|Lecturer||Prof. Dr. Armin Heinzl|
|Credit Points||5 ECTS (WI after Fall 2013), 4 ECTS (WI before Fall 2013)|
|Grading||Seminar paper (70%), presentation (20%), discussion (10%)|
|Exam Date||See course information below|
|Information for Students||Registration: Please see information below!|
Individuals and organizations operate in a world that is increasingly permeated with digital technology. Every day we interact with digital technology that makes our phones smart, our cars safe, and our lives convenient. Likewise, digital technology is embedded in the very core of the products, operations, and strategies of many organizations. The pervasive nature of digital technology is radically transforming our understanding of information systems (IS), encompassing their development, coordination, use, and the way we interact with them. To understand the impact of digital transformation an interdisciplinary approach is needed.
The primary objective of this seminar is to shed light on these issues and enrich our knowledge about how digital technology impacts individuals and organizations. The knowledge should be will be put into an interdisciplinary context.
In this seminar, students do not only gain a profound understanding of how to structure, classify, and evaluate existing research, but they also learn to effectively communicate their detailed and thorough insights. Students are equipped with diverse techniques of scientific writing and academic rigor. The successful participation in the seminar is an important step towards the master's thesis. The topics of the seminar are subdivided into the three tracks listed below. In case of further questions, please don't hesitate to contact us.
You may register via our online registration tool only (accessible inside the university networkper VPN only) . Only in the below-mentioned registration period you can select the seminar in the registration form.
Registration period: see schedule
Please refer to this page for updated information. We will not consider registrations by e-mailor incomplete data in the registration tool.
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.
|Machine Learning, Multitask Learning||
Recently machine learning, specifically deep learning, has been advancing the state of the art in artificial intelligence to a new level, and humans rely on artificial intelligence techniques more than ever. However, even with such unprecedented advancements, certain indispensable characteristics and areas of algorithmic improvement still have to be explored, such as improving performance of machine learning models through multitask learning.
The aim of this seminar thesis is either to review existing approaches of multitask learning or to identify business application domains of multitask learning.
|Software Requirement Elicitation from Online Sources||
The use of Data Analytics and Machine Learning is becoming more and more important in the software engineering process, especially in the domain of requirement elicitation from customer feedback. As a part of the explicit user feedback (in comparison to implicit user feedback), for example the automated analysis of customer feedback from reviews or support forums is one of the corner stones of this trend.
Research has been conducted especially with data from mobile AppStores. The aim of this seminar thesis should be to conduct a comprehensive literature review of academic literature regarding this topic and to compare it with approaches within other domains (e.g. twitter data, or other sources). For technical interested students an already labeled dataset can be provided to test the different approaches from the literature review.
|Cloud Sourcing, Management||With the rise of on-demand cloud solutions for computing capacity and functionality, a wide abundance of different providers and services have established themselves in the market. In the context of cloud computing offerings, it is often differentiated between Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) on the most abstract level. Not only do offered cloud services differ in their technological nature but also in terms of how their features are described by their providers, due to the lack of a universally accepted ontology. Hence, it seems rather difficult to compare, decide on, and evaluate available cloud services from a managerial and strategic perspective. Extant literature proposes multiple ontologies and cloud stack models, trying to put those cloud services in a common context. This seminar thesis aims on identifying an ontology and a framework, facilitating discussions of cloud sourcing models from a managerial and strategic perspective. Essential characteristics, services models, as well as the advantageousness of controlling different types of cloud services are to be examined to provide a framework for further investigations from a business perspective.||Prof. Dr. Heinzl|
|Advanced Analytics, Business Value of IT (BVIT), Machine Learning||Organizations across the world invest into so-called “Advanced Analytics” in a quest to boost performance, efficiency, and innovation. Advanced Analytics rely on the increasing volumes, variety, and velocity of available data and the rapidly increasing number of available methods and technologies (incl. Machine Learning) to predict future events and prescribe fruitful paths of action. Over the last decades, researchers have developed substantial knowledge about how organizations can create value from their investment in Information Systems. It is not clear yet which of these explanations still apply to Advanced Analytics. The goal of the seminar theses will be to advance our understanding of what differentiates Advanced Analytics from other Information Systems and to synthesize extant scientific knowledge on how organizations can create value from Advanced Analytics.||Pascal Kunz|
|Machine Learning, Artificial. Intelligence, Future of Work, Human-Computer Interaction||Systems based on artificial intelligence disrupt current work practices by performing tasks previously reserved for human experts. In particular, scientific community debates whether AI replaces tasks and jobs or whether AI alters human abilities to make decisions (augmentation). One area in which machine learning applications are applied in practice are judicial decisions such as bail and parole decisions. Depending on your research interest, the aim of the seminar thesis will be either (1) to identify machine learning applications that target judicial decisions and classify them according to whether these applications aim to replace humans or augment human capabilities; or (2) to classify behavioral research on factors that affect whether AI is perceived as favorable or negative in judicial decisions (algorithm aversion/ algorithm preference).||Ekaterina Jussupow|
