DE / EN

Bachelor-Seminar

SM 452 für Bachelor­studierende (Wirtschafts­informatik)

Allgemeines

HWS 2023
Verantwortlicher Dozent Prof. Dr. Armin Heinzl
Veranstaltungs­art Seminar
Leistungs­punkte 5 ECTS (WI ab HWS 2013), 4 ECTS (WI bis HWS 2013)
Sprache Englisch
Prüfungs­form und -umfang Seminarpapier (70%), Presentation (20%), Diskussionsbeitrag (10%)
Prüfungs­termin Siehe Infos zur Veranstaltung
Infos für Studierende Registrierung: Bitte beachten Sie unten stehende Informationen!
Timo Himmelsbach, M.Eng.

Timo Himmelsbach, M.Eng.

Ansprech­partner Bachelor-Seminar

Bei Fragen wenden Sie sich bitte an Timo Himmelsbach​​​​​​​.

Infos zur Veranstaltung

New Frontiers in Digital Transformation

  • Kurzbeschreibung

    Digitale Technologien und die ständig wachsenden Datenmengen verändern unser tägliches Leben und die Wirtschaft radikal. Eingebettet in den Kern der Produkte, Abläufe und Strategien vieler Unternehmen, verändern digitale Technologien bestehende Geschäfte in allen Branchen rasant. Neue Markt­angebote, Geschäftsprozesse und Geschäfts­modelle entstehen rund um den Einsatz dieser digitalen Technologien und führen zu digitalen Innovationen1. Die Allgegenwärtigkeit digitaler Technologien verändert unser Verständnis von Informations­systemen (IS) grundlegend, sowohl was ihre Entwicklung, Koordination und Nutzung als auch die Art und Weise, wie wir mit ihnen interagieren, betrifft. An unserem Lehr­stuhl bieten wir ein breites Spektrum an Forschungs­themen in diesem Bereich an, die auch neue digitale Technologien wie künstliche Intelligenz (KI) und maschinelles Lernen (ML) umfassen. Hierbei nehmen wir vor allem nachfolgende Perspektiven ein: Mensch-Computer-Interaktion, System­entwicklung, Wertschöpfung oder Organisation.

    In unserem Seminar untersuchen wir den Einfluss digitaler Technologien auf Individuen und Organisationen. Dabei verknüpfen wir die angebotenen Themen mit unseren laufenden Forschungs­arbeiten, die auf höchstem internationalem Niveau veröffentlicht wurden und werden.

    1. Nambisan, S., Lyytinen, K. & Yoo, Y. Handbook of Digital Innovation. 2–12 (2020) doi:10.4337/9781788119986.00008.

    Falls Sie mehr über digitale Innovation erfahren möchten, werfen Sie gerne einen Blick auf unseren Master­studien­gang IS 607 (https://www.bwl.uni-mannheim.de/en/heinzl/teaching/digital-innovation/)  und/oder folgende Leseempfehlung:

    Nambisan, S., Lyytinen, K. & Yoo, Y. Handbook of Digital Innovation, (2020), doi:10.4337/9781788119986.

    Ziel des Seminars

    In diesem Seminar erwerben Sie die Fähigkeit, bestehende Forschungs­arbeiten zu identifizieren, einzuordnen und zu bewerten. Sie werden lernen, eine eigene Forschungs­agenda zu entwickeln sowie diese zu präsentieren und mit den Teilnehmern des Seminars zu diskutieren. Sie machen sich mit verschiedenen Techniken des wissenschaft­lichen Arbeitens und Schreibens vertraut, so dass Sie optimal auf die Konzeption und Anfertigung Ihrer Master­arbeit vorbereitet werden. Wir bieten fünf verschiedene Themen­bereiche an, die hoffentlich Ihr Interesse wecken.

Nach oben

Herbst/Winter 2023

  • Registrierung

    Die Registrierung erfolgt ausschließlich über das Online-Registrierungs­portal (erreichbar innerhalb des Uni-Netzwerkes oder über VPN). Während des Registrierungs­zeitraums können Sie das Seminar im Anmeldeformular auswählen.

    Registrierungs­zeitraum: siehe Termine  

    Anforderungen:

    • Kurzes formloses Motivations­schreiben (maximal 1 Seite):

    Bitte wählen Sie ein Thema und begründen Sie Ihre Wahl, z. B. was Sie besonders interessiert und was Sie lernen möchten. Bitte geben Sie auch zwei alternative Themen an.

    • Lebens­lauf und Studien­ergebnisse (Notentranskript)

    Es werden weder Registrierungen per E-Mail noch unvollständige Formulare im Registrierungs­tool berücksichtigt.

