Thesis Top­ics

In the digital age, organizations heavily rely on information technology (IT) systems to store and process sensitive data, making them prime targets for cyberattacks. While extensive research has been conducted on the technical aspects of cybersecurity incidents, there is a growing need to understand the psychological impact on IT employees who play a pivotal role in detecting, mitigating, and recovering from such incidents. This master's thesis aims to investigate the psychological reactions of IT employees when confronted with significant cybersecurity incidents and provide insights that can enhance employee well-being and organizational resilience.

Possible Research Objectives:

1. To explore the emotional and cognitive responses of IT employees during and after significant cybersecurity incidents.
2. To identify the factors that influence the psychological reactions of IT employees to cybersecurity incidents, including the severity of the incident, organizational support, and individual characteristics.
3. To examine the long-term effects of cybersecurity incidents on IT employees, such as post-traumatic stress, job satisfaction, and performance.

Methodology:

1. Literature Review: Conduct an extensive review of the existing literature on cybersecurity incidents, their psychological impact on employees, and relevant psychological theories (e.g., stress theory, coping mechanisms, and resilience).
2. Interviews: Conduct expert interviews with IT employees who have experienced significant cybersecurity incidents. Explore their emotional responses, coping strategies, and perceptions of organizational support.
3. Data Analysis: Analyze interview data using qualitative methods to identify patterns and factors influencing psychological reactions.
4. Longitudinal Study: If possible, follow a subset of IT employees over time to assess the long-term effects of cybersecurity incidents on their psychological well-being.

Expected Contributions:

1. Enhanced Understanding: This research will contribute to a better understanding of the psychological reactions of IT employees to significant cybersecurity incidents, shedding light on the emotional and cognitive aspects of incident response.
2. Organizational Insights: Findings will provide organizations with insights into how to better support IT employees during and after cybersecurity incidents, potentially reducing the long-term negative impact.
3. Academic Contribution: The thesis will contribute to the academic literature on the intersection of cybersecurity and psychology, filling a gap in the current research landscape.

Contact:  Prof. Dr. Arne Buchwald

In the plant and engineering industry, the utilization of data-driven approaches has the potential to revolutionize service delivery. Companies in this sector are increasingly exploring innovative data-driven service models to enhance operational efficiency and customer satisfaction. This master's thesis aims to investigate the prerequisites necessary for the successful implementation of innovative data-driven service models in the plant and engineering industry, considering the perspectives of both service providers and service recipients.

Possible Research Objectives:

1. To identify the key prerequisites for companies in the plant and engineering industry to develop and implement data-driven service models effectively.
2. To examine the expectations and requirements of clients and customers (service recipients) within the industry regarding data-driven services and their perceived value.
3. To analyze the alignment between the prerequisites identified on the service provider side and the expectations of clients and customers, with a focus on potential gaps and areas of convergence.
4. To explore case studies of organizations within the plant and engineering industry that have successfully implemented data-driven service models to understand best practices and lessons learned.

Methodology:

1. Literature Review: Conduct an extensive review of the literature on data-driven service models (e.g., pay-per-x), literature in the plant and engineering industry, innovation, and client/customer expectations in the digital age.
2. Expert Interviews: Conduct expert interviews with clients and customers (service recipients) on their respective perspectives, prerequisites, and expectations regarding data-driven services.
3. Case Studies: Select and analyze case studies of organizations within the plant and engineering industry that have successfully implemented data-driven service models, investigating the strategies they employed and the challenges they overcame.

Expected Contributions:

1. Industry-Specific Insights: This research will provide industry-specific insights into the prerequisites necessary for the successful implementation of data-driven service models in the plant and engineering sector.
2. Alignment Insights: Findings will offer insights into the alignment (or misalignment) between service providers' efforts and the expectations of clients and customers, helping organizations bridge potential gaps and deliver more valuable data-driven services.
3. Practical Guidance: The thesis will provide practical recommendations for companies in the plant and engineering industry aiming to innovate their service models through data-driven approaches, based on empirical data and real-world case studies.

Contact: Prof. Dr. Arne Buchwald

Disruptive companies such as FinTechs, RegTechs, LegalTechs or HealthTechs have set themselves the goal of breaking up the value chains of traditional companies.

