Design, Development, and Evaluation of Next-Generation Collaboration Technologies
Permanent URI for this collectionhttps://hdl.handle.net/10125/112404
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Item type: Item , Loss of Communication in Remote Scrum Teams: Assistance System to support Reflection of Interactions and Collaboration(2026-01-06) Bissinger, Bärbel; Fellmann, MichaelCommunication and collaboration are crucial success factors for IT projects, especially in agile software development. Due to increased remote work and global teams triggered by the covid-19 pandemic, the way people communicate and collaborate at work changes. To investigate how this impacts agile teams we conducted expert interviews and a literature review. The results are summarized in this paper and demonstrate that there is a loss of communication, collaboration and social interaction, which may potentially result in harmful long-term effects. The consequences include a decline in trust, psychological safety and engagement. Collaboration tools can help to address these novel challenges. We give an overview of existing tools and applications to promote remote collaboration. Furthermore, we present a concept for an assistance system for reflection to improve remote teamwork and individual ways of working in Scrum teams. Nevertheless, tools and technologies have limitations and cannot replace the full spectrum of human face-to-face communication.Item type: Item , Shifting Roles, Evolving Relations: How Users Perceive GenAI(2026-01-06) Müller, Wieland; Behn, Oliver; Wichmann, Johannes; Richter, Alexander; Leyer, MichaelGenerative AI (GenAI) becomes increasingly embedded in our daily routines. While prior work has focused on improving GenAI adoption, little is known about users perceive their relationship with GenAI. We analyze user-reported experiences and identify two distinct user perspectives on GenAI: as a tool and as a partner. Both are shaped by task context, interaction style, and evolving trust. We identify role perception, co-adaptation, and interaction depth as key factors for human-AI collaboration. We outline variables that more adaptive frameworks should include and offer implications for models that flexibly support different roles, foster trust, and align with user expectations across contexts.Item type: Item , Inter-Organizational Collaborative Machine Learning: A Problem Space Exploration(2026-01-06) Rank, Sascha; Thiebes, Scott; Sunyaev, AliOrganizations can benefit substantially from machine learning (ML), but individual organizations often encounter resource constraints (e.g., related to data and computational resources) when using ML. Inter-organizational collaboration represents a promising approach to overcoming such resource constraints. While there are various inter-organizational collaborative ML solutions, we lack a thorough understanding of the corresponding problem space. Based on a structured literature review and qualitative content analysis, we explore the problem space of inter-organizational collaborative ML and uncover six stakeholders, six needs, seven goals, and seven requirements. We also identify four promising future research directions. Our study lays a foundation for developing design knowledge and more targeted solutions for inter-organizational collaborative ML.Item type: Item , Introduction to the Minitrack on Design, Development, and Evaluation of Next-Generation Collaboration Technologies(2026-01-06) Elshan, Edona; Bittner, Eva; Oeste-Reiss, Sarah; Ebel, Philipp Alexander