|Verantwortlicher Dozent||Prof. Dr. Armin Heinzl|
|Infos für Studierende||Infos zu Bachelorarbeiten anderer Studiengänge finden Sie bei den Abschlussarbeiten|
|3 May 2021||Kick-off meeting|
|4 May 2021||Announcement of topic assignment at 12 pm|
|29 June 2021||Deadline for submission of thesis until 12 pm|
Individuals and organizations operate in a world that is increasingly permeated with digital technology. Every day we interact with Information Systems (IS) that make our phones smart, our cars safe, and our lives convenient. Likewise, Information Systems are embedded in the very core of the products, operations, and strategies of many organizations. Ever more, understanding and leveraging Information Systems is key to business success, not only for large and experienced players like SAP and Google, but also for small start-ups. The pervasive nature of digital technology is radically transforming our understanding of Information Systems, encompassing their development, coordination, use, and the way we interact with them. The primary objective of this seminar is to shed light on these issues and enrich our knowledge about how information systems impact organizations and individuals.
|A: mHealth Use and Behavior Change||An increasing number of individuals use mobile health (mHealth), such as Apple Health, Google Fit and other mHealth applications to adopt healthy behaviors and improve health outcomes. However, mHealth use is often limited to few initial interactions and decreases over time. To overcome this, app developers often nudge use by sending push notifications. Because mHealth apps are constantly collecting data on users, their environment, and their behavior (e.g. location, weather, current app use, step count), it is possible to deliver messages that adapt to an individual’s changing status. 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 mHealth use. This thesis will review academic literature to better understand how to make such messages more effective. The thesis 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 mHealth use and subsequent behavior change. In order to do this, this bachelor thesis will draw on academic literature related to information systems and behavioral science.||Monica Fallon|
|B: Governance of Internet-of-Things Platforms||
Platform business models are becoming increasingly relevant, as recent examples of highly successful platform firms (e.g., Apple, Salesforce, SAP) demonstrate. In contrast to traditional supply chains and seller-buyer relationships, value creation in platforms is organized within an ecosystem of loosely-coupled parties. The platform firm's activities shift towards coordinating these highly heterogeneous parties. We refer to the sum of these coordinating activities as platform governance. The recent advent of the Internet-of-Things (IoT) has opened various potentials for the industrial sector. Nevertheless, the market for industrial IoT platforms remains fragmented and lacks platform leadership (so far).|
A bachelor thesis within this topic area is expected to review recent literature on platform governance and, building on an analysis of existing reference architectures of IoT platforms, discuss the relevance and applicability of known governance mechanisms for the industrial IoT platform context.
|C: Value Creation in B2B Platforms and the Role of Data||
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). Besides some already well-known players in the B2C space (i.e. Uber, AirBnB), the rise of new B2B platforms (i.e. Siemens MindSphere) furthermore underlines the undergoing shift from traditional pipeline business models to platform business models (2). Although data as a resource is becoming more and more important for value creation and value capture in such new business models, existing literature remains under-researched. In this bachelor’s thesis, students are expected to review extant literature related to value creation in B2B platforms with a strong focus on the role of data.|
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).
|D: Distributed Cognition theory in Requirements Engineering||
Requirements engineering is still one of the crucial tasks for software development. Following Pohl (2010), it encompasses the elicitation, validation, and documentation of desired properties and necessary constraints of a software, as well as the frequent validation and continuous management of the same. Especially in enterprise software development, features of a new software under development must be derived from the software vendor with the help of experts and knowledge stakeholders from industry during the elicitation phase. Therefore, establishing a shared understanding of user requirements between the client and development groups is fundamental. The theory of Distributed Cognition may help here for studying the organization of cognition in those collaborative group activities.|
The aim of this Bachelor’s thesis should be to understand the research field of Distributed Cognition theory in IS and conduct a structured literature review about the recent research in regards of establishing a shared understanding in requirements engineering in perspective of this theory.
