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Value Creation and Value Capture in Open Innovation
Master Thesis MSc ETH MTEC
Olivier Esseiva
Tutored by Andreas Schneider
May 2013
Chair of Strategic Management and Innovation
Prof. Georg von Krogh
Department Management, Technology and Economics, ETH Zürich
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Acknowledgements
I would like to thank Andreas Schneider for his kind supervision of this thesis. The discussions, inputs,
and feedback from him were extremely helpful. Also I would like to thank all the other group members
of the Chair of Strategic Management for their support and the fruitful discussions with them. Namely
Zeynep Erden and Renato Sydler were of great help to me. Special thanks go to Fotini Pachidou for
showing me how to access Bloomberg data.
I would like to thank David Klang and Maria Wallnöfer for the helpful discussions on business models and
their view on this topic.
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Abstract
This master thesis investigates what strategies companies pursue to profit from Open Innovation and
how value creation mechanisms interact with value capture. This thesis is unique in the current
literature, since it investigates aspects of both value creation and value capture in Open Innovation and
provides empirical ramification of collaborative innovation strategies that have gained widespread
acceptance in recent years. To answer the research question, the patenting and publishing activity
during the last ten years of the ten largest pharmaceutical companies is investigated. The data-mining
analysis reveals that Open Innovation practices change the appropriability regime by diminishing the
importance of the patent portfolio. By engaging in interfirm alliances, firms can increase R&D
productivity. The main drivers of openness in the value creation process are the need to fill knowledge
gaps, technological demand, and strategic decisions to boost certain business areas.
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List of Figures
Figure 1: Visual representation how theory section is built up .................................................................. 10
Figure 2: The Closed Innovation model. ..................................................................................................... 11
Figure 3: Open Innovation model ................................................................................................................ 12
Figure 4: Possible value distribution of an innovation among different stakeholders ............................... 16
Figure 5: Profiting from Innovation framework .......................................................................................... 17
Figure 6: Distinction between generic, specialized and co-specialized complementary assets according to
their mutual dependence ................................................................................................................. 18
Figure 7: From innovation strategy to financial performance. .................................................................. 22
Figure 8: Framework for determining openness based on value creation and value capture drivers. ..... 23
Figure 9: Evolution of total number and openness in publications from 2002 to 2012. ........................... 34
Figure 10: Type of co-authorship in published papers ................................................................................ 34
Figure 11: Annual growth of R&D intensity (R&D expenditure divided by total sales) and annual growth of
openness from 2002 to 2012. ........................................................................................................... 36
Figure 12: Share of inter-firm alliances and and openness from 2002 to 2012. ......................................... 37
Figure 13: Number of patents and average openness of patents of the top10 pharmaceutical companies
from 2002 to 2012. ........................................................................................................................... 39
Figure 14: Type of collaboration in publications and patents from 2002 to 2012. ..................................... 39
Figure 15: Annual change of patent share of different disease areas against the change in openness of
publications ....................................................................................................................................... 40
Figure 16: Relative share of patents of each of the 14 disease areas. ........................................................ 41
Figure 17: Number of publications and number of patents of all disease areas ........................................ 42
Figure 18: Evolution of focal areas of ten largest pharmaceutical companies from 2002 to 2012 ............ 44
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List of Tables
Table 1: Main aspects of a business model and authors using similar frameworks and concepts. ............ 13
Table 2: Key aspects of Open Innovation regarding business models ........................................................ 15
Table 3: Generic strategies to influence value capture from innovations .................................................. 20
Table 4: The ten largest pharmaceutical companies .................................................................................. 26
Table 5: Queries used in WebOfScience and Derwent Patent database to generate the data set. .......... 28
Table 6: Initial list of 34 subject areas and the corresponding IPC codes.. ................................................. 30
Table 7: Overlap matrix of patent data. ...................................................................................................... 31
Table 8: Overlap matrix of publication data ................................................................................................ 31
Table 9: Total number of publications, average R&D intensity and average openness ............................. 35
Table 10: Number of publications, relative share, and openness in publications of disease areas ........... 38
Table 11: Focus areas of the ten largest pharmaceutical companies. ........................................................ 43
Table 12: Initial overlap matrix of patents. ................................................................................................. 76
Table 13: Initial overlap matrix of patents. ................................................................................................ 77
Table 14: Total number of patents, share of interfirm alliances and openness ......................................... 78
Table 15: Total number of patents, relative share and openness per disease area. .................................. 78
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Contents
Acknowledgements ....................................................................................................................................... 2
Abstract ......................................................................................................................................................... 3
List of Figures ................................................................................................................................................. 4
List of Tables .................................................................................................................................................. 5
1. Introduction ............................................................................................................................................... 8
1.1 Motivation ........................................................................................................................................... 8
1.2 Structure of Thesis ............................................................................................................................... 9
2. Theory ...................................................................................................................................................... 10
2.1 Open Innovation ................................................................................................................................ 10
2.1.1 Conceptual Framework of Open Innovation .............................................................................. 10
2.1.2 Open Innovation and Business Models ...................................................................................... 13
2.2 Value Capture from Innovation ......................................................................................................... 15
2.2.1 Value Capture from Innovation in General ................................................................................ 15
2.2.2 Value Capture Aspects of Open Innovation ............................................................................... 18
2.3 Interplay of Openness, Value Creation, and Value Capture .............................................................. 21
2.3.1 Openness and Innovative Performance ..................................................................................... 21
2.3.2 Drivers of Openness in Value Creation and Value Capture ........................................................ 22
2.4 Research Gap and Research Question .............................................................................................. 23
3. Methodology ........................................................................................................................................... 25
3.1 Research approach ............................................................................................................................ 25
3.2 Study sample ..................................................................................................................................... 25
3.2.1 Pharmaceutical Industry ............................................................................................................. 25
3.2.2 Ten largest companies ................................................................................................................ 27
3.2.3 Using Publications and Patents to Study Value Creation and Value Capture ............................ 27
3.3 Extracting relevant information from dataset .................................................................................. 28
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3.3.1 Extracting company affiliation .................................................................................................... 28
3.3.2 Extracting disease area ............................................................................................................... 29
3.3.3 R&D Intensity data ..................................................................................................................... 32
3.4 Calculating Openness ........................................................................................................................ 32
4. Results and Findings ................................................................................................................................ 33
4.1 Value Creation in Open Innovation in the Top10 Pharmaceutical Companies ................................. 33
4.1.1 Industry-wide evolution ............................................................................................................. 33
4.1.2 Firm-specific Patterns of Value Creation .................................................................................... 35
4.1.3 Disease Area Patterns in Value Creation .................................................................................... 37
4.2 Value Capture in the Top10 Pharmaceutical Companies .................................................................. 38
4.3 Interplay of Value Creation and Value Capture ................................................................................ 41
5. Discussion ................................................................................................................................................ 45
5.1 Interplay of Value Creation and Value Capture in Open Innovation................................................. 45
5.2 Different Open Innovation Strategies in Different Business Areas ................................................... 46
5.3 Difference in Open Innovation Practices ........................................................................................... 47
5.4 Managerial implications .................................................................................................................... 48
5.5 Limitations and Future Research ....................................................................................................... 49
6. References ............................................................................................................................................... 51
7. Appendix .................................................................................................................................................. 55
7.1 VBA function for assigning company affiliation ................................................................................ 55
7.2 VBA Function to Assign Publications to Subject Areas ...................................................................... 55
7.3 VBA function to assign patent codes to Subject Areas ..................................................................... 57
7.4 VBA function to determine openness ............................................................................................... 66
7.5 IPC codes linked to Subject Areas ..................................................................................................... 69
7.6 Overlap matrices ............................................................................................................................... 76
7.7 Summary of Value Capture Data ....................................................................................................... 78
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1. Introduction
1.1 Motivation
Innovation is almost any company’s bread and butter nowadays if they want to achieve their ambitious
growth targets. Decades ago, innovators faced a completely different economic environment and large
corporate research labs such as AT&T’s Bell Labs and Xerox’s PARC flourished. Today, the innovator faces
ever shorter product life cycles, global competitive threats, and customers demanding more and more
while paying less and less.
How can a company simultaneously bring new ideas to market while making sure that it can capture at
least part of the value that is created? Years ago, these questions would have appeared downright
obvious to many companies and hardly any scholar or practitioner would have bothered to answer these
questions in great detail. Nowadays and especially through the advent of modern information and
communication technologies, it is not that easy anymore to defend an innovated product or process
against imitators or competitors. Put differently, making the pie bigger does not automatically lead to a
larger slice of the pie.
In response to the dramatic change in the business landscape, several innovation strategies have
emerged to tackle today’s challenges. Notably, it has been suggested that organizations need to tap into
sources of knowledge that lie outside the traditional boundary of the company and that the highly
inward focusing innovation practices of many companies lie at the heart of an insufficient innovation
performance (Chesbrough, 2003; Von Hippel & Von Krogh, 2003). Concepts that were previously known
only to a few experts of some isolated industries such as Open Innovation and Open-Source, have
become household words in today’s management language. At the heart of modern innovation
strategies lies the idea that companies need to become more open and need to engage with their
external environment because labor mobility has increased, venture capital is abundant, knowledge is
widely dispersed, and product life cycles have contracted dramatically (Chesbrough, 2003). Or simply
put: “Not every smart person works for us. We need to engage with people inside and outside the
company” (Chesbrough, 2003).
Prompted by the internet and with new strategic concepts at hand, many companies have indeed
become more open in the way how they innovate (Enkel, Gassmann, & Chesbrough, 2009). Companies
engage in venturing activities, contract research, license in and out intellectual property, involve
customers in their innovation process, participate in research consortia, form public-private partnerships
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and engage in many more activities that could be termed open (Chesbrough, 2012). However, being
open is not the answer to everything and psychological and organizational barriers impede companies to
become even more open than they are today. Some of these barriers are behavioral in nature such as
the not-invented-here syndrome, which describes the resistance that R&D departments often show
towards outside ideas (Katz & Allen, 1982). But beyond these psychological factors, the main limitation
toward openness is the more strategic question on how an innovator can profit from its innovation
(Teece, 1986). While earlier work that urged companies to become more open focused on the aspect of
value creation, later work has put the emphasis on value capture (Fischer & Henkel, 2012). However,
there is no systematic study that has investigated value creation and value capture aspects of Open
Innovation concomitantly.
