In 2011, the United States Military Academy at West Point Social Sciences Department held its annual Senior Conference on Expeditionary Economics, which highlighted the military’s leading role in economic development, since post-conflict environments are initially too dangerous for U.S. government agencies and Non-governmental Organizations (NGOs) to operate. This military economic development has come to be known as “expeditionary economics.”
US Army Soldiers patrol a market in Northern Iraq
Successful future military operations will hinge on successful expeditionary economic efforts. Additionally, these concepts can be employed as a conflict prevention strategy. Successful economic development leads to security and stability, which will decrease the probability of possible kinetic operations.
While scholars and practitioners agree that expeditionary economic efforts are important, implementation remains a point of contention. Many believe that Small and Medium Enterprises (SMEs) provide the vehicle for economic development. Successful entrepreneurs provide a sustainable solution to economic stagnation, in contrast to more common short-lived “infrastructural aid projects.” Specifically, SMEs supply local communities with jobs and resources, allowing citizens to earn living wages and contribute to the local economy. The ideal environment that fosters entrepreneurial progress is not yet known. A Network Science Center research team is currently investigating the optimal conditions under which developing entrepreneurs can prosper.
Ultimately, our team will develop new techniques to compare networks of entrepreneurs, which involve new metrics that go beyond classic centrality metrics. Nodes represent roles in the local environment, and links represent local perceptions of social capital. For an entrepreneur, Business Incubators may be perceived as the role that supplies access to start-up capital or Family may be perceived as the role that assists in acquiring necessary infrastructure. Our goal is to compare and contrast entrepreneurial ecosystems in different cities of developing countries. Specifically, we aim to answer the following question:
What is different, from a network perspective, about the entrepreneurial environment in cities where entrepreneurs thrive and cities where they do not?
For example, we know that Accra, Ghana has a more advanced entrepreneurial climate than many cities in Sub-Saharan Africa. Can we determine and quantitatively represent the differences between this ecosystem and others that are less advanced?
Kampala Entrepreneurial Network Model developed after a data collection visit to Uganda. Nodes depicted in the network model are roles, or positions, in the local entrepreneurial ecosystem, and the links illustrate how roles are connected through individuals’ perceptions of where to find required resources. Each node is sized according to its influence, and is colored by a grouping algorithm.
The team will then apply the aforementioned comparison techniques to compare “prosperous” and “non-prosperous” ecosystems. Cataloguing differences in network characteristics between the two reveals the “missing requirements for prosperity” of the latter. For example, certain roles may not be sufficiently prominent, or certain links might be missing. From a practical standpoint, we envision the ability to craft policy recommendations that bring a non-prosperous network to a prosperous state. For example, we might determine that commercial banks and technology incubators have very strong relationships in a prosperous-network, but weak relationships in its non-prosperous counterpart. To strengthen such a relationship, we might recommend that the government gives tax-breaks to commercial banks loaning to small business technology incubators.
Demonstration of network evolution to inform policy recommendations.
To validate our policy recommendations, we will compare our network metrics to traditional economic indicators. For example, do our network metrics correctly conclude that a particular ecosystem is non-prosperous? For additional validation, we will perform the same indicator comparisons in other problem spaces.
After the network comparison phase of this research, we will focus on real-world policy implementations for non-prosperous developing entrepreneurial ecosystems. Specifically, we seek to answer the following questions:
• Which policies should be implemented, when, and in what order?
• Can we enact the minimum number of policies in the most cost-effective manner?
These constitute an optimization problem, as well as a network design problem. The team will address issues such as determining the minimum number of policies to enact, or the minimum number of invasive policies to enact, that make the network in question prosperous. Alternatively, we might explore minimizing expenditures to make the network prosperous.
With the assistance of our collaborators at AfriLabs, a network of technology hubs on the African continent, the team has collected 4 initial data sets from Kampala, Uganda, Addis Ababa, Ethiopia, Lusaka, Zambia, and Monrovia, Liberia. We are beginning our initial analysis of these data sets in order to refine our network comparison techniques. Additionally, we will make visits to Accra, Ghana during the spring and a cadet team will visit Dar es Salaam, Tanzania in August.