nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2006‒04‒29
eleven papers chosen by
Roberto Fontana
Universita Bocconi

  1. Industry Dynamics and the Distiribution of Firm Sizes: A Non-Parametric Apporoach. By F. Lotti; E. Santarelli
  2. The Effects of Innovation on Performance of Korean Firms By Heshmati, Almas; Kim, Yee-Kyoung; Kim, Hyesung
  3. The Productivity of UK Universities By Gustavo Crespi; Aldo Geuna
  4. Measuring Informal Innovation: From Non-R&D to On-line Knowledge Production By Marcel Bogers; Stéphane Lhuillery
  5. Not for Lack of Trying : American Entrepreneurship in Black and White By Philipp Köllinger; Maria Minniti
  6. Entry, Exit, and Productivity of Indonesian Electronics Manufacturing Plants By Alfons Palangkaraya; Jongsay Yong
  7. "Selection or Imitation? : Organizational Evolution in the Japanese Cotton Industry, 1905-1935:" By Tetsuji Okazaki
  8. Measuring industry-science links through inventor-author relations: A profiling method By Cassiman, Bruno; Glenisson, Patrick; Van Looy, Bart
  9. Are Co-Active Researchers on Top of their Class? An Exploratory Comparison of Inventor-Authors with their Non-Inventing Peers in Nano-Science and Technology By Martin Meyer
  10. Exploring the "Value" of Academic Patents: IP Management Practices in UK Universities and their Implications for Third-Stream Indicators By Martin Meyer; Puay Tang
  11. Movement of Star Scientists and Engineers and High-Tech Firm Entry By Lynne G. Zucker; Michael R. Darby

  1. By: F. Lotti; E. Santarelli
  2. By: Heshmati, Almas (Ratio); Kim, Yee-Kyoung (Seoul National University); Kim, Hyesung (Seoul National University)
    Abstract: This study empirically examines the relationship between knowledge capital and performance heterogeneity at the firm level. The model is based on a knowledge production function comprising of four interdependent equations linking innovativeness to innovation input, innovation output and productivity. The empirical part is based on Korean firm level innovation data. The model is estimated using advanced econometric methods. We investigate whether innovation is a significant and contributing determinant of performance heterogeneity among firms. In examining the relationship between innovation and productivity we correct for selectivity and simultaneity biases. The results show that there is a two-way causal relationship between knowledge capital and labor productivity. Firm-specific effects positively contribute to innovation output but they are negatively related to productivity. Industry heterogeneity does not affect innovation output or productivity.
    Keywords: Innovation Input; Innovation Output; Productivity; Korea
    JEL: C33 E22 L60 O32
    Date: 2006–04–25
  3. By: Gustavo Crespi (SPRU, University of Sussex); Aldo Geuna (SPRU, University of Sussex)
    Abstract: There is increasing recognition in the UK and other OECD countries of the importance of scientific research in providing the foundations for both innovation and competitiveness. This has resulted in increased public funding for research in the UK and elsewhere. At the same time, there is a lack of systematic evidence on how such investments can lead to increasing levels of scientific output and, ultimately, to better economic performance. Much of the available literature concentrates on the effects of public funding of basic research on either firms' innovative activities (see among others COHEN, NELSON AND WALSH [2002]; KLEVORICK, LEVIN, NELSON AND WINTER [1995]; JAFFE [1989]; NARIN, HAMILTON AND OLIVASTRO [1997]) or firm performance (Adams [1990]), bypassing the question of how to measure scientific output. The reasons for this are the difficulty of identifying a stable causal relationship between the resources spent on the science budget and 'intermediate' scientific outputs. This difficulty originates from the dynamic nature of this relationship. There is a persistent and therefore recursive feedback between inputs and outputs, which is exacerbated by lack of appropriate information for analysis. Among the few studies that have attempted to address the problem, are ADAMS AND GRILICHES [1996] and JOHNES AND JOHNES [1995]. This study is based on and further develops Adams and Griliches's methodology.
