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Bachelor's Seminar

SM 452 for Bachelor's program (Business Informatics)

General Information

Fall 2024
Lecturer Prof. Dr. Armin Heinzl
Course Format Seminar
Credit Points 5 ECTS (WI after Fall 2013), 4 ECTS (WI before Fall 2013)
Language English
Grading Seminar paper (70%), presentation (20%), discussion (10%)
Exam Date See course information below
Information for Students Registration: Please see information below!
Deborah Mateja, M.Sc.

Deborah Mateja, M.Sc.

Contact person for Bachelor's Seminar

For further information please contact Deborah Mateja.

Course Information

New Frontiers in Digital Transformation

  • Brief Description

    Digital technologies and the ever-growing amounts of data are radically reshaping our daily lives 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. The pervasive nature of digital technology is fundamentally transforming our understanding of information systems (IS), especially regarding their development, coordination, use, and the way we interact with them. At our chair, we offer a wide range of research topics in IS, focusing on new digital technologies such as artificial intelligence (AI) and machine learning (ML). In our research, we take human-computer interaction, system design, value creation or organizational perspectives.

    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 (https://www.bwl.uni-mannheim.de/en/heinzl/teaching/digital-innovation/)  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 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 various different topic areas, which hopefully raise your interest.

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Fall 2024

  • Registration

    You may register via our online registration tool (accessible inside the university network or via VPN). During the registration period, you can select the seminar in the registration form (under ‘Application Details’ à ‘Purpose’)

    Registration period: see schedule

    Requirements:

    • 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 provide two alternative topics.

    • Provide your CV and your transcript of records.

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

  • Topics

    Students are asked to write a short letter of motivation (maximum 1 page) to choose a topic and briefly justify your 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.


