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Current research projects
The research focus of the Chair of Management Information Systems lies at the intersection of Human Resources (HR) and Information Systems (IS). The chair serves as a "boundary spanner" between Human Resources and Information Technology, exploring the development of innovative information systems from a technical perspective and their application in Human Resource Management ("Digital HRM") from a managerial standpoint.
HYBRID: Algorithmic and Human Decision-Making
Artificial Intelligence (AI) has become an integral part of most aspects of the digital world. However, it is often overlooked that many people harbor an aversion toward algorithms and AI, posing a significant challenge to the implementation of new AI projects. Therefore the HYBRID project seeks to address this challenge by proposing an innovative approach that combines the best aspects of human and algorithmic decision-making. By integrating a human component, the aim is to reduce aversion and foster acceptance. The project starts by identifying the underlying reasons for algorithm aversion, which will then be empirically tested. Through this study, attitudes toward algorithmic, human, and hybrid decision-making will be examined, specifically in the context of human resource management. Building on these findings, the research will determine which factors contributing to aversion can be empirically validated and whether these biases might also apply to human decision-makers. Ultimately, the project explores the potential of hybrid intelligence to mitigate algorithm aversion and create a more balanced and trusted decision-making framework.
Contact: Ellen Weller, M.Sc.
HR Datacare
In the human resources (HR) domain, where vast amounts of personal data are processed daily, treating this information with care is not only a legal obligation, but also a fundamental aspect of maintaining trust and ethical responsibility. The HR DATACARE project addresses this challenge by balancing the utility of personal data for value creation with the imperative to protect individual privacy. Standing for "Data Authorization Through Automation and Consent, Adhering to Regulations and Ethics," Datacare embodies a proactive and protective approach to responsible data handling. This innovative software system empowers data subjects to control the use of their personal information by automating consent management through a standardized and transparent procedure. Inspired by the concept of personal data stores, Datacare ensures that consent and data processing are managed in a way that respects privacy while unlocking the potential value of personal data in a compliant and ethically sound manner.
Contact: León Rheinert, M.Sc.
TransformHRM
The digital transformation of businesses is a prominent topic of discussion, encompassing various corporate areas, including human resource management (HRM). While studies explore themes such as algorithmic decision-making in HR and the use of text mining for analyzing job applications, there is limited empirical knowledge about the current state of digital transformation in HRM. Information on the motivations, goals, and strategies of companies implementing digitization projects is particularly scarce. The TransformHRM research project aims to address these gaps. It investigates the drivers behind HR digitization, the strategies companies adopt, the different forms this transformation takes, and its anticipated or unexpected effects. The project seeks to establish a typology of digital HR practices and analyze their triggers, implementation methods, and outcomes. Data collection involves qualitative interviews with HR digitization leaders in selected companies. Participants will gain insights into their digital HR practices and comparative benchmarks from the study results.
VISION-HR
In the era of digital transformation, computer vision (CV) technologies such as object detection, face detection, and optical character recognition are revolutionizing a wide range of industries. In human resources (HR), the potential for these innovations to streamline processes and enhance decision-making remains largely untapped. The Visiual Intelligence Systems Insights and Outcomes for Next-Generation HR (VISION-HR) project addresses this gap by developing a structured typology to classify computer vision applications based on HR tasks. This research aims to identify meaningful ways to leverage CV technologies in HR, assessing their practical utility and alignment with HR's unique challenges and objectives. By analyzing tasks such as interviews, time recording, document processing, and workplace safety monitoring, the project evaluates where CV can add value while ensuring compliance with ethical and legal standards. The typology will serve as a decision-making framework for HR professionals, guiding the adoption of CV technologies that enhance efficiency, automation, and employee experience. By utilizing the potential of CV applications, the project contributes to the evolution of HR into a data-driven and technologically empowered domain, ensuring that automation supports strategic goals.
Contact: Mathias Becker, M.Sc.
Digital-HR
This research project focuses on developing and evaluating a procedural model to digitalize HR management in response to increasing emphasis on digital transformation in business and government. Given the complexity and interconnectedness of fields like strategic and technology management within HR digitalization, practical implementation is often challenging and unstructured. The project aims to systematically support companies by designing a structured model that guides the digital transformation of HR processes. To develop this model, a construction-oriented reference modeling approach will be applied, followed by evaluation through expert surveys to ensure it meets the needs of HR professionals. The research will address three key questions: identifying unique digitalization requirements in HR that traditional approaches cannot meet, examining existing models for applicability, and defining the necessary components and structure of an effective HR digitalization model.
Contact: Lukas Mayer, M.Sc.