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IntroductionIndustry and Data

Results and conclusions

Strategic Analysis Through Patent Data

Mariano A. Mantovani

Politecnico di Torino

October, 2014

Supervisor: Dr. Giuseppe Scellato

Mariano A. Mantovani Strategic Analysis Through Patent Data



Outline

1 IntroductionObjectivesTheoretical FrameworkIndicators

2 Industry and DataThe Aircraft Manufacturing IndustryTimelineDataset Construction

3 Results and conclusionsResultsSelected Profitability IndicatorsAirbus in 2006




ObjectivesTheoretical FrameworkIndicators

Objectives

This thesis has the following objectives

Analyze the technological portfolios of the companies.

Test methods for computing distance, coherence andconcentration of their knowledge base.

Analyze the evolution of the innovative strategies and financeperformance of companies in the aeronautic sector, inparticular: Airbus and Boeing.





Main Elements

Knowledge-Based View of the firm: Similar to RBV (Penrose),Knowledge is the main resource for acquiring competitiveadvantage (Grantt, Aino) and factor of production.

Indicators

Concentration (Leten-Firms and markets concentration).Coherence (Nesta Innovative performance of farmaceuticalfirms,Quatraro-Knowledge transferences and its effects inproduction, Bart Leten-Diversification and performance offirms)Distance (Jaffe-Technological opportunities and Spillovers,Bar-Technological distance between firms)





Herfindahl Index

Used to measure the degree of concentration of patents amongdierent classes. The index takes a value of 1 when patents tend tobe concentrated between few classes and of 0 when they arespread.

HI =∑i

(Ni

N)2 (1)





Coherence of the Knowledge Base

Coherence is based on the degree of technological relatednessaccording to a randomness test. Weighted average relatedness oftechnology is dened as:

WARi =

∑i 6=j τijpj∑i 6=j pj

(2)

The coherence of the firm’s knowledge base estimates the averagerelatedness of any technology randomly chosen within the rm withrespect to any other technology.

COH =n∑

i=1

(pi∑i pi

WARi ) (3)





Distance Indicators

Min-Complement Distance

The complement of the share of overlap.

M(Pi ,Pj) = 1 −n∑k

MIN(pik , pjk) (4)

Cosine Index

Measures the cosine of the angle of the vectors.

C (A,B) = 1 −∑n

i=1(tfai logNpi

ni)(tfbi log

Npi

ni)√∑n

i=1(tfai logNpi

ni)2√∑n

i=1(tfbi logNpi

ni)2

(5)

Logarithms are adjustments for information content weighting.




The Aircraft Manufacturing IndustryTimelineDataset Construction

Main Aspects of the Industry

Duopolistic structure.

Huge overhead and R&D expenditures.

Backlog.

High barriers to entry and exit.

Airbus Group

Formed as EADS in 2000.Project to unify the industry inEurope. 80% of revenues comefrom CA, competitive on thissector, but lately also in spaceand helicopters.

Boeing Company

Strongly tied to American historyand government, founded in1916, boosted by wars and spacecampaigns. Competitive in CivilAircraft but also in defense andspace.





Some Events of the Past Decade





Dataset Construction

The analysis is performed using the Thomson patent database.

Patents are grouped by families and inventive activity by thepriority date.

Countings are done according to the IPC classification at classand group levels.

The time framework is from 2000 to 2011.

Financial information and other corporate information is obtainedfrom the Annual Reports, disclosed to the public every year.





Dataset Construction

Using the data:

Compute of concentration at the class level for each portfolio.

Compute of the distance using both indicators at class andgroup level for the most relevant class.

Construction of a matrix of relatedness of the classes andcomputation of the coherence of the knowledge base of eachcompany.




ResultsSelected Profitability IndicatorsAirbus in 2006

Concentrations

The concentration measureshows that Airbus inventions areclassified with moreconcentration, while Boeingremains relatively constant.Please note the increase forAirbus from 2005 to 2006. Highfrequency classes:

B64: Aircraft, aviation,cosmonautics.

G01: Measuring, testing.





Distance - Class Level

Bothdistancemeasuresshow thesamepattern.Since year2007 starts adiversifica-tionprocess.





Selected Evidence of the Distance

The graph showsthe percentage ofinventions of eachportfolio thatclassifies into G01.Notice increasingand decreasingrates from year2007.





Coherence

Coherence may increasefor two reasons:

Investments classifyconstantly to thesame class.

Investments areclassified in classeswith positiverelatedness.

The companies underanalysis follow mostly thesame path.





Returns on Assets

2002 and 2009 falls inworld passenger trafficcaused by the terroristattacks and theinternational financialcrisis. Airbus ratios in2006 and 2007 havedifferent causes.





Some Events of the Past Decade





Airbus in 2006 and the Power8 Program

Airbus suffered falls in profitability in 2006 due to technologicalproblems -Result of unsuccessful R&D- with the A380 and otherprojects like the A400M and the A350.

Two points of thePower8 Program:

Develop Faster

Focus on CoreBusinessActivities





Conclusions, advantages and drawbacks

A couple of drawbacks

Related to patent procedure and database

Other ways of protecting knowledge

Coclusion and Advantages

Results show a dependence between the firms performance andinventive activity. Measuring patent portfolios with indicatorsallows to:

Find periods and fields of diversification and hence

locate and describe trends on the inventive strategy ofincumbents





Thank for your attention


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