Master's Seminar

IS 712 for Master's program (MMM and Business Informatics) / IS 918 (MMBR)

General Information

Fall 2021
Performing Lecturer Timo Himmelsbach
Examiner Prof. Dr. Armin Heinzl
Course Format Seminar
Credit Points 6 ECTS (MMM), 4 ECTS (WI)
Language English
Grading Seminar paper (70%), presentation (20%), discussion (10%)
Exam Date See course information below
Information for Students Registration: Please see information below!
Timo Himmelsbach, M.Eng.

Timo Himmelsbach, M.Eng.

Contact person for Master's Seminar

For further information please contact Timo Himmelsbach​​​​​​​.

    Course Information

  • Brief Description

    Digital technologies and the ever-growing amounts of data are radically reshaping our daily life as well as the economy. Embedded at the very core of the products, operations, and strategies of many organizations, digital technologies are rapidly transforming existing businesses throughout all industries. New market offerings, business processes, as well as business models are emerging around the use of these digital technologies, yielding digital innovation1. This pervasive nature of digital technology is fundamentally transforming our understanding of information systems (IS), encompassing their development, coordination, use, and the way we interact with them. At our chair, we offer a wide range of research topics in this area, encompassing new digital technologies such as artificial intelligence (AI) and machine learning (ML). We take a human-computer interaction, system design, value creation or an organizational perspective.

    In our seminar, we will examine the design of digital technologies as well as their impact on individuals and organizations. In doing so, we link the offered topics to our ongoing research, which has been and is currently being published at leading international outlets.

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

    Interested in learning more about digital innovation? Feel free to have a look at our master course IS 607  and/or see Nambisan, S., Lyytinen, K. & Yoo, Y. Handbook of Digital Innovation, (2020), doi:10.4337/9781788119986. 

    Objectives of the Seminar

    In this seminar, you will not only acquire the ability to identify, classify, and evaluate existing research. You will learn how to develop your own research agenda as well as to present and discuss it with the participants of the seminar. You will be taught different techniques of scientific work and writing so that you will be prepared in the best possible way for the conception and writing of your Master's thesis. We offer five different seminar topic areas, which hopefully raise your interest.

Fall/Winter 2021

  • Registration

    You may register via our online registration tool only (accessible inside the university network or per VPN). During the registration period, you can select the seminar in the registration form (under 'Application Details' -> 'Purpose').

    Registration periodsee schedule


    • Short informal letter of motivation (maximum 1 page):
      Please select a topic and give reasons for your choice, i.e., what are you particularly interested in and what do you want to learn. Please also mention two alternative topics.
    • Provide your CV and your transcript of records.

     We will not consider registrations via e-mail or incomplete data in the registration tool.

  • Topics

    Students are asked to write a short formless letter of motivation (maximum 1 page) to choose a topic and briefly justify their choice. This letter of motivation will be considered as the key reference for seminar entry, in addition to the CV and the transcript of records.