• Which companies have succeeded and why?
• What are the critical success factors?
• What are the implications for the further development of these companies?
• Etc.

Contact:  Prof. Dr. Heiko Gewald (opens in a new window)

The Institute regularly carries out a quantitative survey with those responsible for sourcing in the largest German companies. We are interested in what challenges managers see in the topic of sourcing today and in the near future.

Previous studies were each published with great success, e.g.:
Gewald, Heiko and Schäfer, Leonie (2017) Quo vadis outsourcing? A view from practice. Journal of Global Operations and Strategic Sourcing, 10 (1). pp. 2-17. ISSN 2398-5364

The concrete design of the empirical procedure is determined in close consultation with the supervisor.

Contact: Prof. Dr. Heiko Gewald (opens in a new window)

Many companies employ management consultants to manage large and complex projects. The working relationship between counselors and their clients is still largely unexplored. Exciting questions are, for example:

• How does know-how transfer between consultant and customer take place?
• What role does personal "closeness" between consultant and customer (e.g. same degree) play in the project work?
• Which critical success factors (in the relationship between customer and consultant) increase the chances of successful project work?

Contact:  Prof. Dr. Heiko Gewald (opens in a new window)

As organizations increasingly recognize the strategic importance of data, the role of Chief Data Officer (CDO) has gained prominence. However, the responsibilities and success criteria associated with this role can vary widely across industries and organizations. This master's thesis aims to investigate the nature of the Chief Data Officer role and develop a framework for defining success metrics that can effectively measure the impact of CDOs in different organizational contexts.

Possible Research Objectives:

1. To comprehensively analyze the responsibilities and functions of Chief Data Officers across a diverse range of industries and organizations.
2. To identify key performance indicators (KPIs) and success metrics that are relevant and effective in assessing the impact and contributions of CDOs.
3. To explore case studies of organizations with successful CDO implementations, examining the strategies, challenges, and outcomes associated with their data leadership.
4. To develop a flexible framework for assessing the success of Chief Data Officers that can be tailored to the unique needs and goals of different organizations.

Methodology:

1. Literature Review: Conduct an extensive review of the literature on emerging Top Management Team (TMT) roles, on the role of Chief Data Officers, their responsibilities, and existing success metrics.
2. Expert Interviews: Conduct expert interviews with CDOs and senior executives in various industries to gather insights into their roles, responsibilities, and the metrics they use to measure success.
3. Case Studies: Select and analyze case studies of organizations that have successfully implemented the CDO role, examining their strategies, challenges, and the impact on data-driven decision-making and business outcomes.
4. Framework Development: Based on research findings, develop a flexible framework for defining success metrics for Chief Data Officers that considers the unique characteristics of different organizations.

Expected Contributions:

1. Role Clarity: This research will provide clarity on the evolving role of Chief Data Officers, shedding light on their responsibilities and functions in diverse organizational contexts.
2. Success Metrics: Findings will offer insights into effective success metrics and KPIs that can be used to evaluate the impact and contributions of CDOs.
3. Practical Guidance: The thesis will provide practical guidance for organizations seeking to establish or enhance the CDO role within their structures, including recommendations for measuring the success of CDOs in a way that aligns with their specific goals.

Contact: Prof. Dr. Arne Buchwald

The proliferation of no-code and low-code platforms has empowered non-technical employees to develop applications and automate processes without formal IT involvement. Simultaneously, the phenomenon of "Shadow IT," where employees use unauthorized software and applications, poses challenges to IT governance and security. This master's thesis aims to investigate the intricate relationship and dynamics between the adoption of no-code/low-code platforms and the prevalence of Shadow IT within organizations, exploring the potential synergies and conflicts that arise.

Possible Research Objectives:

1. To examine the adoption patterns of no-code/low-code platforms within organizations, including the motivations and challenges associated with their implementation.
2. To analyze the extent and nature of Shadow IT practices, identifying the reasons why employees resort to unauthorized software and applications.
3. To investigate the influence of no-code/low-code platforms on the emergence and evolution of Shadow IT within organizations.
4. To explore strategies and best practices for organizations to harness the potential benefits of no-code/low-code platforms while managing the associated risks of Shadow IT.

