In this paper, we propose a new method to develop multiscalar industrial policies based on a spatially constrained clustering problem, the -innovation ecosystems (-IE) model, that combines aspects of complexity, relatedness, and geography. Our formulation is motivated by recent developments of economic complexity regarding the evolution of economic output through key interactions among industries within economic regions. The objective of this model is to aggregate a set of geographic areas into a prescribed number of regions (so-called innovation ecosystems) such that the resulting regions preserve the most relevant interactions among industries and encourage the emergence of complex industries. We formulate the
-IE model as a mixed-integer programming (MIP) problem and propose a heuristic solution approach. We explore a case involving the municipalities of Colombia to illustrate how such a model can be applied and used for policy and regional development
