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Abstract Qualitative nonsimulated models (causal loop diagrams, stock‐flow diagrams, or hybrids of both) have been used since within a decade after the inception of system dynamics (SD). In this article, we assert that the well‐known weaknesses of nonsimulated models need to be balanced against the contexts, purposes, and strengths that nonsimulated models provide. We propose a framework consisting of a set of best practices for model reporting and documentation that would improve the quality, consistency, and transparency of nonsimulated models. Several high‐quality examples are described and referenced in the framework to illustrate support of each criterion. The framework's purpose is help improve the transparency around the creation and evaluation of nonsimulated models, thereby enhancing their confidence and legitimate use in SD practice. Ultimately, high‐quality nonsimulated models can offer broader access to the powerful body of SD knowledge to audiences likely never to have access to formal SD simulation models. © 2023 System Dynamics Society. 

Systems involving agriculture and natural resources (AGNR) management and representing integrations of biologic, geologic, socio-economic, and climatic characteristics are incredibly complex. AGNR managers purport using a systems-oriented mental model while many observed management and policy strategies remain linear or symptom-driven. To improve AGNR professionals’ systems thinking abilities, two programs, the King Ranch® Institute for Ranch Management at Texas A&M University-Kingsville (KRIRM) and the Honors College at South Dakota State University (SDSUHC), implemented the famous Production Distribution Simulation Game (a.k.a. the Beer Game) into their programs beginning in 2003 and 2011. A Beer Game database consisting of 10 years of trials or over 270 individual players was compared to seminal work in the literature as well as to one another. We found that AGNR managers and students performed worse than players in a seminal Beer Game study. More interestingly, we found that younger players adapted more readily to inventory surpluses by reducing the order rates and effective inventories significantly when compared to older players (p < 0.10 for retailer and distributors, and p < 0.05 for wholesales and factories). We substantiated our results to those in more recent studies of age-related decision-making and in the context of common learning disabilities. Lastly, we discuss some implications of such decision-making on 21st century AGNR problems and encourage AGNR disciplines to better integrate system dynamics-based education and collaboration in order to better prepare for such complex issues.