Methodology:

1. Literature Review: Conduct a comprehensive review of the literature on no-code/low-code platforms, Shadow IT, and their implications for organizational IT governance.
2. Expert Interviews: Conduct expert interviews with IT professionals, business users, and organizational leaders to gather data on the adoption of no-code/low-code platforms, Shadow IT practices, and the perceived impact on organizational dynamics.
3. Case Studies: Select and analyze case studies of organizations that have experienced the adoption of no-code/low-code platforms and assess how this adoption has influenced Shadow IT dynamics.

Expected Contributions:

1. Insights into Adoption Patterns: This research will provide insights into the motivations and challenges associated with the adoption of no-code/low-code platforms within organizations.
2. Understanding of Shadow IT: Findings will enhance our understanding of Shadow IT practices, shedding light on the reasons why employees resort to unauthorized software.
3. Relationship Dynamics: The thesis will elucidate the complex relationship and dynamics between no-code/low-code adoption and the emergence of Shadow IT.
4. Practical Guidance: The research will offer practical guidance for organizations on how to harness the benefits of no-code/low-code platforms while effectively managing Shadow IT risks.

Contact: Prof. Dr. Arne Buchwald

The introduction of digital technologies into products, e.g. of the manufacturing industry, creates new opportunities for innovation that companies must address in order to remain competitive. At the same time, new opportunities are opening up for corporate customers of these products to run their own business. However, this requires the involvement of customers in the innovation process. Companies that do this well not only achieve a good competitive position, but also strengthen their future viability.

Although this connection is generally recognized, there are some gaps in the research: What role does the involvement of customers play in the short and long-term success of digital innovation? Which methods are effective for involving customers in the development of digital innovation?

Accordingly, in this thesis, conceptual and theoretical foundations from digital innovation research are to be derived from the literature and tested on the basis of an empirical study. The concrete design of the topic takes place in consultation.

Contact:   Prof. Dr. Heinz-Theo Wagner (opens in a new window)

The advancing digitization enables customers to flexibly select from various digital offers and to combine them with each other (the so-called user recombination) so that an individualized product is created. These individualized products are usually made up of offers from different manufacturers and are constantly changed and adapted over their lifetime.

As a result, products are created through both manufacturer innovation and user recombination. A prominent example is the smartphone, the functionality of which is very much determined and regularly adapted by the intended use of the user and the configuration of different apps.

In research, little is known about which factors are decisive for users in the selection and recombination of different digital resources. Just as little is known about how a product changes through user recombination and how it differs between user groups over time. Accordingly, in this thesis, conceptual and theoretical foundations from digital innovation research are to be derived from the literature and tested on the basis of an empirical study. The concrete design of the topic takes place in consultation.

Contact:  Prof. Dr. Heinz-Theo Wagner (opens in a new window)

Digital health technologies (websites, platforms, social networks, apps, wearables, etc.) aim to positively influence the health and well-being of consumers.

However, little is known in research about which factors influence potential eHealth users in their adoption and use of such technologies and what influence actual eHealth use has on the health and well-being of users.

Accordingly, on the basis of theoretical models and empirical studies, new insights into the adoption, use and ideally also the effects of eHealth should be gained.

An empirical study can be carried out both qualitatively (interviews with consumers) and/or quantitatively (questionnaires), with a quantitative study being preferred. The "general" population as well as special groups such as senior citizens or patients can serve as subjects.

The selection of the theoretical bases/models, research method, target group and type of eHealth technology are determined in consultation with the supervisor of the thesis.

Contact: Prof. Dr. Heiko Gewald (opens in a new window)

The online evaluation of doctors (e.g. on Google or jameda) remains an exciting topic. In Germany, this form of doctor assessment still leads a shadowy existence, but is becoming increasingly important.

Examples of interesting questions are:

• How does the doctor's cognitive assessment work in the patient?
• Why do some patients write reviews and others don't?
• Can the number of evaluations be increased through creative measures by doctors?

The specific topic is determined in consultation.

