Collective Learning Group, The MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Masdar Institute, Khalifa University of Science and Technology, Abu Dhabi, P.O. Box 54224, UAE.
Nat Commun. 2018 Apr 6;9(1):1328. doi: 10.1038/s41467-018-03740-9.
Countries and cities are likely to enter economic activities that are related to those that are already present in them. Yet, while these path dependencies are universally acknowledged, we lack an understanding of the diversification strategies that can optimally balance the development of related and unrelated activities. Here, we develop algorithms to identify the activities that are optimal to target at each time step. We find that the strategies that minimize the total time needed to diversify an economy target highly connected activities during a narrow and specific time window. We compare the strategies suggested by our model with the strategies followed by countries in the diversification of their exports and research activities, finding that countries follow strategies that are close to the ones suggested by the model. These findings add to our understanding of economic diversification and also to our general understanding of diffusion in networks.
各国各城市很可能会开展与其现有产业相关的经济活动。然而，尽管这些路径依赖关系是普遍存在的，但我们缺乏一种理解，无法制定出能够最优平衡相关和不相关活动发展的多样化策略。在这里，我们开发了算法来确定在每个时间步中最优的目标活动。我们发现，使经济多样化所需的总时间最小化的策略，在一个狭窄而特定的时间窗口内，目标是高度关联的活动。我们将我们模型建议的策略与各国在出口和研究活动多样化方面所遵循的策略进行了比较，发现各国所遵循的策略与模型所建议的策略非常接近。这些发现增加了我们对经济多样化的理解，也增加了我们对网络中扩散的一般理解。