This master thesis addresses the gap that has been left by the literature on Open Innovation, value
capture, and value creation. Specifically, this thesis explores the interplay between value creation and
value capture in Open Innovation settings. Since no established theory exists for this specific question,
the thesis will be rather explorative in nature and will focus on developing suggestions rather than
formally testing hypothesis. Therefore, the research question is an open question with the goal of
formulating more specific and testable hypotheses.
1.2 Structure of Thesis
This thesis begins by reviewing the existing literature on Open Innovation, focusing on value creation and
value capture aspects of innovation. The theory section is built of three parts. First it reviews the work on
value creation on Open Innovation which comprises the original work of Henry Chesbrough on this topic.
Second, it discusses the literature on value capture aspects. Third, it investigates the existing literature
on the connection between value creation and value capture in Open Innovation settings. Figure 1
depicts how the theory section is built up.
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Value Creation in Open Innovation
Value Capture in Open Innovation
Linking Value Creation and
Value Capture in Open Innovation
Research Gap
Research Question
Figure 1: Visual representation how theory section is built up
The theory section leads to the formulation of a research question. The next chapter describes the
methodology of this thesis. Since the research topic is very explorative, new methods for collecting,
analyzing, and interpreting the data were developed. These methods include a new procedure to
measure the openness of a publication and a patent. After this, the result section highlights the most
important results, visualizes, describes and interprets key points. Following the result section, the
discussion session shows the contribution to the existing literature, formulates hypotheses, highlights
managerial implications, discusses the limitations of this study and shows avenues for future research.
2. Theory
2.1 Open Innovation
2.1.1 Conceptual Framework of Open Innovation
In his book “Open Innovation”, Henry Chesbrough argued that companies should become more open to
external knowledge and ideas (Chesbrough, 2003). He distinguished between a Closed Innovation model
and an Open Innovation Model. The Closed Innovation Model is depicted in Figure 2. The innovation
process is described via a funnel structure; ideas originate on the left hand side (research part), some of
these ideas are pursued further while some are discarded (development part) and a few ideas are
subsequently brought to market (narrow part of the funnel). Every step of the innovation process is
conducted within the confines of the company that originated the idea. Therefore, the closed innovation
paradigm represents a fully vertically integrated model of innovation (Gassmann, Enkel, & Chesbrough,
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2010). Under the premises of Closed Innovation, there are no “exit mechanisms” for knowledge and
ideas that would allow them to be pursued by a different firm. As a consequence, the ideas that
originate from the company’s R&D are either brought to market or are put on the shelf. Furthermore,
there are no mechanisms for ideas to flow from the outside world into the firm’s R&D process. The
innovating company relies solely on its own internal knowledge base to create new ideas and its
development capabilities to bring them to market. The firm’s boundaries are impermeable and are,
therefore, depicted as solid lines in Figure 2. Classical examples of companies that relied on the Closed
Innovation model were AT&T (with the famous Bell Labs), Xerox, and IBM in the 1970ies and 1980ies
that produced outstanding research, but often failed to exploit their ideas commercially (Chesbrough,
2003)
Internal technology
base
Externaltechnology
base
The Market
= Ideas
R DResearch Development
New Products / Services
Figure 2: The Closed Innovation model. Ideas and knowledge originate at the left-hand side, go through the development funnel and are brought to market. Source: (Chesbrough, 2003)
In contrast to the Closed Innovation paradigm, Figure 3 shows the Open Innovation Model. There are
two significant changes to the Closed Innovation model. First, ideas that were spawned within the
internal technology base do not necessarily stay within the company. As an alternative to being
developed and commercialized by the inventing company, ideas can flow out a company’s boundary at
any stage and could be pursued by another company (Inside-Out) (Chesbrough, 2003). Possible inside-
out mechanisms are spin-offs, out-licensing, free revealing of ideas, etc. The second difference to the
Closed Innovation model is that externally conceived and developed ideas are allowed to flow into the
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company for commercialization (Outside-In) (Chesbrough, 2003). Acquisitions and in-licensing, for
example, are outside-in mechanisms. These two fundamental mechanisms, Inside-Out and Outside-In,
can be pursued concomitantly, for example by cross-licensing technologies, joint ventures, private-public
partnerships, strategic alliances, co-marketing arrangements and so forth (Chesbrough, 2012). Since
ideas can flow quite freely between a firm’s R&D and the external environment, the boundaries are no
longer depicted as solid lines, but as dotted lines that allow passing of ideas and knowledge. The Open
Innovation paradigm can be summarized as “… the use of purposive inflows and outflows of knowledge
to accelerate internal innovation, and expand the markets for external use of innovation, respectively”
(Chesbrough & Schwartz, 2007).
Internal technology
base
Externaltechnology
base
DifferentMarket
Market
Inside-Out (Spin-offs,
out-licensing
Outside-in (Acquisitions, in-licensing)
= Ideas
R DResearch Development
Figure 3: Open Innovation model. Source: (Chesbrough, 2003)
The Open Innovation model is inherently focused on creating value through externalizing unused
technologies and ideas and by internalizing outside useful knowledge. However, the aspect of capturing
value and making a profit out of these innovations has received less focus (Fischer & Henkel, 2012). In
order to explore the question of value capture in Open Innovation, the next section will explore the
concept of business models which is a statement of how a company intends to capture value. After the
discussion of business models, the next chapter discusses the literature on value capture. Then, we
explore how the literature on value capture applies to Open Innovation.
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2.1.2 Open Innovation and Business Models
In order to successfully implement an Open Innovation strategy, a company needs to have a clearly
defined business model. The term “Business Model” is a relatively recent concept that emerged in
strategic and entrepreneurial literature, but no generally accepted definition has yet been established
(for a comprehensive review on business models see: (Zott, Amit, & Massa, 2011)) Chesbrough defines
the business model as a framework that links technology and ideas to economic outcomes and, thereby,
encompasses two important functions: Value Creation and Value Capture (Chesbrough, 2006). The six
main aspects are depicted in Table 1.
Aspect of Business Model Authors mentioning similar aspect in Business
Model literature
Value Proposition: What is the need that the
product/service fulfills?
(Hedman & Kalling, 2003; Johnson, Christensen, &
Kagermann, 2008; Magretta, 2002; Shafer, Smith,
& Linder, 2005)
Market Segment: Who is the customer and how
will he be identified?
(Hedman & Kalling, 2003; Osterwalder & Pigneur,
2010; Teece, 2010)
Value Chain: Where does a company position itself
within the value chain and what are the
complementary assets to support this position?
(Amit & Zott, 2001; Hedman & Kalling, 2003;
Magretta, 2002)
Cost Structure / Profit Potential: What is the
firm’s mechanism to generate profit?
(Johnson, Christensen, & Kagermann, 2008)
Value Network: How are suppliers, customers,
complementors, and competitors linked?
(Amit & Zott, 2001; Shafer, Smith, & Linder, 2005)
Competitive Strategy: How does the company
achieve higher returns than its rivals?
(Teece, 2010)
Table 1: Main aspects of a business model and authors using similar frameworks and concepts. Adapted from: (Chesbrough, 2006)
The Business Model determines if a technology should be pursued in-house or should be externalized
and, conversely, if an external technology should be licensed-in or acquired. A technology that serves the
current business model for example by enhancing the value proposition to an existing customer segment
or reducing the production costs can be developed and commercialized internally. On the other hand, a
technology that serves a customer segment that is only marginal to the existing business and, therefore,
does not fit the current business model, should be externalized; for example by licensing the technology
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to a different company or creating a spin-off. The possibility of developing a technology by exploiting a
different business model is immensely valuable for both the licensee and the licensor. The licensee can
exploit a technology and potentially build a very useful value proposition to a customer through the
commercialization of the technology and the licensor will earn a significant amount of royalties if the
technology proves to be successful in the new business model. Therefore, it could be said that the
business model determines the economic value of a technology, and that it can have different values for
different business models. Chesbrough goes even further and claims that a “a mediocre technology
pursued within a great business model may be more valuable than a great technology exploited via a
mediocre business model” (Chesbrough, 2010).
It is interesting to note that the literature on Open Innovation which in its early days focused mainly on
value creation has increasingly shifted its attention to business models (Chesbrough, 2006). In particular,
it has influenced a new kind of innovation: Business Model Innovation. Traditionally, innovation meant
the development and commercialization of new products, processes, and services. Business model
innovation, however, focuses on developing the way how value gets created and captured; by changing
one or more of the six aspects of a business model that are mentioned in Table 1. Several academic
articles have been authored on various aspects of Business Model Innovation (Chesbrough, 2010;
Gambardella & McGahan, 2010; Johnson, Christensen, & Kagermann, 2008). The concept of Open
Innovation has been applied to the field of Business Model Innovation, resulting in “Open Business
Models”. A company that has an Open Business Model is able to change and is changed by the market; it
dedicates resources to experiments with different business model variants and explores alternative ways
to profit from innovation (Chesbrough, 2006). Table 2 highlights some key aspects of the traditional
Closed Innovation model where the business model is more or less static and contrasts them with the
Open Innovation model and a flexible, adaptive business model.
Key Aspect Closed approach (fixed Business
Model)
Open approach (with flexible
Business Model)
1. Fit between Business Model
and technology
Technology needs to fit business
model else technology is put on
the shelf.
Business model needs to fit
technology else the technology is
pursued externally with a
different business model or the
business model is adapted
2. What can be innovated? Products, services, processes Every aspect of the business
model
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3. Which department is
responsible for innovation?
R&D department Every department can influence
and improve one or more
aspects of the business model.
