Bachelor-Seminar
SM 452 für Bachelorstudierende (Wirtschaftsinformatik)
Allgemeines
| 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! |
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.
Frühling/Sommer 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 die Themenauswahl darlegen und kurz begründen. Dieses Motivationsschreiben stellt neben dem Lebenslauf und dem Notentranskript eine wichtige Referenz für die Seminarzulassung dar.
A – IS methods Data-driven Behavior Change, Experimental Designs, IS methods Many individuals desire to change their behavior motivated by health-related or other causes. To do so, they increasingly make use of mobile applications. To improve the efficacy of behavior change apps, researchers are interested in investigating how push-notifications as well as specific message components and app features influence the behavior of individuals (with regard to app use and real-world behavior). A Micro-Randomized Trial (MRT) is an experimental design that stems from behavioral science and psychology which was developed specifically to test Just-In-Time-Adaptive Interventions (JITAIs) – an intervention that aims to provide the right type and amount of support at the right time. MRTs are thus optimally tailored to support Information System’s researchers in investigating and theorizing about JITAIs and could also be used in other IS research fields (e.g., digital nudging, Information Communication Technologies, etc.). The benefits that MRTs hold over other commonly applied experimental designs (such as Randomized Controlled Trials (RCT)), are that they allow for analyzing the immediate impact of intervention components on a specified proximal outcome, how this impact changes over the course of treatment and how it influences a predefined distal outcome. In turn, insights of RCTs can only evaluate the overall treatment effects at a distal point in time. In this seminar students are expected to conduct a structured literature review with the goal to (1) identify quantitative research studies in the IS basket of eight journals, that look at IS use and user behavior as an outcome, (2) determine which IS methods or experimental designs were employed for these studies, and (3) summarize the characteristics of these designs (incl. corresponding applicable methods for data analysis) as well as compare them to the characteristics of an MRT experimental design. More information about MRTs can be found in: • Klasnja, P. et al. (2015) ‘Microrandomized trials: An experimental design for developing just-in-time adaptive interventions’, Health Psychology, 34, pp. 1220–1228. Available at: https://doi.org/10.1037/HEA0000305. • Klasnja, P. et al. (2018) ‘Efficacy of Contextually Tailored Suggestions for Physical Activity: A Micro-randomized Optimization Trial of HeartSteps’, Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 53(6), pp. 573–582. Available at: https://doi.org/10.1093/abm/kay067. • Qian, T. et al. (2022) ‘The microrandomized trial for developing digital interventions: Experimental design and data analysis considerations.’, Psychological Methods [Preprint]. Available at: https://doi.org/10.1037/met0000283 Mechthild Pieper B – Human-Computer Interaction Avatars 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 avatars, with an optimised appearance can provide motivation and inspiration for users to work towards their goals and improve themselves. However, beautifying a user's avatar, or creating an avatar that represents an idealised version of the user, can also have severe negative consequences. It can lead to body dissatisfaction and negative self-image in the user. When the user sees their avatar as more attractive or idealised than their actual appearance, it can create a discrepancy between their digital self and their actual self, leading to negative emotions and self-esteem issues. Additionally, it may also lead to unrealistic expectations and disappointment in the user's real-life interactions and relationships. In some cases, it may even lead to gaming addiction or other forms of abusive technology use. In order to understand how avatars can be designed effectively and responsibly, it is important to understand how digital responsibility for the creation of avatars could be conceptualised. For this seminar paper the student is expected to conduct a structured literature review to identify how (digital) responsibility was captured and conceptualised in previous studies. In addition, the student is expected to outline which theoretical perspectives have been used by previous studies to understand the relationship between (un-)ethical design of technology and negative psychological consequences for an individual. Rosa Holtzwart Artificial Intelligence, Group Decision-Making, Team-AI Collaboration, Teams Systems based on artificial intelligence (AI) increasingly support decision making in different contexts such as medicine and management. A growing body of literature focuses on how individuals perceive and evaluate AI advice. Nevertheless, many decisions in practice are team-based. Research is only starting to acknowledge team-AI collaboration. Research, especially in social science has studied team decision making decades ago. One prominent theory is the multi-level theory of team decision-making. This theory accounts for status differences