  • Themen

    Die Studierenden werden gebeten, ein  formloses Motivations­schreiben (maximal 1 Seite) zu verfassen, in dem Sie dieThemenauswahl darlegen und kurz begründen.Dieses Motivations­schreiben stellt neben dem Lebens­lauf und dem Notentranskript eine wichtige Referenz für die Seminarzulassung dar.


    A – Healthcare IT
    Data-driven behavior change, Objective measurement, mHealth, Resilience & Wellbeing In recent years the potential of mHealth apps for preventing mental health problems and supporting individual wellbeing (as a sign of increased resilience) has been shown in various studies. These studies typically rely on self-reported measures of resilience and wellbeing before and after pre-specified times of mHealth use (often controlled randomized trials or longitudinal pre-post measurement studies). In these setups the dynamics of mHealth feature use and their effects onto wellbeing and resilience remain largely unknown because they cannot be objectively and consistently measured. This seminar thesis is concerned with identifying means to objectively measure stress, wellbeing, and resilience for example via contextual or sensor data, instead of relying on self-reported questionnaire and survey data. The student is expected to find and consolidate literature from informatics and related disciplines to identify which objective data collection methods best respond to existing measurement scales of resilience and wellbeing. Further the implementation feasibility of such measurement in common mHealth technologies is to be assessed and evaluated. Mechthild Pieper
    mHealth, Just-In-Time-Adaptive Interventions, Resilience & Wellbeing Many individuals desire to change their behavior to lead a healthier and happier life. To achieve this goal, some make use of health applications on their mobile devices (mHealth). However, ongoing user engagement to ensure the impact and effectiveness of mHealth use remains a challenging task for research and practice. To overcome this challenge, providers often send push notifications (PNs) to users with the intent to keep them engaged with specifically developed, theory-driven app features. Optimally, these PNs would deliver the right type and amount of support at the right time, i.e., just-in-time-adaptive interventions (JITAI). To achieve this goal researchers and providers need to determine the content, timing, frequency, and communication channel of respective JITAIs. The goal of this seminar thesis is to identify literature that addresses the effectiveness of different types of JITAIs and provides details about their content, timing, and efficacy. Ideally the thesis focuses on studies and applications that address wellbeing and resilience as well as the prevention of common mental health issues such as anxiety, grief, and depression. Mechthild Pieper
    B – Human-Computer Interaction
    Algorithm Aversion This seminar paper aims to investigate algorithm aversion in the context of AI-generated images, examining the existing literature to explore how algorithm aversion manifests in the evaluation and opinions of AI-generated images compared to human-generated images. The analysis will provide an overview of current research, considering various use contexts and user perspectives, with the goal of identifying potential research questions and uncovering additional factors that may contribute to algorithm aversion in the context of AI-generated images. Dr. Anna-Maria Seeger
    Avatars Self-avatars are digital representations of people that are used in virtual environments such as online games, virtual reality experiences, or e-commerce. Previous research has shown that beautified self-avatars, with an enhanced appearance can provide performance increases, as well as motivation and inspiration for users themselves. Furthermore, research on the perception of human beauty indicates that more attractive humans are perceived as more successful, trustworthy or competent. However, research in adjacent fields, such as social media and plastic surgery, has also shown that when artificially beautified humans are perceived by others, they can view them as artificial and inauthentic. In order to understand how beautified humans are perceived by others, it is important to understand whether there are positive or negative feelings, and to understand which mechanisms might be causing the differences in perception. For this seminar paper the student is expected to conduct a structured literature review, to identify the theories that have been used in previous studies to explain the perception of artificial beauty, and to classify the contexts in which artificial beautification has been studied. Rosa Holtzwart
    Algorithmic Beautification Human beauty or attractiveness is a dominant characteristic of physical appearance and humans have a drive for beauty. Humans also have a tendency to enhance their self-presentation, thus they engage in beahviours to optimise their apperance. This also includes enhancements of their appearance in virtual realms, such as improving their beauty with filters or photoshop on social media. With the surge of computational power and generative AI, the methods to enhance the virtual images of humans have been rapidly evolving. For instance, some social media applications now provider pre-configured facial filters that can be applied to the front view of the face in real time. To understand the possibilities and potential developments of virtual beautification in the future, it is necessary to understand past efforts of automation of virtual beauty enhancements. In this seminar paper the student is expected to conduct a structured literature review, to identify the algorithms and methods that have been developed in in previous studies to enhance human beauty. Moreover, the aim of this seminar thesis is to provide an overview of the ways the developed algorithms have been evaluated, where and how they can be applied (e.g. only front face, including profile face view; full-body; static images, live video, 3D etc.). Rosa Holtzwart
    Group decision making, AI, clinical decision support, group decision support Intelligent clinical group decision support systems for improving group decision-making in healthcare. Artificial Intelligence (AI) based systems are increasingly used to support decision-making in various contexts. In medicine, for example, intelligent clinical decision support systems can assist physicians and psychotherapists in making diagnostic and therapeutic decisions. A growing body of literature focuses on how individuals perceive and evaluate AI advice. However, some clinical decisions in practice are team-based. Yet, little is known about how intelligent clinical decision support systems can support group decision making. This seminar paper explores the integration of intelligent clinical decision support systems with group decision making in healthcare. For this seminar paper, the student should conduct a structured literature review to provide an overview of the existing literature on intelligent clinical group decision support systems. Specifically, the student should focus on the following research questions: 1) What are clinical group decisions and in what contexts are they relevant, 2) What intelligent clinical group decision support systems are on the market, and 3) How do they affect group decision processes and outcomes? Désirée Zercher
