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.

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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

Three cheers for industry: Is manufacturing linked to R&D, exports, and productivity growth?

This paper studies the serial autocorrelation of annual growth rates in employment for selected Austrian service industries over a 30-year period using quantile regression techniques. The autocorrelation of growth rates provides important information on firms growth processes. We find that the growth patterns of micro firms are strikingly different from the growth patterns of small, medium-sized and larger firms. First, we do find a positive dependency of growth on size for growing micro firms, while this relationship is negative for the other size groups. Second, growing micro firms are subject to negative autocorrelation of annual growth rates making sustained growth a very rate occurrence, while larger growing firms usually display a positive autocorrelation suggesting that high growth episodes of larger firms stretch over a longer time horizon. This indicates that non-convex adjustment costs leading to lumpy growth are much more important for micro firms than for large firms. Furthermore, we find that the autocorrelation patterns are asymmetric with regard to decline and growth.

On the Autocorrelation of Growth Rates: Evidence for Micro, Small and Large Firms from the Austrian Service Industries, 1975-2004

This article examines an apparent contradiction at the heart of the provision of management training and advice for new and small firms. Assessments using self-report data show high levels of satis...

Why should banks provide entrepreneurship training seminars

This thesis presents empirical investigations into the growth of firms, using datasets on French and US manufacturing firms. We begin with a lengthy literature review to clearly identify the gaps in the existing literature. We then investigate Gibrat's law and examine the distribution of growth rates. We investigate serial correlation patterns in growth rates and observe that small firms have negative autocorrelation whilst larger firms have positive autocorrelation. In a theoretical discussion we contrast the mainstream 'financial constraints' theory with evolutionary theory, and conclude that neoclassical work may have exaggerated the extent of financial constraints. In our dataset, firm growth is more or less independent from financial performance and we conclude that selection pressures are weak In the final part we consider the relationship between innovation and firm performance Quantile regression techniques reveal that innovation leads to remarkably superior performance in a minority of cases (the 'superstar firms') but has little effect for the 'average firm' .

https://tel.archives-ouvertes.fr/tel-00163394/document

Empirical investigations into the characteristics and determinants of the growth of firms

This paper explores the relationship between new digital technologies, internationalisation activity and its impact on High Growth Enterprises (HGEs), using the EIB Group Survey of Investment and Investment Finance and ORBIS data for 27 EU Member States and the United Kingdom. After controlling for sample selection bias, our results suggest that being a HGE is positively associated with the probability that a firm conducts international activities, particularly FDI. Conversely, the internationalisation process seems to trigger strong subsequent firm-growth only for FDI, not for exports. Furthermore, we show evidence on the positive association between firms that are internationalised and those adopting new digital technologies. The adoption of new digital technologies is indirectly related to the status of being a HGE via internationalisation activity in the current period. Our results highlight the complex influence of exporting and FDI on the capacity to become a HGE and the role of new digital technologies in this process.

Alex Coad

Papers

Three cheers for industry: Is manufacturing linked to R&D, exports, and productivity growth?

On the Autocorrelation of Growth Rates: Evidence for Micro, Small and Large Firms from the Austrian Service Industries, 1975-2004

Why should banks provide entrepreneurship training seminars

Empirical investigations into the characteristics and determinants of the growth of firms

The birth of new HGEs: internationalization through new digital technologies