Introduction to the economics of innovation

Introduction to the economics of innovation
UE « I&E Basics »
Diego Useche
diego.useche@univ-rennes1.fr
University of Rennes 1.

Lecture1 : Measuring innovation

• Schumpeter who may be seen
as the grandfather of modern
innovation theory gave a
broader definition of innovation
not only referring to technical
change. He referred also to
new forms of organisation and
to the opening of new sources
of raw materials and new
markets (Schumpeter 1934).
3

Creative destruction
• The way in which old
ways of doing things
are endogenously
destroyed and
replaced by the new
4
Surviving
Creative
Destruction is a
challenge for
firms and
industries

Invention, Innovation, Diffusion
(Schumpeterian trilogy)
• Invention: creation of an idea to do or
make something new ( profitability not yet
verified)
• Innovation: new product/ process/
business model that is commercially
valuable
• Diffusion: the spread of a new invention/
innovation throughout society
5

What is the ‘economics of
innovation’?
Microeconomics – understanding processes,
including how incentives affect firms
Macroeconomics – ‘innovation’ drives economic
growth.. and economic growth drives living
standards, environmental, political…
Economic Policy – are there market failures in the
innovation process and what, if anything, should
the government do?
Business Strategy – this is not a course on
advising firms how to innovate, but does include
some insight into this

Measuring Innovation
Oslo Manual - 2005:
(Guidelines for collecting and
interpreting innovation data)
(central reference document for the statistical
definition of innovation and forms the basis for
surveys of innovation throughout the world)
UIS - Annex to the Oslo
Manual Measuring Innovation
in Developing countries

Why measure innovation?
• Innovation – key to the growth of output and
productivity.
• The relationship between innovation and
economic development is widely acknowledged.
• Innovation policy should be evidence-based.
• Innovation data – to better understand
innovation and its relation to economic growth;
to provide indicators for benchmarking national
performance.

What is innovation?
An innovation is the implementation of a
new or significantly improved product (good
or service), or process, a new marketing
method, or a new organisational method in
business practices, workplace organisation
or external relations.

The innovation measurement framework
Business enterprise (all firms, organisations and institutions whose primary activity is the market production of
goods or services (other than higher education) for sale to the general public at an economically significant price,
as well as the private non-profit institutions mainly serving them. Includes public enterprises). This includes
‘private enterprises’ as well as ‘public enterprises’.

Types of innovations
• Product innovation: introduction of a good or service
that is new or significantly improved with respect to its
characteristics or intended uses. This includes significant
improvements in technical specifications, components
and materials, incorporated software, user friendliness or
other functional characteristics.
• product used by consumers
• Microwaves, computers, mobile phones, etc
• Products use by firms
• Shipping containers, computers, robots, etc

• Process innovation: implementation of a new or
significantly improved production or delivery method. This
includes significant changes in techniques, equipment
and/or software.
• Used by consumers
• Fast food, air travel
• Used by firms
• Assembly lines, software
• Marketing innovation: implementation of a new
marketing method involving significant changes in product
design or packaging, product placement, product
promotion or pricing.
• Organisational innovation: implementation of a new
organisational method in the firm’s business practices,
workplace organisation or external relations.
12

Degree of novelty
• No universal agreement of which
• Radical vs incremental
– Radical (steam, internal combustion engine,
computers, internet)
– Incremental (constant improvements)
– Both important in driving economic growth
• Diffusion
• New to the firm
• New to the market
• New to the world
• Disruptive innovations

Degree of novelty
• Diffusion is the way in which innovations spread,
through market or non-market channels, from their first
worldwide implementation to different consumers,
countries, regions, sectors, markets, and firms. Without
diffusion, an innovation will have no economic impact.
The minimum entry for a change in a firm’s products or
functions to be considered as an innovation is that it
must be new (or significantly improved) to the firm.
• New to the firm: A product, process, marketing method,
or organisational method can already have been
implemented by other firms, but if it is new to the firm (or
in case of products and processes: significantly
improved), then it is an innovation for that firm.

Degree of novelty (continued)
• New to the market:
– the firm is the first to introduce the innovation onto its market.
– The market is defined as the firm and its competitors.
– The geographical scope is subject to the firm’s own view of its
operating market and thus can include both domestic and
international firms.
• New to the world:
– the firm is the first to introduce the innovation for all markets and
industries, domestic and international.
– implies a qualitatively greater degree of novelty than new to the
market.
• Disruptive innovations:
– an innovation that has a significant impact on a market and on
the economic activity of firms in that market.
– focuses on the impact of innovations as opposed to their novelty.
– These impacts can, for example, change the structure of the
market, create new markets, or render existing products
obsolete. However, it might not be apparent whether an
innovation is disruptive until long after the innovation has been
introduced.

Innovation activities
Innovation activities
are all scientific, technological, organisational, financial
and commercial steps which actually, or are intended to,
lead to the implementation of innovations. Some
innovation activities are themselves innovative, others
are not novel activities but are necessary for the
implementation of innovations. Innovation activities also
include R&D that is not directly related to the
development of a specific innovation.

Innovation activities for product and process innovations
• Intramural (in-house) R&D: This comprises all R&D conducted by the enterprise,
including basic research.
• Acquisition of R&D (extramural R&D): R&D purchased from public or private
research organisations or from other enterprises (including other enterprises within
the group).
• Acquisition of other external knowledge: Acquisition of rights to use patents and
non-patented inventions, trademarks, know-how and other types of knowledge from
other enterprises and institutions such as universities and government research
institutions, other than R&D.
• Acquisition of machinery, equipment and other capital goods: Acquisitions of
advanced machinery, equipment, computer hardware or software, and land and
buildings (including major improvements, modifications and repairs), that are
required to implement product or process innovations.
• Other preparations for product and process innovations: Other activities related
to the development and implementation of product and process innovations, such as
design, planning and testing for new products (goods and services), production
processes, and delivery methods that are not already included in R&D.
• Market preparations for product innovations: Activities aimed at the market
introduction of new or significantly improved goods or services.
• Training: Training (including external training) linked to the development of product
or process innovations and their implementation.

Innovation activities for marketing and
organisational innovations
• Preparations for marketing innovations: Activities
related to the development and implementation of new
marketing methods. Includes acquisitions of other
external knowledge and other capital goods that are
specifically related to marketing innovations.
• Preparations for organisational innovations: Activities
undertaken for the planning and implementation of new
organisation methods. Includes acquisitions of other
external knowledge and other capital goods that are
specifically related to organisational innovations.

Kinds of innovation activities
• Successful in having resulted in the
implementation of a new innovation
(though they need not have been
commercially successful).
• Ongoing, work in progress, which has not
yet resulted in the implementation of an
innovation.
• Abandoned before the implementation of
an innovation.

Classifying firms by degree of
innovativeness
• The innovative firm is one that has introduced an innovation
during the period under review. The innovations need not have
been a commercial success – many innovations fail.
• An innovation active firm is one that has had innovation
activities during the period under review, including those with
ongoing and abandoned activities. In other words, firms that
have had innovation activities during the period under review,
regardless of whether the activity resulted in the
implementation of an innovation, are innovation active.
• A potentially innovative firm is one type of “innovation active
firm”, that has made innovation efforts but not achieved
results. This is a key element in innovation policies: to help
them overcome the obstacles that prevent them from
being innovative (converting efforts into innovations) – Annex
for developing countries.

Factors influencing innovation
• Objectives: Identifying enterprises’ motives for
innovating and measuring their importance
• Hampering factors: reasons for not starting innovation
activities at all, or factors that slow innovation activity or
have a negative effect on expected results. These
include economic factors, such as high costs or lack of
demand, enterprise factors such as lack of skilled
personnel or knowledge, and legal factors such as
regulations or tax rules. The ability of enterprises to
appropriate the gains from their innovation activities is
also a factor affecting innovation.

Objectives and effects of innovation
• Competition, demand and
markets
• Replace products being phased out
• Increase range of goods and services
• Develop environment-friendly products
• Increase or maintain market share
• Enter new markets
• Increase visibility or exposure for
products
• Reduced time to respond to customer
needs
• Production and delivery
• Improve quality of goods and services
• Improve flexibility of production or
service provision
• Increase capacity of production or
service provision
• Reduce unit labour costs
• Reduce consumption of materials and
energy
• Reduce product design costs
• Achieve industry technical standards
• Reduce production lead times
• Reduce operating costs for service
provision
• Increase efficiency or speed of
supplying and/or delivering goods or
services
• Improve IT capabilities
• Workplace organisation
• Improve communication and
interaction among different business
activities
• Increase sharing or transferring of
knowledge with other organisations
• Increase the ability to adapt to different
client demands
• Develop stronger relationships with
customers
• Improve working conditions
• Other
• Reduce environmental impacts or
improve health and safety
• Meet regulatory requirements

Factors hampering innovation activities
• Knowledge factors:
• Innovation potential (R&D, design, etc.)
insufficient
• Lack of qualified personnel: Within the
enterprise / In the labour market
• Lack of information on technology / markets
• Deficiencies in the availability of external
services
• Difficulty in finding co-operation partners
for: Product or process development /
Marketing partnerships
• Organisational rigidities within the
enterprise: Attitude of personnel/ managers
towards change, Managerial structure of
enterprise
• Inability to devote staff to innovation activity
due to production requirements
• Institutional factors:
• Lack of infrastructure
• Weakness of property rights
• Legislation, regulations, standards, taxation
• Cost factors:
• Excessive perceived risks
• Cost too high
• Lack of funds within the enterprise
• Lack of finance from sources outside the
enterprise: Venture capital / Public sources
of funding
• Market factors:
• Uncertain demand for innovative goods or
services
• Potential market dominated by established
enterprises
• Other reasons for not
innovating:
• No need to innovate due to earlier
innovations
• No need because of lack of demand for
innovations

Impacts and outcomes
• Impacts of innovations on firm performance range
from effects on sales and market share to changes
in productivity and efficiency. Important impacts at
industry and national levels are changes in
international competitiveness and in total factor
productivity, knowledge spillovers of firm-level
innovations, and an increase in the amount of
knowledge flowing through networks.
• The outcomes of product innovations can be
measured by the percentage of sales derived from
new or improved products.

