Forman Slides

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What we do Examine geographic distribution of the site

of software patenting activity worldwide(using inventor location)

Examine extent to which patents inventedabroad are assigned to US MNCs

Decompose software patenting activity byindustry

This is not easy because of way USPTOclassifies patents

Seek to examine how user innovation shapeslocation of inventive activity


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Use of US patent data to measure location of

inventive activity What exactly is a software patent? Since software

is often an input into other inventions, it is foundthroughout the USPTO classification system

Several methods have been proposed to identifysoftware patents

Classification-based (Graham and Mowery 2003, 2005;Hall and MacGarvie 2006)

Key word based (Bessen and Hunt 2004)

Intersection of two (Cockburn and MacGarvie 2006; Halland MacGarvie 2006)

We use a combination of methods


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Inventive activity in software continues

to be concentrated in the US

0

1000

2000

3000

4000

5000

1988 1992 1996 2000 2004

Year

Japan Other G-7

All Others US

US Software Patents invented in US and Other CountriesSource: USPTO data and authors calculations


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Few software patents have been granted to

inventors in the software underdogs

0

20

40

60

80

100

1988 1992 1996 2000 2004

Year

Brazil India

China Ireland

Israel

Number of US Software Patents Invented in Underdog Countries

Source: USPTO data and authors calculations


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More software patents in the Asian Tigers,

but many are electronics-related

0

50

100

150

1988 1992 1996 2000 2004

Year

Korea Taiwan

Singapore Hong Kong

Number of US Software Patents Invented in East Asian Tigers



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An increasing share of patents invented in

underdogs are assigned to US firms

0

20

40

60

80

100

1988 1992 1996 2000 2004

Year

020406080

100

1988 1992 1996 2000 2004Year

Asian Tigers Other G-7

Underdogs All Others

Percent of Patents Assigned to Firms in Region for US Software PatentsInvented in Software Underdogs (Top Panel US; Bottom Panel All Others)



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How does globalization of software

invention vary by industry? Some dimensions that may influence

where to locate inventive activity insoftware

Distance to technical frontier: Proximity to USuniversities and highly skilled software labor(e.g., Thursby and Thursby 2006)

Proximity to lead users: Transition of new

inventions to usable economic products oftenis a difficult process, often requires user inputs(e.g., Rosenberg 1963; Rosenberg 1983)


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Importance of lead user innovation

varies by software industry User co-invention has been found to be

particularly important to enterprisesoftware that is embedded in business

processes (Bresnahan and Greenstein1996)

Likely less important for new softwaretools and technical enhancements that are

not connected with business processes


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Classifying software patents Existing classification systems (e.g., USPTO, IPC)

are based upon technological rather than marketdifferences

Need to derive independent classification systembased upon software markets

We use text mining to perform this classification Use features (words) of patents to group similar patents

together

Cockburn and MacGarvie (2006) develop another

classification system based on USPTO classes andcitation patterns Our results are robust to use of their classification

system


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Use of text mining to classify software

patents Use industry classification system in Corptech

database of technology companies

e.g., artificial intelligence, warehousing/distribution,transportation software, utility software

Aggregated some classes together which were small andsimilar

Develop training set of patents for which weknow the classification

Patents in single industry firms Feature selection: words in patent abstract and

title (also experimented with description, claims)

Also used USPTO and IPC classes as features


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Percent of all software patents by

category

Percent of Patents Invented in Each Software Category Worldwide,1989-2005


Percent Patents by Softw are Category, Wor ldw ide

17.46%

25.67%

56.87%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

Business Sof tw are Other Technical Sof tw are


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Software Underdogs are less likely to

patent in enterprise software

Percent of Patents Invented in Each Software Category inUnderdogs, normalized by comparable US percentage, 1989-2005


Relative Contribution to Innovation Input in Software Underdogs vs. U.S.

80.48%

93.48%

108.93%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Business Software Other Technical Software

%S

of.Und.

/%U.S

.


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However, there is variation within the

underdogs: Israel

Percent of Patents Invented in Each Software Category in Israel,normalized by comparable US percentage, 1989-2005


Relative Contribution to Innovation Input in Israel vs. U.S.

75.81%

86.55%

113.50%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


%S

of.Und.

/%U.S.


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However, there is variation within the

underdogs: India

Percent of Patents Invented in Each Software Category in India,normalized by comparable US percentage, 1989-2005


Relative Contribution to Innovation Input in India v s. U.S.

105.69%

140.87%

79.80%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

140.00%

160.00%

Business Sof tw are Other Technical Sof tw are

%S

of.Und.

/%U.S.


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Asian tigers also predominately patent in

technical areas

Percent of Patents Invented in Each Software Category in AsianTigers, normalized by comparable US percentage, 1989-2005


Relative Contribution to Innovation Input in Asian Tigers vs. U.S.

75.11%

55.98%

127.51%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

140.00%


%S

of.Und.

/%U.S.


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Conclusions Considerable evidence that US continues

to lead in inventive activity in software

US MNCs account for large and increasing

share of patents invented in softwareunderdogs However, relatively little evidence of shift in

inventive activity assigned to US firms abroad

Demonstrate that lead user innovationshapes location of inventive activity Inventive activity offshore is primarily intechnical software industries


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Next Steps Field work to further understand the

mechanisms driving our results

Additional empirical analysis of the factors

shaping the site of inventive activity insoftware


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Thanks!


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Backup Slides


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Investigation of Potential Home Country

Bias: European Software Data

European Patent Office Software PatentGrants by Country of the Assignee and Year

of ApplicationSource: Thoma and Torrisi (2006)

Documents

Forman Slides