4. Nature of R&D department Cost-center Profit-center. Generates
revenues by licensing unused
technologies
5. Relationship to customers and
suppliers
Arm’s-length relationship Partnership. Supplier innovation
and customer co-creation play an
important role
Table 2: Key aspects of Open Innovation regarding business models
Business Model literature is highly relevant to this thesis since a Business Model represents a company’s
stance to Open Innovation, value creation, and value capture (Chesbrough & Schwartz, 2007). However,
this study aims at examining the interplay between value creation and value capture in open innovation
settings from a fundamental, theoretical perspective and does not intend to provide a concrete
framework for developing a company’s business model. For this purpose, the next section reviews the
literature on value capture in general before these concepts are applied to the Open Innovation model.
2.2 Value Capture from Innovation
In the previous section, we saw how Open Innovation changes the way a company interacts with its
environment, how it collaborates with external stakeholders, and how these changes affect a company’s
business model. In this section, we will focus on the aspect of profit and value appropriation: How can a
company sustain a competitive advantage even though it shares some of its key resources with
customers and/or competitors? Can a company following the Open Innovation concept not only create
value, but also appropriate a big part of this value? The following section discusses how value generated
by an innovation can be captured by the innovator and what determines the trade-off between benefits
and risks of research collaboration.
2.2.1 Value Capture from Innovation in General
An innovation delivers value either by fulfilling an unmet need, improving the quality of a product or
service, or by reducing the cost of providing a given quantity of a product or service (Becerra, 2009).
Who captures this value? Usually, the value is shared among the innovator, customers, suppliers, owner
of complementary assets, and imitators (see Figure 4).
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Figure 4: Possible value distribution of an innovation among different stakeholders
The customer captures part of the value if the innovation improves the value proposition or the cost of
the goods or services provided. The innovator obviously can benefit because the better value proposition
allows him to sell his product or service at a higher price or the innovation decreases his internal costs
which increases the profit margin. The supplier captures part of the value because the better value
proposition or reduced costs due to the innovation lead to a higher demand of the product or service
which in turn increases the demand for the supplier’s goods and services. The owner of complementary
assets benefits because the higher demand in the innovator’s good also increases the demand in
complementary assets. For example if a breakthrough innovation for mountain bikes increases the
overall demand for mountain bikes, sales for biking equipment is likely to go up in parallel. Lastly,
imitators capture part of the value since they can reproduce the technology without incurring the costs
to develop it. They are effectively freeriding on the innovator’s efforts. (Teece, 1986)
Teece proposed a framework to determine if an innovator is likely to capture value from his innovation
(Teece, 1986). The three factors that determine the share of value that the innovator can capture are the
appropriability regime, complementary assets, and the emergence of a dominant design (Figure 5).
Customer
Innovator
Supplier
Owner of complementary
assets
Imitator
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Appropriability regime
Complementary assets
Dominant Design
WeakStrong
Owned / controlled by innovator
Not owned/controlled by innovator
Already emerged Not yet emerged
Innovator likely to capture value from innovation
Value likely to be captured by others
Figure 5: Profiting from Innovation framework (Teece, 1986)
First, the appropriability regime is the extent to which an innovation can be protected from imitation.
Protection mechanisms can be either via legal impediments (trade secrets, patents, copyrights) or by a
low inherent replicability of the technology (Teece, 2006). Low inherent replicability means that an
imitator cannot easily understand and imitate the technology because it involves tacit knowledge that is
not easily transferable. Examples of technologies with low inherent replicability are biotechnology and
semiconductors. The protection that is granted by patents also differs greatly across industries.
Traditional product-oriented industries such as pharmaceuticals rely more heavily on patents than
industries that are primarily based on complex processes that are hard to disentangle and where patents
are primarily used as “bargaining chips” in negotiations (Cohen, Nelson, & Walsh, 2000).
Second, complementary assets are capabilities or assets that are required in conjunction with the
successful commercialization of the innovation (Teece, 1986). Teece distinguished three types of
complementary assets: Generic, specialized, and co-specialized. The difference between these three
types lies in the dependence between the innovation on complementary assets (Figure 6). Generic
complementary assets usually are the easiest to handle since they do not pose a strategic risk.
Specialized and co-specialized assets on the other hand require the strategic positioning of the
innovating firm if it intends to fully benefit from the innovation. Strategic positioning could mean to buy
the complementary asset (integration) or to partner with the owner of the strategic asset in order to
secure the access to it.
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De
pe
nd
en
ce o
f co
mp
lem
en
tary
ass
et o
n
inn
ova
tio
n
Dependence of innovation on complementary asset
Specialisedcomplementary
assetCo-specialised
GenericSpecialisedinnovation
Low High
Low
Hig
h
Figure 6: Distinction between generic, specialized and co-specialized complementary assets according to their mutual dependence (Teece, 1986).
The third factor is the emergence of a dominant design. The idea of a dominant design has been coined
by Abernathy and Utterback and describes an industry-wide accepted standard for a certain technology
(Abernathy & Utterback, 1978). If an innovator focuses on a standard before it has gained widespread
acceptance in the marketplace, the innovator bears the risk of having to change standard if another
standard emerges as the winner in the industry. Therefore, Abernathy and Utterback distinguish
between a pre-paradigmatic phase and a paradigmatic phase (Abernathy & Utterback, 1978). In the pre-
paradigmatic phase the dominant design has not yet emerged and the design should be left intentionally
open and the focus lies on product innovation. In the paradigmatic phase, on the other hand, a winning
standard has emerged and companies can now focus on process improvements and achieving economies
of scale.
2.2.2 Value Capture Aspects of Open Innovation
A central concern to an Open Innovation strategy is how the generated value can be captured and how
potential risks can be managed and minimized. Especially, risks arise from the fact that many Open
Innovation mechanisms require the disclosure of information, for example by detailing a process
innovation in a patent or freely reveal an experimental result to the public. Various concerns about the
appropriability of returns in relation with Open Innovation practices have been raised in the literature.
For instance, Oxley has shown that the type of agreement which is used in an inter-firm-alliance depends
very much on how the relevant property rights can be specified and on how difficult the monitoring is
(Oxley, 1997). If the property rights can easily be specified and monitored, firms tend to use a less
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hierarchical, unilateral agreement such as long-term supply or R&D contracts. On the other hand, if
property rights are blurred and enforcement is difficult, firms will choose a hierarchical agreement such
as an equity-based alliance (Joint venture) or a research corporation. Cohen, Nelson, and Walsh have
described that a major barrier for firms to patent their innovation is the necessity to disclose information
which might be useful for competitors (Cohen, Nelson, & Walsh, 2000). In addition, Van de Vrande and
coworkers have concluded that issues of ownership for co-invented technologies is an important
hampering factor for small to medium enterprises in pursuing collaborative innovation practices (Van De
Vrande et al., 2009).
Extending Teece’s framework, 4 generic strategies for capturing value in Open Innovation have been
identified in the literature and are depicted in Table 3. Three of them have been derived directly from
Teece’s “Profiting from innovation” model; namely changing the appropriability regime, controlling
complementary assets, and influencing the dominant design. The fourth strategy, creating intermediary
markets for innovation reflects the technological change brought by modern information technology
(Gambardella & McGahan, 2010) and is a peculiar aspect of Business Models and Open Innovation
(Chesbrough, 2006) . The first strategy, changing the appropriability regime covers the realm of formal IP
protection (patents, copyrights, trade secrets) and strategic uses of a patent portfolio, e.g. for cross-
licensing. Possible practices that fall under this strategy are aggregating patents to stop infringing
companies (defensive patent strategy) and acquiring innovating companies in order to fully appropriate
the generated value. Fischer and Henkel distinguish between product-related patents which are used to
prevent imitation and the strategic uses of a patent portfolio which is used as bargaining chips for cross-
licensing and deterrence of infringement suits (Fischer & Henkel, 2012). Strategic uses of a patent
portfolio are especially important in process-driven industries such as semiconductors that rely on many,
different broad technologies and where cross-licensing agreements are common (Grindley & Teece,
1997). Conversely, product-driven industries such as pharmaceuticals rely more heavily on formal,
product-related patents. Usually, formal IP protection is more effective for technologies that are
codifiable and nontacit (Winter, 1987). The second strategy is to control assets complementary to the
innovation activities. Dahlander and Wallin provide the example of software firms that actively support
open-source communities in order to promote the sales of complementary goods and services
(Dahlander & Wallin, 2006). The control of complementary assets is a main determinant when it comes
to decide to commercialize a technology in-house or to license it out (Arora & Ceccagnoli, 2006). Arora
and Ceccagnoli have shown that a more effective patent protection has a different effect on companies
in control of complementary assets than on those without it; the former being more inclined to
commercialize in-house while the latter will have an increased likelihood of licensing out the technology.
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The third one, influencing the dominant design can have two different motives; the first one being to
exploit a possible opportunity by gaining knowledge in a potentially fruitful area and the second one
being the ability to share risks across more players, for instance because an industry-wide accepted
standard has not yet emerged. The fourth strategy involves the emergence of an intermediary market
for technology. Chesbrough describes the case of six innovation intermediaries that act for example as IP
brokers or a buffer between solution seekers and providers (Chesbrough, 2006). Gambardella has
described the emergence of such intermediary markets and their effect mature industries (Gambardella
& McGahan, 2010). It is interesting to note that the first strategy is primarily concerned with formal IP
protection, the second and third one cover strategic issues and the fourth strategy focuses on business
models.
Strategies Literature mentioning aspect
Changing appropriability regime Choosing a more hierarchical agreement type
(Oxley, 1997)
Controlling complementary assets Open-source communities as complementary
assets (Dahlander & Wallin, 2006)
Influencing dominant design / getting access to
knowledge resources
Achieving early-mover advantage (Fischer &
Henkel, 2012; Grant & Baden-Fuller, 2004) Keeping
in touch and influencing technological change
(Grindley & Teece, 1997)
Creating intermediary markets for innovation General purpose technologies (Gambardella &
McGahan, 2010) Innovation intermediaries
(Chesbrough, 2006)
Table 3: Generic strategies to influence value capture from innovations
The four generic strategies are similar to other frameworks that have been proposed in the literature.
