This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

The Rise of the Creative Class

Economics Of Discrimination

Economists have long puzzled over the astounding differences in productivity between firms and countries. For example, looking at disaggregated data on U.S. manufacturing industries, Syverson (2004a) found that plants at the 90th percentile produced four times as much as the plant in the 10th percentile on a per-employee basis. Only half of this difference in labor productivity could be accounted for by differential inputs, such as capital intensity. Syverson looked at industries defined at the four-digit level in the Standard Industrial Classification (SIC) system (now the North American Industry Classification System or NAICS) like 'Bakeries and Tortilla Manufacturing' or 'Plastics Product Manufacturing.' Foster, Haltiwanger, and Syverson (2008) show large differences in total factor productivity even within very homogeneous goods industries such as boxes and block ice. Some of these productivity differences across firms and plants are temporary, but in large part they persist over time. At the country level, Hall and Jones (1999) and Jones and Romer (2009) show how the stark differences in productivity across countries account for a substantial fraction of the differences in average per capita income. Both at the plant level and at the national level, differences in productivity are typically calculated as a residual-that is, productivity is inferred as the gap between output and inputs that cannot be accounted for by conventionally measured inputs.

/pdf/why-do-management-practices-differ-across-firms-and-58rczn83xl.pdf

Why Do Management Practices Differ across Firms and Countries

We propose an independence criterion based on the eigen-spectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator (we term this a Hilbert-Schmidt Independence Criterion, or HSIC). This approach has several advantages, compared with previous kernel-based independence criteria. First, the empirical estimate is simpler than any other kernel dependence test, and requires no user-defined regularisation. Second, there is a clearly defined population quantity which the empirical estimate approaches in the large sample limit, with exponential convergence guaranteed between the two: this ensures that independence tests based on HSIC do not suffer from slow learning rates. Finally, we show in the context of independent component analysis (ICA) that the performance of HSIC is competitive with that of previously published kernel-based criteria, and of other recently published ICA methods.

Measuring statistical dependence with Hilbert-Schmidt norms

We study the effects of diverse team composition on the survival and growth of new ventures using the Danish Linked Employer-Employee database. To get cleaner measures of diverse team composition, we focus on entrepreneurial dyads, and also investigate the asymmetric effects of team composition by distinguishing between the `primary' and the `secondary' founder. We complement existing work by showing that heterogeneity in team composition is affected by the asymmetric hierarchical structure within the team, and that a unidimensional diversity indicator (which is usually applied) fails to capture a number of performance effects of heterogeneous team composition. Ventures with a STEM-educated primary founder and a Business-educated secondary founder have high employment growth, while the opposite combination (Business first, STEM second) has low employment growth. Pairs of younger individuals have lower survival chances but higher employment growth. Family firms have lower employment growth, especially when formed with your mother.

Two's Company: Human Capital Composition and Performance of Entrepreneurial Pairs

We focus on the relationship of age and diversification patterns of German machine tool manufacturers in the post war era. Based on trade journals we track the entire firm populations' product portfolio development throughout each firm's lifetime. We distinguish between 'minor diversification' and 'major diversification', where these two concepts refer to adding a new product variation within a familiar submarket, or expanding the product portfolio into new submarkets. Our analysis reveals four main insights. First, we observe that firms have lower diversification rates as they grow older, and that eventually diversification rates even turn negative for old firms on average. Second, we find that product portfolios of larger firms tend to be more diversified. Third, with respect to consecutive diversification activities, quantile autoregression plots show that firms experiencing diversification in one period are unlikely to repeat this behavior in the following year. Fourth, survival estimations reveal that diversification activities reduce the risk of exit controlling for various additional firm and industry specific fixed effects and business cycles. These results are interpreted using the Penrosean growth theory.

https://www.econstor.eu/bitstream/10419/57567/1/682915432.pdf

Age, diversification and survival in the German machine tool industry, 1953-2002

Firm Size Distributions

We focus on the relationship of age, growth and diversification patterns of German machine tool manufacturers in the post war era. Based on trade journal data our analysis reveals four main insights. Firstly, we observe that firms have lower diversification rates as they grow older, and that eventually diversification rates even turn negative for old firms on average. Secondly, we find that product portfolios of larger firms tend to be more diversified, although less than proportionally so (which suggests that larger firms are composed of larger submarkets). Thirdly, with respect to consecutive growth activities, quantile autoregression plots show that firms experiencing diversification in one period are unlikely to repeat this behavior in the following year. Fourthly, survival estimations reveal a lower hazard risk for older organizations as well as the fact that growth activities in general reduce the risk of failure controlling for various additional firm and industry specific fixed effects and business cycles. Interestingly, when differentiating between various age cohorts and their specific consequences when growing, we find that especially teenaged firms face the highest risk of failure. JEL codes: L20, L25

/pdf/age-growth-and-diversification-in-the-german-machine-tool-3mfw0byum7.pdf

Age, growth and diversification in the German machine tool industry, 1936-2002

Unemployment has been robustly shown to strongly decrease subjective well-being (or "happiness") In the present paper, we use panel quantile regression techniques in order to analyze to what extent the negative impact of unemployment varies along the subjective well-being distribution In our analysis of British Household Panel Survey data (1996-2008) we find that, over the quantiles of our subjective well-being variable, individuals with high well-being suffer less from becoming unemployed A similar but stronger effect of unemployment is found for a broad mental well-being variable (GHQ-12) For happy and mentally stable individuals, it seems their higher well-being acts like a safety net when they become unemployed We explore these findings by examining the heterogeneous unemployment effects over the quantiles of satisfaction with various life domains

Alex Coad

Papers

Two's Company: Human Capital Composition and Performance of Entrepreneurial Pairs

Age, diversification and survival in the German machine tool industry, 1953-2002

Firm Size Distributions

Age, growth and diversification in the German machine tool industry, 1936-2002

Heterogeneity in the Relationship between Unemployment and Subjective Well-Being: A Quantile Approach