nep-ino New Economics Papers
on Innovation
Issue of 2005‒01‒16
nine papers chosen by
Koen Frenken
Universiteit Utrecht

  1. Density and strength of ties in innovation networks: an analysis of multimedia and biotechnology By Gilsing, V.; Nooteboom, B.
  2. The size distribution of innovations revisited: an application of extreme value statistics to citation and value measures of patent significance By Silverberg, G.; Verspagen, B.
  3. Late industrialisation and structural change: the Indonesian experience By Jacob, J.
  4. History friendly simulations for modelling industrial dynamics By Garavaglia, C.
  5. The evolution of alliance capabilities By Heimeriks, K.; Duysters, G.M.; Vanhaverbeke, W.P.M.
  6. A study into the alliance capability development process By Heimeriks, K.; Duysters, G.M.
  7. Heterogeneous preferences and new innovation cycles in mature industries: the camera industry 1955-1974 By Paul Windrum
  8. Why firm-established user communities work for innovation: The personal attributes of innovative users in the case of computer-controlled music instruments By Lars Bo Jeppesen & Lars Frederiksen
  9. Lobbies and Technology Diffusion By Diego Comin; Bart Hobijn

  1. By: Gilsing, V. (Ecis, Technische Universiteit Eindhoven); Nooteboom, B. (Erasmus University Rotterdam)
    Keywords: innovation, networks, biotechnology
    Date: 2004
    URL: http://d.repec.org/n?u=RePEc:dgr:tuecis:0416&r=ino
  2. By: Silverberg, G. (MERIT, Maastricht University); Verspagen, B. (Ecis, Technische Universiteit Eindhoven)
    Keywords: distribution, patent, innovation
    Date: 2004
    URL: http://d.repec.org/n?u=RePEc:dgr:tuecis:0417&r=ino
  3. By: Jacob, J. (Ecis, Technische Universiteit Eindhoven)
    Keywords: industrialisation, structural, change, Indonesia
    Date: 2004
    URL: http://d.repec.org/n?u=RePEc:dgr:tuecis:0418&r=ino
  4. By: Garavaglia, C. (CESPRI, Bocconi University, Milan, Italy and Cattaneo University, LIUC, Castellanza (VA), Italy)
    Keywords: simulation, models, industrial dynamics
    Date: 2004
    URL: http://d.repec.org/n?u=RePEc:dgr:tuecis:0419&r=ino
  5. By: Heimeriks, K. (Ecis, Technische Universiteit Eindhoven); Duysters, G.M. (Ecis, Technische Universiteit Eindhoven); Vanhaverbeke, W.P.M. (Ecis, Technische Universiteit Eindhoven)
    Keywords: evolution, alliance
    Date: 2004
    URL: http://d.repec.org/n?u=RePEc:dgr:tuecis:0420&r=ino
  6. By: Heimeriks, K. (Ecis, Technische Universiteit Eindhoven); Duysters, G.M. (Ecis, Technische Universiteit Eindhoven)
    Keywords: simulation, models
    Date: 2004
    URL: http://d.repec.org/n?u=RePEc:dgr:tuecis:0421&r=ino
  7. By: Paul Windrum
    Abstract: The paper examines the innovation dynamics of the mature camera market between 1955 and 1974. This highlights the importance of heterogeneous preferences in determining industry structure. By recognising and accommodating consumer heterogeneity, new firms engaged in radical product and process innovation and overcame the first-mover advantages of dominant firms. The case raises important issues for our understanding of industry life cycles. First, a number of innovation cycles are possible over the life cycle. Second, new rounds of entry, exist and market shake-out can occur, with new, innovative entrants displacing old firms. If the new firms are in developing countries then a shift in global production occurs. Third, a basic tenet of Porterian competitive advantage is overturned because success is based on innovation not wage-cost advantages. Fourth, market structure can change, the industry dividing into a number of market niches that contain distinct user groups. Fifth, incremental modular innovations may be adopted by some user groups but not by others. Consequently, incremental product innovations may be adopted in low-priced goods but not in high-priced goods.
    Keywords: industry life cycle, innovation, heterogeneous preferences, cameras, photography
    JEL: L10 L60
    Date: 2004–12
    URL: http://d.repec.org/n?u=RePEc:esi:evopap:2004-18&r=ino
  8. By: Lars Bo Jeppesen & Lars Frederiksen
    Abstract: Studies of the sources of innovations have recognized that many innovations are developed by users. However, the fact that firms employ communities of users to strengthen their innovation process has not yet received much attention. In firm-established user communities users freely reveal innovations to a firm’s product platform, which in turn puts the firm in a favorable position (a) because these new product features become available to all users by sharing on a user-to-user basis, or (b) because it allows the firm to pick up the innovations and integrate them in future products and then benefit by selling them to all users. We study the key personal attributes of the individuals responsible for innovations and the creation of value in this organizational context, namely the innovative users, to explain why firm-established user communities work. Analyzing data derived from a web-based questionnaire generating 442 answers we find that innovative users are likely to be (i) hobbyists, an attribute that can be assumed to affect innovators’ willingness to share innovations (positively), and (ii) responsive to “firm-recognition” as a motivating factor for undertaking innovation, which explains their decision to join the firm’s domain. In agreement with earlier studies we also find that innovative users are likely to be “lead users”, an attribute that we assume to affect the quality of user innovation. Whether or not a firm-established user community can be turned into an asset for the firm is to a great extent conditioned by the issues studied in this paper.
    Keywords: Innovation, User community, User Characteristics
    JEL: L21 L23 O31 O32
    URL: http://d.repec.org/n?u=RePEc:ivs:iivswp:04-02&r=ino
  9. By: Diego Comin; Bart Hobijn
    Abstract: Do lobbies affect technology diffusion and growth? A number of authors have identified the importance of vested interests as a deterrent to technology diffusion and the relevance that this may have for growth. however, the evidence that exists about this mechanism is just anecdotal. In this paper we build a model of lobbying and technology diffusion where the speed of diffusion of new technologies depends on some dimensions of the political regime and on the whether there is an old technology that may be substituted by the new technology. This differential effect of institutions on the diffusion of technologies with a predecessor constitutes the central element of our identification strategy. To implement this test we use technology diffusion data from Comin and Hobijn [2004]. We find that the relevant institutional variables have a differential effect on the diffusion of technologies with a predecessor technology as predicted by the theory. We show that this result is unlikely to be driven by omitted variables, or reverse causality.
    JEL: N10 O30 O57
    Date: 2005–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:11022&r=ino

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