The current database project aims at developing science and innovation indicators through patent and publication data

for world top business R&D spenders.

The EU Industrial R&D Investment Scoreboard of European Commission (The Scoreboard) represents around 90% of

total world business R&D spending in 2014. 1 The project firstly matches this highly representative firm sample with their

patent and publication data. . The core constructed database combine firms’ science and innovation indicators with firms’

financials data.

Furthermore, cleaning of researcher names and matching between inventors and authors allow for identification of two

important information about the private sector researchers: (i) Firm-level author-inventor pairs among researchers that

are active in publishing and patenting and (ii) Accurate information about the inventor teams of patents and author teams

of publications such as their size, geographical dispersion and affiliations.

The following sections describe the database construction, main results of matching of the Scoreboard with PATSTAT

and SCOPUS and then give further insights developed by the cleaning and matching of the researchers’ data of patent

and publications.

2. Data and Methodology

4. Conclusion

1. Introduction

3. Results

5. References

3.Results (Continued)

Business patenting and publishing:

Evidence from world top R&D spendersEla INCE

ULB, SBS – EM

European Center for Advanced Research in Economics and Statistics (ECARES)

The International Centre for Innovation, Technology and Education Studies (iCite)

Arora, A., Belenzon, S., & Patacconi, A. (2015). Killing the Golden Goose? The Decline of Science in Corporate R&D,

NBER Working Paper No. 20902.

Czarnitzki, D., & Kraft, K. (2010). On the profitability of innovative assets. Applied Economics, 42(15), 1941–1953.

Debackere, K., Magerman, T. & Van Looy, B., (2011). In search of anti-commons: patent paper pairs in biotechnology. An

analysis of citation flows. ZEW Conference on Economics of Innovation and Patenting edition:4.

Jones, B. F., Wuchty, S., & Uzzi, B. (2008). Multi-university research teams: shifting impact, geography, and stratification

in science. Science (New York, N.Y.), 322(November), 1259–1262.

Kaiser, U. (2009). Patents and profit rates. Economics Letters, 104(2), 79–80.

6. Acknowledgements

3.4. University – industry links in scientific publications

3.2. Firm-level author – inventor pairs

3.1. Patenting and publishing propensities

3.3. Technological applicability and team size in patenting

3.1.1. Patenting and publishing of top 10

Dividing number of patents and publications by R&D

spending for top R&D spenders exhibit clustering

depending on the main sector of the firm.

Samsung and Siemens mainly active on industrial goods

& services sector hold the highest patenting propensities.

However, Samsung, being active on more than one

sector, publishes more and patents less on average with

respect to its overall R&D spending.

Firms active on automobiles sector have higher patenting

but lower publishing propensities than firms active in

health care sector except for Johnson & Johnson.

Microsoft is the only software-technology firm shown

among the sample.

3.1.2. Patenting and publishing by sector

To ease the reading of graphics, sectors are aggregated

to Industry Classification Benchmark (ICB) 2-digit sector

codes.

The results exhibit differences in terms of patenting and

publishing propensities across sectors.

While some sectors are more intensively patenting such

as industrial goods & services and automobiles & parts,

other sectors such as food & beverage and utilities are

more intensive in publishing.

Except for financial services, bank and insurance sectors,

top business R&D spenders are substantially publishing

and patenting as a result of their R&D activities.

2.1. Matching the Scoreboard with PATSTAT & SCOPUS

The Scoreboard allows for building an unbalanced firm

panel with capital expenditure, operational profit, R&D

spending and employment information for the years 2000-

2013.

With the use of HAN database for PATSTAT, 79 % of the

Scoreboard firms is matched with patent applicant names.

The matching rate of the Scoreboard firms with SCOPUS is

70%.

The matching procedure allows constructing firm, sector,

patent and publication level variables for the project.

2.2. Cleaning and matching of author–inventor names

Researchers that patent are called inventors and

researchers that publish articles in scientific journals are

called authors.

Author-inventor names are cleaned and harmonised. The

first letter of first name and the full last name matching

between the author and inventor names for each

Scoreboard firm is applied for the author-inventor name

matching.

Firm-level author-inventor pairs construct on average 9.7%

of the total number of authors and 8.5% of the total

inventors of the firms.

3.3.1. Team behaviour

Firm - level inventor names’ harmonisation is implemented

for the inventor names of European Patent Office (EPO)

patents.

Cleaning and taking into account the commonness of the

first names and the surnames of inventors, inventor names

are harmonised within a firm.

The results show that the size of the patenting teams of

firms is significantly rising over time on average, leaving a

small sample of travel & leisure sector firms as an

exception.

3.3.2. Specialization vs generalization

The extent of technological applicability in patenting are

measured by the number of 4-digit international patent

classification (IPC) codes given to each patent.

IPC codes of patents represent the different areas of

technology to which they pertain.

Significant decline in the number of IPC codes of firms’

patents between 2000 and 2010 points out specialisation of

firms’ patenting over time. The only exception for this trend

is, as for the size of patenting teams, the travel and leisure

sector firms.

