Mapping the Time-progression of Generality in Nanotechnologies: Illustrative Examples Fernando Gómez-Baquero M.S.
[email protected]
College of Nanoscale Science and Engineering University at Albany, Albany NY 12203
Panel: New approaches to analyzing nanotechnology emergence Transatlantic Workshop on Nanotechnology Innovation and Policy March 24-26, 2010.
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Outline 1. Introduction 2. Patents and Generality 3. Time-progression of Generality a) The Dataset b) Methodology c) Results I. Pairs of Patents II. Groups of Patents
4. Conclusions
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Literature on Patent Statistics • Schmookler (1951): Patent statistics can be used as an index of inventive activity. • Griliches (1984,1991): Patent statistics are closely related to R&D expenditures, and can give insight on the returns to scale of R&D. • Trajtenberg et al. (1996): There are several patent statistics that can give insight into forms of economic activity. Some of these are: • • • • •
Number of citations Distance in technological space Average citation lag Number of self-citations Generality
1. Schmookler, J. "Invention and Economic De-velopment." Unpub. Ph.D. Dissertation, U. of Pennsylvania, 1951. 2. Griliches, Z. (1991). Patent Statistics as Economic Indicators: A Survey, National Bureau of Economic Research, Inc. 3. Trajtenberg et al. (1996). " Economics of Innovation and New Technology 5(1): 19 - 50.
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Literature on GPT and Nanotech Generality • Hall and Trajtenberg (2004): calculated Generality for U.S. patents granted 1967-1999. Described the details and limitations of the calculation. • Moser and Nicholas (2004): calculated Generality for a set of patents related to Electricity, and found no support for Electricity as GPT when compared to other technologies. • Youtie et al. (2008): calculated the Generality of “Nanotechnology”, “Drugs”, and “Computers for patents between 1990-1993. They find evidence of a higher Generality of “Nanotechnology” patents. • Gomez-Baquero (2009): calculated Generality for ‘Semiconductors’, ‘Biotechnology’, ‘Proteomics’, ‘Nanotechnologies’, ‘Carbon Nanotubes’, ‘Nanoparticles’, ‘Quantum Dots’ and ‘Self Assembly’. The Generality of ‘Nanotechnologies’ and of each nanosubclassification was on average higher than the one for ‘Semiconductors’. 1. 2.
Hall, B. H. and M. Trajtenberg (2004). Uncovering GPTS with Patent Data, National Bureau of 3. Youtie, J., M. Iacopetta, et al. (2008). The Journal of Technology Transfer 33(3): 315-329. Economic Research, Inc. 4. Gomez-Baquero, F. (2009). "Measuring the generality of nanotechnologies and its Moser, P. and T. Nicholas (2004). "Was Electricity a General Purpose Technology? Evidence from potential economic implications." Proceedings of the 2009 Atlanta Conference on Science cnse.albany.edu Historical Patent Citations." The American Economic Review 94(2): 388-394. and Innovation Policy, ed. Susan E. Cozzens and Pablo Catalán: 1-9.
How is Generality Measured? Example 1 Class
Generality Index, based on the Herfindahl Index (HHI)1: i
CITIG 2 ik G i = GEERALITYi = 1− CITIG i k=1
t=0
Originating patent
∑
Correction Factor2:
i G˜ i = Gi i −1
Forward citations
t>0 1
2
3 4 5
6
7
8
2 2 0 2 3 2 1 2 2 2 G i = 1− + + + + = 0.72 8 8 8 8 8
8 G˜ i = (0.72) 8 −1 1. Trajtenberg et al. (1996). " Economics of Innovation and New Technology 5(1): 19 - 50. 2. Hall, B. (2000). A Note on the Bias in the Herfindahl Based on Count Data. UC Berkeley and Nuffield College, Oxford. September.
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= 0.82
Problems When Calculating Generality If two patents have the same Generality, are they the same? 1. Stationary Analysis: neglects the information of how Generality evolved or transitioned to the measured value. 2. Missing information: neglects details of technological classes permeated by the technology.
Originating patent
Forward citations
Class
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t=0
t>0
Objective of This Work What information is missing? 1. Calculate time-progression profiles: for individual patents and compared in pairs. 2. Map technological classes: compare basic differences in technological classes between patents1.
