Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado, United States of America.
Department of Knowledge Integration, Faculty of Environment, University of Waterloo, Waterloo, Ontario, Canada.
PLoS One. 2023 Jul 31;18(7):e0288928. doi: 10.1371/journal.pone.0288928. eCollection 2023.
Cross-impact balance (CIB) analysis provides a system-theoretical view of scenarios useful for investigating complex socio-economic systems. CIB can synthesize a variety of qualitative or quantitative inputs and return information suggestive of system evolution. Current software tools for CIB are limited to identifying system attractors as well as describing system evolution from only one scenario of initial conditions at a time. Through this study, we enhance CIB by developing and applying a method that considers all possible system evolutions as transitions in a Markov chain. We investigated a simple three-variable system (27 possible scenarios) of the demographic transition and were able to generally replicate the findings of traditional CIB. Through our experiments with four possible approaches to produce CIB Markov chains, we found that information about transition pathways is gained; however, information about system attractors may be lost. Through a comparison of model results to a recent literature review on human demography, we found that low-income countries are more likely to remain stuck in a demographic trap if economic development is not prioritized alongside educational gains. Future work could test our comparative methodological findings for systems comprised of more than three variables.
交叉影响平衡（CIB）分析提供了一种系统理论视角，可以用于研究复杂的社会经济系统。CIB 可以综合各种定性或定量的输入，并提供有关系统演化的信息。目前用于 CIB 的软件工具仅限于识别系统吸引子，以及每次仅从一个初始条件的场景描述系统演化。通过本研究，我们通过开发和应用一种方法来增强 CIB，该方法将所有可能的系统演化视为马尔可夫链中的转换。我们研究了人口转型的一个简单的三变量系统（27 个可能的场景），并能够普遍复制传统 CIB 的发现。通过对四种可能的方法生成 CIB 马尔可夫链的实验，我们发现可以获得有关转换途径的信息，但可能会丢失有关系统吸引子的信息。通过将模型结果与最近关于人类人口统计学的文献综述进行比较，我们发现如果不优先考虑经济发展和教育收益，低收入国家更有可能陷入人口陷阱。未来的工作可以测试我们针对由三个以上变量组成的系统的比较方法学发现。