For instance, Fischer and Henkel have studied how perceptions of R&D and marketing personnel differ
when it comes to the effectiveness of appropriation mechanisms (Fischer & Henkel, 2012). The
framework contains five factors: Patent portfolio (e.g. strategic usage of patents), product-related
inventions which are patented, time-to-market, relevant complementary assets, and contributions to
open standards. The patent portfolio and product-related inventions aspect can be broadly mapped to
the appropriability regime, while time-to-market conveys ideas of early-mover advantage. Fischer and
Henkel extend the above framework with “contributions to Open Standards” (Fischer & Henkel, 2012).
21
Contributions to open standards lead to competitive advantage if they allow reputation building,
standard setting, and increased demand for complements.
While the first two section of this theory part have reviewed value creation and value capture in
isolation, the next section looks at the mutual relationships between Open Innovation, Value Creation,
and Value Capture.
2.3 Interplay of Openness, Value Creation, and Value Capture
2.3.1 Openness and Innovative Performance
Firms innovate in order to differentiate their products and service which in turn increases the customer’s
willingness to pay and allows the firm to earn a higher profit; under the caveat that the innovating firm
can capture at least part of the value(Becerra, 2009). Figure 7 shows this two-step process. The first step
describes the link between the firm’s innovation assets and its innovative output. This step is termed
“value creation” and the firm’s innovation strategy determines the breadth and depth of collaborative
partnerships. Laursen and Salter have described breadth as the number of external sources and search
channels a firm draws upon in its innovation activities and depth as the intensity with which these ties
are maintained (Laursen & Salter, 2006). Obviously, the choice of breadth and depth of the firm’s
innovation activities is highly dependent on the firm’s available assets and its external environment. One
asset is the firm’s knowledge stock, i.e. the information and experience about products, markets,
technologies, and political contexts (Levinthal & March, 1993). Beyond the firm’s internal capabilities,
external conditions such as the available technological opportunities and competitors’ activities
influence the strategic innovation choices to a large extent (Enkel, Gassmann, & Chesbrough, 2009;
Lichtenthaler, 2008). The second step in Figure 7 describes the link between the innovative and the
financial performance. As we have seen in the previous section, being innovative is by no means a
guarantee of being financially successful. Financial performance depends very much on the control of
complementary assets, the protection of intellectual property, and market timing. This next section
analyzes the mechanisms of value creation and value capture in more details and how they interact in an
Open Innovation setting.
22
- Knowledge Stock- Technological
opportunities- Activities of
competitors
Breadth and depth of
collaborative partnerships Innovative
performanceFinancial
performance
Complementary Assets /
Appropriability Regime /
Dominant Design
Value Creation
Value Capture
Figure 7: From innovation strategy to financial performance. Two-step process including value creation and value capture.
2.3.2 Drivers of Openness in Value Creation and Value Capture
A company’s innovation strategy can range from completely closed and internally-focused to highly
adaptive and externally-oriented. What determines a firm’s relative position on this scale? The answer to
this question lies partly in the social nature of research and science. Social scientists have studied for a
long time what causes researchers to pursue collaborations. Katz and Allen have identified financial
(Rising costs of fundamental research, decreasing costs of travel and communication), technological
(increased specialization, need for complicated instrumentation), psychological (social nature of science,
need for peer recognition), and political factors (e.g. European Union) that drive collaboration (Katz &
Martin, 1997). Of course, the same arguments hold true for collaborations that private companies
pursue, especially in science-driven industries such as semiconductors or pharmaceuticals. However, the
situation for private innovators is slightly more complicated since they need to cope with questions of
appropriability (Teece, 1986) and psychological barriers in organizations such as the not-invented-here
syndrome (Katz & Allen, 1982) and the lack of managerial commitment to external innovation (Van De
Vrande et al., 2009).
Drechsler and Natter have provided a framework for determining a firm’s openness that integrates
aspects of value creation and value capture (Drechsler & Natter, 2012). It is one of the very few
frameworks on Open Innovation that brings together aspects of value creation such as informal external
ties and external support to fill knowledge gaps and aspects of value capture such as appropriability
regime and market dynamics (e.g. entry timing). However, despite having the advantage of bringing
together isolated factors of value creation and value capture, Drechsler’s framework has still some
shortcomings. First, it does not specify what type of “openness” a company exhibits. Openness can mean
many things such as publications, patents, participation in research consortia, collaboration with public
institutions and so forth. What drives a firm to favor one form of openness over the other remains
23
unexplained. Second, the framework does not take into account that firms may have a differentiated
openness across their business units and areas of expertise. It has been shown in the embedded
software industry that firms reveal their knowledge quite selectively (Henkel, 2006). It has been argued
that selective revealing behavior is induced if the knowledge base is very modular, i.e. a firm can reveal
its knowledge without negatively affecting the value of the knowledge that remains proprietary (Alexy,
George, & Salter, 2012). Third, the framework does not really account for path dependence of Open
Innovation activities. However, it has been shown that in order to participate in Open Innovation
activities a company needs to build up skills and reputation; a process that can take years (Henkel, 2006).
This path-dependence reflects the notion that openness is a strategic choice that requires time and
resource commitment.
Innovative capacity:- Knowledge stock- Informal ties to
external partners
Scarce firm resources:- Financial gaps- Knowledge gaps
Appropriability Regime:- Product-related
patents- Strategic patent
portfolio
Market dynamics:- Technological change- Uncertain demand- Competitive threats
Openness of innovation activities
Controlling variables:- Product/Service oriented- Firm size- Number of competitors
Val
ue
Cre
atio
n a
spe
cts
Val
ue
Cap
ture
asp
ect
s
Figure 8: Framework for determining openness based on value creation and value capture drivers. Adapted from Drechsler and Natter 2012.
This section ends the review on the current literature of value creation and value capture aspects of
Open Innovation. The next section summarizes the research gap and leads to the research question.
2.4 Research Gap and Research Question
Open Innovation is a fairly new concept and has seen a staggering growth in interest both from academia
and business (Chesbrough, 2012). However, most of the work has focused on questions of value creation
while value capture has by and large been neglected (Fischer & Henkel, 2012). Even though some studies
in recent years have tried to shed light on the issue of value capture in open innovation (Fischer &
24
Henkel, 2012; Van De Vrande et al., 2009), they do not provide a sufficient theoretical framework for
value creation and value capture in Open Innovation. First, they do not study aspects of value creation
and value capture concomitantly, but focus either on value creation or value capture. Second, they do
not explain why a firm would decide to be more open in one business area but not in the other even
though such behavior exists in reality (Alexy, George, & Salter, 2012; Henkel, 2006). Third, existing
literature does not provide enough differentiation between different forms of openness and why a firm
would engage in a particular form of Open Innovation activities such as joint-ventures, research
consortia, and so forth. Fourth, since many studies rely on cross-sectional surveys or decision games,
they lack a comprehensive view of the path-dependence and time evolution of Open Innovation
practices.
In order to give possible hints how these questions could be answered, an explorative research question
is stated:
What patterns of value creation and value capture can be observed in Open Innovation and how does
value creation and value capture interact in an Open Innovation setting?
25
3. Methodology
3.1 Research approach
To answer the research question, an explorative research method has been chosen. It has been noted in
the literature that research needs to achieve a fit between the level of maturity of the field and the
research methodology (Edmondson & McManus, 2007). As it was shown in the literature review, no fully
developed theory for value creation and value capture in Open Innovation exists at the moment. Given
the nascent state of the field, we cannot build hypothesis and confirm them using statistical methods
since the resulting correlations would not be backed up by a solid theory (Edmondson & McManus,
2007). Rather is it essential to develop detailed knowledge of the available data and to achieve intimacy
with the many layers of patterns that occur (Behrens & Yu, 2003). This approach is termed “Exploratory
Data Analysis” and was developed by John Tukey and is a method that tries to extract and interpret
patterns that occur in the data (Tukey, 1977). The goal of this method is to construct a terse,
mathematical description of a problem that eventually leads to hypothesis formulation (Behrens & Yu,
2003). Conversely, traditional confirmatory data analysis focuses on verification of testable hypothesis
using rigorous and well-defined statistical methods (Behrens & Yu, 2003).
This master thesis provides an explorative study of value creation and value capture aspects in Open
Innovation. The next section details the nature and scope of the data set and justifies the reason for this
choice.
3.2 Study sample
3.2.1 Pharmaceutical Industry
In order to understand the value creation and value capture aspects of Open Innovation, this study
analyses the publications and patents that were published and issued from 2002 to 2012 of the ten
largest pharmaceutical companies. The ten largest pharmaceutical companies are shown in Table 4. In
this section, it is first explained why the pharmaceutical industry has been chosen and in a second step
why the research was limited to the ten largest firms of the industry.
26
Company Sales Profits Assets Market Value
Pfizer 67.4 10.0 188.0 165.4
Novartis 58.6 9.1 117.5 150.4
Sanofi 43.2 7.4 125.3 103.3
Merck & Co 48.0 6.3 105.1 115.8
Roche Holding 45.3 10.0 62.9 152.0
GlaxoSmithKline 42.5 8.2 59.4 111.8
Abbott Laboratories 38.9 4.7 60.3 93.4
AstraZeneca 32.4 9.6 51.4 58.0
Eli Lilly & Co 24.3 4.3 33.7 46.6
Bristol-Myers Squibb 21.2 3.7 33.0 56.0
Table 4: The ten largest pharmaceutical companies based on a weighted average of sales, profits, assets and market value. Values in billion US Dollars and based on 2011 financial reports. Source: (Forbes, 2012)
The pharmaceutical industry has been chosen for several reasons. First, the pharmaceutical industry has
suffered in recent years from a declining R&D productivity (Garnier, 2008). The cost of developing a new
molecular entity, i.e. a drug containing an active ingredient that has not been approved previously, has
risen to 1.8 billion US dollars (Paul et al., 2010). Several authors have suggested more open approaches
to drug development (Munos, 2010; O’Hagan & Farkas, 2009; Tralau-Stewart et al., 2009). Second,
compared to other industries, patents in the pharmaceutical industry are seen as an effective means of
IP production (Teece, 1986). Hence, it provides a suitable proxy for value capture in research; especially
given the readily availability of patent filings online. Data on intellectual property protection such as
patent filings can easily be retrieved from public and private databases (USPTO Web Patent Database,
Thomson Reuters’ Derwent Innovations Index, etc.). Conversely, in industries where patenting activity is
spurious and heterogeneous across companies, one cannot rely on patent filings as a proxy for value
capture (Drechsler & Natter, 2012). Third, pharmaceutical companies are highly complex endeavors that
require the integration of many specialists and technologies. Therefore, it provides a rich data set with
many different forms of collaboration and institutional arrangements that can be studied. Fourth,
pharmaceutical companies possess a high amount of specialized complementary assets such as
investments in research facilities and human capital. Previous research has shown that great differences
in patenting and licensing activity exist between companies with no complementary assets such as start-
ups and companies with a lot of complementary assets (Arora & Ceccagnoli, 2006).