Lecture 2 : the origins of innovation

Causation? Demand pull or
technology push
• Who initiates innovation projects? The
R&D departement or the marketing
departement ? Is innovation a reaction to
user demand, or it create demand?
• Technology push- linear model from
technology to market
• Demand pull- linear models from market to
technology
26

The laser
• Charles Townes on the laser:
• « Bell’s patents departement at first
refused to patent the our amplifier or
oscillator for optical frequences because, it
was explained, optical waves had never
been of any importance to communication
and hence the invention had little bearing
on Bell system interest »
27

Technology push
• When R&D or a technology breakthrough drives the
launch of a new product
• Example: laser invented with out direct application, now
applied in a wide range (telecom, medical, music,
science, etc)
• R&D split into basic, applied and development
• Specialization pattern of institutions carrying out R&D
• Implications
– Large firms have an advantage because science
takes resources
28

Demand pull
• When the market demand for a solution to a
problem or need in the marketplace triggers the
development of a new product
• Innovation as a response to profit opportunities
• Example: Miniaturization of digital cameras and
photo editing software
29

Chain-linked model of
innovation (Rosenberg & Kline, 1986)

Technology push approach
• 1. Focus on technical issues & problems
• 2. Trigger a search for scientific and
technical knowledge both within the firm
and external knowledge sources
• 3. Develop an innovative, technical
solution to offer in the marketplace
32

Market-pull approach
• 1. External market needs are recognized
that trigger a search for scientific and
technological knowledge
• 2. Analized by the firm for pontential
solutions
• 3. Leads to an innovative offering in the
marketplace
33

Technical Linking
• Prerequisites:
– Creative insigth and talent
• Relate a technical problem to external or internal
scientific knowledge
• Which resources are available inside and outside
the firm?
• Unique expertise
• View a solution to the problem as both feasible and
relevant for users or customers
34

Emphasis on technical Linking
35
Emphasis on need
Linking
Low
Low
High
High
Technology and market Linking
Low
Linking:
Weak
venture
potential
Technology-
Push
Market Pull
Double
Linking :
Strong
Ventire
pontential
Innovation will have greater impact

How innovations Informs Markets
• Start with a minor
innovation
• Unclear technology
opportunity
• Absence of a product
champion
• Identify market
response
• Validate the need with
research and data
• Test feasibility
• Product champion
guides developement
36

• Innovation has the dynamics of an upspiral
• with social returns substantially greater than
private returns.
– The extra is due to consumer benefits from better and
less expensive products,
– spillover benefits to other firms from the availability of
better and less expensive inputs,
– generalized benefits from the dissemination of the
knowledge and information content of the innovation,
– all net of the losses of profits to the losers in the
innovation competition that the successful firms won.
Such positive externalities make the case
for public support to foster innovation

The “Four Pillars of the Knowledge
Economy”
Education and training
Information
infrastructure
Innovation systems
Economic incentives
and the institutional
regime
Need proactive policies and market forces working
together
http://go.worldbank.org/5WOSIRFA70

Inside and market-oriented
innovation
• Market-oriented innovations apply to the
products and services sold into the market.
• New outputs may also require new internal modes of
operation.
• Inside-oriented innovations apply to the inner
workings of an enterprise,
• are aimed at improving productivity and performance
through establishment or change of best practices,
• include process innovations that apply to
manufacturing technology, but extend to services
providing organizations as well.

Inside-oriented innovation faces
fewer hurdles for its benefits
• Less needy of IP protection
• less subject to escape and imitation.
• Less needy of special modes of finance
• personnel opportunity costs
• cash purchases of ICT and other equipment
that can serve as collateral for their own
financing.

But, inside-oriented innovation needs
adaptive management skills
• Recent research on European experience:
– inside-oriented innovation key for productivity,
– but highly vulnerable to inhospitable firm culture.
– e.g. managerial flexibility and organizational
devolution are critical for ICT to drive inside-oriented
innovation and productivity gains. (see Bloom, Sadun and
Van Reenen papers)
• Public-private partnerships can bring needed
management models and training, along with
financed equipment and systems.

The drivers of innovation
firm and industry level
42
See for an example; WIPO report 2017, Chapter 4 -Smartphones: what,s
inside the box? Intagible Capital in Global Value Chains

The drivers of innovation
• 1.Market
attractiveness
• 2. Growth potential
• 3. Competitor reactivity
• 4. Risk distribution
• 5. Industry restructure
potential
• 6. Political and social
constraints
• 7. Availability of capital
• 8. Manufacturing
competence
• 9. Marketing and
distribution channels
• 10. Technical support
capability
• 11. Access to critical
components
• 12. Level of
management support
43

44
Up to 35% of all
patents filed
worldwide since 1990
may
35%
relate to
smartphones.
Designs of user
interfaces are also
heavily protected.

• 1.Market
attractiveness
• Sales/ profits
• Existence of barriers to entry
• Firms capacity to take a part of
the market and generate sales
and profits
• Example:
• How samsung’s next
generation of smartphones is
likely to break into the market
and displace sales of
competitors’ products
• 2. Growth potential
• The size (expected) of a
market and the degree of
competition
• Example:
• How much growth potential is
there for a new smartphone
before market demand is
satisfied or competitors provide
an alternative?
45

• 3. Competitor
reactivity
• Can be measured in 3 ways:
• 1) the ability of a dominant
competitor to quickly respond
to a new entrant
• 2) the degree of IP protection
of the innovative idea
• 3) the rate at which competitive
solutions reduce the product
life cycle of new innovation-
46

• 4. Risk distribution
• Product line diversity that can respond to a competitor’s innovations
• An example:
• The broad product portfolio of smartphone producer that has a range
of products to weather economic turbulence in the market place
• Diversification reduce risk
47

• 5. Industry restructure
potential
• Can be measured in 3 ways:
• Some innovations may cause
a complete restructuring of
an industry or segment within
an industry
• An example:
• Imagine a new technology as
poweful battery that allows
smartphones to run for more
of 10 days without re-
charging- this is a disruptive
technology
• 6. Political and social
constraints
• Changing tariff and trade
restrictions can often create
barriers for firms to move
innovative products across
borders and into potential
markets
• An example:
• Microsoft/ Google ware sued
by EU governments for
operating as monopolies
48

• 7. Availability of
capital
• For start-ups, limited
capital reduces
management flexibility
• An example:
• Most of start-ups in
technology sectors are
confronted to lack of
capital
• See also Lecture 4:
Financing of innovation
• 8. Manufacturing
competence
• Have the company the
abililty to rapidly
prototype a new product
and gain market entry
• An example:
• The phone industry is
confronted to rapid
technology change
49

• 9. Marketing and
distribution channels
• The ability to gain early
entry and rapid
penetration to global
markets
• Global companys have
an advantage compared
to small local company
• Internet related company
also have an advantage
• 10. Technical support
capability
• How well a service
function support sales
with expertise to carry out
incremental
improvements
• Example:
• Most of the MNC have a
service support where
customer data is used to
modify operations
50

• 11. Access to critical components
• Reliability of critical materials supply and components
essential for a sustained operation
• Dependence to providers (cameras, processor, etc)
• Dependence of software (OS)
51

• 12. Level of management support
• Measure of top management support for internal
entrepreneurial initiative
• Example:
• When google top managers allows employees time to
explore innovative opportunities as part of their regular work
responsabilities
52

Lecture 3: Economics of intellectual property

Traditional Explanations for IP
1. The non-rivalrous nature of knowledge and information
– Knowledge and information are private goods (costy to production)
– They are public goods in consumption
– IP creates a policy restriction in order to compensate for the cost of
production of the knowledge or information
–
54

2.To get new knowledge into the open (Saxophone vs Violin)
– The saxophone is the only instrument in the orchestra that was
once patented (in 1846 by Adolphe Sax in France). The next 70
years, 14 patents were taken out in relation to the saxophone
by Adophe and competitors. Much of knowledge for that
technology has been in the public domain for well over 100
years now, and anyone can make or use the saxophone.
– The technology for making violins was family- based and
secret, in Cremona (Italy) in the 17th and 18th centuries.Today
nobody knows how -the very best violins that the world has ever
heard – by Stradivari, Guarneri and others – were made. The
secret of their manufacture has been lost in time.
55

