Forward patent citations as predictive measures for diffusion of emerging technologies

Fallah, M. Hosein; Fishman, Elliot A.; Reilly, Richard R.

doi:10.1109/picmet.2009.5262201

Cited by 15 publications

(6 citation statements)

References 20 publications

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“…There are two types of citations: backward and forward citations. The former refers to patents that have been cited by the patent in consideration [42]. This is an indicator of preceding knowledge and the average number of backward citations has proven to be invertly related to the radicalness of the respective invention; lower numbers of backward citations are associated with more radical inventions [38].…”

Section: Patent Citation Analysismentioning

confidence: 99%

Limits of Biotechnological Innovation

Fernald¹,

Weenen²,

Sibley³

et al. 2013

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During the past two decades the biopharmaceutical industry has been facing an innovation deficit, characterized by increasing research & development costs and stagnant productivity. From its inception, biotechnology has been expected to counter this deficit by its revolutionary science-based approach to drug discovery. For this study we gathered patent and product data related to the technological development of the first two biotechnologies: recombinant DNA technology and monoclonal antibody technology. We studied the technological lifecycles of these technologies in terms of scientific discoveries and inventions as well as product innovations. Results indicate that over the years inventions related to these technologies have simultaneously become less radical and less valuable. Furthermore, our analysis shows that these biotechnologies have reached a stage of technological limit or saturation, which may be followed by an innovation cliff. Now, more than ever, it is crucial to examine new strategies and opportunities for value creation, capturing, and delivery, within the biopharmaceutical industry

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Section: Patent Citation Analysismentioning

confidence: 99%

Limits of Biotechnological Innovation

Fernald¹,

Weenen²,

Sibley³

et al. 2013

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“…Its hierarchical tree-structure allows to group semantically related terms at various levels of abstraction. A taxonomy-based trend analysis can then retrieve information on a technology more exhaustively than the dominating search techniques in Technology Forecasting that are based on single or few keywords (as e.g., used in Guo et al, 2009;Fallah et al, 2009). Another related problem of the latter techniques is that simple term occurrence frequencies will invariably be noisy as the contexts in which this term appears will be extremely diverse and will contain a large number of extraneous mentions.…”

Section: Introductionmentioning

confidence: 99%

Forecasting Renewable Energy Technologies in Desalination and Power Generation Using Taxonomies

Dawelbait¹,

Henschel²,

Mezher³

et al. 2011

International Journal of Social Ecology and Sustainable Development

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Renewable Energy (RE) technologies are increasingly viewed as crucially important. Knowledge that helps to predict the likely growth of emergent technologies is essential for well-informed technology management. The vast amount of available data in publications hinders the acquisition and analysis of this knowledge. Therefore, there is a need for intelligent search techniques capable of grouping semantically similar concepts together, such that, for example, terms containing “photovoltaic” are hierarchically subsumed under solar energy-related technologies. Consequently, articles related to “Photovoltaics” should be included in the analysis. To accommodate this in an automated fashion, the authors deploy a renewable energy taxonomy for comprehensive trend discovery in publications and patents. This taxonomy is based on the hierarchical structure of Wikipedia categories and their subordinate Wikipedia terms. This paper analyzes promising trends of renewable energy sources in two case studies: power generation and desalination techniques.

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“…This metric is one of the metrics that provide insight into the dynamic of how a technology field evolved over time. Other metrics can be found in literature but are not incorporated in this research [21,22,9] and provide a wide range of insight into a technology field including, but not limited to, breadth of technology field, key companies in the technology field, rate of development, influence on and from other technology fields etc. This is followed by creating a patent map using patent citations.…”

Section: Methodsmentioning

confidence: 99%

Determining the Life Cycle Phase of a Technology Based on Patent Data

2019

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Developing new technologies is one of the most important goals of today's scientific and industrial research. Understanding how technology evolves, as well as its current state, is invaluable in an ecosystem where technology is evolving at an increasingly rapid pace. In this paper, patent data is used to determine a technology's life cycle. Two patent maps are created, one based on patent citations and one based on keywords. The citation patent map visualizes how patents cite each other, while the keyword patent maps visualize keywords used to describe patents and their relations. Both of these patent maps are dynamic, meaning they change over time thus giving insight into an examined technology's evolution. A growth analysis of both networks is conducted as well as a degree distribution analysis. Both of these analyses are used to help determine the technology's lifecycle phase as well as its patterns of growth. This insight is invaluable to stakeholders tasked to make strategic decisions related to technology development.

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Forward patent citations as predictive measures for diffusion of emerging technologies

Cited by 15 publications

References 20 publications

Limits of Biotechnological Innovation

Limits of Biotechnological Innovation

Forecasting Renewable Energy Technologies in Desalination and Power Generation Using Taxonomies

Determining the Life Cycle Phase of a Technology Based on Patent Data

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