    Keywords: bibliometrics, university graduate students, national science budget, research funding, economic performance, scientific output
    JEL: O3 I2
    Date: 2006–04–11
  4. By: Marcel Bogers (Chaire en Economie et Management de l'Innovation, Ecole Polytechnique Fédérale de Lausanne); Stéphane Lhuillery (Chaire en Economie et Management de l'Innovation, Ecole Polytechnique Fédérale de Lausanne)
    Abstract: In this paper we explore the concept of informal innovation by investigating it both on the input (activities) and output (impact) side of the innovation process. Informal innovation is defined as innovation that is not explicitly planned and budgeted and therefore remains largely hidden in (aggregate) innovation data. We take a statistical approach to reveal the significant potential of informal innovation. We furthermore conceptualize and operationalize informal innovation as an activity taking place without R&D (in non-R&D firms). In general, on the input side, we show that around half of the innovative firms in our sample (of innovative firms in the Swiss Innovation Survey of 2002) develop innovations without any R&D. Moreover, on the output side, over one third of the innovative sales and production cost reductions can be attributed to informal innovation. Although the results appear to be rather pervasive, they are strongest for small firms, low-tech firms and firms in service industries. This leads us to conclude that informal innovation is not just an important complement to formal innovation – as scarcely acknowledged in literature – but that is largely takes place next to and as a substitute for formal innovation as well – which is largely neglected in literature to date. We furthermore explore the possible attributes of the process of informal innovation and develop a preliminary framework that needs to be investigated into further detail by future research. In particular, we argue that ‘on-line’ activities are a crucial part of the innovation process, although it has been largely neglected to date. It becomes clear that the literature on learning-by-doing and learning-by-using needs to be expanded by more explicitly focusing on the processes that are at the heart of the (informal) innovation process in order to clearly show the sources of innovation. In order to do this, we indicate some possible avenues for future research to improve the measurement of (informal) innovation.
    Date: 2006–03
  5. By: Philipp Köllinger; Maria Minniti
    Abstract: Using a sample obtained from a survey conducted in the United States during summer 2002, we study the variables related to observed differences in the rate of entrepreneurial involvement between black and white Americans. We find strong evidence that differences in subjective and often biased perceptions are highly associated with entrepreneurial propensity across these two racial groups. In addition, we find that black Americans tend to exhibit more optimistic perceptions of their business environment than other racial groups and are more likely than others to attempt starting a business. In fact, our results show that blacks are almost twice as likely as whites to try starting a business. Thus, our results suggest that the under representation of black Americans among established entrepreneurs is not due to lack of trying but may instead be due to stronger barriers to entry and higher failure rates.
    Keywords: Entrepreneurship, Black Entrepreneurship, Minority Entrepreneurship, Nascent Entrepreneurship.
    JEL: J15 J23 M13
    Date: 2006
  6. By: Alfons Palangkaraya (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne); Jongsay Yong (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)
    Abstract: We study the link between plant turnover and productivity using Indonesian plant-level data for the period of 1990-95. First, we compare productivity differentials among incumbents, entrants, and exiting plants by constructing the Farrell technical efficiency index using data envelopment analysis. We test the significance of these differentials using Simar and Wilson (1998) bootstrap algorithm and Li’s (1996) nonparametric test of closeness between unknown distributions. We find that the incumbent plants are on average the most productive group in every year of the estimation period. Also, the new plants are relatively less productive than the exiting plants in the early years. However, they are more productive than the exiting plants in the later years. Second, and more importantly, we estimate the productivity change during the study period using the Malmquist productivity change index and decompose the change to see if the differences in measured productivity change among the three groups of plants come from differences in the efficiency change or the technical change. Since the existing literature rarely distinguishes between these two different components, little is known whether exiting plants are less productive because of their inability to catch up to the current frontier or to adopt a better technology. Similarly, not much known whether entrants’ ability to survive come from their being equipped with a ’better’ technology or being able to catch up to the current frontier. Our findings indicate that although new plants enter with relatively lower productivity levels, they exhibit the highest productivity change during the early years. In addition, we find entrants’ high productivity growth in the early period is due to a movement toward the frontier, while in the later period is due to an upward shift of the technology frontier. Exiting plants, on the other hand, exhibit the lowest productivity change during the early years when entrants experience high productivity change.
    JEL: D24 L63
    Date: 2006–04
  7. By: Tetsuji Okazaki (Faculty of Economics, University of Tokyo)
    Abstract: This paper explores the mechanisms by which the industrial organization of the Japanese cotton spinning industry changed over time, focusing on the rise and fall of the firms that integrated spinning and weaving processes. The basic idea is to decompose the change in the proportion of integrated firms into factors representing "selection" and "imitation" in an evolutionary sense. It was found that the factor which made the largest contribution differed between the growing phase and the declining phase of integrated firms. In the growing phase, imitation, namely the change in the attribute of the incumbent firms, was the major factor in the proportion change. On the other hand, in the declining phase, selection, in particular, birth rate, was the major factor, not only in the case where the proportion is measured in terms of firm number but also in terms of production.