    A) Human-Computer Interaction
    Human- Computer Interaction, Avatars Adaptable avatars in online games are a player’s virtual representation of their selves in a virtual space. Not only do they enable players to interact with the game, but they also play a central role in computer-mediated communication between players. To represent and express themselves, players often customize their avatars, such as their gender, face, hair, body, apparel accessories, or game-relevant items. In their customizations, players can also optimize their avatars to represent an “ideal” version of themselves. In this, avatars can act as a creative platform for identity construction.
    While this identity construction may be beneficial, by boosting self-esteem in the virtual environment, it might also cause conflicts between a player’s online and offline identity. This conflict can cause negative effects in the offline world, including gaming addiction, loss of self-esteem, or loss of physical relationships, amongst others.
    For this seminar paper, the student should conduct a structured literature review to provide an overview of the unintended social and psychological consequences of avatar use in online gaming. In addition, the student is expected to outline which theoretical perspectives have been used by previous studies to understand the relationship between avatar use and the identified negative consequences.
    Rosa Holtzwart
    B) Exploring Technological Advances of Artificial Intelligence
    Machine Learning in Auctions Auctions describe the concept of selling one or multiple goods to multiple bidders, who try to acquire it to the lowest possible price, outbidding each other. Thus, auctions, for example, concern public tenders, private sales (for example via eBay) or ad auctions (for example Google Ads). Auction theory, a branch of game theory, deals with the question of how auctions can be structured and how utility maximizing auctions can be defined.
    In order to approach optimal pricing strategies and optimal auction design and to better understand complex auctions, as well as their equilibria, Machine Learning methods have finally been applied in the subject area of auction theory in the last few years and already show first, promising successes. Nevertheless, the use of these methods in the field of auctions is still largely unexplored and many questions are still open.
    For this seminar paper, the student is expected conduct a structured literature review to provide an overview of the use of Machine Learning in auction design and bidding strategies. The goal is to analyze the state of Machine Learning applications and concepts considering auctions and, in addition to that, derive further research questions and topics that arise from the review.
    Prof. Dr. Armin Heinzl
    Computational Creativity; UI/UX Design Creativity is one of the most essential organizational skills as it is key for product innovation. Increasingly, machines replace or supplement classical ‘offline’ approaches regarding creative processes. Creativity supported or conducted by machines is studied in the field of computational creativity (CC). An outcome of a creative process can be considered creative when it is useful and novel. In this seminar, the aspect of ‘usefulness’ is regarded, which is usually associated with the ‘utility’ and ‘functionality’ of a product. However, especially in design, we assume that usefulness likewise arises from the ‘appeal’ and ‘aesthetics’ of a product. Based on a structured literature review, the goal of this seminar paper is to explore extant research that investigates the connection between these two aspects, i.e., ‘appeal’ and ‘utility’. Particularly, as context, the organizational task of designing user interfaces (UI) and user experience (UX) is considered. This may encompass the design of layouts, fonts, illustrations, animations, interaction mechanisms, interaction paths, etc. Thus, eventually, the seminar paper should suggest avenues for future research to include and enhance the knowledge on the connection between ‘utility’ and ‘appeal’ to be usable in computational creative systems for designing UIs/UX. Deborah Mateja
    Requirements Elicitation in Information Systems A target-oriented Requirements Engineering (RE), the process of deriving the necessary requirements for a piece of software, is one of the key success factors of Information Systems Development (ISD). Information systems (IS) research has been addressing the topic from a behavioral and empirical as well as from a design science perspective.
    A tremendous evolutionary step in RE is called data-driven RE. Data-driven RE enriches the methods of collecting and analyzing user input in traditional RE with the automated and continuous analysis of novel feedback sources as well as with the analysis of context-aware usage data to identify, prioritize, document, and manage requirements for a software product.
    For this seminar thesis, the student should review current IS and software engineering literature to gain an overview on the main ideas for the second part of data-driven RE, namely leveraging usage-data for RE. The discussion of the findings should compare the identified approaches from a self-derived framework or taxonomy.
    Philipp Hoffmann
    Hybrid AI, Explainable AI The “black box nature” and lack of reasoning of Machine and Deep Learning applications are critical in high-stakes domains such as healthcare. Therefore, it has accelerated scientific interest in the development of eXplainable AI (XAI) to provide explanations for the cause of its decisions. In a recent trend, research identified synergies in combining several AI techniques in order to get the best from each method. Enriching data-driven machine learning with knowledge, such as rules represented in symbolic form, brings a deeper level of understanding to intelligent systems and enhances explainability. Therefore, this seminar paper assesses the current state of hybrid AI to provide an overview of the forms of hybrid AI systems that exist and how recent works contribute to explainability. Luis Oberste
    C) Value Creation in Platform Ecosystems
    Platform Ecosystems, Platform Governance, Soft Governance Mechanisms In a platform business model, platform owners (e.g., Apple or Google) allow independent third-parties, so-called complementors, to participate in the development and commercialization of their technology. Apple, for example, opened its iOS mobile operating system to independent “app” developers in 2008 which has since then grown to a platform with more than two million complementary apps. The success of platform ecosystems is highly dependent on innovative and high-quality complements of third-party developers. Yet, incentivizing complementary innovation is a complex endeavor for platform owners. Platform governance remains one of their major challenges. Up until now, academic literature has focused on hard governance mechanisms. Hard governance establishes output control and assures app quality by limiting the access of third-party developers and their app submissions to the platform market based on rules and guidelines (e.g. app review process). In contrast, so-called soft governance mechanisms aim to increase app quality and direct innovation by highlighting and rewarding desirable behavior of outstanding complementors (e.g., selective app endorsement, developer awards). Thereby, platform owners create role models that are likely to be followed by other complementors.
    In this seminar thesis, students are expected to review academic literature on platform governance to deepen our understanding of ‘soft’ governance mechanisms that shape complementary innovation in platform ecosystems.
    What is a platform ecosystem? Start reading here:
    Nele Lüker
    Platform Ecosystems, Platform Evolution, Platform Governance Digital platforms have become omnipresent both in personal and professional contexts. Prominent examples include Apple iOS, Google Android, Salesforce or Siemens Mindsphere. In contrast to traditional seller-buyer relationships, value creation in platforms is organized in loosely coupled inter-firm networks, so-called platform ecosystems. In this way, a platform as “stable element” promotes variety in its periphery, i.e., complementary innovation (e.g., mobile app development), by potentially unlimited external parties (e.g., app developers). In any ecosystem, evolution is a central process yielding continuous change and adaptation. Despite the notion of platforms as “stable core” (Baldwin and Woodard 2009; Jacobides et al. 2018), platforms continuously evolve over time. For example, platform owners release updates to the platform core, addressing maintenance or feature issues and frequently engage in acquisitions thereby integrating technology of external companies into the platform. In this seminar project, students are expected to review extant literature that deals with the evolution of platforms to identify mechanisms through which platforms evolve and to discuss implications on ecosystem participants and platform governance.