Contact: Prof. Dr. Heiko Gewald (opens in a new window)

Large enterprises are increasingly adopting cloud computing services and Software as a Service (SaaS) applications to enhance agility, scalability, and cost-effectiveness. However, the proliferation of SaaS subscriptions can lead to complex cost management challenges. This master's thesis aims to investigate the adoption of cloud computing in large firms, focusing on the challenges and strategies related to cost management amid the growing number of SaaS subscriptions.

Possible Research Objectives:

1. To identify the challenges and complexities associated with managing the costs of a vast number of SaaS subscriptions in large firms.
2. To investigate the strategies and best practices employed by large enterprises to effectively manage and optimize SaaS-related costs while maximizing value.

Methodology:

1. Literature Review: Conduct an extensive review of the literature on cloud computing adoption, SaaS subscriptions, and clou computing cost management.
2. Expert Interviews: Conduct expert interviews with IT professionals, finance executives, and decision-makers in large enterprises to gather data on cloud adoption, SaaS subscriptions, and cost management practices.
3. Case Studies: Select and analyze case studies of large enterprises that have successfully managed and optimized SaaS-related costs, examining their strategies, tools, and outcomes.

Expected Contributions:

1. Adoption Patterns: This research will provide insights into the patterns and drivers of cloud computing adoption, with a particular emphasis on the proliferation of SaaS subscriptions in large firms.
2. Cost Management Challenges: Findings will elucidate the challenges and complexities associated with managing a vast number of SaaS subscriptions and their associated costs.
3. Best Practices: The thesis will offer valuable best practices and strategies for large enterprises to effectively manage and optimize SaaS-related costs while maximizing value.

Contact: Prof. Dr. Arne Buchwald

In the evolving landscape of IT outsourcing, organizations often consider transitioning from one IT outsourcing vendor to another, seeking to improve service quality, cost efficiency, and alignment with evolving business needs. At the same time, organizations often experience a decrease in the capabilities of their internal IT team to effectively steer the IT outsourcing vendor. This master's thesis aims to investigate the complex challenges associated with multi-transitions in IT outsourcing, where the internal retained IT organization's ability to manage and govern the vendor diminishes with each switch. It explores the economic, organizational, and technical implications of such transitions and seeks to identify strategies for navigating these challenges successfully.

Possible Research Objectives:

1. To analyze the economic factors driving organizations to transition from one IT outsourcing vendor to another and assess the cumulative cost implications of multiple transitions.
2. To investigate the organizational challenges arising from diminishing in-house IT steering capabilities, including the impact on governance, stakeholder alignment, and IT outsourcing vendor management.
3. To examine the technical complexities and risks involved in successive transitions and assess the impact on IT systems, data, and processes.
4. To identify best practices and strategies for organizations facing multi-transitions in IT outsourcing, focusing on mitigating challenges and optimizing vendor relationships in this evolving landscape.

Methodology:

1. Literature Review: Conduct an extensive review of the literature on IT outsourcing transitions, multi-transitions, and technical complexities.
2. Expert Interviews: Conduct expert interviews with IT professionals, decision-makers, and IT outsourcing vendor representatives from organizations that have undergone multiple IT outsourcing transitions.
3. Data Analysis: Analyze interview findings to identify common economic, organizational, and technical challenges faced during multi-transitions in IT outsourcing.
4. Case Studies: Select and analyze case studies of organizations that have successfully managed multi-transitions in IT outsourcing, examining their strategies, best practices, and lessons learned.
5. Framework Development: Develop a practical framework for organizations to assess and plan for multi-transitions in IT outsourcing, including strategies for addressing the identified challenges.

Expected Contributions:

1. Economic Insights: This research will provide insights into the economic drivers and cumulative cost implications of transitioning between IT outsourcing vendors while experiencing diminishing internal steering capabilities.
2. Organizational Challenges: Findings will shed light on the organizational challenges, including governance and stakeholder alignment, associated with successive transitions.
3. Technical Complexities: The thesis will explore the technical complexities and risks involved in multi-transitions and their impact on IT systems, data, and processes.
4. Mitigation Strategies: The research will offer practical strategies and best practices for organizations to navigate multi-transitions in IT outsourcing, optimize vendor relationships, and mitigate associated challenges.