What exactly is IP?
• The term ‘IP’ refers to unique, value-adding creations of
the human intellect that results from human ingenuity,
creativity and inventiveness.
• An IP right is thus a legal right, which is based on the
relevant national law encompassing that particular type
of intellectual property right.
• Such a legal right comes into existence only when the
requirements of the relevant IP law are met
• IP provides the owner of such legal property rights the
right to exclude all others from commercially benefiting
from it.
56

The different types of IP rights
include:
• Copyright
• Industrial Property
• a.Trademarks
• b. Patent
• c. Industrial designs
• d. Confidential information
• E Geographical Indications

The IP Chain of Activities
• Creation
• Innovation
• Commercialization
• Protection
• Enforcement

IP as intangible property
• Tangible property
– Land, houses, estates,car
• Intangible property
– intellectual property
– Intangible wealth, easily appropriated and
reproduced, once created the marginal cost of
reproduction is negligible

The role of IP as intangible
property
1. Economic rights of creators
2. Commercial exploitation of owner of IP
3. Capital expenditure
4. Transfer of technology
5. Cultural development

Why IP protection is given?
• Increase capital expenditure for new products
• Favor R&D
• Serve as : marketing and advertisement tool
• Avoid free loaders (free riders)-
• Maintaining loyal followers
• profit

IP as a property
• Can be sold
• Can be bought
• Can be lease or rent
• Can pass under a will (heritage)
• Can be assigned

Role of IP in Innovation
• Innovation is cumulative and collective
• IP will play an important role in reducing
risk for the players involved, who may then
be able to reap acceptable returns for their
participation in the process.
• IP plays a major role in enhancing
competitiveness of technology-based
enterprises
63

The Laws For Intellectual
Property Protection
• Copyright Act 1987
• Trademarks Act 1976
• Patent Act 1983
• Industrial Design Act 1996
• Geographical Indications Act 2000
• Law of Tort
• -passing-off
• Confidential information

Protection for Copyright
• Protection given by law for a term of years
to the composer, author etc… to make
copies of their work..
• Work include literary, artistic,
musical,films, sound
recordings,broadcasts.
• Commercial and moral rights.
• No registration provision.

Protection for trade marks
• Commercial exploitation of a product
• To identify the product, giving it a name
• “mark” includes a device, brand, heading,
label, ticket, name, signature,word, letter,
numeral or any combination.
• Does not include sound or smell

Trade marks (cont.)
• Can either be registered or not registered
• Advantages of registered trade marks
• Application can be made for goods and
services
• Perform certain function such as indication
of quality,identifying a trade connection

• Trademarks and industrial designs play an important role in the
marketing process
• A trademark is a useful tool in launching new product segments
• Trademarks can be very effective in penetrating new markets.
Honda, for example, took advantage of its reputation in
motorcycle engineering to penetrate the US car market
• Trademarks are also useful in extending commercial benefits
beyond the life of a patent.
• ------------------------------------------------------------------------------
« The case of Aspirin® provides a good example. Developed in
1897 by Felix Hoffman, a research chemist working with Bayer
Company in Germany, the drug was patented in 1899 by the
Bayer Company. Knowing that patents have a limited duration,
the Bayer Company embarked upon promoting a trademark for
its new product. When the Aspirin ® patent expired, the company
continued to benefit from the sale of aspirin through its
established trademark Aspirin ®. »
68

Protection for patent
• Basic idea of granting a patent
• “ the applicant applied to the government
for the right of patent and in return for the
monopoly given he must disclose
everything about the invention in the
patent document” ( the description)
• Duration 20 years.

Patent (cont.)
• Patent for invention
• Patent can be applied for a product or a
process.
• Patentable invention must be new,involves
an inventive step and industrially
applicable (EU )
• Priority date- first to file

Requirements for a Patent (US)
• To obtain a patent, the new invention
must be:
– Novel – not known or used in this country
and not published anywhere.
– Nonobvious – cannot be an obvious way to
do something.
– Useful – must have some application, even
if not commercially practical.

Patentable Subject Matter
• Must be:
–composition of matter, machine, article of manufacture,
plant, design, or process/method.
• Cannot be:
–An idea (i.e., Scientific principle, law of nature, or pure
algorithm), printed matter, naturally occurring substance
(i.e., not purified or genetically engineered), mental steps,
or something illegal.
• Foreign Law
– May additionally exclude some biological inventions, methods of
treating patients, patenting living things, etc..

Role of Patents in R&D
• Role of patent exclusivity
– Patents enable members of a research and
development team to ensure that the “output”
of the effort (e.g., a new product or service)
cannot be used without authorization
• Prevents “free riding” on the investments made by
the team by preventing unauthorized use of what is
patented
• Enables the team to (a) receive a fair return on their
investment, and (b) ensure that the patented
technology is effectively exploited by delivering new
products and services to the market

10/22/18
Patent Activity – Value to
Industry (1)
Question: How do patents drive
industry?
Answer: They capture the
“knowledge” component of a
product and permit value
extraction.

10/22/18
Patent Activity – Value to
Industry (2)
Why Companies Care About IP:
§ Freedom to Operate (FTO)– make
sure someone else’s IP will not
prevent your company from carrying
out its business objectives
§ Competitive Advantage – Protect
your company’s IP so it can be used
to gain a competitive advantage in
the marketplace through precluding
others from utilizing the IP

Protection for industrial designs
• Protection for industrial designs that are
new or original
• Design are feature of shape, configuration,
pattern or ornament
• The design must be applied to an article
• The design must be applied by an
industrial process.
• Appeal to the eye.

Protection for geographical
indications
• Meaning “ an indication which identifies
any goods as originating in a country or
territory, or a region or locality where a
given quality, reputation or other
characteristic of the goods is essentially
attributable to their geographical origin”

Protection for geographical
indication
• Product must come from a particular
geographical territory
• Uses a name link to the particular geographical
nature of the territory
• Such as labu sayung from the sayung Perak,
• Batik Trengganu,batik Kelantan etc.
• To stop others from using

Examples of GI
• Swiss made
• Swiss chocolates
• Sarawak pepper
• Salted egg
• Sweet tamarind

Lecture 4: Financing of innovation
Main sources:
Bravo-Biosca et al. (2014) Financing Business Innovation: A Review of External Sources of Funding for
Innovative Businesses and Public Policies To Support Them. World Bank Group
Paschen, J. 2017. Choose wisely: Crowdfunding through the stages of the startup life cycle. Business
Horizons, 60(2): 179–188.
Rossi, M., Lombardi, R., Siggia, D., & Oliva, N. 2015. The impact of corporate characteristics on the
financial decisions of companies: evidence on funding decisions by Italian SMEs. Journal of Innovation
and Entrepreneurship, 5(1).

The returns to innovation investment are
highly uncertain
• Not only is innovation a risky activity, with failure a common
outcome; it is also uncertain.
• Two types of uncertainty are typically present—technological and
market uncertainty
– Developing a new pharmaceutical often carries considerable
technology risk but the market is usually easy to define because the
number of people with a particular medical condition and the system
for purchasing drugs in each country can both be easily identified.
– Clean technologies vary in the degree of technology risk but often
have considerable market risk (government policies often changes)
– The technology risk of new online businesses is often quite low,
market risk can be very high (hard market identification and complex
B. models)
81

• Risk and uncertainty depends on many factors
1.The nature of the innovation activity and its industry
2.The stage of the innovation process:
3.The size and age of the firm
4.Business environment (country, region,
country/industry)
82

The market as provider of finance for innovation
Markets underinvest in innovation for several reasons:
• Asymmetric information: Information about
the likelihood of success of a particular innovation project
is not only limited, but asymmetric. The entrepreneur (or
firm) looking for finance has more accurate information
than potential investors about how promising an
innovation project is, as well as about the entrepreneur’s
effort and choices when developing it. This leads to two
classical sources of market failure
– Adverse selection
– Moral hazard
83

Adverse selection:
• If banks don’t know the default risk of an INNOVATOR/
INVENTOR, they can only price a loan based on the
average default risk. As a result, low-risk INNOVATORS
face higher interest rates than they would if there were
perfect information, and they may choose not to seek
loans. This increases the risk of the remaining pool of
INNOVATORS, since those who are willing to pay high
interest rates are usually also high-risk. Therefore, this
pushes up the interest rate the bank needs to charge to
break even, which in turn may discourage lower-risk
INNOVATORS from applying for funding, increasing
again the default risk in the remaining pool.
84

Moral hazard:
• Banks cannot perfectly monitor the activities of the
INNOVATOR/INVENTOR after the loan has been
approved. As a result, an INNOVATOR may be tempted
to take on a more risky project than what had been
originally agreed upon, since in case of success he or
she gets of all the upside, while in case of failure the loss
is capped. Moreover, if the firm is close to being in
financial distress, the cost for the inventor of taking on
additional risk becomes negligible, which can lead to the
inventor’s choosing recklessly risky projects.
85

3 additional market failures
1. Externalities: Innovation activities generate spillovers,
since inventors rarely can fully appropriate the returns their
innovation. They cannot, however, prevent other firms’
learning from both their successes and failures (which can
also provide valuable lessons) and replicating, fully or
partially, some of their successes, whether by launching
similar products or services or adopting similar processes or
business models. As a result of these spillovers, the
social return to innovation investment is higher than the
private return, and markets invest less in innovation than
is socially optimal.
86