    Date: 2006–04
  8. By: Cassiman, Bruno (IESE Business School); Glenisson, Patrick (KU Leuven and Business & Decision Benelux); Van Looy, Bart (KU Leuven and Steunpunt O&O Statistieken)
    Abstract: In this pilot study we examine the performance of text-based profiling in recovering a set of validated inventor-author links. In a first step we match patents and publications solely based on their similarity in content. Next, we compare inventor and author names on the highest ranked matches for the occurrence of name matches. Finally, we compare these candidate matches with the names listed in a validated set of inventor-author names. Our text-based profile methodology performs significantly better than a random matching of patents and publications, suggesting that text-based profiling is a valuable complementary tool to the name searches used in previous studies.
    Keywords: innovation; industry-science links; text-based profiling;
    Date: 2006–03–27
  9. By: Martin Meyer (SPRU, University of Sussex)
    Abstract: This paper explores the relationship between scientific publication and patenting activity. More specifically, this research examines for the field of nanoscience and nanotechnology whether researchers who both publish and patent are more productive and more highly cited than their peers who concentrate on scholarly publication in communicating their research results. This study is based on an analysis of the nanoscience publications and nanotechnology patents of a small set of European countries. While only a very small number of nanoscientists appear to hold patents in nanotechnology, a considerable number of nano-inventors seem to be actively publishing nanoscience research. Overall, the patenting scientists appear to outperform their solely publishing, non-inventing peers in terms of publication counts and citation frequency. However, a closer examination of the highly active and cited nano-authors points to a slightly different situation. While still over-represented among the highly cited authors, inventor-authors appear not to be among the most highly cited authors in that category with one notable exception. A policy-relevant conclusion is that, generally speaking, patenting activity does not appear to have an adverse impact on the publication and citation performance of researchers.
    Keywords: nanotechnology, inventors, bibliometrics, patenting activity, publications
    JEL: O34
    Date: 2006–04–11
  10. By: Martin Meyer (SPRU, University of Sussex); Puay Tang (SPRU, University of Sussex)
    Abstract: Third-Stream activities have become increasingly important in the UK. However, valuing them in a meaningful way still poses a challenge to science and technology analysts and policy makers alike. This paper reviews the general literature on "patent value" and assesses the extent to which these established measures, including patent citation, patent family, renewal and litigation data, can be applied to the university context. Our study examines indicators of patent value for short and mid-term evaluation purposes, rather than indicators that suffer from long time lags. We also explore the extent to which differences in IP management practices at universities may have an impact on the validity and robustness of possible indicators. Our observations from four UK universities indicate that there are considerable differences between universities as to how they approach the IP management process, which in turn has implications for valuing patents and how they track activity in this area. In their current form, data as collected by universities are not sufficiently robust to serve as the basis for evaluation or resource allocation.
    Keywords: intellectual property management, patenting, United Kingdom universitities, technology transfer, third stream, performance indicators
    JEL: O34
    Date: 2006–04–11
  11. By: Lynne G. Zucker; Michael R. Darby
    Abstract: This paper extends the concept of star scientist to all areas of science and technology. We follow 1,838 stars' careers 1981-2004, using their publication history to locate them each year. The number of stars in a U.S. region or in one of the top-25 science and technology countries has a consistently significant and quantitatively large positive effect on the probability of firm entry in the same area of science and technology. Thus the stars themselves rather than their potentially disembodied discoveries play a key role in the formation or transformation of high-tech industries. Other measures of academic knowledge stocks have weaker and less consistent effects. We identify separate economic geography effects in poisson regressions for the 179 BEA-defined U.S. regions, but not for the 25 countries analysis. Stars become more concentrated over time, moving from areas with relatively few peers to those with many in their discipline. A special counter-flow operating on the U.S. versus the other 24 countries is the tendency of foreign-born American stars to return to their homeland when it develops sufficient strength in their area of science and technology. In contrast high impact articles and university articles and patents all tend to diffuse, becoming more equally distributed over time.
    JEL: O31 J61 J44 M13
    Date: 2006–04

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