Using Science and Technology Indicators to Manage R&amp;D as a Business

Thomas, P.; McMillan, G. Steven

doi:10.1080/10429247.2001.11415121

Cited by 23 publications

(15 citation statements)

References 12 publications

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“…Citation-related indicators include science-technology links (Tijssen et al 2000;Van Looy et al 2004;Verbeek et al 2002), current impact indices (Thomas and McMillan 2001), and total citation counts (Narin et al 1997). Science-technology links are the number of citations to a patent by other scientific papers.…”

Section: Patent Qualitymentioning

confidence: 99%

“…The current impact index (CII) is defined as the number of times a patent is cited by other patents in the most recent five-year period. This index shows the impact of a patent on the latest technological developments (Thomas and McMillan 2001). The most widely used measurement of patent quality is patent citation count (Coombs and Bierly 2006;Hagedoorn and Cloodt 2003).…”

Section: Patent Qualitymentioning

confidence: 99%

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Network structure of innovation: can brokerage or closure predict patent quality?

Wang

Chiang

Lin³

2010

Scientometrics

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Patents are important intellectual assets for companies to defend or to claim their technological rights. To control R&D cost, companies should carefully examine their patents by patent quality. Approaches to evaluating patent quality are mostly a posteriori uses of factual information of patent quality. This paper examined whether patent quality can be predicted a priori, i.e., during the early years after a patent is granted, by analyzing information embedded in a network of patent citations. Social network analysis was applied to analyze two network positions occupied by a patent, brokerage and closure to determine whether either position is a good predictor of patent quality. Patent renewal decisions and forward citations were adopted as surrogates of patent quality. The analytical results showed that forward citations can be positively predicted by the brokerage position and negatively predicted by the closure position in the early and mature stages. Renewal decisions can be negatively predicted by the brokerage position in the early stage, and the closure position influences the renewal decision in a different way in the early and mature stages. These analytical results imply that a company should focus on developing patents that bridge different technologies as its technological developments reach maturity.

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Section: Patent Qualitymentioning

confidence: 99%

Section: Patent Qualitymentioning

confidence: 99%

Network structure of innovation: can brokerage or closure predict patent quality?

Wang

Chiang

Lin³

2010

Scientometrics

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“…Citation-related indicators include sciencetechnology links [21][22][23] , current impact indices [24] , total incoming citations counts [6], and incremental differences in citation count . Science-technology links are the number of citations to a patent by other scientific papers.…”

Section: Patent Qualitymentioning

confidence: 99%

Network Structure of Innovation: Can Brokerage or Closure Predict Patent Quality?

Wang

Chiang

Lin

2009

2009 42nd Hawaii International Conference on System Sciences

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Patents are important intellectual assets. Approaches to evaluating patent quality are mostly a posteriori uses of factual information of patent quality. This paper examines whether patent quality can be predicted a priori, i.e., at an early stage after a patent is granted by analyzing information embedded in a network of patent citations. Social network analysis was applied to analyze two complementary network positions occupied by a patent brokerage and closure to determine whether either position predicts patent quality. Differences in patent citation counts and maintenance years were adopted as surrogates of patent quality. The analytical results showed that higher brokerage value can lead to higher increments of patent citation counts; higher closure value can lead to longer maintenance. The interactive effect of brokerage and closure position was confirmed. These analytical results imply that a company should focus on developing patents that bridge different technologies as technology development reaches maturity.

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“…Previous researches in this field have proven the significance of the study on patent quality. Deng et al (1999) and Thomas et al (2001) use patent quality to predict stock returns and market-to book (M/B) ratios and gain remarkable result. This study uses ROA as standard variable making a contribution to the research finding for the relationship between patent quality and a company's economic performance.…”

Section: Introductionmentioning

confidence: 98%

Profitability decided by patent quality? An empirical study of the U.S. semiconductor industry

et al. 2009

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The investment in research and development (R&D) for semiconductor industry is never small as the technology cycle time (TCT) is relatively short comparing to other industries, thus a semiconductor company requires lots of technological innovations and capital offerings to maintain. The semiconductor industry contributes primarily part of the micro-electronic industries. Advancing technology and patent application are the centre of attention within the semiconductor sector. This research examines the relationship between patent quality and the profits a patent creates for a company in this selected field. This study distinguishes itself from prior research by including cross-sectional data, time series data to simultaneously collect and analyze. The study result shows that some indicators of patent quality are statistically significant to return on assets.

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Using Science and Technology Indicators to Manage R&D as a Business

Cited by 23 publications

References 12 publications

Network structure of innovation: can brokerage or closure predict patent quality?

Network structure of innovation: can brokerage or closure predict patent quality?

Network Structure of Innovation: Can Brokerage or Closure Predict Patent Quality?

Profitability decided by patent quality? An empirical study of the U.S. semiconductor industry

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