Multiplying Effects of Urban Innovation Districts. Geospatial Analysis Framework for Evaluating Innovation Performance Within Urban Environments

Abstract

AbstractUrban innovation performance is the main driving force behind sustained economic growth. There have been many attempts to quantify innovation performance in order to guide decision-making, promoting investment and innovation projects. Most studies do not accurately describe innovation in terms of how knowledge-intensive activities develop over multiple phases, how they are distributed geographically, and the ways in which agglomerated urban innovation efforts can enhance economic growth. Primarily, they fail to effectively combine urban practice and economic findings through data science efforts to design quantitative innovation performance metrics. This paper presents a novel database and analytical methodology to measure and describe the nonlinear benefits of geographic aggregation of knowledge-intensive activities within urban environments. The results of this research empirically demonstrate that innovation districts, characterized by their geographic concentration of knowledge-intensive activities, benefit from the superlinear growth of innovation, both in terms of innovation output per employee (new patents, new products, new services, R&D, scientific papers) and in terms of innovation-related employment creation per resident. The geospatial, analytical framework has been applied to the study of 50 notable Innovation Districts to benchmark them against a baseline of all districts in the United States. We have extracted the most salient features of these districts that illustrate the value of investing in the geographic concentration of innovation activities. The analytical framework can then be applied to any geographical area to evaluate the economic performance of knowledge-intensive activities within urban environments. The work expands on general knowledge of how cities operate as complex systems and how they shape the collective knowhow of urban communities. Further research may identify the key factors, features, and dynamics underlying the success of innovation districts, such as urban design criteria and smart specialization strategies, and apply them to specific communities to support the economic growth of urban environments.KeywordsCity scienceGeospatial analysisUrban innovationComplexity economicsDatabase creationInnovation districtsSuperlinear growthUrban developmentTerritorial analysisNetwork scienceInnovation performanceComplex systems analysis