert interviews, case studies, …), quantitative (Survey, Field-Experiment, …), literature-based research(systematic literature research), or the development of an application / PoC (model development, Python, R, …).

About You:
You should
– have a strong interest in AI and machine learning, and a desire to contribute to cutting-edge research in this field.
– are a self-starter who can work independently
– be a communicative and open person
– work in an accurate way
– have scientific writing skills in English

Experience with programming languages such as Python, R, or Java could be advantageous depending on the field of research and/or research method.

About Me:
I will offer you
– a close supervision, with regular review meetings, feedback discussions, etc.
– to start immediately, but the thesis should be completed within +- 6 months
– the possibility of publishing your thesis (e.g., European Conference on Information Systems) as long as the results are worth publishing

Application:
If you are interested in this opportunity, please apply with the following documents:
– CV
– Transcript of records
– An estimated timeline for the thesis
– Max. 150 word motivation

Contact: Alexander Meier ()

If you want to learn more about bias in AI:
https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans
https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1270.pdf

Level:
Bachelor & Master
Kontakt:
Kevin Schmitt

The Situation:
The field of biometrics has gained considerable attention in recent years due to its potential to provide secure and accurate means of identifying and authentifying individuals based on their physical and behavioral characteristics. Biometric technology offers unique advantages over traditional security methods, such as passwords or PINs, which are prone to hacking and theft. Biometric technology is increasingly being adopted in various domains, including border control, banking, healthcare, and law enforcement, to provide a more secure and reliable means of verifying identity.

Objective of the Thesis:
The main objective of this thesis is to build a taxonomy for the micro-level analysis of Biometric service offerings and to calculate clusters for the macro-level analysis. Furthermore, the results should be validated using quantitative (i.e., Fleiss` Kappa) and qualitative (i.e., semi-structured interviews) methods.
This thesis should provide valuable insights into the structure and dynamics of the Biometric industry and their service offerings and will contribute to the advancement of our understanding of this complex and rapidly evolving field. In addition, the study’s results will be of interest to researchers, practitioners, and stakeholders in the field of Biometrics.
We are looking for a highly motivated and qualified individual with a strong interest in Business Innovation or a related field of study. A successful candidate will be expected to demonstrate a solid ability to conduct independent research and communicate their work’s results effectively, both verbally and in writing.

About You:
You should
– be interested in Biometrics
– have a good understanding of statistics
– have a basic understanding of qualitative research methods (i.e., semi-structured interviews)
– be a communicative and open person
– work in an independent and accurate way
– have scientific writing skills in English

About Me:
I will offer you
– a close supervision, with regular review meetings, feedback discussions, etc.
– to start immediately, but the thesis should be completed within the next 9 months
– the possibility of publishing your thesis (e.g., European Conference on Information Systems) as long as the results are worth publishing

Application:
If you are interested in this opportunity, please apply with the following documents:
– CV
– Transcript of records
– An estimated timeline for the thesis
– Max. 150 word motivation

Contact: Kevin Schmitt ()

If you want to learn more about Biometrics:
– https://frontex.europa.eu/assets/Images_News/2021/Tech_Foresight_on_Biometrics_Taxonomy.pdf

Literature:
These related Papers will give you a good understanding of what is expected from you
– https://ieeexplore.ieee.org/document/8598491
– https://link.springer.com/chapter/10.1007/978-3-030-66218-9_24

I recommend either Nickerson et al. (2013) or Kundisch et al. (2022) for the taxonomy development process.
– https://www.tandfonline.com/doi/abs/10.1057/ejis.2012.26?cookieSet=1
– https://link.springer.com/article/10.1007/s12599-021-00723-x

For the calculation of the clusters, I recommend Ward (1963) (Ward’s Hierarchical Agglomerative Algorithm). With SPSS, you can comfortably utilize Ward’s Hierarchical Agglomerative Algorithm to calculate clusters. Other algorithms might also be suitable depending on the research questions.
– https://www.tandfonline.com/doi/abs/10.1080/01621459.1963.10500845