|Augmenting and Automating Software Development||Increasingly powerful technologies of artificial intelligence (AI) are changing how software is being developed today. Technologies based on AI are increasingly capable of completing development tasks that have formerly been reserved for developers as intelligent human beings. Managers envision a future where application software will refine and extend itself while developers primarily curate the inputs for this self-development (https://www.cio.com/article/3437436/rethinking-software-development-in-the-ai-era.html). This seminar thesis assesses the current state of technology to elaborate how the different tasks of software development are changing with the arrival of increasingly powerful AI technologies from a practical and from an academic angle. It outlines where we stand regarding the target vision of autonomously developing application software and identifies the relevant academic research streams.||Kai Spohrer|
|Platform ecosystems, platform governance, innovation||Firms increasingly adopt platform strategies as they open their core technology and allow for third-party participation in development and commercialization activities. In this way, a platform owner (e.g., Apple, Salesforce) and complementors (i.e. third-party providers of complementary products) jointly co-create value within a loosely coupled inter-firm network, the platform ecosystem. A key challenge for platform owners concerns the coordination of potentially myriads of participating complementors and their innovative contributions. While platform owners may control for the quality of complements on a platform via formal control mechanisms such as input or output control, they can employ a variety of mechanisms to foster innovative activities by complementors. Examples include a platform’s shared values, the provision of supportive resources to support third parties in their development work or the promotion of cooperative relationships within the platform ecosystem. In this seminar project, students are expected to review literature that deals with such mechanisms that go beyond formal control from predefined sources, examine the focus of current research and develop research questions for future research.||André Halckenhäußer|
|Healthcare IT, System design||Nowadays, there are countless possibilities to use smartphone applications and larger information systems in health care. Be it in hospitals, insurance companies, for patients or to monitor their own state of health and to prevent disease. Developing such applications is usually more complex compared to common applications. A seminar paper in this field therefore deals with the literature that is relevant for a particular medical cases that might be supported with such an application. The medical case to be examined will be worked out together with the supervisor. The seminar paper should serve as a basis to actually implement an application in the context of a Bachelor's or Master's thesis. As an alternative there might be the possibility to engage with the analysis of health care data, which accumulates in the numerous IT systems in hospitals.||Okan Aydingül|
|mHealth, effective use, behavior change||An increasing number of individuals use mobile health (mHealth), such as Apple Health, Google Fit, Strava and other mHealth applications to adopt healthy behaviors and improve health outcomes. However, the extent to which use of mHealth impacts the desired outcomes remains inconsistent. This seminar takes the viewpoint of information systems research to investigate whether and how features in mHealth contribute to its effectiveness. More specifically, it explores how social features (e.g. features that facilitate social support and social comparison) can impact outcomes of mHealth use. It thereby focuses on reviewing the literature in order to bring together research related to mHealth, effective use, and behavior change.||Monica Fallon|
|Healthcare IT, Data-Driven Business Models||
New technologies and the increasing amount of data are transforming traditional businesses. As one of the largest sectors of the world’s economy, the healthcare industry needs to adapt their business models in order to keep up with the speed of digitalization. Recently, data-driven business models (DDBMs) have become an important area of research with increasing interest.
The aim of the seminar is to conduct a comprehensive literature review in the field of DDBMs outside and inside the healthcare domain and a comparison of both findings. Furthermore, the current structure of a healthcare system (specialization will be discussed with the supervisor) should be analyzed and mapped to the best-fit DDBMs obtained by prior research. The seminar work should serve as a basis for further research in terms of a Bachelor or Master’s thesis, within the scope of DDBMs in personalized healthcare.
|Registration Period||01.01. - 10.02.2020||
- Register via online registration tool
- Motivate your topic interests with a first draft of your research approach as a letter of motivation
- Include your CV, transcript of records and your letter of motivation
|Notification of acceptance / rejection||13.02.2020 (noon)|
|Deadline for Drop out||14.02.2020 (noon)|
Room O 048,
- Participate in the introductory kick-off session
- Contact and meet your advisor
Submit first draft to your advisor
- Detailed outline
- List of literature
Submit second draft to your advisor
- Table of contents
- Introduction: fully formulated
- Methodology: fully formulated
- Results: fully formulated
- Discussion: structured draft
|Submission of Paper||20.04.2020||
- Submit two printouts of the seminar paper to the secretary (by noon)
- Send a digital version of the seminar paper via e-mail to your advisor (by midnight)
|Presentation submission||08.05.2020, 6 pm||- Send your presentation in PDF format via e-mail to Timo Himmelsbach|
Room SO 418
- Attend the seminar
- Present and discuss your seminar paper in a joint workshop
- Discuss and provide feedback for at least one of the other students’ seminar papers