    C – Exploring Technological Advances of Artificial Intelligence
    Generative AI, fashion design, computational creativity Recently, generative AI technologies have captured significant attention. Innovations such as Dalle, Imagen, and GPT-3, among others, have demonstrated their remarkable creative capabilities. The seminar thesis explores the intersection of fashion design and generative AI. Through this seminar thesis, students will delve into the theoretical foundations, practical applications, and ethical implications of using generative AI in fashion design. They will critically analyze existing research, industry case studies, and emerging trends to develop a well-rounded perspective on the subject. The goal is to capture the current state of research on generative AI and fashion design as well as prospective frontiers. Deborah Mateja
    Explainable AI, Radiology, Design Knowledge, User-Centricity Healthcare professionals need to understand the reasoning behind AI-generated recommendations to trust and confidently act upon them. Explainable artificial intelligence (XAI) techniques enable the generation of explanations, allowing clinicians to comprehend the underlying factors influencing AI-driven outcomes and help in validating the results. However, despite well-known theoretical goals and needs for explainability in AI applications, there is a lack of comprehensive understanding of how and in which situations XAI precisely unfolds its potential in clinical practice. Based on a structured review of information systems, computer science, and medical informatics literature, this seminar thesis is targeted at uncovering the situations, conditions, and reasons for clinicians to use explanations in the time-constrained daily routine, which could differ in simple vs. difficult patient conditions, workflow characteristics, as well as personal characteristics. Additionally, a seminar paper in this context could carve out the wide range of latent effects (benefits and risks) that were observed in XAI, including overreliance, diagnostic efficiency, and the ability to detect errors, to name just a few. Luis Oberste
    Artificial Intelligence (AI) pair programming Over the last decade, pair programming has become an important technique for developing better code and facilitating a robust development flow. In 2021, GITHub has introduced a new tool to assist developers by transforming the traditional approach of pair programming into an AI-based solution. In this seminar paper, you will analyse different streams of academic literature to categorise and summarise current research on AI assisted pair programming. Furthermore, the aim of the thesis should be to identify the differences between traditional and AI-based pair programming and how this transition affects existing research. A good starting point may be the following paper on traditional pair programming: Kude, T., Mithas, S., Schmidt, C. T., & Heinzl, A. (2019). How pair programming influences team performance: The role of backup behavior, shared mental models, and task novelty. Information Systems Research, 30(4), 1145-1163. Philipp Hoffmann
    D – Value Creation in Platform Eco­systems
    Data sharing, data monetization, data eco­systems, healthcare Data sharing and monetization provides organizations with new sources of revenue and value creation. Especially, in one of the world’s largest economies, the healthcare industry, data has the potential to unlock new revenue streams while making businesses such as healthcare providers profitable and more competitive. However, an accepted and scalable approach to data sharing and monetization is still lacking in practice. Research on data sharing is still in its infancy and lacks of insightful studies that go beyond identified challenges such as data management, privacy, and security hindering the sharing of data. In this seminar thesis, the student is expected to conduct a structured literature review in order to elaborate and summarize different data sharing solution approaches in the healthcare industry. Hereby the student should focus on relevant literature from the Computer Science, Data Science, and Information Systems fields. Timo Himmelsbach
    Decoding Artificial Intelligence Eco­systems: Towards a Holistic Macro perspective for Democratizing AI in Industry Artificial intelligence (AI) has emerged as a pivotal force reshaping industries and economies. While existing research has shed light on data eco­systems, innovation eco­systems, and big data eco­systems, a comprehensive, holistic overview of AI eco­systems remains elusive. Moreover, a universally accepted definition for AI eco­systems has yet to be established, creating a critical knowledge gap in understanding the intricate interplay of actors, roles, and interactions within this dynamic landscape. This seminar thesis aims to bridge this gap by investigating AI eco­systems from a macro perspective, unraveling the complexity of their structures and functions. By analyzing the collective endeavors of various stakeholders, including startups, established industry players, research institutions, and governmental bodies, the research will provide valuable insights into the collaborative nature of these eco­systems. It will contribute to the AI democratization in industry, offering firms a path to access AI resources and capabilities that are otherwise not easy to obtain. Good starting points are: – https://eit.europa.eu/sites/default/files/creation_of_a_taxonomy_for_the_european_ai_ecosystem_final.pdf – https://www.tandfonline.com/doi/epdf/10.1080/02650487.2022.2122249?needAccess=true&role=button – https://dl.acm.org/doi/pdf/10.1145/3467022 Tobias Maier
    Platform eco­systems, governance, power asymmetries, (de-) centralization Firms following platform strategies open a core technology and involve external parties in developing and commercializing products. To date, the majority of the world’s most valuable firms, including Apple, Google and Microsoft, are platform companies. This development gives rise to what has been called the “platform economy” and incorporates significant changes regarding the way firms cooperate and compete with each other. Unlike traditional seller-buyer relations­hips, value creation on platforms is organized in an eco­system logic. Participating actors on digital platforms, such as Google Android or Apple iOS, highly depend on each other. On the one hand, developers of complementary products (such as mobile apps) rely on development and distribution capabilities provided by the platform (such as software development kits or module deployment). On the other hand, the platform owner relies on external innovation that complements the platform. Despite these organizational interdependencies, platform eco­systems may exhibit inherent power asymmetries between platform owner and complementors. While these asymmetries may be conducive in ensuring a joint creation of value, they may also turn into a significant threat for complementors, who base their business model on a particular platform technology. In this seminar project, students are expected to review extant literature on platform eco­systems and elaborate on power distribution, the nature of power asymmetries as well as on corresponding challenges for complementors in centralized and decentralized platform contexts. André Halckenhäußer
  • Kursüberblick und -termine