2. Coordination failures: Innovation activity happens
within a “system,” with different actors and networks as well
as underlying infrastructure and institutions. Entrepreneurs
come up with ideas, investors back them with their funding,
and the new firms try to attract talent, suppliers, partners,
and customers. If successful, they expand, go through an
IPO, or are acquired in a profitable trade sale. Most (if not
all) parts of the system need to be in place for it to function
well, and missing parts may not emerge if some others are
missing. This creates the typical chicken-and-egg
problem and is one reason clusters are so difficult to
replicate.
87

3. Institutional failures: Markets require a set of well-
functioning institutions. While not a market failure in a strict
sense, an institutional failure can severely damage access
to finance for innovative firms. Individuals will not invest in
building innovative businesses if property rights are not
guaranteed and their firms can be confiscated.
– Inefficient contract enforcement
– Inefficient bankruptcy regulation
88

The rational for public intervention
• The market failure rationale is not the only possible
justification for government intervention in access to
finance.
• The innovation system consists of the set of actors,
rules, and relationships that interact in the innovation
process. System failures refer to the components that
are not working appropriately and therefore should be
fixed
• Mission-driven policy: the motivation in this case is to
address a social challenge or develop a new industry
89

How companies finance their innovation activities?
• Internal Finance:
– The main internal source of finance is retained earnings, the profits
accumulated over time which have not been returned to
shareholders.
– Sale of existing assets
– Cut down in stock levels
Source: Rossi et al. 2015

External Finance:
• Debt: Debt finance consists mostly of loans and bonds. The
financer provides funding for a determined period of time and
requires the firm to pay back the lent amount and interest on
that amount on an agreed-upon schedule. With debt finance, an
entrepreneur maintains full control of the firm.
• Equity: Equity finance entitles the provider of capital to an
ownership stake and a share of the revenue of the venture.
Issuing new equity dilutes an entrepreneur’s control of the firm
and can become a source of conflict if disagreements among
shareholders emerge
91
Source: Rossi et al. 2015

• Dedicated innovation funding: Firms may also be able
to obtain funding with no payback requirements, no cost
of capital, and no dilution of ownership. Direct
government funding in the form of grants is the clearest
example, but some private sources may also offer
funding with few strings attached, such as gift-based
crowdfunding platforms.
• Firms usually prefer to fund their
investments with internal funds and then
with debt, and only then issue new equity
92

93
Financing lifecycle. Source: Lasrado, 2013

• The amount of resources required for the first stage of the
innovation process (new ideas, opportunities and
challenges) varies widely, depending on the type of
innovation being created.
• Knowledge and ideas are intangible, uncertainty is
typically very high, and spillovers are thought to be
stronger. This is especially the case for small, young
companies with few assets and revenues.
• Available finance:
– Public funding R&D grants and R&D tax incentives
94
1st stage-KNOWLEDGE CREATION AND
IDEA GENERATION
Bravo-Biosca et al. (2014)

2nd stage: PROTOTYPE DEVELOPMENT
AND MARKET DEMONSTRATION
• The second stage of the innovation process involves
getting from an idea to a new product, service, or
process by developing prototypes and testing their
potential for adoption in a real environment, be it with
real customers or real employees.
• Several forms of finance provision are available at this
stage:
– Business angels
– Early-stage venture capital funds
– crowdfunding platforms
– accelerators, and big corporates
95

3th stage- COMMERCIALIZATION AND
SCALING UP
• Once an innovation has been developed and
successfully user tested, the next challenge is to take it
to market, start generating revenue, and scale it
up. Available finance:
– Venture capital for high-risk proyects
– bank debt if risk is low and the investment required involves
mainly the acquisition of easily redeployable tangible assets
• Firms that are scaling up their innovations may use
several other sources of finance. Available finance:
– business angels and VC
– private equity funds, public markets (initial public offerings—
IPOs—and bonds), and corporates. 96

97
Financing lifecycle. Source: Lasrado, 2013
Asymetric
information -
risk

• BUSINESS ANGELS
• The informal venture capital market is composed of
wealthy individuals, called business angels, who invest
their own capital in young, unquoted firms.
• Business angels do not have familial or institutional
connections with the firms they finance. Rather, they are
generally successful business people and entrepreneurs
who look for attractive investment opportunities in a
segment of the market that is not covered by institutional
investors.
• Business angels have basically three motivations (Van
Osnabrugge and Robinson 2000): (1) obtaining financial
returns, (2) participating in the development process of
the ventures they finance, and (3) satisfying altruistic
feelings by, for example, transferring experience and
knowledge to amateur entrepreneurs.
98

• CROWDFUNDING
• Crowdfunding is defined as the practice of funding a
project or venture by raising many small amounts from a
large number of people, typically via the Internet.
• Crowdfunding often follows this process: first the
entrepreneur pitches his or her idea to the operators of
the platform. They will, in turn, screen the proposal and,
if they approve
it, launch the pitch. Each pitch has its own microsite,
containing a description of the project, its needs (funding
target), the timeline, and the reward model. A
crowdfunding round ends with one of two scenarios. In
the all-or-nothing model (AoN), the money that has been
pledged is transferred only if the target is reached by the
end of the period. In the keep-it-all (KiA) model, the
money is transferred even if the target is not reached. 99

100
• Typology of crowdfunding
Paschen, 2017

101
Framework for startup crowdfunding
Paschen, 2017

• VENTURE CAPITAL
• Venture capital firms are fund managers that invest in
companies with high growth potential. These tend to be
newer firms that need capital to grow but do not have a
significant asset base, strong cash flows, or a long credit
history that would allow them to raise debt finance. The
distinguishing feature of investee businesses is their
potential to grow exponentially in size and value if
successful (Barry et al. 1990).
• Venture capital funds are raised from institutional
investors (for example, pension funds and insurance
companies) and wealthy individual investors and are
usually managed via partnerships.
102

• Selection: Before investing in a business, a VC firm
conducts a thorough analysis to gain a detailed insight
into the business’s strengths and weaknesses, its growth
potential, and the prerequisites for achieving this growth.
• This includes assessing the originality of the potential
intellectual property, evaluating the risks of imitation, and
examining the market conditions (Florida and Kenney
1988).
• Investment is usually provided in tranches and only
when particular milestones have been met.
• VC funds often co-invest with other VC funds, and,
unlike in private equity investment, they usually have
minority shareholdings in their investees, with founders,
management, business angels, and other VC funds as
the other co-investors.
103

Process of VC investments
104
Source: Sbigroup

Lecture 4: Intellectual property rights and
financial markets in the strategy of software
companies in Europe and the United States.

Axe 1 : Finance of innovation and firm performance
Axe 2 : Innovation and survival

107
Plan
• 1. Introduction
• 2. The role of patents as a signal for investors in high-tech
companies
• 3 The value of patents through space
• 4. Research design and measures
• 4.1 Econometric model
• 4.2 Data Analysis
• 5. Results
• 6. Conclusion
Diego Useche
University of Rennes 1

1. Introduction
• IPOs are important events in a firm's life cycle.
• SMEs go public in order to improve their innovative capabilities through raising a
high amount of cash which :
• gives VCs the opportunity to exit (Black and Gilson, 1998),
• capture a first-mover advantage (Maksimovic and Pichler, 2001)
• help to finance valuable projects,
• facilitate takeover activity
• Attract valuable resources: workforce and alliance partners
• Remunerate entrepreneurship activity
• IPO creates information asymmetry between firms and investors
• Several studies have found that some metrics of firm quality are considered as
signal for investors:
• Influence of individuals (Certo et al., 2007)
• Role of venture capital (Gompers, 1995)
• Internationalization (Lipuma, 2011)
• Firm’s financial performance
• Public support
108
Reducing problems
of asymmetric
information
Diego Useche

109
• This empirical study addresses a double gap.
• 1) Do patents signal for IPO value in software industry?
• Patents have become particularly controversial in the software
industry.
• - to enforce patents may impede rather than promote innovation.
• - any positive effect patents will be annulled by the higher transaction
cost, multiplied threat of litigation
• - strategically used, especially by established firms to build “thickets” for
anticompetitive reasons.
• 2) What is the value of patents and other metrics of
“quality” as signals to evaluate software IPOs in two
different geographical regions ?
• Are financial markets providing incentives for growth-up software
companies to multiply patent applications before going public?.
Diego Useche