Contact: Prof. Dr. Arne Buchwald

The landscape of cloud computing has evolved significantly in recent years, with many companies initially migrating as much of their IT operations as possible to hyperscale cloud providers. However, a growing trend is emerging, wherein organizations are considering and experimenting with bringing some of their IT functions back in-house while still relying on hyperscalers. This master's thesis aims to investigate the future of hybrid cloud computing, focusing on the shift towards companies complementing hyperscale cloud vendors with in-house IT, and the strategic implications of this shift.

Possible Research Objectives:

1. To analyze the historical context and motivations that led companies to migrate IT to hyperscale cloud providers.
2. To examine the drivers behind the recent trend of bringing some IT functions back in-house and the strategic considerations that influence this decision.
3. To assess the technical challenges and benefits associated with managing a hybrid IT environment that combines hyperscalers and in-house IT infrastructure.
4. To identify the key success factors and best practices for effectively implementing and managing a hybrid cloud strategy in the evolving landscape.

Methodology:

1. Literature Review: Conduct a comprehensive review of the literature on cloud computing.
2. Expert Interviews: Conduct expert interviews with IT professionals and decision-makers in organizations that have adopted or are considering a hybrid cloud approach. Gather insights into their motivations, challenges, and strategies.
3. Technical Analysis: Assess the technical aspects of managing a hybrid cloud environment, including compatibility, security, and performance considerations.
4. Case Studies: Analyze case studies of organizations that have successfully implemented a hybrid cloud strategy, examining their experiences, lessons learned, and outcomes.
5. Framework Development: Develop a framework of strategies and recommendations for organizations looking to navigate the transition from a hyperscale-dominated environment to a hybrid cloud model effectively.

Expected Contributions:

1. Trend Understanding: This research will provide a comprehensive understanding of the evolving trend towards hybrid cloud computing and the motivations behind it.
2. Strategic Insights: Findings will offer insights into the strategic considerations that influence organizations in bringing some IT functions back in-house while complementing hyperscale providers.
3. Technical Assessment: The thesis will assess the technical challenges and benefits of managing a hybrid IT environment, offering insights into best practices for technical implementation.
4. Practical Guidance: The research will provide practical guidance for organizations aiming to adopt and manage a hybrid cloud strategy in an evolving cloud computing landscape.

Contact: Prof. Dr. Arne Buchwald

In recent years, the world of technology has witnessed a significant transformation as Information Technology (IT) and Operational Technology (OT) have started to converge. This convergence marks a fundamental shift in how organizations manage and utilize their technological infrastructure. To put it simply, IT encompasses the technologies and systems used for data processing, networking, and general computing tasks, while OT includes the specialized technologies that control and monitor physical processes, such as machinery, sensors, and industrial equipment. The convergence of IT and OT refers to the merging of these traditionally distinct domains, creating a unified ecosystem where IT systems and applications interconnect with OT technologies. IT and OT convergence holds promise for various industries, such as manufacturing, energy, healthcare, and transportation, as it allows for more seamless data sharing, increased automation, and better control over complex operational processes. However, this transformative trend also brings challenges and implications for IT management, as it blurs the boundaries between traditional IT responsibilities and those associated with OT systems. This master's thesis aims to investigate the consequences of the IT and OT convergence for IT management, focusing on the changes in roles, responsibilities, and strategies required to effectively navigate this evolving landscape.

Possible Research Objectives:

1. To investigate the specific consequences of IT and OT convergence on IT management practices, including changes in roles, responsibilities, and skillsets.
2. To assess the impact of IT and OT convergence on IT governance, cybersecurity, and risk management strategies.
3. To identify best practices and strategies for organizations to adapt their IT management frameworks to the demands of a converged IT and OT environment.

Methodology:

1. Literature Review: Conduct a comprehensive review of the literature on IT and OT convergence, the drivers behind the trend, and the implications for IT management.
2. Expert Interviews: Conduct expert interviews with IT professionals, decision-makers, and experts in organizations that have attempted to integrate their IT and OT.
3. Data Analysis: Analyze interview data to identify common consequences and challenges in IT management practices.
4. Framework Development: Develop a practical framework of strategies and recommendations for organizations to adapt their IT management to the demands of a converged environment.