The percentage of academia affiliated authors within the

team of authors per publication is constructed through the

cleaning and harmonisation of author names per firm. This

gives possibility to look at the evolution of percentage of

authors from academia per publication over time.

The graphic shows the evolution for countries where the

most of the private sector publishing takes place among

the headquarter countries of top business R&D spenders.

Chinese firms have experienced the most significant rise

in university - industry links for the period 2000 – 2010.

European firms lag their American and Asian counterparts.

Correcting the EU sample size

The Scoreboard provides a separate list of the

top European business R&D spenders which leads to

a bias in the sample in terms of size between

the EU and the non - EU firms.

Excluding the medium size of the EU firms from the

full sample, the results for the low levels of university –

industry links remain significant between

the EU and the non - EU firms.

0.1

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2000 2002 2004 2006 2008 2010year

USA France Germany

UK Japan China

Contact Information:

SBS-EM, Université Libre de Bruxelles

Avenue F.D. Roosevelt 50, Brussels, Belgium

Phone: +32 (0)650 3929

Email: ela.ince@ulb.ac.be

3.2.1. Publishing of inventors

An inventor that doesn’t appear in scientific articles as an

author is called “Only Inventor” whereas the one that

publishes scientific articles in journals is called “Author

Inventor”.

Inventor – level patent quality and quantity variables are

constructed as follows through patent data:

i. Patent quality: forward citations from 3 - year window

corrected by patent family size and technology codes.

ii. Patent quantity: patent divided by the size of the

inventor team

Testing the difference between the average patenting

quality and the patenting quantity suggests that inventors

that are also active in publishing are significantly making

better and more patents than the inventors that are

concentrated only on patenting:

3.2.2. Patenting of authors

An author of a firm that is not listed among the listed

inventors of firm patents is called “Only Author” whereas a

firm author that is also active in firm patenting is called

“Inventor Author”.

Author - level publication quality and quantity variables

are constructed as follows through publication data:

i. Publication quality: publication weighted by their

journal impact factor.

ii. Publication quantity: publication divided by the size of

the publisher team.

Testing the difference between the average publishing

quality and quantity per author suggests that authors that

are also active in patenting are significantly making better

and more publications than their counterparts that only

publish:

The database is a joint project with Lauriane Dewulf, Prof. Michele Cincera and Prof. Nicolas van Zeebroeck.

I thank all members of iCite for the advice on the data.

0 .2 .4 .6 .8 1

InsuranceBanks

Financial ServicesUtilities

TechnologyMedia

Travel & LeisureRetail

Food & BeverageReal Estate

TelecommunicationsOil & Gas

Automobiles & PartsBasic Resources

Personal & Household GoodsConstruction & Materials

ChemicalsHealth Care

Industrial Goods & Services

Sectors

patent propensity publication propensity

The developed science and innovation indicators for the world top business R&D spenders allow for investigating various

questions in the literature with a highly representative sample.

First of all, as for Kaiser (2009) and Czarnitzki & Kraft (2010), the database generates profitability variable measured by

operational profit divided by sales and allows for looking at the impact of the innovative assets on the firm performance.

Furthermore, through patent and publication data and indicators generated by their combination, it is possible to make a

comparative analysis on their contribution or on firms’ preferences on the disclosure of innovation through patents and

publications as Arora et al (2015).

Second, following Jones et al (2008), research team organisations - technological behaviour in innovation could provide

evidence for the literature from private sector patenting. Furthermore, publication data enables to observe linkages

between industry and other institutions through authors’ affiliations.

Lastly, author - inventor pairs may lead to contribute to current strand of literature on author - inventor and patent –

publication pairs. Following Debackere et al., (2009), the project adds one more level to the matching procedure which is

firm - level matching and may generate firm-level patent-publication pairs. This extends the literature concentrated on

sector level analysis, on small sample of firms or on academic patent-publication pairs.

1The 2015 EU Industrial R&D Investment Scoreboard: http://iri.jrc.ec.europa.eu/scoreboard.html

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0 .05 .1 .15 .2Publishing propensity (Number of publications/€m)'

Top Business R&D Spenders

Automobiles

Basic Resources

Chemicals

Construction

Food & Beverage

Health Care

Industrials

Media

Oil & Gas

HH GoodsRetail

Technology

Telecomm.

Travel & Leisure

Utilities

Automobiles

Basic Resources

Chemicals

Construction

Food & BeverageHealth Care

Industrials

Media

Oil & GasHH Goods

Retail

Technology Telecommunications

Travel & Leisure

Utilities

11.5

22.5

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year 2000 year 2010

App

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Team size - Number of inventors per patent

Variable Obs.Only

InventorObs.

Auth.

Inventor

Mean

Diff.

Quality 1914119 0.643 277124 0.697 -0.053***

Quantity 1914162 1.670 277134 2.034 -0.365***

(*) if p < 0.05, (**) if p < 0.01, and (***) if p < 0.001.

Variable Obs. Only

Author

Obs. Invt.

Author

Mean

Diff.

Quality 2337323 1.771 227285 2.557 -0.786***

Quantity 2337319 1.307 227285 1.848 -0.542***

(*) if p < 0.05, (**) if p < 0.01, and (***) if p < 0.001.