This book constitutes the proceedings of the 19th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2024, which was held in Trollhättan, Sweden, during June 3–5, 2024.

The 30 full papers presented in this book were carefully reviewed and selected from 69 submissions. The papers are divided into the following topical sections: DSR for a resilient world (theme track); general track; DSR methods and education; DSR in practice; and emerging topics in DSR.

This paper addresses the design of software for web-based psychosocial care – an increasing and highly relevant societal issue. The paper explores two primary research questions: 1) What design principles should guide the creation of web-based software for online psychological support, and 2) How can design science research facilitate the development and assessment of innovative eHealth solutions? Our research – a tailored DSR approach – was conducted over a 10+ year period within the multi-disciplinary research programme U-CARE. As information systems researchers, we worked as researchers and developers, in tight collaboration with psychologists, economists, medical doctors, nurses, and other key stakeholders. Through this process, we continually reflected and abstracted our experiences into design principles and DSR methodology. In response to the first research question, we introduce a set of design principles for web-based psychosocial support, shaped by the overarching LAME DSR approach. These principles include malleability for adaptability and sustainability, privacy and accountability in online environments, and a focus on stakeholder-specific functionalities like therapist dashboards and smooth authentication processes. In response to the second research question, we present the LAME DSR approach and an informed argument concerning its role in the establishment of a strategic, high-impact research environment. © 2024 by the Association for Information Systems.

In several design science research (DSR) frameworks and methods, the need for generalising problemsand solutions has been emphasised. For example, various DSR studies present generalised designprinciples as nascent theories. Due to the creative and contextual nature of DSR, several scholars reportthat generalisation can be challenging. The challenge is particularly valid for single qualitative studiesbecause the design of an artefact always reflects the circumstances in the context where it is to be used.Therefore, the purpose of this study is to present guidelines regarding generalisation. The suggestedguidelines are: strategically plan the generalisation process, validate the generalised knowledge toaugment the reusability and find an appropriate generalisation level. The formulation of the guidelinesis based on the analyses of three DSR projects and insights from previous knowledge. Our knowledgecontribution consists of prescriptive knowledge (guidelines) as a complement to existing explanativeand descriptive knowledge.

The problem we address in this paper is that the potential impact of Large Language Models (LLMs) on the research practice in information systems is not well understood. The focus has been on how LLMs could support literature review processes. Therefore, this paper aims to advance knowledge on how Large Language Models (LLMs) could support knowledge exploration through literature reviews. The knowledge contribution consists of meta-requirements that inform the design of LLM-based tools assisting knowledge exploration. The meta-requirements are theoretically justified by scrutinizing established IS literature review methodologies, reported challenges of LLMs and design process experiences. Furthermore, we introduce an LLM supported literature review process model that maps the relationships between the meta-requirements and specific phases of the process model. This work contributes to the field by providing a foundation for designing transparent, controllable, and resource-efficient tools for knowledge exploration, and supporting the rigor of knowledge exploration in information systems research.