27
3.2.2 Focus on Large Companies
The pharmaceutical industry has been chosen because of its characteristics that make it interesting to
study Open Innovation. This study also limits its scope to the ten largest companies of the
pharmaceutical industry for several reasons. First, the exploratory nature of this study makes it more
difficult to control for variables such as firm size and fundamentally different patenting policies. The ten
largest companies of an industry constitute a rather homogeneous sample that allows to infer
conclusions more easily. Second, it is assumed that the publishing and patenting of large firms remains
fairly stable over time while a larger variance would be observed for smaller firms. In addition, due to a
high Mergers & Acquisitions activity, extreme variations could occur if two similar sized companies
merge and double their output of publications and patents basically overnight (LaMattina, 2011). Third,
by limiting the sample to the ten largest pharmaceutical companies, the size of the data set is more
manageable. Since all patents and publications over ten years are retrieved, a very large data set is
obtained, amounting to almost 1 gigabyte of data. For computational reasons, the data analysis process
is much easier if the data set does not exceed a certain size
3.2.3 Using Publications and Patents to Study Value Creation and Value Capture
In order to operationalize value creation and value capture, publications and patents are used as proxies.
Publications represent a contribution to the existing body of knowledge and they signify a better
understanding of the nature of human diseases. Even though the increase in knowledge cannot be
stated as value as such, it is obvious that knowledge will eventually create value by allowing the
development of better drugs and therapies. Therefore, publications are used as proxy for value creation
in this thesis. Patents on the other hand, represent value capture since they have an intrinsic economic
value and can be sold or licensed to other companies. It has been noted that patents can have a wide
range of uses from fending of patent trolls to revenue generating mechanisms (Cohen, Nelson, & Walsh,
2000). Patents provide a good proxy for value capture because they require not only being non-obvious,
but they must also have a commercial value for the patenting company. Else, they would not choose to
patent the innovation and pay the patenting fees.
In order to uncover the underlying evolution of value creation and value capture mechanisms in Open
Innovation, a time-frame of 10 years (from 2002 to 2012) was chosen. The publications were retrieved
from the ThomsonReuters WebOfScience database and the patents from ThomsonReuters
DerwentPatent Index. The search queries depicted in Table 5 were used to generate the data set. The
search queries were designed to include all publications and patents by the major legal entities of the
ten largest pharmaceutical companies.
28
Company Publications-Query Patents-Query #Publications #Patents
Pfizer AD=PFIZER AE=PFIZER 11280 2604
Novartis AD=NOVARTIS AE=NOVARTIS 9471 3597
Sanofi
AD=SANOFI OR AD=AVENTIS AE=SANOFI or AE=AVENTIS 4378 2988
Merck & Co AD=MERCK AE=MERCK 10833 5364
Roche Holding AD=ROCHE AE=ROCHE 6836 2772
GlaxoSmithKline AD=GLAXOSMITHKLINE or
AD=SMITHKLINE
AE=GLAXO or
AE=SMITHKLINE 10431 3285
Abbott Laboratories AD=ABBOTT AE=ABBOTT 4293 4154
AstraZeneca AD=ASTRAZENECA or
AD=ZENECA
AE=ASTRAZENECA or
AE=ZENECA 7535 2371
Eli Lilly & Co AD=ELI LILLY or AD = LILLY AE=ELI or AE=LILLY or
AC=ELIL-C 4999 1297
Bristol-Myers Squibb AD=BRISTOL MYERS SQUIBB AE=BRISTOL MYERS SQUIBB 4099 1913
Table 5: Queries used in WebOfScience and Derwent Patent database to generate the data set. AD stands for “Address”, AE for “Assignee Name + Code” and AC for “Assignee Code” Mergers and name changes that happened during 2002 and 2012 or just before, such as the merger between Sanofi and Aventis in 2004, required to search for two entities instead of one in some cases.
Since we are interested in the authors’ affiliation, the query was performed on the authors’ address for
publications (Query code “AD”) and on the assignee (Query code “AE”) for patents. The query was
performed on the 24th of February 2013. After eliminating empty of ill-formatted records, a data set
containing 73840 publication records and 29620 patent records was obtained.
3.3 Extracting Relevant Information from Dataset
3.3.1 Extracting Company Affiliation
The first step in extracting relevant information from the data was to determine to which of the ten
largest pharmaceutical companies a publication or patent should be assigned. This was done by looking
for the company name in the address field in the publications record and the assignee in the patent
records. To accomplish this quickly for >100’000 records and to take into account slight name variations
(e.g. “Bristol Myers” and “Bristol-Myers”) a function was written in Visual Basic for Applications (VBA)
which is a scripting language within several Microsoft applications such as Microsoft Excel. The function
takes the address field and, optionally, the reprint author as an input and yields one or more company
names as an output. The VBA function is given in appendix 7.1.1.
29
3.3.2 Extracting Disease Area
The second step in getting useful information out of the data was to assign each patent and publication
to one or more therapeutic areas based on two newly developed procedures. Both publications and
patents are assigned to categories; publications in WebOfScience via the subject areas and patents via
the International Patent Classification (IPC) code. The subject area classification is a proprietary
classification algorithm by Thomson Reuters that assigns each article to one or more categories out of a
list of more than 250 categories (Thomson-Reuters, 2013). The IPC code is maintained by the World
Intellectual Property Organization (WIPO) and classifies each patent to a category according to the
technology to which it pertains (WIPO, 2013).
In order to have a consistent and comparable classification between the WebOfScience subject area and
the IPC patent classification, each relevant subject area has been linked to one or more IPC codes by
manually comparing the classifications and mapping them individually to each other. Out of the >250
subject area classifications, 34 categories have been initially deemed relevant for pharmacological and
medical research. These categories and the IPC codes which have been mapped to them are depicted in
Table 6. The most relevant IPC code for pharmaceutical purposes is A61P: “Specific therapeutic activity
of chemical compounds or medicinal preparations”. Almost all A61P categories were linked to at least
one subject area based on individual judgment which category would fit best. A detailed table is given in
the appendix.
Life Sciences & Biomedicine Corresponding IPC code(s)
Allergy A61P-037/08; A61P-011/06; A61P-027/14
Anesthesiology A61P-023
Biotechnology & Applied Microbiology C12N; C12P; C12Q
Cardiovascular System & Cardiology A61P-009
Dentistry, Oral Surgery & Medicine A61Q-011; A61K-006
Dermatology A61P-017
Endocrinology & Metabolism A61P-003; A61P-005; A61P-021/06
Gastroenterology & Hepatology A61P-001
Genetics & Heredity A61K-048; A01H-001/06; C12N-015; C12N-001; C12N-005; C12N-007
Hematology A61P-007
Immunology A61P-037/02; A61P-037/04; A61P-037/06; G01N-033/50; G01N-033/53; G01N-033/54; G01N-033/55; G01N-033/56
Infectious Diseases A61P-031
Mathematical & Computational Biology C40B
Medical Laboratory Technology C12Q
Mycology C12N-001/12; C12N-001/13; A61P-031/10
Neurosciences & Neurology A61P-025; A61P-021/02; A61P-021/04
30
Obstetrics & Gynecology A61P-015/02; A61P-015/04; A61P-015/06
Oncology A61P-035
Ophthalmology A61P-027/02; A61P-027/04; A61P-027/06; A61P-027/08; A61P-027/10; A61P-027/12; A61P-027/14
Orthopedics A61F-005
Otorhinolaryngology A61P-027/16
Parasitology A61P-033
Psychiatry A61P-025/18; A61P-025/20; A61P-025/22; A61P-025/24; A61P-025/26; A61P-025/28; A61P-025/30; A61P-025/32; A61P-025/34; A61P-025/36
Radiology, Nuclear Medicine & Medical Imaging
A61N-005; A61B-006; A61M-036
Reproductive Biology A61P-015/08
Respiratory System A61P-011
Rheumatology A61P-029; A61P-019
Substance Abuse A61P-025/30; A61P-025/32; A61P-025/34; A61P-025/36
Surgery A61B-018; A61B-017
Toxicology A61P-039/02
Transplantation A61P-037/06
Urology & Nephrology A61P-013
Veterinary Sciences A61D
Virology A61P-031/12; A61P-031/14; A61P-031/16; A61P-031/18; A61P-031/20; A61P-031/22
Table 6: Initial list of 34 subject areas and the corresponding IPC codes. The IPC codes were assigned according to individual judgement.
A VBA function was written to check for each publication and patent if it pertained to a certain category.
Additionally, a VBA procedure created automatically an overlap matrix that measured the relative
occurrences of entries that were assigned to multiple categories. The VBA function and procedure is
detailed in the appendix. Since every category has a potential overlap with every other category, the
resulting overlap scheme is a 34 x 34 matrix. The initial overlap matrices for publications and patents are
depicted in the appendix. Table 7 and Table 8 show the 14 final categories and the overlap they have
with each other.