    EventZeitraum / DeadlineArbeits­ergebnisse
    Registrierungs­zeitraum 01.08. – 04.09.2023 (23:59) – Registrierung über das Online-Tool – Fügen Sie Ihren Lebens­lauf, das Notentranskript und Ihr Motivations¬schreiben an
    Versand der Bestätigungen 06.09.2023 (mittags)  
    Deadline zum Rücktritt 07.09.2023 (mittags)  
    Kick-Off Meeting 13.09.2023, 12:45Uhr – 13:30Uhr, EO 256 – Teilnahme an der Kick-Off-Einführungs­veranstaltung
    – Kontakt und Treffen mit Ihrem Betreuer
    1. Meilenstein 27.09.2023 Ersten Entwurf bei Ihrem Betreuer einreichen: – Detaillierte Gliederung – Literatur¬verzeichnis
    2. Meilenstein 25.10.2023 Zweiten Entwurf bei Ihrem Betreuer einreichen: – Inhaltsverzeichnis – Einführung: vollständig formuliert – Methodik: vollständig formuliert – Ergebnisse: strukturierter Entwurf – Diskussion: strukturierter Entwurf
    Abgabe der Arbeit 08.11.2023 (mittags) – Senden Sie Ihre Arbeit bis 12 Uhr im PDF-Format per Mail an Timo Himmelsbach (himmelsbach@uni-mannheim.de) und setzen das Sekretariat (wifo1@uni-mannheim.de) auf Kopie (CC-Feld). – Reichen Sie so bald wie möglich nach dem Abgabetermin zwei gedruckte Exemplare der Seminararbeit im Sekretariat ein. – Senden Sie eine digitale Version der Seminararbeit per E-Mail an Ihren Betreuer
    Abgabe der Präsentation 27.11.2023 (23:59) – Optional: Bitten Sie Ihren Betreuer vorab um Feedback zur Präsentation – Senden Sie Ihre Präsentation im PDF-Format per E-Mail an Timo Himmelsbach
    Präsentation 28.11. von 8:00 – 13:00Uhr und am 01.12. von 14:00Uhr – 18:00Uhr, ExpLAB Schloss Schneckenhof – Besuchen Sie das Seminar und beteiligen Sie sich aktiv an der Diskussion am Seminartag – Präsentieren und diskutieren Sie Ihre Seminararbeit im gemeinsamen Workshop – Diskussion und Feedback für mindestens eine Seminararbeit der anderen Studierenden
  • Literatur