System dynamics I: stocks and ﬂows

Nonprofit organizations are typically seen as institutional settings that contribute to finding grassroots solutions to various social problems. But in their own turn, these entities exhibit by design manyfold frailties given by factors such as - precarious funding sustainability, balancing the multiple and, at times, divergent interests of stakeholders, finding a suitable manner to assess managerial performance. The aim of this paper consist in employing a system dynamics approach to modelling the managerial behaviour of nonprofit entities delivering their output through project networks. The system dynamics concepts of causal loops, stocks and flows dependencies are used to depict the complex relationships between projects, funding sources and social outcomes. This approach leads to identifying the systemic threatening to nonprofit sustainability and the dynamic nature of managerial decisions in the context of the interactions between nonprofit organizations, their beneficiaries and funding agencies.

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Visualized System Dynamics models as Information and Planning Tools

10.28945/2693 ◽

2003 ◽

Author(s):

Hanne-Lovise Skartveit ◽

Katherine J. Goodnow ◽

Magnhild Viste

Keyword(s):

System Dynamics ◽

Dynamic Models ◽

System Dynamic ◽

Time System ◽

Management Tools ◽

Client Group ◽

Stocks And Flows ◽

Graphic Complexity ◽

New Research ◽

Dynamics Models

In this paper, we describe the use of visualization of system dynamics models as client information and management tools. System dynamics is a methodology for analyzing and understanding how complex systems change over time. System dynamic models have been developed for a broad range of information to client applications - from resource management problems to the mapping of stocks and flows on factory floors. The problem faced by many users of system dynamic models is their graphic complexity for users not trained in the field. This paper addresses new research into visualization of system dynamics models to make client information more efficient and accessible. This research involves the use of narrative, video and sound embedded in statistical material. This paper also considers one particular client group - that of politicians, planners and civil society in developing countries.

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Teaching Sustainability Through System Dynamics: Exploring Stocks and Flows Embedded in Dynamic Computer Models of an Agricultural Land Management System

Journal of Geoscience Education ◽

10.5408/16-169.1 ◽

2017 ◽

Vol 65 (2) ◽

pp. 146-157 ◽

Cited By ~ 5

Author(s):

Amy Pallant ◽

Hee-Sun Lee

Keyword(s):

System Dynamics ◽

Land Management ◽

Management System ◽

Agricultural Land ◽

Computer Models ◽

Stocks And Flows ◽

Land Management System ◽

Agricultural Land Management

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System Dynamics Approach to TALC Modeling

Sustainability ◽

10.3390/su13094803 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4803

Author(s):

Marko Hell ◽

Lidija Petrić

Keyword(s):

System Dynamics ◽

Feedback Loops ◽

Information Feedback ◽

System Dynamics Model ◽

Dynamics Model ◽

Saturation Point ◽

Tourist Destination ◽

Destination Area ◽

Stocks And Flows ◽

Living Labs

The system dynamics applied in this research on modeling a tourist destination (area) life cycle (TALC) contributes to understanding its behavior and the way that information feedback governs the use of feedback loops, delays and stocks and flows. On this basis, a system dynamic three-staged TALC model is conceptualized, with the number of visitors V as an indicator of the carrying capacities’ dynamics and the flow function V(t) to determine the TALC stages. In the first supply-dominance stage, the model indicated that arrivals are growing until the point of inflexion. After this point, arrivals continue growing (but with diminishing growth rates), indicating the beginning of the demand-dominance stage, ending up with the saturation point, i.e., the maximum number of visitors. The simulated TALC system dynamics model was then applied to five EU destinations (Living Labs) to explain their development along the observed period (2007–2019). The analysis revealed that all observed Living Labs reached the second lifecycle stage, with one entered as early as in 2015 and another in 2018. Lifecycle stage durations may significantly differ across the destinations, as do the policies used either to prevent stagnation or to restructure the offer to become more sustainable and resilient.

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