Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities

With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents (1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime

Does Size Matter? Scaling of CO\u3csub\u3e2\u3c/sub\u3e Emissions and U.S. Urban Areas

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO2) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO2 emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones

Mapping Patent Classifications: Portfolio and Statistical Analysis, and the Comparison of Strengths and Weaknesses

The Cooperative Patent Classifications (CPC) jointly developed by the European and US Patent Offices provide a new basis for mapping and portfolio analysis. This update provides an occasion for rethinking the parameter choices. The new maps are significantly different from previous ones, although this may not always be obvious on visual inspection. Since these maps are statistical constructs based on index terms, their quality--as different from utility--can only be controlled discursively. We provide nested maps online and a routine for portfolio overlays and further statistical analysis. We add a new tool for "difference maps" which is illustrated by comparing the portfolios of patents granted to Novartis and MSD in 2016.Comment: Scientometrics 112(3) (2017) 1573-1591; http://link.springer.com/article/10.1007/s11192-017-2449-

Context Factors and the Performance of Mobile Individuals in Research Teams

This article studies how workforce composition is related to a firm’s success in introducing radical innovations. Pre-vious studies have argued that teams composed of individuals with diverse backgrounds are able to perform moreinformation processing and make deeper use of the information, which is important to accomplish complex tasks.We suggest that this argument can be extended to the level of the aggregate workforce of high-technology firms. Inparticular, we argue that ethnic and higher education diversity within the workforce is associated with superior per-formance in radical innovation. Using a sample of 3,888 Swedish firms, this article demonstrates that having greaterworkforce diversity in terms of both ethnic background and educational disciplinary background is positively corre-lated to the share of a firm’s turnover generated by radical innovation. Having more external collaborations does,however, seem to reduce the importance of educational background diversity. The impact of ethnic diversity is notaffected by external collaboration. These findings hold after using alternative measures of dependent and indepen-dent variables, alternative sample sizes, and alternative estimation techniques. The research findings presented inthis article would seem to have immediate and important practical implications. They would suggest that companiesmay pursue recruitment policies inspired by greater ethnic and disciplinary diversity as a way to boost the innova-tiveness of the organ ization. From a managerial perspective, it may be conc luded tha t workforce disciplinary diver-sity could be potentially replaced by more external links, while ethnic diversity could not

New and atypical combinations: An assessment of novelty and interdisciplinarity

Novelty indicators are increasingly important for science policy. This paper challenges the indicators of novelty as an atypical combination of knowledge (Uzzi et al., 2013) and as the first appearance of a knowledge combination (Wang et al., 2017). We exploit a sample of 230,854 articles (1985 - 2005), published on 8 journals of the American Physical Society (APS) and 2.4 million citations to test the indicators using (i) a Configuration Null Model, (ii) an external validation set of articles related to Nobel Prize winning researches and APS Milestones, (iii) a set of established interdisciplinarity indicators, and (iv) the relationship with the articles\u2019 impact. We find that novelty as the first appearance of a knowledge combination captures the key structural properties of the citation network and finds it difficult to tell novel and non-novel articles apart, while novelty as an atypical combination of knowledge overlaps with interdisciplinarity. We suggest that the policy evidence derived from these measures should be reassessed

Innovation across cities

This paper examines the distribution of patenting activity across cities in the OECD, using a sample of 218 cities from 2000 to 2008. We obtain three main results. First, patenting activity is more concentrated than population and GDP. Second, patenting activity is less persistent than population and GDP, especially in the middle of the distribution. Third, in a parametric model, patenting does not exhibit mean-reversion, and is positively associated with GDP and population density. Our results suggest that policymakers can influence the amount of innovative activity through the use of appropriate policies