and distributed expertise, resulting in an unequal knowledge distribution across team members. To make a group decision, teams have to aggregate their knowledge though different levels (from individual to group). However, the theory has never been applied to the human-AI interface. For this seminar paper, the student should conduct a structured literature review to provide an overview of existing literature on group decision support systems using the multi-level theory of team decision making as a theoretical framework for their analysis. Moreover, the student is expected to discuss how these findings apply to AI based group decision support and how AI might affect group decision making based on the multi-level theory of group decision making. Basic literature: Hollenbeck, J. R., Ilgen, D. R., Sego, D. J., Hedlund, J., Major, D. A., & Phillips, J. (1995). Multilevel theory of team decision making: Decision performance in teams incorporating distributed expertise. Journal of applied psychology, 80(2), 292. Désirée Zercher C – Exploring Technological Advances of Artificial Intelligence Technology Diffusion, Computational Creativity Recently, creative technologies, such as Dalle, Imagen, GPT3, and more, raise our attention. Such Artificial Intelligence systems exhibit own creative capabilities. In this seminar, you will explore the diffusion of such creative technologies. Research on technology diffusion aims to explain how, why, and at what rate new ideas spread. You will investigate existing information systems research on technology diffusion to derive meaningful theories and models that can help us investigate the diffusion of creative technologies. Deborah Mateja Explainable AI, Radiology, Design Knowledge, User-Centricity Research on eXplainable AI (XAI) aims to develop explanations for the cause of AI-based decisions, which are critical in high-stakes domains such as healthcare. Meanwhile, extant XAI tools are developer-centric and data-driven. I.e., approaches purely rely their explanations on patterns found in the input data (e.g., through highlighting relevant parts of a radiological image by heatmaps). While these mainly meet developers’ demands (e.g., to debug and improve AI models), they mismatch clinical users’ demands (such as doctors) in practice. Therefore, we argue that designing explanations that carry medical knowledge and concepts might rather be useful to reflect medical decision-relevant information and thus, be more effective. Based on a structured review of information systems literature, this seminar thesis is targeted at uncovering (a) main theoretical discourses about explainable information systems for healthcare and (b) relevant design knowledge for the development of explainable systems for clinical users based on the identified theoretical properties. Luis Oberste Release notes – A communication channel between developers and users The release management covers all tasks and activities to deliver source code into finished software products. This does not only include the initial deployment of software but also possible ongoing updates for the already shipped software. Thereby, release notes play an important part to describe the content of a software update as well as they act as the most important communication bridge between development teams and software users. In this seminar thesis, you will analyze different academic literature streams to categorize and summarize current research on release notes. This includes existing research on the content and influence of release notes as well as on technical approaches to automatically create them. A good starting point for the topic you can find in the following paper: Bi, T., Xia, X., Lo, D., Grundy, J., & Zimmermann, T. (2022). An empirical study of release note production and usage in practice. IEEE Transactions on Software Engineering. Philipp Hoffmann Ethical Challenges of Generative AI Generative artificial intelligence (AI) refers to AI systems that can create new content, such as text, images, or music. Such new content can create ethical challenges including biases, misleading content, as well as problems concerning intellectual property or accountability. The objective of this seminar paper is to conduct a systematic literature review of scholarly work that provides knowledge on ethical challenges of AI and related these findings to the specificities of text generative AI (such as chatGPT or Google Bard). Dr. Anna-Maria Seeger D – Management and Impact of Artificial Intelligence Business Analytics, Machine Learning, Value Creation For more than a decade, Business Analytics (BA) has been the largest annual IT investment in organizations. Emerging empirical findings suggest that BA can have a significant impact on firm performance, but organizations often fail to realize value and only 20% of analytics projects are expected to deliver business benefits. One of the reasons for this failure is that BA profoundly affects business processes, but the rationale behind process-level value creation from BA remains underexplored. In addition, the availability of increasingly powerful Machine Learning (ML) algorithms enables the application of BA systems with more reliable predictions and recommendations in even more diverse business processes. Therefore, ML-based BA systems further increase the relevance