The most common issues in development of causal-loop diagrams and stock-and-flow diagrams

Bureš, Vladimír; Otčenášková, Tereza; Zanker, Marek; Nehéz, Martin

doi:10.1504/ijiei.2020.115722

Cited by 2 publications

(3 citation statements)

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“…In Figure 3, it can be seen that there are 5 variables and their polarity are all positive. Therefore, we can say that the loop is positive, and the system exhibits instability [16]. Negative loop.…”

Section: Analysis 211 Causal Relationshipmentioning

confidence: 99%

“…Positive causal relationship: a causal relationship is positive, when one variable influences the other variable, directly proportional [16]. For example from Figure 1 shown, it is a positive causal relationship, where the student variable influences the graduate variable [17] in a positive way; that is, more students will have more graduates, or fewer students will have fewer graduates, this is called directly proportional, that is, if one increases the other increases or if one decreases the other also decreases [18].…”

Section: Analysis 211 Causal Relationshipmentioning

confidence: 99%

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Simulation with system dynamics on university student research

Nuñez

Delgado

2022

IJEECS

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Currently, student research at the university under study is carried out from the first semesters until the student graduates, but it is necessary to make adjustments to its guidelines that include student research within a teaching-learning process. The objective of the research is to propose a model of student research, using causal diagrams and forrester diagram; then carry out a simulation of the projection from 2021 to 2026 with the variables, students, quality teachers in the research, completed work for publication in journal or conference; and thus index in Scopus or Web of Science. Besides, in the methodological part, the systems dynamics method was applied, based on the systemic approach. The research work is predictive, which was carried out with the Vensim software, obtaining as a result of the simulation, an increase in the production of complete Works by the students; where in 2026 around 300 articles will be published by the students. In addition, there will be about 12 full-time quality research professors and approximately 6,000 students in 2026. The conclusion reached in the research is that the model helps the authorities make decisions appropriately according to the forecasts made in the different scenarios made with the Vensim software.

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Section: Analysis 211 Causal Relationshipmentioning

confidence: 99%

Section: Analysis 211 Causal Relationshipmentioning

confidence: 99%

Simulation with system dynamics on university student research

Nuñez

Delgado

2022

IJEECS

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“…A common SDM technique is a stock-and-flow diagram (SFD), which simulates accumulations and changes within the system through a set of integral equations. SFD models require numerical descriptions of system performance over time, which are not often available when considering novel policies and the dynamics of human behavior (Bureš et al, 2020).…”

Section: A Holistic Systems-thinking Paradigmmentioning

confidence: 99%

Systems-thinking for environmental policy coherence: Stakeholder knowledge, fuzzy logic, and causal reasoning

Castro¹

2022

Preprint

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Nature-based solutions (NBSs) are often managed according to hydro-environmental characteristics that disregard the complex interactions between decision-makers, society, and the environment. Numerous barriers to NBS adoption have been identified as stemming from human behavior (e.g., community buy-in, political will, culture), yet we lack an understanding of how such factors interrelate to inform policy design. The identification of synergies and trade-offs among diverse management strategies is necessary to generate optimal results from limited institutional resources. System dynamics modeling (SDM) has been used within the environmental community to aid decision-making by bringing together diverse stakeholders and defining their shared understanding of complex behavior. While these approaches have enhanced collaboration efforts and have increased awareness of complexity, SDM models often result in numerous feedback loops that are difficult to disentangle without further, data-intensive modeling. When investigating the complexities of human decision-making, we often lack robust empirical datasets for SDM quantification. An alternative to SDM is fuzzy cognitive mapping (FCM), which combines the strengths of stakeholder knowledge with network theory to produce semi-quantitative scenarios of system change. However, sole reliance upon computer-simulated outputs may obscure our understanding of the underlying system behavior. Therefore, the aim of this study is to assess the applicability and strength of combining SDM and FCM to both identify areas of policy coherence from stakeholder engagement and also to explain the emergence of synergies and trade-offs according to causal loop logic. This framework is demonstrated through a case study of NBS policy-making and socio-institutional feedbacks in Houston, Texas, USA.

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The most common issues in development of causal-loop diagrams and stock-and-flow diagrams

Cited by 2 publications

References 0 publications

Simulation with system dynamics on university student research

Simulation with system dynamics on university student research

Systems-thinking for environmental policy coherence: Stakeholder knowledge, fuzzy logic, and causal reasoning

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