Expected Contributions:

1. Convergence Understanding: This research will provide a comprehensive understanding of the motivations and drivers behind IT and OT convergence and its implications for organizations.
2. IT Management Consequences: Findings will offer insights into the specific consequences of IT and OT convergence on IT management practices, including changes in roles, responsibilities, and skillsets.
3. Governance and Security Impact: The thesis will assess the impact of IT and OT convergence on IT governance, cybersecurity, and risk management, highlighting strategies to mitigate risks.
4. Practical Guidance: The research will provide practical recommendations and best practices for organizations to adapt their IT management frameworks to effectively manage the demands of a converged IT and OT environment.

Contact: Prof. Dr. Arne Buchwald

Due to demographic change, aging people are increasingly becoming the focus of society and the economy: increasing health risks, increasing social isolation, declining self-determination. Increasing digitalization is creating completely new opportunities – for example through social platforms, IT wearables and mobile applications – to achieve general well-being, social inclusion, active health care and thus a longer, self-determined life for the aging population.

However, a prerequisite for the development of this potential is that people or seniors make use of these technologies - and the actual use of these technologies by seniors often takes place only to a small extent. Older people tend to say "I'm too old for computers" - they associate their age with technology use. However, it has also been shown that people often do not "feel as old" as they actually are: subjective age and chronological age are not always consistent.

Little is known in research about the influence of this subjective assessment of one's own age on IT acceptance and use. Accordingly, in this thesis, conceptual and theoretical foundations from "aging research" are to be derived from the literature and tested on the basis of an empirical study in the context of IT acceptance. The specific design of the topic takes place in consultation.

Contact: Prof. Dr. Heiko Gewald (opens in a new window)

Due to demographic change, aging people are increasingly becoming the focus of society and the economy: increasing health risks, increasing social isolation, declining self-determination. Increasing digitization creates a problem area that has so far received little attention.

For practically every piece of software, hardware, apps, etc., users have to authenticate themselves, usually by entering a PIN or password. However, the aging society has to contend with two problems: declining memory and declining motor skills. Passwords are easily forgotten, biometric recognition and entering passwords are made more difficult by trembling fingers, for example. If more and more activities are digitized, while at the same time society is getting older, we are faced with a dilemma.

Creative mechanisms are being sought for how users can authenticate themselves securely and unequivocally, taking into account the problems outlined above. In terms of research methods, a wide range of interviews and surveys about controlled experiments and the use of the usability lab at the HNU is available. This topic can therefore also be worked on independently by several students. The concrete design of the topic and the empirical procedure is determined in close consultation with the supervisor.

Contact: Prof. Dr. Heiko Gewald (opens in a new window)

Congestion, noise and air pollution - urban mobility is one of the most challenging issues of the 21st century. More and more people live in cities and metropolitan areas and are dependent on a functioning transport system. In addition to public transport, e-scooter sharing services have been providing another sustainable option as an alternative to the use of private cars in cities for several years.

The thesis will first analyze user behavior in the city centers of Ulm/Neu-Ulm. For this purpose, user data from the largest e-scooter provider (TIER) in the region will be used and analyzed.  Furthermore, this user data will be compared with the route networks of public transport in order to deduce whether e-scooters are used in addition to or instead of public transport.

Within the scope of the final thesis, the following research questions are to be answered:

• What is the current state of research in the (IS) literature on e-scooter use and the impact on public transportation?
• What is the mobility behavior of e-scooter users in the city centers of Ulm/Neu-Ulm?
• How does the use of e-scooters in the city centers of Ulm/Neu-Ulm influence the use of public transport?

The thesis must be written in English. The specific topic is determined in consultation with the student.

Contact: Sina Zimmermann

Traffic jams, noise and air pollution - urban mobility is one of the most challenging issues of the 21st century. More and more people are living in cities and metropolitan areas and are dependent on a functioning transport system. But although the public transport network in German cities is already very well developed and the negative effects of car traffic are well known, many people still do not use sustainable means of transport in everyday life.

This thesis deals with the question of how the use of different technologies such as mobility apps and incentive mechanisms can make public transport in a city more attractive. The work includes a literature analysis of previous experiments with incentive mechanisms in the mobility sector. Furthermore, preliminary studies and initial data collection are to be carried out and evaluated.