2. The role of patents as a signal for investors in
high-tech companies
• Innovation, managerial and legal scholars have shown that patents have a
“real development” value as well as “certification” component which may
help reduce information asymmetries in markets for entrepreneurial financing
(Long, 2002; Mann, 2005; Heeley, Matusik and Jain, 2007; Hsu & Ziedonis,
2007).
• The “private value” of patents- historically highly controversial issue
for academics, industrials and policy makers.
Software industry is a complex industry interacting with many sectors-
patents are not necessary “software patents”
• Software is a complex technology
• Cumulative technology
• Difficult to replicate
• very fast technical change and
short effective life on innovation
Other mechanism to protect IP (Copyrigth…
Diego Useche
Value of patents ???
- Value to prevent imitation is lower
- Obsolete before obtaining the patent
- Patents may not adequately reward
innovators
-IP fragmentation may impede
innovation
-Higher transaction cost and multiplied
threat of litigation
- Strategically used

high-tech companies
• The “private value” of patents is also strategic
• The strategic use of patents may take different forms as for example to block
competitors, gain bargaining leverage with other market actors, favours cross-
licensing and to prevent hold-ups (defensive patenting).
• Patents may also have an additional “certification value”
• Signal- readily observed attribute correlated with company performance, costly
to obtain and provide a selection mechanism
• Voluntary and under a firm’s control measures (signal may be altered) and the
marginal cost of obtaining the signal is inversely related to the productive
capability of the firm.
• Improve reputation which may help the firm to find valuable external resources
As instance: VC investors (experts in a particular technology field )
• Patents facilitate the financing of software firms by Venture Capital.
• Depending on the stage of firm’s development, sub-sector, the venture capital
cycle (Mann, 2005; Mann and Sager, 2007)
US
Diego Useche

high-tech companies
• Patents may also convey information credibly to uninformed observers at low
cost
• The examination process at the patent office is designed to provide a
certification function through the rejection of inventions that fail to meet the
standards required for patentability (Hsu & Ziedonis, 2007).
• The patent office serve as an intermediary who increases the credibility and
clarity of the information conveyed by patents (Long, 2002)
• Patents may convey information about
- the firm’s lines of research and how quickly the research is proceeding
- how the firms manage their IP strategy, their stage in development or its
market strategy (diversified or niche market)
- to benchmark firms relative to each other and as indicator of the productivity of
the R&D spending.
- may reduce the transaction costs associated with operating in a “thicketed”
market
Diego Useche

3. The value of patents through space
• There is little evidence on how software IPO investors use patents as a credible
signal of high firm value and future firm’s performance in US and Europe.
• The strategic patenting of software firms- may increase the number of patent
applications before IPO in order to increase the amount of cash (expected) at
IPO.
• A less “applicant friendly” patent system may discourage this behaviour
increasing the credibility of patents as signal and their value for IPO
investors.
• Differences in patent systems concerning the legal standars and their
operational desing (van Pottelsberghe de la Potterie, 2007 ) :
• The patentable subject matters (patentability of computer programs and BM)
• The requirements for patentability- USTPO (novelty, usefulness, and non-
obviousness) and the EPO (novelty, industrial application, and inventive step)
(Graham et al., 2002)
• the procedures that ensure the “quality of patents” as the examination
procedures and the fees.
• Patents in Europe seem to remain harder to get in comparison to the US
(Jaffe and Lerner, 2004) 113
Diego Useche

• It can be expected a different magnitude in the value of
patents as a signal in different geographies.
• The main hypothesis of this paper is that the importance of
a signal which may vary between regions is related to the
scarcity of the signal.
Diego Useche

115
4. Methodology and simple
• Our approach to build the dataset was to identify software
(USSIC737) IPO deals from the United States, Germany, the United
Kingdom, France, Sweden, Italy and Spain, between 1st January
2000 to 31st December 2009 in ZEPHYR database.
• After having cleaned up the database for our study, our sample is
composed of 476 software firms (234 from the US and 242 from the
EU). IPO information of each firm is matched with patents metrics
searched by hand using the company name from the Questel-Orbit
QPAT database
• Doubtful matches were verified by checking the inventor name, the
address information, the content of abstracts and the co-applicants
names.
Diego Useche

116
4.1 Econometric model
• This study includes an OLS model using the amount of cash collected by firms at their
IPOs as the dependent variable. This measure of IPO performance avoids potential
problems of over allocation in the pre-money valuation (Ritter and Welch, 2002;
Higgins et al., 2011).
• A log-transformed variable of IPO valuation and Tobin’s Q is used to addresses the
valuation data skew and reduce its heterogeneity.
• Coefficients should reflect the differences in the value of patents as signals for
investors (receptors of signals) and also the differences in the importance of use of
patents for the industry (emitters).
Diego Useche
i
i
EU
EU
US
US
EU
EU
US
US
i X
VC
VC
P
P
PROCEEDS i
i
i
i
e
b
g
g
l
l
a +
+
+
+
+
+
= 0
)
log(
EU
l - US
l > 0

Independent variables
• Patent metrics
Orbit’s FamPat database-
“a single family record
combines together all
publication stages of the family”
• Financial ratios (IPOT-1)
• Venture capital support and Corporte VC
• Asset, revenues (IPOT-1) and age at IPO
• Temporal, geographical and industrial effects
117
Diego Useche
- Number of patent application at IPO
- Number of patent obtained at IPO
- Number of Forward citations at IPOt
and IPOt +3
- ROA= prof. after taxes/ sales
- Equity ratio: shareholders’ funds/ total assets

Summary Statistics
118
Variable code Definition Source
Dependent variables
LOG (PROCEEDS) Logarithm of amount collected at IPO. BvD Zephyr
LOG (TOBIN'S Q) Logarithm of TOBIN'S Q : PROCEEDS/ total assets in year prior to IPO. BvD Zephyr
Independent variables
PAT Dummy variable recorded a value of 1 if company has at least one patent application at IPO, 0 otherwise. Q-Qpad
PATAPP Number of patents applied for by the firm at date of IPO (total patent application stock) Q-Qpad
PATAPPy4 Number of patents applied for by the firm in last four years prior to IPO Q-Qpad
LOCALPATAPP Number of patent applications at the USPTO by US firms and number of patent applications Q-Qpad
at EPO (and national patent offices) by European firms at date of IPO.
FCITATIONS Number of forward citations per patent application at date of IPO Q-Qpad
FCITATIONS3 Number of forward citations per patent application 3 years after date of IPO Q-Qpad
SHAREPCT Share of international applications in total stock of patent applications at IPO Q-Qpad
Controls
ROA RATIO After-tax net income divided by total assets of year prior to IPO BvD Zephyr
EQUITY RATIO Shareholders' funds in proportion to total assets in year prior to IPO BvD Zephyr
LOG (SALES TO ASSETS) Logarithm of sales related to total assets in year prior to IPO BvD Zephyr
LOG ( TOTAL ASSETS) Logarithm of total assets of firm in year prior to IPO BvD Zephyr
LOG (AGE AT IPO) Logarithm of age of company at IPO (difference between effective date of IPO and date of legal incorporation) BvD Zephyr- others
NEW MARKET
Dummy variable recorded a value of 1 if company was quoted on NASDAQ (US), AIM (UK), Nouveau Marché
(FR), BvD Zephyr- others
Nuovo Mercato(IT), Neuer Markt (DE) or Aktietofget (SE), 0 otherwise
VC Dummy variable recorded a value of 1 if company is a venture capital-backed IPO, 0 otherwise BvD Zephyr
CORPVCAP Dummy variable recorded a value of 1 if company is a corporate venture-backed IPO, 0 otherwise BvD Zephyr
SOFT_RATIO Ratio of software IPOs divided by total number of IPOs in a given year and country BvD Zephyr
LOG (PERCENT SOLD) Logarithm of percentage of firm to be sold during a public equity offering BvD Zephyr- others
Intra-industry dummies Eight dummy variables related to company’s principal software segment sectors using Fourth-Digit SIC Codes BvD Zephyr
Annual Dummies Dummies are coded as “Y2000” to "Y2009" indicating the IPO date. BvD Zephyr
Country or market
dummies Seven dummy variables are coded 1 or 0 to differentiate companies according to their country locations BvD Zephyr
Stock market dummies Sixteen dummy variables are coded 1 or 0 to differentiate IPOs according to their IPO stock-market. BvD Zephyr- others
Instruments
EXPORT3yav 3-year average share of computer and information technology exports in a country's total trade in services at t UNCTADstat
PATAPPt-4 Number of patents applied for by the firm four years prior to IPO date Q-Qpad
PATAPPt-3 Number of patents applied for by the firm three years prior to IPO date Q-Qpad
Firstapptoipo Number of years from first patent application to IPO Q-Qpad

