Lund University Publications

Strengthening the quality of qualitative models: a quality framework for future-oriented sustainability research

• Mark

Svensson-Hoglund, Sahra ; Guzzo, Daniel ; Richter, Jessika Luth ^LU and Russell, Jennifer D.

Abstract

Alternative Economic Models (AEMs) are theoretical frameworks that, if implemented, could fundamentally transform economic systems by aligning financial objectives with sustainability goals. Conducting rigorous research on future-oriented AEMs and other complex sustainability systems presents challenges, particularly due to the exploration of largely unverifiable future possibilities. Qualitative models can enhance the completeness, insights, and communications of such research. However, the absence of comprehensive guidelines for ensuring and assessing the quality of future-oriented qualitative models raises concerns about their reliability. The aim of this paper is to improve the quality of qualitative models used in future- and... (More)

Alternative Economic Models (AEMs) are theoretical frameworks that, if implemented, could fundamentally transform economic systems by aligning financial objectives with sustainability goals. Conducting rigorous research on future-oriented AEMs and other complex sustainability systems presents challenges, particularly due to the exploration of largely unverifiable future possibilities. Qualitative models can enhance the completeness, insights, and communications of such research. However, the absence of comprehensive guidelines for ensuring and assessing the quality of future-oriented qualitative models raises concerns about their reliability. The aim of this paper is to improve the quality of qualitative models used in future- and sustainability-focused AEM research by defining three key aspects of model quality: (1) scientific validity; (2) scientific usefulness; and (3) practical usefulness. Drawing on diverse fields, including futures studies, modeling methodologies, and the philosophy of science, we identify 11 Model Quality Considerations (MQCs). These MQCs are tested and refined through two AEM model case applications. We propose a framework for model developers and evaluators to understand their roles and the interactions among MQCs. Our analysis reveals that some MQCs are inherently incompatible, making it impractical to fully satisfy all considerations in a single model. Instead, developing high-quality models requires strategically prioritizing quality aspects, based on the model’s intended purpose. The paper concludes by outlining directions for future research. (Less)