|E: Algorithmic Fairness||With technological developments in artificial intelligence, algorithms strongly influence business and individuals. However, literature suggests that although algorithms are often superior in performance, they can be unfair towards socially disadvantaged groups. Algorithmic fairness has been considered as one major challenge in the development of AI systems. But, from a human-computer-interaction perspective, very little is known how users evaluate the fairness of an algorithm. The aim of the bachelor thesis is to review current research on human-computer interaction to understand how users evaluate algorithmic fairness and which consequences the perceived fairness of the algorithm has on trust towards it.||Ekaterina Jussupow|
|F: Impact of AI on Work Practices and Organizational Performance||
Organizations apply algorithms based on artificial intelligence (e.g., machine learning) across various domains with the goal to create value. Such algorithms support or take over different decisions in the organization, incl. financial planning, fraud detection, preventive maintenance, product development, and many others. Research and practice assume that algorithms contribute to business value by improving decision making, but it is not clear what exactly changes in the organization to achieve this goal.|
As sociotechnical systems, algorithms and human users have to be considered in their dynamic interaction: humans shape algorithms, but also adjust towards them. These interactions change work practices and organizational processes. Currently, very little is known about how AI-based algorithms change existent work practices and how these changes impact organizational performance, but recent studies have started to address this issue (see exemplary literature below).
In your bachelor’s thesis, you will conduct a literature review on the impact of AI-based algorithms on work practices and discuss their effect on performance outcomes. Further specification of the focus will be agreed with your supervisor (e.g., on particular theoretical perspectives).
– Faraj, S., Pachidi, S., & Sayegh, K. (2018). Working and organizing in the age of the learning algorithm. Information and Organization, 28(1), 62-70.
– Grønsund, T., and Aanestad, M. 2020. “Augmenting the algorithm: Emerging human-in-the-loop work configurations,” Journal of Strategic Information Systems (29:2), p. 101614.
– Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366-410.
– Pachidi, S., Berends, H., Faraj, S., & Huysman, M. (2020). Make Way for the Algorithms: Symbolic Actions and Change in a Regime of Knowing. Organization Science.
– Lindebaum, D., Vesa, M., & den Hond, F. (2020). Insights from “the machine stops” to better understand rational assumptions in algorithmic decision making and its implications for organizations. Academy of Management Review, 45(1), 247-263.
|G: Platform Governance and Innovation||
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 that encompasses more than 2 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 bachelor 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: hbr.org/2016/04/
|H: Computational Creativity; UI/||
Creativity is one of the most essential organizational skills as it lies ground to product and content innovation. Increasingly, machines replace or supplement classical ‘offline’ approaches to the creative process. Creativity supported or conducted by machines is studied in the field of computational creativity (CC). One particular organizational task requiring creativity is the design of user interfaces (UI) and user experience (UX). This may encompass the design of layouts, fonts, illustrations, animations, interaction mechanisms, interaction paths, etc. This Bachelor thesis should focus on identifying and evaluating fields of application for the automated creation of creative UI/||Deborah Mateja|
|I: AI in Healthcare||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. However, with manifold XAI developments, integrated into popular AI toolkits, such methods often convey information that does not fully account for complete, satisfying explanations in clinical practice. Instead, explanations are rather summary statistics or may bring information that is already known to doctors. While enriching explanations with contextual and background knowledge seems promising, it is not yet clear whether this leads to more relevant and auxiliary explanations in practice. Therefore, a bachelor thesis should conduct a structured literature review and aim to explore the effect and types of external information, presented to clinical users in XAI implementations, with practical examples.||Luis Oberste|
|J: Anthropomorphic Design of Conversational Agents||
Conversational agents (CA) can interact with users via text (e.g., Whatsapp chatbot) or voice (e.g., Siri, Alexa). With regard to anthropomorphic design text- and voice-based CAs offer different possibilities to increase the perceived human-likeness. For example, text-based CAs can use emoticons to send emotional information, which is not possible for purely voice-based CAs. However, voice-based CAs can use voice pitch to send emotional information. Research has also found that such speech-related cues alone stimulated perceived anthropomorphism. Therefore, it may not be possible to design non-anthropomorphic versions of voice-based CAs. This thesis conducts a structured literature review to identify and cluster anthropomorphic cues for voice-based CAs, similar to existing classifications for text-based CAs (e.g., Seeger et al. 2021*). In addition this thesis assesses the possibility to use these cues to manipulate and control users’ perceived anthropomorphism and related outcomes variables, and to compare these findings to the anthropomorphic design of text-based CAs.|