    Explainable AI, Counterfactual Reasoning Ensuring transparency and interpretability in artificial intelligence (AI) is crucial as AI systems become increasingly integrated into critical decision-making processes. Explainable AI (XAI) addresses these needs by making AI decisions more understandable to humans. Among XAI techniques, counterfactual explanations are particularly important because they offer clear, actionable insights by illustrating “what if” scenarios. These scenarios show how altering input variables can change the AI's output, making the decision process more transparent.Counterfactual explanations are essential because they align closely with human cognitive processes. Humans naturally engage in counterfactual thinking, considering alternative realities and their possible outcomes to make sense of events and decisions. This cognitive alignment makes counterfactual explanations intuitive and effective for users trying to understand AI decisions. This seminar will explore the intersection of counterfactual XAI and cognitive psychology, examining recent literature on how these explanations can enhance the interpretability of AI models. It will delve into the methods of generating counterfactual explanations, highlight practical applications, particularly in healthcare, and discuss how counterfactual explanations align with human reasoning. The seminar will also lay out future research directions on improving counterfactual explanations to better align with human cognition, paving the way for enhanced explainability of AI. Florian Rüffer
    Team-AI Collaboration, AI Team Members Organizations are beginning to incorporate artificial intelligence (AI) as team members to assist humans in handling complex tasks. The literature in the field of human-AI teaming and team-AI collaboration is currently working towards establishing an understanding of the characteristics of AI team members. However, there is no consensus on the characteristics and capabilities that define AI team members and shape the perception of their team-likeness. This seminar paper aims to contribute to a better understanding of what qualifies an AI system as a team member by synthesizing the literature on team-AI collaboration published since 2022. Desiree Zercher
    Responsible AI; Organizational Outsourcing Relationships Developing AI inhouse raises new organizational and managerial challenges for firms. Often-cited obstacles are the scarcity of AI/ML talent in the market, volatile regulatory environments, and overall, the high complexity of transforming towards an AI-driven company. In this regard, accessing external, readily available AI services offer firms a quick and easy way to AI. For example, the large cloud service providers such as Amazon, IBM, SAP, Google, and Microsoft have started to offer generic AI services (Lins et al., 2021). Currently, there is a lack of understanding of additional governance requirements for sourcing AI externally. Against this background, this seminar paper will delve into the practices organizations apply to responsibly access third-party AI services, exploring the governance mechanisms of ‘Responsible AI’ inter-firm relationships. As a student, you will gain deep insights on managerial challenges of AI in organizations and the make vs. buy decision and related practices that many firms face today. Tobias Maier
    Automation of Avatar Creation The creation of 3D avatars using AI is transforming digital marketing and online interactions. With advanced AI methods, we can generate 3D avatars for various applications, from virtual reality to social media. This seminar thesis will explore the current state of algorithms used for automating avatar generation. In this thesis, the student will conduct a structured literature review to identify and analyze existing AI algorithms for 3D avatar creation. The aim is to understand the capabilities, limitations, and contexts in which these algorithms are applied. The research can cover methods for both the generation of new avatars (e.g. rigs, textures). Additionally, the thesis will examine how these algorithms have been evaluated and validated, focusing on their realism, quality, and adaptability, and whether they were compared with manually created avatars. The thesis should provide insights into the effectiveness of AI in producing engaging and realistic virtual characters. Applicants should have a background in computer science or a related field, with an interest in AI and/ or digital marketing. Experience with programming and AI frameworks is advantageous. Rosa Holtzwart, Deborah Mateja
    Digital Fashion Artefacts The improvements of digital rendering methods have sparked a wave of innovation in the design and development of virtual clothing and accessories. From virtual try-on experiences to personalized digital avatars, these assets offer consumers new ways to engage with fashion in the digital realm. However, as the demand for digital fashion continues to grow, it is crucial to understand the processes and principles underlying its design and development, as well as use and consumption of these digital artefacts. Existing research has highlighted the potential for digital fashion assets to reduce the environmental footprint of traditional fashion production by minimizing the need for physical materials and transportation. Yet, little is known about the specific resources and capabilities required to design digital fashion artefacts effectively. Furthermore, questions remain about the scalability and accessibility of these innovations. This bachelor thesis aims to address this gap by investigating theories and empirical evidence related to the construction and consumption of digital fashion assets. Through a structured literature review, the student will analyse existing research to uncover the processes, principles, and technologies involved in crafting digital fashion artifacts. Simultaneously, the thesis will explore user interactions and utilization patterns, including factors such as engagement, satisfaction, and their influence on real-world fashion consumption behaviors. By synthesizing insights from both realms, the thesis seeks to offer comprehensive understanding for optimising the creation and usage of digital fashion assets, with implications for sustainability, user engagement, and industry advancement. Rosa Holtzwart
    Dehumanization, Generative AI, HCI This seminar paper adopts Haslam's (2006) dual model of dehumanization as a foundational framework, with the goal of constructing a comprehensive literature synthesis on the dehumanization caused by the use of generative AI within the realms of Information Systems (IS) and Human-Computer Interaction (HCI) research. Haslam's model posits that humanness comprises two dimensions: human uniqueness and human nature. Denying uniquely human attributes to others characterizes them as animal-like, while denying human nature represents them as objects. Psychological research validates these dimensions as distinct facets of humanness. The objective of this seminar paper is to develop a literature review encompassing studies on the dehumanization effects within the domains of IS and HCI. Which theories have been applied? What technologies have been researched? What is the role of generative AI in exacerbating or mitigating dehumanization? The resulting body of literature should be scrutinized through the lens of the dual model of dehumanization. Ultimately, the literature review aims to synthesize existing knowledge on the dehumanization in IS and HCI and identify potential research gaps. Dr. Anna-Maria Seeger
    Emotion Regulation, mHealth, App Store Scraping For this seminar thesis students will investigate the landscape of wellbeing apps available on the GooglePlay and Apple App Store. The focus will be on systematically collecting data on these apps and evaluating their features and functionalities based on established emotion regulation (ER) categories from psychological literature. The ER literature and categories will be provided by the supervisor. The student is expected to become familiarized with the theoretical background in order to develop a coding schema according to which each app’s feature and functionalities can be assigned to one of the five ER categories. Based on the developed schema the collected app features will then be grouped to ER categories to deliver an overview of the existing landscape of wellbeing apps for ER. The seminar aims to provide a practical, hands-on research experience that integrates technology with psychological theory. Mechthild Pieper
    Nudges; User Behavior; IS Use An increasing number of individuals use information systems (IS) for explaining, shaping, and changing individuals’ intentions, cognitions, and behavior. Developers often nudge use of these technologies by sending messages to users. Concurrently IS are constantly collecting data on users, their environment, and their behavior (e.g. location, weather, use behavior, contextual behavior, and mood). This data could be leveraged to deliver messages that adapt to an individual’s dynamic state and context over time. However, little is known about what content such messages should contain, under what circumstances messages should be sent, and when the best time is to nudge IS use and behavior. This seminar paper will review academic literature that employs nudges to change individual’s behavior. It will focus on what dynamic states or contexts can be captured with technology to improve the receptivity of nudges. The seminar paper will identify what theoretical perspectives are used, identify research gaps, and provide avenues for future research. The results of the literature review will have implications for how to better design messages to nudge use and subsequent behavior. In order to do this, this seminar paper will draw on academic literature related to information systems and behavioral science. Dr. Monica Fallon
    Human-AI Collaboration The field of AI is evolving rapidly, especially with the recent introduction of large-scaled pretrained AI systems such as ChatGPT. It is not only the underlying technologies that are changing but also the way we interact with such systems. As the field is evolving so rapidly, this seminar thesis targets the synthesis and analysis of the most recent research on human-AI collaboration. In particular, this seminar thesis will investigate high-level, peer-reviewed human-AI collaboration literature that has been published in the research streams of information systems, management, and human-computer interaction since the year 2021. The results of the literature review will have implications for where to target future research on human-AI collaboration. Deborah Mateja
    Human-AI Collaboration This seminar thesis investigates literature on organization search and showcases how it can be applied to study human-AI collaboration (Raisch & Fomina, 2024). The search process is central to a broad variety of organizational behaviors, including the creation of novel strategies, the pursuit of entrepreneurial activities, and the development of new products. This literature review will synthesize studies that apply the theoretical lens of organizational search in computational modeling from the management and information systems research disciplines and beyond. The goal is to synthesize elements of the search literature that can be transferred to the context of human-AI collaboration and derive respective avenues for future research. Deborah Mateja
    Explainable AI, Healthcare Explainable Artificial Intelligence (XAI) techniques enable the generation of explanations that allow clinicians to comprehend the underlying factors influencing AI-driven outcomes and help validate the results. While a variety of XAI methods have been developed, there is a lack of understanding of which methods and in which situations can provide clinicians with an adequate understanding of AI outputs. As clinicians will face challenges in deciding when to rely on the advice and when not to, it has been observed that XAI often alters this ability for the worse. Based on a structured review of information systems, computer science, and medical informatics literature, this seminar paper aims to uncover the theoretical discourses around clinicians’ cognitive capabilities to use XAI assistance. The paper could relate the findings from the medical context to the risks that were commonly observed in XAI, including overreliance, diagnostic efficiency, and the ability to detect errors, to name but a few. Luis Oberste
    Platform ecosystems, platform core, Generative Artificial Intelligence Digital platform business models have evolved into a dominant form of value creation and are the basis of many of the most successful firms. Recent developments regarding Generative Artificial Intelligence have already started to impact digital platform ecosystems. Established platform owners are incorporating Generative AI into their platform cores and potentially change the way how complementors (e.g., developers on iOS) and users interact with and contribute to the ecosystem. For example, in its recent announcement of iOS 18, Apple presented various AI services and features, including a feature to create personalized emojis based on textual inputs. In this seminar project, students are expected to review extant research on platform ecosystems and elaborate on how incorporating Generative AI may influence existing roles like complementors and users. Dr. André Halckenhäußer
  • Course Outline & Schedule