    • Baldwin, C. Y., and Woodard, C. J. 2009. “The Architecture of Platforms: A Unified View,” in Platforms, Markets and Innovation, A. Gawer (ed.), Cheltenham, UK and Northampton, US: Edward Elgar Publishing Limited, p. 1.
    • Jacobides, M. G., Cennamo, C., and Gawer, A. 2018. “Towards a Theory of Ecosystems,” Strategic Management Journal, pp. 1–22.
    André Halckenhäußer
    B2B2P Platform Ecosystems, Scaling Mechanisms, Healthcare New technologies and the increasing amount of data are transforming traditional businesses. Today, the most valuable companies are built on digital platforms that bring together two or more market actors and grow through network effects (1). Especially in the healthcare sector, organizations recently start to shift from traditional pipeline business models to platform business models by establishing new digital platforms (2). In comparison to the well-known B2C platform business models (i.e. Uber, AirBnB), healthcare digital platforms recently focus on B2B (i.e. Siemens Teamplay), or so called business-to-business-to-patient (B2B2P) platform business models (i.e. Teladoc Health). Research on scaling digital platforms has so far concentrated on B2C digital platform ecosystems, specifically with focus on various influencing factors of network effects. Research on their B2B and B2B2P counterparts however, is still sparse. Particularly, in the context of the healthcare industry, research still lacks on insightful studies. To work on the seminar paper, students can select between two main research goals:
    (a) The student is expected to conduct a structured web search in order to identify B2B2P digital platform ecosystems. Furthermore, the student should derive the key characteristics of B2B2P digital platform ecosystems and elaborate the similarities and differences of these emerging business model.
    (b) The student is expected to conduct a structured literature review in order to elaborate key scaling mechanisms of healthcare digital platform ecosystems.

    1. Cusumano, M. A., Yoffie, D. B. & Gawer, A. The Future of Platforms. MIT Sloan Management Review (2020).
    2. Alstyne, M. W. V., Parker, G. G. & Choudary, and S. P. Piplelines, Platforms and the New Rules of Strategy. Harvard Business Review (2016).
    Timo Himmelsbach
  • Course Outline & Schedule

    Event Deadline Deliverables
    Registration period 15.7. - 6.9.2021 (11.59 pm) – Register via online registration tool
    – Include your CV, transcript of records, and your letter of motivation
    Notification of acceptance/rejection 8.9.2021 (noon)  
    Deadline for drop out 9.9.2021 (noon)  
    Kick-off meeting 13.9.2021,
    8.30 am – 9.30 am
    Room: 001 (L 9) + ZOOM
    – Participate in the introductory kick-off session
    – Contact and meet your advisor
    Milestone 1 27.9.2021 Submit first draft to your advisor
    – Detailed outline
    – List of literature
    Milestone 2 25.10.2021 Submit second draft to your advisor
    – Table of contents
    – Introduction: fully formulated
    – Methodology: fully formulated
    – Results: structured draft
    – Discussion: structured draft
    Seminar paper submission 8.11.2021 (noon) – Submit two printouts of the seminar paper to the secretary
    – Send a digital version of the seminar paper (in PDF format) via e-mail to Timo Himmelsbach (himmelsbach and your advisor

    Modification due to Corona: Please send your seminar work until 12 noon in PDF-Format to Timo Himmelsbach (himmelsbach and add as well the chairs mail address (wifo1 on CC. Please also submit as soon as possible after the submission deadline two printouts to the secretary.
    Slide deck submission 22.11.2021 (noon) – Optional: Request feedback on presentation in advance from your supervisor
    – Send your presentation in PDF format via e-mail to Timo Himmelsbach (himmelsbach
    Final presentation 26.11.2021 – Attend and actively participate in the discussion on the seminar day
    – Present and discuss your seminar paper in the joint workshop
    – Discuss and provide feedback for at least one of the other students’ seminar papers
  • Literature

    •  Webster, J., & Watson, R. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Q., 26.
    • Leidner, Dorothy E. (2018) “Review and Theory Symbiosis: An Introspective Retrospective,” Journal of the Association for Information Systems: Vol. 19 : Iss. 6 , Article 1.

    To access the literature you have to be in the VPN of the University of Mannheim.