31
Alle
rgy,
R
esp
irat
ory
Syst
ems,
EN
T
Bio
tech
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y &
Ap
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Car
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yste
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Car
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End
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Gas
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logy
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Infe
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V
iro
logy
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Par
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Ne
uro
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Op
hth
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gy
Rh
eum
ato
log
y Uro
gen
ital
&
Pre
gnan
cy
Allergy, Respiratory Systems, ENT
100.0% 1.0% 0.0% 0.0% 0.0% 0.0% 1.9% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Biotechnology & Applied Microbiology 2.9%
100.0% 4.6% 2.7% 4.8% 4.8% 3.1% 0.0% 8.4% 2.9% 8.6% 2.4% 4.9% 2.5%
Cardiovascular System & Cardiology 0.0% 1.5%
100.0% 0.0% 0.0% 0.0% 0.0% 3.2% 1.8% 6.6% 6.0% 0.0% 11.6% 0.0%
Dermatology 0.0% 1.4% 0.0% 100.0
% 0.0% 0.0% 10.4% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Endocrinology & Metabolism 0.0% 1.6% 0.0% 0.0%
100.0% 0.0% 0.0% 1.4% 1.1% 6.3% 2.0% 0.0% 6.9% 0.0%
Gastroenterology & Hepatology 0.0% 1.6% 0.0% 0.0% 0.0%
100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Hematology 3.7% 2.0% 0.0% 13.5% 0.0% 0.0% 100.0
% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Immunology 0.0% 0.0% 5.3% 0.0% 2.3% 0.0% 0.0% 100.0
% 10.8% 2.7% 6.1% 0.0% 9.9% 0.0%
Infectious Diseases, Virology, Parasitology 0.0% 4.2% 2.8% 0.0% 1.7% 0.0% 0.0% 10.0%
100.0% 1.3% 3.7% 0.0% 4.0% 0.0%
Neurosciences & Neurology 0.0% 1.7% 11.4% 0.0% 11.1% 0.0% 0.0% 2.9% 1.5% 100.0
% 3.0% 0.0% 0.0% 0.0%
Oncology 0.0% 5.1% 10.9% 0.0% 3.7% 0.0% 0.0% 6.8% 4.5% 3.2% 100.0
% 0.0% 16.7% 0.0%
Ophthalmology 0.0% 1.2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0
% 0.0% 0.0%
Rheumatology 0.0% 1.4% 9.9% 0.0% 5.9% 0.0% 0.0% 5.1% 2.3% 0.0% 7.8% 0.0% 100.0
% 0.0%
Urogenital & Pregnancy 0.0% 0.9% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0
%
Total Number 888 2610 857 1342 848 843 1744 1410 1305 1496 1570 1315 731 919
Table 7: Overlap matrix of patent data. All overlap greater than 20% has been eliminated by orthogonalization.
Alle
rgy,
Res
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ry
Syst
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EN
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Allergy, Respiratory Systems, ENT ### 0.0% 8.7% 1.0% 0.0% 0.0% 0.0% 0.0% 0.3% 0.2% 3.3% 0.0% 0.0% 0.0%
Biotechnology & Applied Microbiology 0.0% ### 0.5% 0.0% 0.1% 0.0% 1.3% 10.5% 2.9% 0.4% 5.0% 0.3% 0.0% 0.3%
Cardiovascular System & Cardiology 13.8% 0.5% ### 0.0% 1.7% 0.0% 0.0% 0.0% 0.0% 1.3% 0.0% 0.0% 0.0% 0.8%
Dermatology 0.2% 0.0% 0.0% ### 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.3% 0.0% 0.0% 0.0%
Endocrinology & Metabolism 0.0% 0.1% 1.8% 0.0% ### 0.0% 3.0% 0.4% 0.0% 1.4% 0.4% 0.0% 0.0% 3.5%
Gastroenterology & Hepatology 0.0% 0.0% 0.0% 0.0% 0.0% ### 0.0% 0.7% 1.5% 0.9% 0.0% 0.0% 0.0% 0.0%
Hematology 0.0% 0.5% 0.0% 0.0% 1.2% 0.0% ### 3.0% 0.0% 0.5% 3.8% 0.0% 0.0% 0.1%
Immunology 0.0% 7.9% 0.0% 0.0% 0.3% 1.5% 5.5% ### 0.0% 0.5% 1.4% 0.0% 0.0% 3.5%
Infectious Diseases, Virology, Parasitology 0.5% 2.7% 0.0% 0.0% 0.0% 4.0% 0.0% 0.0% ### 0.0% 0.0% 0.0% 0.0% 0.0%
Neurosciences & Neurology 0.8% 0.9% 3.2% 0.0% 3.3% 5.4% 3.0% 1.4% 0.0% ### 0.9% 1.5% 0.0% 0.1%
Oncology 8.2% 7.1% 0.0% 3.6% 0.6% 0.0% 13.1% 2.7% 0.0% 0.6% ### 0.0% 0.0% 7.6%
Ophthalmology 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.1% 0.0% ### 0.0% 0.0%
Rheumatology 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% ### 0.0%
Urogenital & Pregnancy 0.0% 0.1% 0.5% 0.0% 1.8% 0.0% 0.2% 2.4% 0.0% 0.0% 2.7% 0.0% 0.0% ###
Total Number 1'797 3'153 2'866 419 3'073 1'106 1'281 2'364 2'868 7'005 4'430 333 906 1'585
Table 8: Overlap matrix of publication data
Especially for patents, the initial overlap between certain categories was extremely high. This is probably
due to the fact that patents are usually filed with very broad claims, for example to block competitors
32
from patenting the same compound for a different indication. In order to reduce highly overlapping
categories (such as allergy and respiratory systems) a method by Agarwal and Searls to orthogonalize the
classification scheme was used (Agarwal & Searls, 2009). It consists of merging highly overlapping
categories (e.g. Allergy and Respiratory Systems) into one single category and to subtract some
categories from each other (e.g. changing the category from (Gastroenterology) to (Gastroenterology
BUT NOT hematology). The initial overlap matrices before orthogonalization are depicted in the
appendix.
3.3.3 R&D Intensity Data
Information on R&D intensity was retrieved from a Bloomberg terminal. The data extracted includes all
R&D intensities, i.e. total R&D expenditure divided by total sales, from 2002 to 2012. The figures for
2012 are preliminary figures since the annual reports for 2012 had not been published at the time of
extraction.
3.4 Calculating Openness
In order to calculate the degree of collaboration, it is important to distinguish between different forms of
collaboration. Collaboration can mean between individuals, departments, institutions, industries, or
geographic locations (Katz & Martin, 1997). In the context of Open Innovation where the boundaries of a
company are relevant, it makes sense to focus on inter-institutional collaboration. To measure inter-
institutional collaboration, co-authorship based on the author’s affiliation has been taken as a measure.
Co-authorship has been shown to be a reliable proxy for research collaboration in literature (Schummer,
2004).
To calculate openness, an “Openness measure” has been developed. The openness measure describes
the nature of collaboration that is embodied in a publication or patent. It takes the value of zero if
authors are only affiliated with one institution, hereby called “home institution”. If the article features
authors affiliated with three institutions (home institution, Univ A, and Univ B), the value would be 0.67.
The formula is detailed below.
( )
In our data set, the openness measure was calculated for the ten largest pharmaceutical companies. In
case a paper is written by authors affiliated with two or more of these companies, the openness score
was averaged (since the openness might be different between companies). The VBA function that
calculates the Openness measure is given in the appendix.
33
The same procedure was used for determining the openness of patents. Instead of the address the
assignee name was compared.
( )
4. Results and Findings
Based on the publishing and patenting activity of the ten largest pharmaceutical companies, the
following section presents the findings of an in-depth analysis of value creation and value capture in
Open Innovation. First, it investigates the value creation which is measured by the number and nature of
publications. Second, it analyzes how the ten largest pharmaceutical companies capture value which is
measured by the patents that have been issued from 2002 to 2012. Third, it offers a comprehensive
picture of value creation and value capture, and integrates and contrasts the patterns that occur in both
value creation and value capture.
4.1 Value Creation in Open Innovation
4.1.1 Industry-wide Evolution
The analysis of publication data from 2002 to 2012 reveals that the overall openness in value creation
has steadily increased. Figure 9 shows the increase of co-authored publications of all 10 pharmaceutical
companies combined. The openness increases significantly from below 50% in 2002 to 57% in 2012. The
increase in openness parallels the increase in total numbers of publications; hence the total number of
publications and the relative share of co-authored papers have increased in lockstep.
Figure 10 indicates the type of co-authorship in the publications from 2002 to 2012. One observes a
steady decrease of purely internal research papers (neither co-authored with other firms or public
institutions) and an increase in interfirm co-authorship while the percentage of inter-firm co-authored
papers has reached 10%. Still, most of the papers (around 70%) are co-authored with researchers from
public institutions.
Figure 9 and Figure 10 aggregates data of the ten largest pharmaceutical companies. The next section
digs deeper into these numbers and looks at firm-specific patterns.
34
Figure 9: Evolution of total number and openness in publications from 2002 to 2012. The blue line represents total number of publications and the red line the openness measure as defined in section 3.4.
Figure 10: Type of co-authorship in published papers. Orange bars indicate the percentage of interfirm co-authorship between the ten largest pharmaceutical companies. Blue bars indicate the percentage of papers that were authored purely by authors affiliated to one company. The grey line shows the R&D intensity (R&D expenditure divided by Total Sales)
47%
48%
49%
50%
51%
52%
53%
54%
55%
5900
6100
6300
6500
6700
6900
7100
7300
7500
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Op
en
ne
ss
Nu
mb
er
of
pu
blic
atio
ns
Number of publicationsOpenness
0%
5%
10%
15%
20%
25%
30%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Interfirm alliance Purely internal research R&D intensity
35
4.1.2 Firm-specific Patterns of Value Creation
Table 9 highlights the interfirm differences in openness, R%D intensity, and number of publications. The
openness ranges from 43.4% (Merck) to 64.7% (Roche). R&D intensity and the total number of
publications do not provide an explanation for the inter-firm differences.