    Event Deadline Deliverables
    Registration period 01.08. – 02.09.2024 (23:59) – Register via online registration tool – Include your CV, transcript of records, and your letter of motivation
    Notification of acceptance/rejection 04.09.2024 (noon)  
    Deadline for drop out 09.09.2024 (noon)  
    Kick-off meeting 11.09.2024, 15:00 pm – 15:45 pm Room: B6, A103 – Participate in the introductory kick-off session – Contact and meet your advisor
    Milestone 1 25.09.2024 Submit first draft to your advisor – Detailed outline – List of literature
    Milestone 2 23.10.2024 Submit second draft to your advisor – Table of contents – Introduction: fully formulated – Methodology: fully formulated – Results: structured draft – Discussion: structured draft
    Seminar paper submission 06.11.2024 (noon) – Send your seminar work until 12:00 (noon) in PDF-format to Deborah Mateja (mateja@uni-mannheim.de) and add the chair’s secretary mail address (wifo1@uni-mannheim.de) on CC – Submit two printouts to the secretary as soon as possible after the submission deadline. – Send a digital version of the seminar paper (in PDF format) via e-mail to your advisor
    Slide deck submission 26.11.2024 (noon) – Optional: Request feedback on presentation in advance from your supervisor – Send your presentation in PDF format via e-mail to Deborah Mateja
    Final presentation Thursday, 25.11.2024 Room: Experience Lab – Attend and actively participate in the discussion on the seminar day – Present and discuss your seminar paper in the joint workshop – Discuss and
  • 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.