The WISE team presented and discussed several research papers at DESRIST 24. The DESRIST 2024 conference, with the theme "Design Science Research for a Resilient Future," focused on how the development of knowledge and innovative digital technology can foster skills and capabilities for a resilient future and took place from June 03 to 05, 2024. Matthias Söllner was one of the three editors of the conference proceedings, alongside Munir Mandviwalla, and Tuure Tuunanen.

The following three papers were presented:

Eva Zahn and Ernestine Dickhaut - Theory-Driven Design of a Negotiation Canvas for Reaching Win-Win Agreements (June 3, Springer, pp. 123-138) (Nominated for the Best Paper Award) 
In today's interconnected world, negotiation is crucial to manage the complexities of personal and professional life. This research presents a theory-based negotiation canvas aimed at preparing for negotiations and achieving win-win agreements. The canvas considers essential negotiation elements and provides a structured approach to prepare for upcoming negotiations.
link.springer.com/chapter/10.1007/978-3-031-61175-9_9

Eva Zahn and Sofia Schöbel - Let's Chat to Negotiate: Designing a Conversational Agent for Learning Negotiation Skills (June 3, Springer, pp. 229-243) 
This paper designs a conversational agent that acts as a personal tutor and negotiation partner to support learners in developing negotiation skills. The agent provides individualized, action-oriented interactions that make the learning process more interactive and effective. The research provides evaluated design principles and practical guidelines for the creation of negotiation training agents.
link.springer.com/chapter/10.1007/978-3-031-61175-9_16

Sophia Meywirth - Designing a Large Language Model-Based Coaching Intervention for Lifestyle Behavior Change (June 3, Springer, pp. 81-94) 
Adopting and maintaining healthy lifestyle habits, such as regular exercise and a balanced diet, remain challenging despite their benefits. This research proposes an innovative approach to deliver Motivational Interviewing (MI) digitally using large language models (LLMs). The prototype, developed with ChatGPT (GPT-3.5), was evaluated in a qualitative study, resulting in five design principles and thirteen system requirements.

link.springer.com/chapter/10.1007/978-3-031-61175-9_6

The chair team was able to gather some impressions of Swedish culture.