Company Total Publications
R&D Intensity Openness
Roche 7750 18.8% 64.7%
Sanofi 4380 15.2% 59.0%
Eli Lilly 6600 20.2% 55.9%
Novartis 9471 16.3% 55.3%
Astrazeneca 7931 16.2% 54.0%
GlaxoSmithKline 10681 14.2% 52.2%
Pfizer 11272 15.1% 48.7%
Abbott 4312 9.7% 47.4%
Bristol Myers Squibb 4099 16.6% 44.1%
Merck 10835 17.2% 43.4%
Table 9: Total number of publications, average R&D intensity (R&D expenditure divided by Total Sales) and average openness of the ten largest pharmaceutical companies from 2002 to 2012 as defined in section 3.4
Figure 11 shows the annual changes in R&D intensity and openness in the timeframe of 2002 to 2012.
Clearly, most of the companies have significantly increased their openness and slightly increased their
R&D intensity. However, the drivers of publication output seem to be complex. On the one hand, the
two largest firms in the sample, Novartis and Pfizer, have seen the highest increase in the number of
publications even though they have not significantly increased their openness. On the other hand, the
two companies with the largest increase in openness (Abbott and Bristol Myers) have also seen a
substantial increase in the number of publications.
36
Figure 11: Annual growth of R&D intensity (R&D expenditure divided by total sales) and annual growth of openness from 2002 to 2012. Bubble size corresponds to total sales in the year 2012. The color indicates the annual growth in number of publications.
Figure 12 links on a firm-level the type of collaboration between pharmaceutical companies (such as
interfirm alliance, purely internal research – see Figure 10) and the efficiency of publication activity (the
total R&D expenditures in a year divided by the number of papers in a year). Two observations can be
made. First, companies that engage more frequently in interfirm-alliances are also more open in general.
Second, companies that are the least efficient in creating publications (Merck, GlaxoSmithKline,
AstraZeneca, EliLilly) tend to be located on the lower left (low openness, low share of inter-firm alliances)
while the most efficient firms in publications tend to be on the upper right (high openness, high share of
inter-firm alliances)
37
Figure 12: Share of inter-firm alliances and and openness from 2002 to 2012. An interfirm alliance is defined as a paper that is jointly published by two or more of the ten largest pharmaceutical companies. Bubble size corresponds to Total Sales in 2012. The color indicates the R&D expenditure per published paper.
Two main observations from the firm-level analysis of Value Creation can be drawn. First, increasing the
openness seems to increase the number of published papers, however with the exception of the notable
exceptions of the two largest firms in the sample. Second, the data indicates that engaging in inter-firm
alliances and displaying a high degree of openness increases the efficiency of publishing activity. The
next section will focus on value creation aspects across different disease areas.
4.1.3 Disease Area Patterns in Value Creation
Table 10 provides an overview of the publications across disease areas. We observe openness scores
from 58.5% (Immunology) to 70.5% (Gastroenterology & Hepatology). Biotechnology has the lowest
openness of 43%.
38
Total publications
Relative share Openness
Gastroenterology & Hepatology 1106 3.3% 70.5%
Cardiovascular System & Cardiology 2866 8.6% 69.5%
Rheumatology 906 2.7% 69.5%
Urogenital & Pregnancy 1585 4.8% 67.1%
Allergy, Respiratory Systems, ENT 1797 5.4% 66.8%
Dermatology 419 1.3% 65.6%
Oncology 4430 13.3% 64.9%
Hematology 1281 3.9% 64.1%
Infectious Diseases, Virology, Parasitology
2868 8.6% 62.4%
Endocrinology & Metabolism 3073 9.2% 61.9%
Ophthalmology 333 1.0% 61.1%
Neurosciences & Neurology 7005 21.1% 59.0%
Immunology 2364 7.1% 58.5%
Biotechnology & Applied Microbiology 3205 9.6% 49.0%
Not assigned 42691 n/a 43.3%
Table 10: Number of publications, relative share, and openness in publications of disease areas from 2002 to 2012. ENT = ear, nose, throat. Not assigned are records which could not be clearly attributed to one disease area.
The next section presents the patterns and finding from the analysis of patent data from 2002 to 2012.
Hence, the attention moves from value creation to value capture.
4.2 Value Capture in the Top10 Pharmaceutical Companies
While publications have increased both in total number and in openness, patents have decreased in
these two respects. Figure 13 indicates the decline in total number of patents and average openness of
patents which is contrary to the increase in publications (see Figure 9). Within 10 years the number of
patents has halved and the openness has been reduced by a factor of three.
Figure 14 sheds light on the different collaboration types that are present in publications and patents.
Almost 80% of the publications are co-authored by at least one external author. Conversely, 80% of the
patents are assigned to one company only. Co-issuance with other institutions such as universities
amounts to only 20%. Interfirm co-issuance in patents is almost non-existent.
39
Figure 13: Number of patents and average openness of patents of the top10 pharmaceutical companies from 2002 to 2012.
Figure 14: Type of collaboration in publications and patents from 2002 to 2012. Interfirm alliance describes a publication that is co-authored or a patent that is issued with another Top10 pharmaceutical company.
0%
2%
4%
6%
8%
10%
12%
14%
0
500
1000
1500
2000
2500
3000
3500
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Ave
rage
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aten
ts
Patents issued
Patent openness
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Publications Patents
Internal research
Alliance with otherinstitution
Interfirm alliance
40
Figure 15 visualizes which disease areas have gained in importance relative to other disease areas and
how their openness has evolved in the last 10 years. One observes that some key disease areas such as
oncology and infectious diseases have gained in importance. More mature disease areas like urogenital
and hematology have lost significance. Interestingly, an increase in relative importance does not parallel
an increase in openness and a rather complex picture emerges. Please note that openness refers to
openness in publications since openness in patents is very spurious for patents (see Figure 14). The
company-level and disease area specific data on patent openness is given in appendix 7.7.
Figure 15: Annual change of patent share of different disease areas against the change in openness of publications. Bubble size corresponds to total number of patents. The color does not have any special meaning in this case and is for illustration purposes only.
Some pharmaceutical companies specialize in certain disease areas, hence they issue more patents
specific to this therapeutic field. Figure 16 indicates the focus of the ten largest pharmaceutical
companies. While some companies (GlaxoSmithKline, Pfizer) have a fairly equal distribution across all
disease areas, some companies focus on key areas (Novartis on oncology, Eli Lilly on neurosciences &
neurology).
41
Figure 16: Relative share of patents of each of the 14 disease areas. Color indicates the relative share of patents from 2002 to 2012 for the ten largest pharmaceutical companies. The companies are ordered in increasing order (measured in total sales) from top to bottom.
4.3 Interplay of Value Creation and Value Capture
One might expect that the number of publications and patents follow a linear relationship: The more
publications, the more patents. However, the data clearly suggest that this is not the case. Figure 17
plots the number of publications against number of patents of each disease area. Even though we see
that more publications generally also means more patents, certain areas have a relatively high numbers
of publications, but not that many patents (Hematology, Neurosciences & Neurology) while certain other
areas (Biotechnology & Applied Microbiology) have a low number of publications but many patents.
42
Figure 17: Number of publications and number of patents of all disease areas
Table 11 shows in which areas the ten largest pharmaceutical companies had the largest share of
publications and patents. We see that they focused mostly on Neurosciences, Oncology, and
Biotechnology.
43
Company 1st area of focus 2nd area of focus
Pfizer Neurosciences & Neurology Oncology
Novartis Oncology Biotechnology
Roche Biotechnology Immunology
Merck Neurosciences & Neurology Biotechnology
Sanofi Biotechnology Oncology
GlaxoSmithKline Neurosciences & Neurology Biotechnology
Abbott Neurosciences & Neurology Biotechnology
AstraZeneca Oncology Cardiovascular diseases
Eli Lilly Neurosciences & Neurology Oncology
Bristol Myers Squibb Oncology Neurosciences & Neurology
Table 11: Focus areas of the ten largest pharmaceutical companies. Focus areas determined by taking the average of the publications and patents share. The two areas with the highest average are the two focal areas.
Figure 18 shows the evolution of the share of focal areas in the total publication and patent portfolio.
While the share of focal areas on publications has remained constant, we see a slight increase at around
2010 in the share of focal areas in the overall patent portfolio. However, at this time the total number of
patents has also drastically decreased, therefore it could be that this is a statistical artifact.
In addition, no significant differences in disease areas on which the large pharmaceutical companies
focus on can be observed. Both have increased by about the same amount.
44
Figure 18: Evolution of focal areas of ten largest pharmaceutical companies from 2002 to 2012. Focal areas means the highest relative share of disease areas (Average of patent share and publication share)
0%
10%
20%
30%
40%
50%
60%
70%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Openness total
Openness focal areas
Publications focal areas
Patents focal areas
45
5. Discussion
This master thesis provides answers to how value creation and value capture interact in Open Innovation
and aims to fill the gaps that have been identified in the literature. The thesis contributes to the existing
body of literature by suggesting how Open Innovation practices in value creation influence value capture
mechanisms and vice versa, if firms display a different degree of openness in different business areas,
and which forms of Open Innovation are chosen under different circumstances.
5.1 Interplay of Value Creation and Value Capture in Open Innovation
The results suggest that Open Innovation practices in value creation have a profound effect on value
capture. While the number of publications has steadily increased, the number of patents has plummeted
in the pharmaceutical industry (see Figure 9 and Figure 13). Furthermore, most of the companies have
become more open in their value creation process (measured in terms of co-authored publications) and
less open in their value capture process (measured in terms of co-issued patents). How should this result
be interpreted?
In recent years, open-source and Open Innovation concepts have gained a foothold in company’s
innovation practices. Several pharmaceutical companies have publicly announced that they embrace
Open Innovation concepts. For instance, GlaxoSmithKline started an initiative in 2010 called “Tres
Cantos” where over 13’500 potential drug candidates for treating malaria or tuberculosis were released
to the public (GlaxoSmithKline, 2013). Another example includes Eli Lilly’s “Open Innovation Drug
Discovery” initiative where external institutions can submit potential drug candidates for testing in Eli
Lilly’s proprietary phenotypic and target-based assays. The submitting institution retains intellectual
property rights and if the compound demonstrates an interesting activity fingerprint, a partnership
between Eli Lilly and the external institution could unfold. This allows Eli Lilly to leverage its capabilities
in screening potential drug candidates by opening up its proprietary screening assays (EliLilly, 2013).
