Conference Agenda
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Agenda Overview |
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D343: DESIGN RESEARCH METHODS AND COMPLEXITY METRICS
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Mapping design research methods: foundations for a design research quality hub 1Dresden University of Technology, Germany; 2Université Grenoble Alpes, CNRS, Grenoble INP, G-SCOP, France; 3Federal University of Uberlândia, Brazil Design research lacks a unified methodological framework, leaving researchers underexposed to diverse approaches and limiting informed method selection. This paper proposes a multidisciplinary cartography of design research methods, mapping research designs, data collection techniques, associated risks, and required resources. It provides a structured overview to support method selection and planning. This non-exhaustive, high-level cartography serves as a proof of concept to demonstrate feasibility and lay the foundation for a future community-driven Design Research Quality ecosystem. Guidelines for dual impact research methodology: a framework for industry-academia collaboration University of Twente, The Netherlands Industry–academia collaborative research faces a persistent challenge: how to promote effective knowledge transfer while maintaining both scientific rigor and industrial relevance. This paper introduces nine methodological guidelines for a Dual Impact Research Methodology (DIRM). The guidelines include mechanisms such as dual-purpose artifacts, hybrid evaluation criteria, and institutionalized knowledge capture. The paper concludes the guidelines provide a coherent yet adaptable framework for achieving dual impact: advancing theory while delivering actionable industrial value. Toward design for complexity: an integrated framework for iterative co-evolution across complex socio-technical systems 1Cornell University, United States of America; 2University of Texas at Dallas, United States of America; 3University of Michigan, United States of America Traditional design methods fall short for complex socio-technical systems where social and technical elements co-evolve and emergent behaviors resist decomposition. This paper proposes a seven-stage Design for Complexity Framework integrating systems science and design theory. Stages 3–6 form an iterative co-evolution space where modeling, architecture, and stakeholder co-design mutually shape problem and solution development. A healthcare example illustrates how the framework's co-evolutionary approach addresses coordination failures that purely technical or purely participatory methods miss. Measure it to manage it – quantitative review of product family complexity metrics 1Hamburg University of Technology, Germany; 2Odego GmbH, Germany Product variety increases complexity across product, process, and organizational domains, yet existing complexity measures offer limited guidance for design decisions. This study implements established metrics within a framework to enable consistent assessment across domains. The results reveal substantial redundancies among these metrics - with the notable exception of modularity, emphasizing its central role in complexity management. The consolidated measure set provides practitioners with a systematic basis for evaluating design strategies and managing complexity in product families. | ||
