Exploring the landscape of system dynamics archetypes: A systematic review
Systems Research and Behavioral Science, ISSN: 1099-1743
2024
- 9Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures9
- Readers9
Article Description
System dynamic archetypes reflect common problematic behaviours that occur in the real world. The high level of abstraction embodied in these archetypes is both promising and daunting. Identifying relevant archetypes for real-world problems is not a straightforward task. In this work, we aim to provide a comprehensive background for understanding current knowledge on the application of system archetypes. The methodology is based on a systematic literature review. Most of the works contribute with prescriptive models that address problems in specific areas. These models generally tackle complex problems where social, environmental and political issues converge. The unit of analysis encompasses geographical units, organizations and artefacts. The steps followed in the development are described with different level of detail. Stakeholders' participation is typically integrated into the development process. Some reported problems are that archetypes could induce a hypothesis that does not include all relevant factors; some participants may have difficulty in understanding the models; confidence in results, difficulty of having data to configure all the variables; and the cost burden for small enterprises.
Bibliographic Details
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know