2026/06/11 by Claudio Lazo, Andrea Kerstens, Angela Greco · 1 voice
Environmental Science · Decision Sciences · Social Sciences · #Sustainability and Climate Change Governance #Complex Systems and Decision Making #Policy Transfer and Learning
paper · doi:10.1093/polsoc/puag017
openalex publication_date 2026/06/11 · openalex created_date 2026/06/25 · openalex updated_date 2026/06/25
Abstract Complex societal problems (CSPs) such as climate change, pandemics, and polarization are persistent, interdependent, and difficult to define, yet they are often reduced to binary labels like “wicked” or “tame” or high-level typologies that oversimplify their underlying complexity. This paper revisits these typologies and proposes a conceptual framework that treats complexity as a layered structure of interacting dimensions rather than discrete categories. Based on an integrative review of 25 typologies from policy science, systems science, and management, the framework organizes problem complexity into two families: system complexity (structure, dynamics, and scope) and stakeholder divergence (values, knowledge, and power). These dimensions can be visualized through multi-level representations such as radar diagrams that reveal a problem’s complexity profile. The paper outlines three modes of application: problem diagnosis to support sensemaking; frame comparison to monitor (temporal) problem perception differences; and method and governance alignment to connect salient complexity dimensions to appropriate governance instruments and systems methods. This approach reduces risks of misclassification, improves analytical precision, and provides a shared language that supports interdisciplinary collaboration. The framework offers a more nuanced characterization of CSPs and introduces concrete tools for governance and design.