119
Diego Useche
Results are unbiased only if the number of patent applications is
statistically independent of the potential IPO pricing.
First source of endogeneity: Self-selection occurs when companies which apply for
patents before their IPO are not randomly selected for the population. A firm’s decision to
apply for at least one patent before going public may be modelled by:
Finally, we use temporal, country and stock market differ-
ences in IPO deals. It has been documented that IPOs tend to
come in waves, characterized by periods of hot and cold mar-
kets. We include the variable SOFT RATIO, which is a ratio defined
as the number of software IPOs divided by the total number of
IPOs in a given year and country. Year and geographic year dum-
mies are included to take into account variations in cycle and
any country-specific characteristics. The dummies are coded as
‘Y2000′ to ‘Y2009′ indicating in which year the IPO took place.
Additionally, seven dummy variables are coded 1 or 0 to differ-
entiate companies according to their country locations. ‘UK’, ‘DE’,
‘FR’, ‘SE’, ‘ES’, ‘IT’, and ‘EU’ represent the dummies of IPOs in British,
German, French, Swedish, Spanish, Italian, and European stock
exchanges respectively. We also introduce a dummy variable called
‘new market’ which is coded 1 if the companies were quoted in
NASDAQ (US), AIM (UK), Nouveau Marché (FR), Nuovo Mercato
(IT), Neuer Markt (DE) or Aktietofget (SE). These markets were
designed to ‘provide high-growth companies with access to the
international investment community, within an accessible and well
regulated market structure’ (Euro.nm, 1999; Bottazzi and Da Rin,
2001). Finally, we also include sixteen dummy variables to differ-
entiate company IPOs according to their stock market. Table 1b
shows the software IPO stock market distribution in our sam-
ple.
4.9. Summary statistics
We present variable description and descriptive statistics for US
and European software companies in Tables 2 and 3. The summary
statistics are separated to emphasize differences in firm character-
istics between the US and European IPO deals. Some characteristics
related to patent behaviour should be highlighted. First, 66% of US
software companies filed at least one patent prior to their IPOs,
compared with only 23% of European software companies. Second,
US software companies filed on average 14.10 patents prior to their
IPOs while European companies filed only 2.07 patents. Descriptive
statistics also suggest that European companies are more cash con-
strained and riskier than US companies. European companies are
on average, smaller (in total assets and sales), younger and more
insolvent. In addition, they are part of a smaller and more frag-
mented market that reduces their growth potential compared with
US companies. In this context, it is also expected that the value of
a signal is stronger in a context of average lower quality of the
companies.
where log(PROCEEDS) is the amount of money collected by firm i
at the IPO date (t). We also interact our key independent variable
(PATAPP) with European and US dummy variables to allow for dif-
ference in slopes. Thus, in our model, PATAPPUSi
and PATAPPEUi
are
the patents applied for by US and European companies before IPO.
Similarly, VCUSi
and VCEUi
are dummy variables equal to 1 for US
and European firms receiving VC financing before their IPO. Xi is a
set of control variables. Positive and significant estimates of !US and
!EU are expected. The difference in the value of patents as signals
can be tested by performing the following Wald test:
!EU − !US > 0
OLS estimates of the relationship between patent applications
and the amount of money collected at IPO are unbiased only if
the number of patent applications is statistically independent of
the potential IPO pricing. However, a first source of endogeneity
arises if software firms going public are interested in applying for
patents before IPO because the benefits of patent applications (such
as a larger amount of money collected at IPO) outweigh the cost
of applying for the patent. Self-selection occurs when companies
which apply for patents before their IPO are not randomly selected
for the population. A firm’s decision to apply for at least one patent
before going public may be modelled by:
PAT∗
i
= ω · Zi + %i
PATi = 1 if PAT∗
i
> 0
PATi = 0 if PAT∗
i
< 0
(2)
where PAT∗
i
is the latent variable. Zi is a set of observable vari-
ables influencing a firm’s choice to patent before IPO. ω is a set of
coefficients and %i is the error term. Firm observable variables influ-
encing a firm’s choice to patent before IPO could also determine its
IPO pricing. Some of these variables which are not observable, such
as the value of R&D projects, are included in the two error terms in
εi in Eq. (1) and %i in Eq. (2). The correlation between the two error
terms will result in endogeneity in Eq. (1) which means that PATi
is correlated to εi. We take the endogenous selection process into
account by way of a two-step Heckman’s procedure to control for
self-selection bias (Heckman, 1978 ). The Heckman model as a two-
step procedure is flexible and attractive because it allows different
covariates to have a different impact on the two parts of the model.
In our case, the flexibility of the Heckman selection model is a big
advantage as the determinants of patent applications before IPO
(Zi) in software-related industries are not particularly well-defined
ple.
companies.
and PATAPPEUi
are
Similarly, VCUSi
and VCEUi
!EU − !US > 0
PAT∗
i
= ω · Zi + %i
PATi = 1 if PAT∗
i
> 0
PATi = 0 if PAT∗
i
< 0
(2)
where PAT∗
i
ple.
companies.
and PATAPPEUi
are
Similarly, VCUSi
and VCEUi
!EU − !US > 0
PAT∗
i
= ω · Zi + %i
PATi = 1 if PAT∗
i
> 0
PATi = 0 if PAT∗
i
< 0
(2)
where PAT∗
i
ple.
companies.
and PATAPPEUi
are
Similarly, VCUSi
and VCEUi
!EU − !US > 0
PAT∗
i
= ω · Zi + %i
PATi = 1 if PAT∗
i
> 0
PATi = 0 if PAT∗
i
< 0
(2)
where PAT∗
i
i
PAT *
= i
Ζ
⋅
ω + i
η (2)
i
PAT = 1 if i
PAT *
>0
i
PAT = 0 if i
PAT *
< 0
Table 4. The probability of having applied for at least one patent before
IPO
Variables Coefficient t-Statistic
LOG (SALES ) -0.0489 -1.27
VCAPUS 1.385*** 4.72
VCAPEU 0.453* 1.89
AGE AT IPO 0.0665** 2.42
SQUARED-AGE AT IPO -0.00213** -2.28
EXPORT3yav 0.386** 2.39
SOFT_RATIO -3.220 -1.22
EU -1.838*** -4.07
Country dummies Yes
Intra-industry dummies Yes
Annual Dummies Yes
Constant 1.395
(1.229)
Wald chi2 526.51
Observations 476
*** p<0.01, ** p<0.05, * p<0.1

Diego Useche
1 2 3
EU-US EU-US EU-US
VARIABLES OLS HECKMAN 2S2 GMMEUUS
PATAPPUS 0.00338** 0.00341** 0.00507***
(0.00150) (0.00145) (0.00137)
PATAPPEU 0.0134*** 0.0108*** 0.0113***
(0.00349) (0.00378) (0.00378)
FCITATIONSUS 0.000906 0.00002 -0.000155
(0.00132) (0.00253) (0.00150)
FCITATIONSEU 0.00975 0.0232 0.00996
(0.0341) (0.0146) (0.0334)
LOG ( TOTAL ASSETS) 0.622*** 0.535*** 0.614***
(0.0401) (0.0477) (0.0386)
LOG (SALES TO ASSETS ) 0.163*** 0.155*** 0.159***
(0.0459) (0.0522) (0.0442)
VCUS 0.397*** 0.633** 0.360***
(0.127) (0.309) (0.123)
VCEU 0.483*** 0.609* 0.508***
(0.167) (0.325) (0.160)
CORPVCAP 0.0407 0.0404 0.0807
(0.169) (0.191) (0.163)
LOG (AGE AT IPO) 0.00136 0.0639 -0.00457
(0.0609) (0.0991) (0.0579)
NEW MARKET 0.0353 -0.261* 0.0378
(0.116) (0.150) (0.111)
SOFT_RATIO 3.921** 1.370 4.296***
(1.546) (2.304) (1.374)
LOG(PERCENT SOLD) 0.501*** 0.283*** 0.482***
(0.0927) (0.104) (0.0885)
EU -0.673*** -1.278*** -0.675***
(0.142) (0.335) (0.136)
Financial ratios Yes Yes Yes
Annual Dummies Yes Yes Yes
Intra-industry dummies Yes Yes Yes
Country dummies Yes Yes Yes
Constant 1.976** 4.229*** 1.948***
(0.823) (1.055) (0.753)
Mills 0.984**
(0.491)
Observations 476 476 476
Table 5. Patent
applications and
the amount of
money collected
at IPO

6. Alternative
models and
Robustness
checks
models
Diego Useche
GREThA UMR CNRS 5113
4 5 6 7 8
EU-US EU-US EU-US EU-US EU-US
VARIABLES OLS-LOC OLS-PATPPy4 GMMy4 GMMy4SM GMM-LOC
LOCALPATAPPUS 0.00440** 0.0108***
(0.00195) (0.00361)
LOCALPATAPPEU 0.0426*** 0.0291**
(0.0136) (0.0129)
PATAPPy4US 0.00362* 0.00878*** 0.00828***
(0.00206) (0.00305) (0.00279)
PATAPPy4EU 0.0204*** 0.0173*** 0.0152**
(0.00586) (0.00646) (0.00649)
FCITATIONSUS 0.00104 -0.000920
(0.00132) (0.00181)
FCITATIONSEU 0.00641 -0.0112
(0.0321) (0.0346)
FCITATIONS3US 0.000469 -0.000422 -0.000327
(0.00100) (0.00112) (0.00104)
FCITATIONS3EU 0.0226 0.0307 0.0221
(0.0253) (0.0240) (0.0265)
LOG ( TOTAL ASSETS) -0.379*** -0.373*** -0.387*** -0.422*** -0.429***
(0.0402) (0.0398) (0.0389) (0.0424) (0.0425)
LOG (SALES TO ASSETS ) 0.165*** 0.170*** 0.164*** 0.159*** 0.151***
(0.0459) (0.0450) (0.0435) (0.0424) (0.0431)
VCUS 0.425*** 0.419*** 0.332*** 0.289** 0.305**
(0.129) (0.128) (0.125) (0.125) (0.122)
VCEU 0.472*** 0.471*** 0.504*** 0.546*** 0.551***
(0.167) (0.167) (0.160) (0.169) (0.168)
CORPVCAP 0.0557 0.0452 0.0820 0.0549 0.0487
(0.165) (0.168) (0.164) (0.153) (0.154)
LOG (AGE AT IPO) -0.000286 -0.00377 -0.0122 0.00331 0.0109
(0.0610) (0.0610) (0.0581) (0.0571) (0.0569)
NEW MARKET 0.0327 0.0225 0.0273 -0.355 -0.558
(0.117) (0.116) (0.109) (0.474) (0.477)
SOFT_RATIO 3.349* 3.428* 4.042*** 2.809** 2.241
(1.944) (1.768) (1.403) (1.396) (1.512)
LOG(PERCENT SOLD) 0.502*** 0.485*** 0.461*** 0.418*** 0.438***
(0.0923) (0.0929) (0.0895) (0.0907) (0.0902)
EU -0.679*** -0.684*** -0.697*** -0.610 -0.359
(0.143) (0.137) (0.131) (0.426) (0.425)
Financial ratios Yes Yes Yes Yes Yes
Annual Dummies Yes Yes Yes Yes Yes
Intra-industry dummies Yes Yes Yes Yes Yes
Country dummies Yes Yes Yes No No
Stock market dummies No No No Yes Yes
Constant 2.251** 2.217** 2.151*** 3.214*** 3.450***
(0.962) (0.904) (0.780) (0.830) (0.878)
Observations 476 476 476 476 476
Adjusted R-squared 0.518 0.518 0.510 0.519 0.518
*** p<0.01, ** p<0.05, * p<0.1

