Contribution of Data Visualization to Decision-Making: A Classification of Data Visualization Research Based on the Characteristics of Decision Problems

Data visualization is a critical tool for supporting decision-making across various domains. However, its effectiveness in addressing various decision-making problems is yet to be investigated.This study systematically reviewed over 300 papers from major visualization journals and conferences and focused on 40 empirical studies. Using Franz and Kramer’s multidimensional decision-making framework, we classified and analyzed the characteristics of decision problems supported by data visualization.The findings revealed three key insights: (1) data visualization predominantly supports organizational and community-level decision-making, whereas applications at individual and family levels remain limited; (2) support has expanded from structured evaluation problems to include semi-structured and recognition-primed decision-making; and (3) challenges persist in addressing unstructured problems and small-scale contexts.These results highlight the evolving role of data visualization in supporting complex and interdependent decision scenarios. Future studies should address gaps in unstructured decision-making and investigate applications in small-scale contexts to enhance the adaptability and impact of visualization tools.