The hunt for S -shaped growth paths in technological innovation: a patent study *

Andersen, Birgitte

doi:10.1007/s001910050093

Cited by 135 publications

(73 citation statements)

References 21 publications

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“…Trend analysis often consists in fitting the progress and growth of bibliometric data with technology diffusion models. In this regard, cumulative technology development is generally recognized to follow an S-shaped curve over time (Andersen 1999;Daim et al 2006). In this model, development in a discipline grows exponentially until an inherent upper limit is reached.…”

Section: Introductionmentioning

confidence: 99%

“…At this point, growth slows down and eventually saturates. These two phases of growth and saturation are representative of technological opportunities in a given disciplines (Andersen 1999). An emerging discipline initially offers great opportunities and thus exhibits exponential growth in terms of bibliometric indicators.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the accumulation of patent stocks in a discipline takes place because of interactions between scientists, inventors and entrepreneurs. Changes in patenting activity can therefore be used to assess the development stage of various technological sectors (Andersen 1999). Naturally, the analysis of trends and patterns of patenting activity in emerging industries is a popular subject of research.…”

Section: Introductionmentioning

confidence: 99%

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Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

2012

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Document publié chez l'éditeur commercial ABSTRACTDiscovering and assessing fields of expertise in emerging technologies from patent data is not straightforward. First, patent classification in an emerging technology being far from complete, the definitions of the various applications of its inventions are embedded within communities of practice. Because patents must contain full record of prior art, co-citation networks can, in theory, be used to identify and delineate the inventive effort of these communities of practice. However, the use patent citations for the purpose of measuring technological relatedness is not obvious because they can be added by examiners. Second, the assessment of the development stage of emerging industries has been mostly done through simple patent counts. Because patents are not all valuable, a better way of evaluating an industry's stage of development would be to use multiple patent quality metrics as well as economic activity agglomeration indicators. The purpose of this article is to validate the use of 1) patent citations as indicators of technological relatedness, and 2) multiple indicators for assessing an industry's development stage. Greedy modularity optimization of the 'Canadian-made' nanotechnology patent co-citation network shows that patent citations can effectively be used as indicators of technological relatedness. Furthermore, the use of multiple patent quality and economic agglomeration indicators offers better assessment and forecasting potential than simple patent counts.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

2012

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“…His empirical model generates an S-curve diffusion path. Andersen (1999) confirmed the S-shaped growth path for the diffusion of entrepreneurial activity, using corporate and individual patents granted in the U.S. between 1890and 1990. Jovanovic and Rousseau (2001 provide more evidence for an S-shaped curve diffusion process by matching the spread of electricity with that of personal computer use by consumers.introduction of personal computers and the acceleration in the price reduction of semiconductors, which constituted the necessary building blocks for the information technology revolution.…”

Section: Introductionmentioning

confidence: 62%

The dynamic effects of general purpose technologies on Schumpeterian growth

Petsas

2003

Journal of Evolutionary Economics

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Abstract. General purpose technologies (GPTs) are drastic innovations, such as electrification, the transistor, and the Internet, that are characterized by the pervasiveness in use, innovational complementarities, and technological dynamism. The transitional and long-run dynamic effects of a GPT are analyzed within a quality-ladders model of scale-invariant Schumpeterian growth. The diffusion path of a GPT across a continuum of industries is governed by S-curve dynamics. The initial balanced growth equilibrium exhibits endogenous growth and no industry has adopted the new GPT. The final steady-state equilibrium, in which all industries have adopted the new GPT, exhibits a higher steady-state Schumpeterian growth and a higher per capita R&D. The model generates a unique, stable saddle-path. During the transition path, the measure of industries that adopt the new GPT increases, consumption per capita falls, and the interest rate increases. The growth rate of the stock market depends negatively on the rate of GPT diffusion process and the magnitude of the GPT-ridden R&D productivity gains, and positively on the rate of population growth. It also follows a U-shaped path during the diffusion process of the new GPT. Finally, the model generates transitional growth cycles of per-capita GNP.

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“…As a growth model depicting technology trajectory over time, TLC is composed of four phases: Emerging -Growth -MaturitySaturation (in other words, research and development phase -ascent phase -maturity phasedecline phase in terms of R&D; or initial diffusion -early growing -late growing -maturity in terms of technology diffusion). These phases entail different levels of technological maturity (or risk) in a specific technology area and show different patterns of development across various technologies (Andersen, 1999). Figure 29 below, for instance, shows multiple S-shaped curves that represent the life cycle of class G01 (measuring or testing) technologies.…”

Section: S Curvesmentioning

confidence: 99%

Accelerating the Transition of Technologies Created through the U.S. Department of Defense Small Business Innovation Research Program

Ryu

2017

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For more information on this publication, visit http://www.rand.org/pubs/rgs_dissertations/RGSD405.html Published by the RAND Corporation, Santa Monica, Calif. © Copyright 2017 RAND Corporation R® is a registered trademark Limited Print and Electronic Distribution RightsThis document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions.html.The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.Support RAND Make a tax-deductible charitable contribution at www.rand.org/giving/contribute www.rand.org iii AbstractThe objective of this dissertation is to better understand the contextual effects on the success of the transition of technologies generated through the U.S. Department of Defense (DOD) Small Business Innovation Research (SBIR) program, and to pull out policy recommendations for facilitating the way the SBIR transitions technologies from abstract concepts to concrete engineering capabilities that the U.S. can use in its military systems. To that end, I explore how social (network), spatial (region), and industrial (technology) factors affect the SBIR's ability to do this. Specifically, I examine the contextual effects of network, regional, and industrial characteristics on the success of technology transition using various regression models. To incorporate multilevel factors, in particular, I employ hierarchical linear models with firm-and region/ industry-level variables related to state-level innovation capacity, anchor tenants, innovation brokers, technology life cycle, technology market, technological and network positions of SBIR awardees in relation to the DOD (including its research laboratories) and prime contractors.Findings of this dissertation include: small firms' larger SBIR awards, higher age, more cutting-edge technology or high-tech focus are more likely to lead to success in technology transition; small firms' higher technological distance (in particular, relative to prime contractors) and more central network position are more likely to facilitate technology transition; the number of defense labs in a state may matter in small firms' winning federal procurement contracts and improving their return on investment; the number of DOD mentors (i.e., large prime contractors who signed up for mentoring small busin...

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The hunt for S -shaped growth paths in technological innovation: a patent study *

Cited by 135 publications

References 21 publications

Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

The dynamic effects of general purpose technologies on Schumpeterian growth

Accelerating the Transition of Technologies Created through the U.S. Department of Defense Small Business Innovation Research Program

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