122
Diego Useche
GREThA UMR CNRS 5113
1 2 3 4 5 6
GMM GMM GMM GMM GMM GMM
VARIABLES
PATAPP US 0.00658*** 0.00657*** 0.00540*** 0.00656*** 0.00655*** 0.00540***
(0.00109) (0.00109) (0.00120) (0.00109) (0.00109) (0.00118)
PORFTQUALITY US -0.000673 -0.000679 -0.000335
(0.00149) (0.00149) (0.00125)
LOG ( TOTAL ASSETS) US 0.362*** 0.362*** 0.374*** 0.359*** 0.359*** 0.370***
(0.0366) (0.0366) (0.0357) (0.0352) (0.0352) (0.0343)
LOG (SALES TO ASSETS ) US 0.221*** 0.222*** 0.229*** 0.216*** 0.217*** 0.221***
(0.0723) (0.0724) (0.0732) (0.0720) (0.0720) (0.0720)
VC US 0.198* 0.199* 0.236** 0.194* 0.195* 0.227**
(0.104) (0.104) (0.104) (0.102) (0.102) (0.101)
CORPVCAP US -0.132 -0.128 -0.152
(0.183) (0.183) (0.181)
AGE AT IPO US -0.00736 -0.00739 -0.00777
(0.00828) (0.00828) (0.00821)
NEW MARKET US -0.395 -0.395 -0.401 -0.428* -0.427* -0.439*
(0.264) (0.265) (0.269) (0.239) (0.239) (0.244)
SOFT_RATIO US 1.374 1.370 1.310
(0.935) (0.936) (0.943)
LOG(PERCENT SOLD) US 0.0906 0.0886 0.108
(0.0955) (0.0955) (0.0936)
PATAPP EU 0.0103** 0.0120*** 0.0103** 0.00992** 0.0116*** 0.00975**
(0.00477) (0.00393) (0.00477) (0.00464) (0.00386) (0.00463)
PORFTQUALITY EU 0.000939 0.000252 0.00118
(0.0340) (0.0334) (0.0339)
LOG ( TOTAL ASSETS) EU 0.709*** 0.708*** 0.706*** 0.696*** 0.694*** 0.693***
(0.0536) (0.0532) (0.0536) (0.0583) (0.0580) (0.0582)
LOG (SALES TO ASSETS ) EU 0.0903 0.0918 0.0928
(0.0792) (0.0787) (0.0791)
VC EU 0.450*** 0.454*** 0.451*** 0.416*** 0.416*** 0.415***
(0.164) (0.164) (0.164) (0.161) (0.161) (0.161)
CORPVCAP EU -0.345 -0.348 -0.341
(0.325) (0.325) (0.325)
AGE AT IPO EU -0.00862 -0.00902 -0.00831
(0.0101) (0.0102) (0.0101)
NEW MARKET EU 0.172 0.178 0.172
(0.146) (0.147) (0.146)
SOFT_RATIO EU 3.363*** 3.378*** 3.280*** 3.201*** 3.199*** 3.136***
(0.579) (0.573) (0.584) (0.580) (0.579) (0.581)
LOG(PERCENT SOLD) EU 0.616*** 0.613*** 0.623*** 0.620*** 0.621*** 0.625***
(0.132) (0.131) (0.132) (0.135) (0.135) (0.135)
EU -6.719*** -6.725*** -6.517*** -6.660*** -6.663*** -6.477***
(0.750) (0.750) (0.732) (0.770) (0.769) (0.755)
Financial ratios Yes Yes Yes Yes Yes Yes
Annual Dummies Yes Yes Yes Yes Yes Yes
Intra-industry dummies Yes Yes Yes Yes Yes Yes
Country dummies Yes Yes Yes Yes Yes Yes
Stock market dummies No No No No No No
Constant 7.171*** 7.177*** 7.016*** 7.212*** 7.214*** 7.072***
(0.499) (0.499) (0.478) (0.474) (0.474) (0.457)
Observations 476 476 476 476 476 476
Adjusted R-squared 0.775 0.783 0.784 0.774 0.774 0.774
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

123
6. Discussion and conclusion
This study provides new insights into the literature on the role and nature of patents
as signals for uninformed observers (IPO investors) in the US and Europe.
First, we argue at a theoretical level that differences in the patent systems are
related to differences in the value of patents as signals for investors to reduce
informational asymmetries.
Second, we construct an original database linking Bureau van Dijk's Zephyr
database and Q-qpad database.
Third, we found evidence of a self-selection bias, which means that software firms
going public with patent applications are not randomly selected from the population.
We also found that patent applications are used strategically to increase the IPO
proceeds raised (simultaneity) in the US while they are not in Europe.
Fourth, our research findings are consistent with the ideal that the degree of
importance of a signal changes between the US and Europe and it is related to the
scarcity of the signal and the difficulty to get access to that signal.
An international comparison offers a new and original perspective to consider the
differences in the institutional architecture of the patent systems and its impact in
firms’ performance.
Diego Useche

124
IPOs markets provides incentives for growth-up
software companies to multiply patent applications
before going public.
• A higher number of patents applied and obtained prior to
IPO allow us to suggest that patents behavior profits
principally US software companies at IPO.
• This suggests that even if all the applications are related
with additional cash at IPO as a R&D reward, companies
interested in patenting have an incentive to apply for a
patent as soon as possible, especially in Europe.
Diego Useche

125
Plan
•1. Introduction
•2. Firms’ characteristics, innovation and survival of new entrants
•3. Patents, innovation and acquisition risk
•4. Data description and empirical strategy
•5. Results
•5. Empirical Results
•6. Conclusion and discussion
Diego Useche

• It is usually claimed that in the European software industry there are
few success stories
• They rarely become large global leaders
• IPOs are important events in a firm's life cycle
• In Europe and US
• A considerable number of speculative software firms go public
(unsolvable, unprofitable, younger, with complex business models and
poor business plans )
• an unprecedented decline in the quality of high-tech firms going public
• Factors tending to improve the survival of newly-listed software firms
could be important in order to improve their performance, growth and
success
126
Introduction and context:
Diego Useche

Patenting software related technologies in Europe.
• Few evidence about the value and nature of patents in Europe for SMEs and high-tech
companies(especially for the software industry)
• A belief widely established is that European Software companies cannot use patents
because computer programs “as such” are excluded from patentability in Article 52(3).
• Political problem:
• Despite the high policy attention and several policy interventions to improve innovation
capabilities and innovation commercialisation of YICs in Europe, IT European firms had
very limited access to protect their computer program-related inventions through
patents
This paper seeks to provide new evidence concerning the relationship between
pre-IPO patenting behaviour and the survival of newly-listed software firms in
Europe while considering that firms face both a risk of acquisition and a risk of
failure.
Diego Useche

2. Firms’ characteristics, innovation
and survival of new entrants
Value of patents in the survival of newly-listed
companies: heterogeous literature
Managerial
Importance of financial
markets and IPO in
firms’ dynamics.
Emergence of new
markets
IPO and Post-IPO
performance
Industrial organisation
(IO) and survival
literature
Stochastic vs Firms’
characteristics approach
Value of patents
- Competitive advantage
-signaling, etc
-The risk of patents in
the software industry
Diego Useche

Two different approachs in the IO
literature concerning survival:
The stochastic approach
The likelihood of survival should be
stochastically distributed across all
firms, independent of (observable) firm
and industry characteristics.
(Jovanovic,1982)
- The firm post-entry performance
depends on the learning process.
(Ericson and Pakes, 1995)
- Efficient firms grow and survive while
inefficient firms decline and fail.
Firms’ characteristics specific
Post-entry performance is not random
across firms. (see Audretsch et all, 1999;
Agarwal and Audretsch, 2001; Santerelli
and Vivarelli, 2007)
-Varies or not depending :
-Size (Audretsch, 1991; 1995)
-Experience (Agarwal and Gort, 2002;
Ritter, 1991; Schultz 1993 )
-Financial fragility (Klepper, 1996;
Cooley and Quadrini, 2001)
-Firms’ ability to learn about their
market environment
- Innovative and imitative investments
(Nelson and Winter,1982; Hall,198; Cefis
and Marsili, 2006; 2007; 2012, etc)
Diego Useche