Originating patent
t=0 t=1 t=2
Forward citations
t=3P
Class
1. For a more sophisticated approach look at: Rafols, I. and M. Meyer, Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience. Scientometrics, 2010. 82(2): p. 263-287. , and Porter, A. L., Roessner, J. D., Cohen, A. S. & Perreault, M. (2006). Interdiscipinary research: meaning, metrics and nurture. Research Evaluation 15, 187-96.
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Methodology 1. 2. 3. 4. 5.
1.
Choose the search strategy for ‘Semiconductors’ and ‘Nanotechnologies’. Choose a classification system. Obtain dataset of patents and their corresponding forward citations (top 1,000 cited patents for each technology). Calculate the Generality Index for all patents. Find patents with the same Generality as: Technologies
Issued Year
Patents Found
(SEMI,NANO)
Same
1
(SEMI,NANO)
Different
1
(SEMI,SEMI)
Same
0
(SEMI,SEMI)
Different
0
(NANO,NANO)
Same
3
(NANO,NANO)
Different
2
Compare Generality measurements and time-progression maps.
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Search Strategy
• Database: ISI Web of Knowledge – Derwent Innovations Index • Time span of sample: 1980-2009 • Sample: Top 1000 cited patents for each technological subject • Classification systems: International Patent Classification (4-digit level).
Search Strings from: Mogoutov, A. and B. Kahane, Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking. Research Policy, 2007. 36(6): p. 893-903. cnse.albany.edu
Dataset
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Dataset
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Pair 1
• Citations for SEMI411 expanded to B0(Separating;Mixig), B2(Shaping), C3(Metallurgy), G(Instruments) and H(Nucleonics), while citations for NANO374 are mostly on the G(Instruments) and H(Nucleonics) classes. • SEMI411 refers to a manufacturing and inspection method, while NANO374 refers to a modular electronic system. The manufacturing and inspection method would be mostly applicable for instrumentations, while the electronic system would be most applicable as a basic electronic component. cnse.albany.edu
Pair 2
• For SEMI149 most citations come from H(Nucleonics) and B6(Transporting), while for NANO457 most citations come from C1(Chemistry) and G(Instruments). • NANO457 is receiving a greater number of citations in classes C1(Chemistry) and G(Instruments), even though its original call was B(Mixing;Separating). • SEMI149 refers to a semiconductor wafer conveyor system, and NANO457 refers to a DNA sequencing array. cnse.albany.edu
Pair 3
• Both patents expand over a long range of classes, concentrating mostly on C(Chemistry) and B8(Micro- and Nanotechnology). • NANO779 refers to a method to incorporate a nanostructured chemical into a polymer. NANO536 refers to a method to solubilize carbon nanotubes. • Growth of citations of NANO536 in D0(Textiles) is consistent with the interest seen in the last few years in nanostructured textiles and reinforced fibers. cnse.albany.edu
Pair 4
• Perhaps a pair showing “expected behavior” of an emerging GPT: expanding Generality, wide variety of classes. Nevertheless, the growth in citations seems to have stagnated. • NANO836 refers to a hybrid nanocomposite for surface coatings, while NANO893 refers to an aqueous dispersion of nanocrystalline particles.
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Group 1
• Distinct paths to the same Generality for all patents. • A variety of classes with overlapping technological classes and others in separate fields. • If this was a patent portfolio, the “investor” could aim for high generality, expanding classes, and expanding number of citations.
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Group 2
• High Generality and follow almost exactly the same path. (unlike previous pairs.) • NANO398 and NANO416 have expanded in citations in almost exactly the same technology classes ( G(Instruments) and H(Nucleonics) ), while NANO721 seems to be pervasive in both these classes and in more classes. • All assigned to the same company: NANTERO INC., a private company focusing on nextgeneration semiconductor devices (primarily storage technologies) using carbon nanotubes. More than 80% of all citations in each patent are self-citations! cnse.albany.edu
Conclusions • Time-progression plots of Generality for different patents have different profiles. Relevant information might be missed when analyzing only the current value of Generality of a technology. • Maps of time-progression of citations are different for technologies with the same generality, and can aid in understanding how a technology is permeating several technological fields. • Time-progression plots and maps might be helpful in identifying emerging technologies versus mature technologies. • Time-progression plots could serve as a strategic analytical tool for both policy makers that want to promote the emergence and continued growth of GPTs.
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Fernando Gómez-Baquero M.S.
[email protected]
255 Fuller Road; Suite 214 College of Nanoscale Science and Engineering University at Albany, Albany NY 12203
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