and timeliness of explanations on process-level value creation from BA. In this seminar thesis, you will conduct a structured review of recent literature to address the following research questions: (1) How does Business Analytics create value for organizations at the process level? (2) How does Machine Learning change process-level value creation from Business Analytics? Pascal Kunz E – Value Creation in Platform Ecosystems Platform ecosystems, governance, competition, power asymmetries, complementors Platform strategies are increasingly omnipresent: Firms decide to open a core technology and involve external parties in developing and commercializing products. To date, the majority of the world’s most valuable firms, such as Apple, Google, Microsoft, or Meta, 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 (e.g., mobile apps) rely on development and distribution capabilities provided by the platform (e.g., 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 value co-creation, 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, elaborate on power distribution and the nature of power asymmetries on digital platforms and provide insights on main challenges complementors are confronted with in light of power asymmetry André Halckenhäußer Data Sharing, Distributed-Ledger-Technology, 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 monetization of data. Distributed-Ledger-Technology (DLT) has the potential to transform healthcare delivery, by overcoming these challenges and facilitating a secure and scalable approach to data sharing and monetization. In this seminar thesis, the student is expected to conduct a structured literature review in order to elaborate and summarize different DLT-based 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 Data Monetization Digital transformation challenges how organizations across all industries create and capture value. Most companies have understood data as a key resource for their digital business endeavors. However, the majority of organizations – particularly small and mid-sized enterprises (SMEs) – lack the digital capabilities and structured approaches to collect, process, and create business value with the data they generate along their value chain. Simultaneously, organizations increasingly leverage and experiment with emerging technologies, such as AI, IoT, RPA, etc. as well as methods for business analytics to inform decision-making and enhance their operations, offerings, strategies, and business models. Improved decision-making and operational efficiency are widely understood application fields for data-based value creation. Digital innovations and new legislations, such as the recently proposed Data Governance Act of the European Commission, open new approaches for organizations to monetize on their own data as well as creating data ecosystems as novel source of competitive advantage for firms and economies. This seminar paper aims to explore data-based value creation strategies by conducting a structured literature review. Good starting points: Data and Value (Alaimo, Kallinikos, and Aaltonen, 2020) – accessible in Uni network: https://www.elgaronline.com/view/edcoll/9781788119979/9781788119979.00022.xml Data Governance Act: https://ec.europa.eu/commission/presscorner/detail/en/ip_22_1113 Tobias Maier Kursüberblick und -termine
Event Zeitraum / Deadline Arbeitsergebnisse Registrierungszeitraum 01.01. – 13.02.2023 (23:59) – Registrierung über das Online-Tool
– Fügen Sie Ihren Lebenslauf, das Notentranskript und Ihr Motivationsschreiben anVersand der Bestätigungen 15.02.2023 (mittags) Deadline zum Rücktritt 16.02.2023 (mittags) Kick-Off Meeting 20.02.2023 10:15 – 11:15 Uhr Raum: TBD – Teilnahme an der Kick-Off-Einführungsveranstaltung
– Kontakt und Treffen mit Ihrem Betreuer1. Meilenstein 06.03.2023 Ersten Entwurf bei Ihrem Betreuer einreichen:
– Detaillierte Gliederung
– Literaturverzeichnis2. Meilenstein 03.04.2023 Zweiten Entwurf bei Ihrem Betreuer einreichen:
– Inhaltsverzeichnis
– Einführung: vollständig formuliert
– Methodik: vollständig formuliert
– Ergebnisse: strukturierter Entwurf
– Diskussion: strukturierter EntwurfAbgabe der Arbeit 17.04.2023 (mittags) – Zwei Ausdrucke der Seminararbeit beim Sekretariat einreichen (bis 12 Uhr)
– Senden Sie eine digitale Version der Seminararbeit per E-Mail an Timo Himmelsbach (himmelsbachuni-mannheim.de) und an Ihren Betreuer (bis 12 Uhr)
Änderung aufgrund von Corona: Bitte senden Sie Ihre Arbeit bis 12 Uhr im PDF-Format per Mail an Timo Himmelsbach (himmelsbachuni-mannheim.de) und setzen das Sekretariat (wifo1uni-mannheim.de) auf CC. Bitte reichen Sie zudem, so bald wie möglich nach dem Abgabetermin, zwei Ausdrucke im Sekretariat ein.Abgabe der Präsentation 09.05.2023 (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 (himmelsbachuni-mannheim.de)Präsentation Donnerstag, 11.05.2023 12:45 – 18:00 und Freitag, 12.05.2023 12:45 – 18:00 Raum: ExpLAB – 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 StudierendenLiteratur
- Webster, J., & Watson, R. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Quarterly, 26(2), XIII-XXIII.
- Leidner, D. E. (2018). Review and theory symbiosis: An introspective retrospective. Journal of the Association for Information Systems, 19(6), 1.
Für den Zugriff auf die Literatur müssen Sie sich im VPN der Universität Mannheim befinden.