The research questions of the work can be summarized as follows:

Which experiments on incentives for sustainable mobility behavior are there in the literature so far?

What can a meaningful experiment design look like? What are the factors to consider when designing and running an experiment?

Contact:  Sina Zimmermann (opens in a new window)

The permanent challenge of marketing consists in recognizing the needs and desires of the customers quickly, individually and precisely and to satisfy them accordingly. However, a good half of all customers see further need for action on the part of companies. The analysis of the emotional state offers new possibilities for optimally segmenting customers and thus serving their needs in the best possible way. Possible use cases include, for example, targeted marketing, chatbots that react to emotions or making the queue dynamic. However, there are a few obstacles to overcome on the way to precise emotion extraction. The biggest hurdle, especially in German-speaking countries, is the poor or missing data basis. First, it is a relatively new field of research. On the other hand, the intonation of emotions varies across cultures and languages, which means that an analysis based on a non-German dataset does not lead to satisfactory results. Before random data is collected, many interesting questions arise: How do (potential) customers feel about the extraction of their emotions by AI for marketing purposes? In which environment (B2C/B2B) are young adults (customers) particularly willing to have their emotions analyzed? Which channels (voice, facial expressions, text) are best suited for emotion extraction? How can such an analysis be carried out in compliance with data protection? These and many other topics can be addressed in the course of a thesis.

The exact design of the topic and the procedure is determined in close consultation with the supervisor.

Contact:  Fabian Thaler (opens in a new window)

Language-based systems are becoming increasingly important. Companies like Google and Amazon invest large sums in the propagation of their respective systems. Little is known about the mechanisms that promote or prevent the use of such systems. Data protection is probably a big issue, especially in Germany. But maybe also a missing benefit? Or is the application considered too difficult? Many question marks accompany this question. The observation of young and old people is also of great interest.

Are there systematic differences here? The institute would like to research this question further and has purchased a set of Amazon Alexa devices for this purpose, which can be used in an empirical study. We are happy to assign the work as a tandem to several students who share a jointly developed theoretical core and investigate different groups of (potential) users. The exact design of the topic and the empirical procedure is determined in close consultation with the supervisor.

Contact: Maximilian Haug (opens in a new window)

Alzheimer's disease (AD) is the most common form of dementia. Due to the increasing average life expectancy, especially in developed societies, the number of those affected is constantly increasing. Since AD ​​is defined by a gradual disappearance of memory and other cognitive functions, including language, at an early stage, it is obvious that the latter should be the focus of attention. Machine learning methods in particular have proven to be very encouraging.

However, there is a lack of research on mobile applications related to the diagnostic procedure. The aim of this thesis is to develop a conceptual framework that is suitable for use in a mobile application that supports the diagnostic process by recognizing pathological speech patterns with the help of machine learning methods. The exact design of the topic and the procedure is determined in close consultation with the supervisor.

Contact:  Fabian Thaler (opens in a new window)

Classification of the different forms of collaboration and exchange of views on health in social media. Sample questions:

• Why do people interact with strangers in these topics?
• What is the influence of professional moderation?
• Classification of users and forms of interaction

The specific topic is determined in consultation.

Contact:  Prof. Dr. Heiko Gewald (opens in a new window)

Misinformation has emerged as one of the biggest societal problems on social media. So-called "fake news" is shared daily by millions of users on Facebook, Twitter or Instagram. Misinformation has always been a problem in societies. Social media, however, offers mechanisms that favor the spread of those. Furthermore, fact checkers are increasingly influencing the social media network The thesis deals with the possibility for users of social media to use the internet to verify information.

The aim is to examine whether users actively verify information when they are given the opportunity to do so. For example, hyperlinks should be offered as a possibility for verification in order to find out how intensively users deal with information. Furthermore, it should be found out under which circumstances users even consider verifying information. The research questions of the work can be summarized as follows:

• Under what circumstances do users consider verifying information?
• How high or low are the barriers users are willing to cross to verify information?
• What influence do individual differences have in the use of verification strategies?

The specific topic is determined in consultation.

Contact:  Maximilian Haug (opens in a new window)