Level:
Bachelor or Master
Kontakt:
Alexander Meier

The Situation:
While the circle of the ever falling and rising Bitcoin and NFT-Art prices dictate the news headlines when it comes to blockchain related topics, the emergence of blockchain applications in other domains is still a niche. At IWI we are researching how blockchain based systems could influence learning and education. Possible fields for deploying NFTs could be micro-credentials. Micro-credentials are a form of certification. The biggest challenge for universities and employers has always been verification. NFTs could depict a tamper proof way of documenting academic or applied skill records. Hence using the decentralized nature of a blockchain could tackle multiple trust, transparency, and incentivization related challenges in education for numerous stakeholders.

Objective of the Thesis:

Your thesis should entail a systematic literature review on applications of Blockchains in the field of education using the methodology of Webster and Watson (2002) and Vom Brocke et al. (2009; 2015)

About You:
You should
– be interested in NfTs/Blockchain
– have a basic understanding of qualitative research methods (i.e., semi-structured interviews)
– be a communicative and open person
– work in an independent and accurate way
– have scientific writing skills in English

About Me:
I will offer you
– a close supervision, with regular review meetings, feedback discussions, etc.
– to start immediately, but the thesis should be completed within +- 6 months
– the possibility of publishing your thesis (e.g., European Conference on Information Systems) as long as the results are worth publishing

Application:
If you are interested in this opportunity, please apply with the following documents:
– CV
– Transcript of records
– An estimated timeline for the thesis
– Max. 150 word motivation

Contact: Alexander Meier ()

If you want to learn more about NFTs in education:
https://medium.com/the-future-of-learning-and-education/nfts-in-education-957ce434047c

Literature:
– Webster, Jane, and Richard T. Watson. “Analyzing the Past to Prepare for the Future: Writing a Literature Review.” MIS Quarterly, vol. 26, no. 2, 2002, pp. xiii–xxiii. JSTOR, http://www.jstor.org/stable/4132319
– vom Brocke, J.; Simons, A.; Niehaves, B.; Riemer, K.; Plattfaut, R.; Cleven, A. (2009): Reconstructing the Giant: On the Importance of Rigour in Documenting the Literature Search Process. In: Proceedings of the 17th European Conference on Information Systems. Eds. 2009, pp. 2206–2217.

Level:
Bachelor/Master
Kontakt:
Philipp Gordetzki

Why:
AI text generation tools such as ChatGPT are emerging with strong capabilities of solving various tasks. We want to use them to generate feedback on innovation ideas allowing users and companies faster innovation, higher quality ideas, and lower costs. Nevertheless, there is currently still a need for improvement. We need to understand how we can collaborate with such AIs and profit from their feedback on our ideas. As innovation is a challenging creativity process, we aim to support humans in a hybrid approach. Your task is to investigate how tools like ChatGPT or other AI tools can provide feedback, what concept of feedbacks exist in the literature, and develop your own categorization of tomorrow’s AI feedback on our work.

How?

• Thesis that conducts a systematic literature review on the conceptualization of AI feedback using the methodology of Webster and Watson (2002) and Vom Brocke et al. (2009; 2015)

Key-Facts:

• Close supervision, with regular review meetings, feedback discussions, etc.
• Thesis can start immediately but should be completed within the next ±6 months
• If the work is worth publishing, you will be listed as an author

If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

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    Ihre Bewerbung für eine Abschlussarbeit

    Danke für Ihr Interesse, Ihre Abschlussarbeit bei Prof. Dr. Blohm zu schreiben. Wir betreuen gerne Studierende, die sich für unsere Forschungsthemen begeistern und die bisher gute akademische Leistungen erbracht haben. Weil wir eine grosse Anzahl an Bewerbungen bekommen, können wir nur jene berücksichtigen, die gut zu unseren Forschungsgebieten passen. Mehr zu unseren Forschungsgebieten erfahren Sie auf dieser Webseite. Um sich zu bewerben, können Sie eines der Themen in Betracht ziehen, an denen wir arbeiten oder Sie können ein eigenes Thema vorschlagen.



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