Patents and survival
• Patents may have a “strategic value” that may improve the ability of software
firms to operate in the market:
• Use of patents..
• ..in cross-licensing negotiations to defend themselves against litigation and to prevent
hold-ups (Noel and Schankerman, 2006; Hall and Ziedonis, 2001).
• … to exploit to block or delay a competitor.
• … to reduce the probability of being involved in a suit on any individual patent
(Lanjouw and Schankerman, 2001).
• … to set up patent pools to increase their market power and pose entry barriers or
disincentives to others innovators (Bessen, 2003; Bessen and Meurer, 2008).
• …to convince different kinds of investors as venture capitalist (Mann, 2005; Mann
and Sager, 2007) and IPO investors (Useche, 2014) that a company may be worth
investing
•
• … to motivate the inventiveness of employees and reduce the risk and impact of
people leaving the company
• .. To Improve the firms’ reputation which may help the firm to find valuable external
resources (Muller and Pénin, 2006) Diego Useche

Innovation and M&A
• Empirical results show contrasting evidence concerning the firm’s
characteristics and performance affecting the likelihood of acquisition.
• M&A to access to resources, skills and markets (Cohen and Levinthal, 1990).
• Through innovation, firms increase their stock of knowledge and capabilities
and therefore their attractiveness as acquisition targets.
• Knowledge capital is highly heterogeneous, hard to identify and transfer (Coff,
1999; Ranft and Lord, 2002; Cefis and Marsili, 2012). In this perspective,
patents may be considered as more easy identifiable and transferable
intangible assets
• Then, valuable patents are key assets which may facilitate a strategic exit
through M&A in particular when the company has not the resources,
capabilities and experience necessaries to exploit the patented technology
(Gans and Stern, 2003; Cefis and Marsili, 2012)
Diego Useche

132
• What is the “value” of patents in the survival of newly-listed software
firms in Europe while considering that firms face both a risk of
acquisition and a risk of failure
• Hypothesis 1. Patents are related with a ‘competitive advantage’
that reduces the probability of a firm exiting through business
failure depending on the type of company.
• Hypothesis 2. Patents and particularly high-quality patents are
valuable assets that increase the attractiveness of a company as
an acquisition target depending on the type of company.
Diego Useche

133
4. Methodology and simple
Diego Useche
We match BvDZ
database and Questel-Orbit
QPAT database by firm
name
We match BvDZ
database IPOs with:
-M&A information
-The current status of the
company
Bureau van Dijk's Zephyr
information was completed
and verified with financial
documents publicly available
Identify software
(USSIC737) IPO
On the Bureau van Dijk's
Zephyr database (BvDZ)

4.1 Objectives of survival analysis
• Estimate time-to-event for a group of individuals, such as to time for
M&A after IPO.
• To compare time-to-event between two or more groups, such as
money-losing companies versus profitable companies.
• To assess the relationship of covariables time-to-event, such as:
Are patents related with a ‘competitive advantage’ that reduces the
probability of a firm exiting through business failure?
• Survival analysis take into account censoring and time.
• Time-to-event: The time from entry in a study until a subject has a
particular outcome
• Censoring: Subjects are said to be censored if they are lost to follow
up or drop out of the study, or if the study ends before they exit or
have an outcome of interest. They are counted as alive or even-free
for the time they were enrolled in the study.

135
4.1.1 Econometric model
• Semi-parametric approach based on Crox regression and Kaplan–
Meier survival curves as such as competing-risk regressions.
• Survive time is usually defined a non-negative random T, the failure rate at
time t and the hazard function H (T) is defined as the limit
The hazard function of a firm hf(t) is expressed as a linear function of a set
of k fixed covariates that is exponentiated:
• The where h0(t) is an arbitrary and unspecified baseline hazard function
reflecting the probability of failure conditional on the firm having survived till
time t after its IPO. Does not assume Knowledge of absolute risk (estimate
relative rather than absolute risk).
Diego Useche
;
)
(
0
)
(
t
t
T
t
t
T
t
p
Lim
h
t
t
D
³
D
+
<
£
=
®
D
)
(
0
i )
(
)
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( i
k X
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t
h
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h
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=

4.1.2 The Cox stratified model
• Cox regression uses the proportional hazard assumption
• The Cox proportional hazards models assume that the hazard ratio is constant
over time. The hazards fuctions should be strictly parallel. In the presence of
hazards that do not satisfy the proportional assumption the estimates can give
biased and inefficient results for all the parameters. (test PH assumption!!)
• First variation: Cox stratified model
• Separate baseline hazard are estimated for the j different groups
• We assume that two groups of firms may have different risks of exit.
)
exp(
)
(
)
x
|
( 0
i i
k
j X
t
h
t
h b
=
b
b
e
t
H
e
t
H
t
h
t
h
HR =
=
=
=
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)
(
)
(
)
0
x
|
(
)
1
x
|
(
0
0
Strong assumption
Diego Useche

137
Sample construction
• Basically, the sample was built through six steps.
1. Our approach to build the dataset was to identify software (USSIC737) IPO deals
from DE, the UK, FR, SE, IT and SP, between 1997 to 2005 on the Bureau van
Dijk's Zephyr database (BvDZ) Considering only companies with available
information considering Pre-IPO characteristics, our sample is composed of 578
software IPOs
2. We match BvDZ database and Questel-Orbit QPAT database by firm name.
“Weak” matches were verified by looking the content of the patents (the inventor
names, address information, citations to other patents, and the content of
abstracts).
3. Then, all the software M&A deals from 1997 to 2011 were collected on the BvDZ
database (12848 deals). IPO information is matched with M&A deals to identify
which companies were acquired after the IPO and the date of the acquisition.
4. Information concerning the current status of the company after its IPO (whether or
not a firm is still listed) was used to identify companies delisted for another reason
different to M&A.
5. A significant effort was made to identify companies that were to bankruptcy or
voluntary liquidation process after their IPO. Thus, BvDZ information was
completed and verified with several publicly financial documents available on the
company’s websites and specialized websites
6. We also searched the web (on firm’s websites and specialized websites) for
companies that survive to verify if they continue to operate in the financial
markets.
Diego Useche

Time invariant regressors
• Patent metrics
• Financial ratios (IPOT-1)
• Venture capital support
• Employees, Assets, revenues and Age at IPO
• Temporal, country and intra-industrial effets
138
Diego Useche
- Number of patent application at IPO
- Number of patent obtained at IPO
- Number of Forward citations (t+3)
- Number of International applications.
- ROS
- Equity ratio: shareholders’ funds/ total assets

Data structure: Survival analysis
• Two variable outcome:
• Time variable (ti)= time at event (M&A or failure).
• Censoring variable: Ci= 1 if had the event; Ci=0 no event
by time ti.
• Right censoring (T>t)
• We know that subjet survived at least to time t
• We considered competing risks through fitting models
separately for each type of failure and treat other failure
as censored (Kay, 1986). Then, we have 239
acquisitions and 82 failures after IPO.

Summary Statistics
140
Diego Useche
UK GERMANY FRANCE SWEDEN ITES
VARIABLE Mean Min Max Mean Mean Mean Mean Mean
SURVIVAL TIME (days to exit) 2829,35 55,00 5445,00 2429,29 2994,48 3038,74 2935,47 3113,18
DELISTED 0,56 0,00 1,00 0,62 0,51 0,53 0,55 0,55
ACQUIRED 0,41 0,00 1,00 0,36 0,40 0,43 0,50 0,50
BANKRUPCY/ VOLUNTARY LIQUIDATION 0,14 0,00 1,00 0,25 0,11 0,10 0,05 0,05
AT LEAST ONE PATENT APPLIC 0,20 0,00 1,00 0,19 0,19 0,21 0,25 0,13
PATENTAPPLIED 1,13 0,00 137,00 1,27 0,69 0,75 1,23 3,39
PATENTOBTAINED 0,81 0,00 117,00 0,87 0,37 0,47 0,97 3,26
FORWARD CITATIONS 6,23 0,00 1359,00 8,92 1,20 8,25 6,86 3,34
PCT APPLICATIONS 0,30 0,00 32,00 0,33 0,27 0,29 0,42 0,03
RETURN ON SALES -0,16 -355,04 478,81 -0,31 -0,58 2,76 -4,47 -2,16
MONEY-LOSING (NEGATIVE ROS) 0,43 0,00 1,00 0,42 0,44 0,37 0,48 0,58
EQUITY RATIO -3,76 -2337,67 1,00 -12,85 0,27 0,47 0,63 0,45
INSOLVENT ( NEGATIVE EQUITY RATIO) 0,08 0,00 1,00 0,16 0,04 0,05 0,02 0,05
VENTURE BACKED 0,11 0,00 1,00 0,09 0,09 0,13 0,13 0,18
AGE AT IPO 8,47 0,04 62,27 5,25 10,41 8,68 11,48 10,71
EMPLOYEES 351,52 1,00 30209,00 503,07 290,43 259,77 80,45 676,76
LOG ( ASSETS TO REVENUES) 1,02 -3,96 11,22 0,49 1,14 0,83 2,45 1,43
LOG ( REVENUES ) 8,85 -1,15 15,24 8,62 9,09 9,35 6,90 10,31
SOFT_ENTRY 0,35 0,09 0,46 0,31 0,39 0,35 0,33 0,40
NEW MARKET 0,36 0,00 1,00 0,34 0,59 0,31 0,08 0,29
Main-sic-software 0,71 0,00 1,00 0,61 0,78 0,77 0,77 0,61
Software Developer (Business description) 0,42 0,00 1,00 0,40 0,48 0,32 0,56 0,37
Internet_related (Business description) 0,33 0,00 1,00 0,38 0,31 0,30 0,23 0,47
Number of companies 578 182 143 151 64 38
EUROPE

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