These are examples on how Open Innovation activities can have an impact on pharmaceutical
companies’ business model.
However, the results suggest that not all firms open up to the same degree. Interestingly, the two largest
firms (Pfizer and Novartis) have seen the largest relative increase in value creation even though they
have not become significantly more open from 2002 to 2012. Drechsler and Natter suggest that financial
gaps are an important driver of openness in value creation (Drechsler & Natter, 2012). Probably, Pfizer
and Novartis have had the financial resources to fuel their knowledge stock by different mechanisms,
e.g. hiring star scientists from universities or buying smaller innovative firms. Nonetheless, leaving these
two firms out, we observe that smaller firms opened up their R&D (Abbott and Bristol Myers) were able
46
to increase their knowledge output. Similar results were obtained in the embedded software industry
where it was shown that smaller firms revealed more code to the public in order to benefit from external
development support (Henkel, 2006). This result confirms that financial and knowledge gaps are the
main drivers of openness in value creation besides rich technological opportunities (Drechsler & Natter,
2012).
The decline in patenting activity of the ten largest pharmaceutical companies indicates that the
appropriability regime plays a less important role in value capture than it did ten years ago. This could
suggest that the costs to monitor and enforce a patent have gone up while the protection a patent offers
seems to have gone down.
Interestingly, the openness in patents has also declined. Arora and Ceccagnoli have shown that a
decrease in the efficacy of IP protection leads to less collaboration because both sides experience
increased risks and costs associated with monitoring and enforcing the agreement (Arora & Ceccagnoli,
2006). This observation is confirmed by the fact that the total number of patents and the openness of
patents decreased.
When the appropriability regime weakens, firms usually react by focusing on complementary assets. In
the case of the pharmaceutical industry this could mean gaining tacit knowledge, an enhanced
reputation among the scientific community and better ties to external institutions. The increase in
openness in publications indicates that this was indeed the case from 2002 and 2012. Therefore, the
following hypothesis can be formulated.
“A weaker appropriability regime decreases openness in value capture, but increases the openness in
value creation aspects of Open Innovation.”
5.2 Different Open Innovation Strategies in Different Business Areas
Current literature does not address the question if companies can have a differentiated strategy
regarding Open Innovation. They regard a firm as either being open or closed. The results of this thesis
clearly show that this is not the case. The results show that companies exhibit different openness in
different disease areas and that some disease areas receive a high number of patents while only a
relatively modest number of publications (e.g. biotechnology) or a high number of publications but only
few patents (neurosciences). This suggests that innovation practices are very much depend on the
strategic priority a certain technology or business area has. Chesbrough and Schwartz differentiated
between core, critical, and contextual capabilities; core capabilities requiring a limited number of
strategic partners and contextual capabilities requiring many arm’s length partnerships (Chesbrough &
Schwartz, 2007). The maturity is important determinant in setting innovation practices. Chesbrough
47
described the IP life cycle where he states that growth technologies should receive more IP protection
because later on the company can license out the technology (Chesbrough, 2006). Pre-emergent
technologies, however, should not receive too much IP protection since the dominant design has not yet
emerged and is more or less still fluid (Chesbrough, 2006). This would explain the high number of
publications in neurosciences which is a hot topic in medicine (Alzheimer, Parkinson etc.), but has not yet
many validated targets for drug development. Here, the focus lies on gaining knowledge, before value
can captured through patents. In biotechnology, however, the pre-paradigmatic phase is over and a lot
of value is created which can now be captured by pharmaceutical companies. Interestingly, for mature
disease areas such as hematology, the number of publications is extremely small while there are still a
number of patents issued. This can be rationalized by the fact that there is not a lot of new knowledge
generated in these areas, however pharmaceutical companies focus on incremental improvements and
gaining new patent protection for well-established drugs (ever-greening). Based on the combined data
on publications and patents the following hypothesis can be formulated.
“In the emergent phase of a technology, value creation processes prevail over value capture processes in
Open Innovation.”
“In the growth and mature phase of a technology, value capture processes are dominant in Open
Innovation.”
From a theoretical point of view we would expect that when patent activity is reduced, pharmaceutical
companies would focus in building up specialized and co-specialized complementary assets in order to
capture value (Teece, 1986). This would result in individual companies focusing more on a few
specialized areas such as oncology. However, the data does not confirm this idea. It could be that in the
pharmaceutical industries spill overs from different disease areas or too important and too much focus is
bad for R&D productivity. In addition, it might be that there is a low modularity between research areas
which means that revealing knowledge in one area does automatically affect knowledge in other
research areas (Alexy, George, & Salter, 2012). Figure 18 also showed that the areas where the
pharmaceutical companies focus the most, these areas are not more or less open than other areas.
5.3 Difference in Open Innovation Practices
Open Innovation means different things in different circumstances. As discussed in the literature, Open
Innovation can mean joint-ventures, technology in-licensing and out-licensing, research collaboration
and consortia, technology acquisitions, cross-licensing and so forth. This thesis provides a clearer picture
on different practices than the current literature since it looks at value creation and value capture
aspects and makes a difference between inter-firm collaboration, non-interfirm collaboration (mostly
48
with public institutions), and purely internal research. In both publications and patents, a decline in the
purely internal research has been observed while both interfirm-alliances and other types of alliances
have increased (see Figure 12). The literature mentions two main factors that rationalize these results.
The first one is that non-financial elements such as a good reputation in research circles and ties with
external institutions have become more important. In order to have a good reputation, pharmaceutical
companies actively seek collaboration and participation in research consortia. This motive has also been
seen in the open-source software industry where software companies freely reveal parts of their code to
the public in order to get recognition by the development community (Henkel, 2006). This reputation
effect is an example of a complementary asset in the value capture process (Teece, 1986). The second
factor is knowledge gaps especially in areas of high technological change. To create tacit knowledge,
people need to work in close proximity to enable efficient transfer of knowledge (Winter, 1987). This
integration is important in the pharmaceutical industry. External researchers can sometimes use the
infrastructure such as laboratories or measurement equipment of pharmaceutical companies. The
pharmaceutical companies in turn get access to new targets and possible directions for future research.
Besides finding out that pharmaceutical companies have become increasingly open and have increasingly
engaged in different forms of Open Innovation, the study has found indices that engaging in inter-firm
alliances improves the R&D efficiency in value creation (R&D spent / published paper). In conjunction
with the overall openness in value creation, the degree to which firms engage in deep inter-firm alliances
and the overall degree of openness seems to predict R&D efficiency to a large extent. The data therefore
leads to the conclusion that the breadth and depth of collaboration (Laursen & Salter, 2006) increase
R&D productivity. The hypothesis that is formulated is hence:
“An increase in breadth and width of research collaborations increase R&D productivity”
5.4 Managerial Implications
This research suggests that the traditional mindset of managers in research-intensive industries such as
the pharmaceutical industry needs to change. Companies can no longer rely on an internally grown
knowledge base to create value and on an extensive intellectual property portfolio to capture the value.
Manager needs to build and develop complementary assets such as reputation, a wide network of
experts, research collaboration and ties to other pharmaceutical companies.
Especially, the management of patents becomes a different perspective. It is less a tool to appropriate
value through a time-bound monopoly on the invention, but it is more a defensive tool against patent
trolls or should be used as a bargaining chip in licensing negotiations.
49
Another implication is that the collaboration strategy needs to be tailor-made to each business area.
Different technological requirements and maturity of the technology require different responses to the
challenges given. The innovation strategy needs to serve the overall strategic positioning which is
embodied in its business model. In today’s fast changing world, the answer to the question how value
can be created and captured becomes a difficult one.
5.5 Limitations and Future Research
This thesis is an explorative study and does only suggest certain hypothesis for future research. Given
that the field of value creation and value capture is nascent, there are certain limitations in this research
It has been noted in the literature that different author’s affiliations do not necessarily reflect a
collaborative research effort (Katz & Martin, 1997). For instance, it could be that a single author has two
different affiliations, e.g. one with Pfizer and one with University of Michigan. If this person authors a
publication, it would be counted as an alliance with a public institution even though a single person has
authored the paper. Therefore, it would artificially increase the share of collaborative publications.
Another potential bias could be present if there is a research collaboration between researchers from
different institutions, but they decide to publish separately. Therefore, they would artificially decrease
the share of collaborative publications. However, a researcher that works partly for a public institution
and partly for a pharmaceutical company and, hence, is affiliated with both of them, still represents
some form of collaborative effort in the sense of Open Innovation. There will be to some extent an
exchange of ideas and know-how between the pharmaceutical company and the public institution. It is
therefore justified, to count this publication as a collaborative publication. And even though co-
authorship is not a perfect proxy for collaboration, there is no indication of a systematic bias in the data
from 2002 to 2012 and the large size of the data set (over 73’000 publications) reduces the effect of
random noise.
Another limitation to this thesis is that it focuses on only one industry and only on the ten largest
pharmaceutical companies. If the study would include more companies across different industries a
higher validity would be achieved.
In addition, this study has no data on joint ventures, equity deals, research consortia and so forth which
are important mechanisms of Open Innovation. Even though this thesis already differentiates between
interfirm collaborations and other forms of collaboration, a more fine-grained differentiation would be
beneficial and shed more light onto which forms are the most beneficial.
50
Furthermore, the classification scheme on which basis the publications and patents are assigned to
disease areas could be further improved and validated, for instance by cross-validation with some
experts on the field of pharmaceutical sciences.
Future research could enlarge the base of the data (more companies, more industries) and also move
further up in the development funnel for instance by taking into account financial results as a more
precise description of value capture. In the pharmaceutical industry one might investigate which
compound are later allowed into phase 2 and phase 3 clinical trials and which research leads drugs that
get FDA approval. By investigating science-driven industries, new insights can be gained into Open
Innovation practices that are not only relevant for high-tech industries, but for low-tech industries as
well (Chesbrough & Crowther, 2006).
51
6. References
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Alexy, O., George, G., & Salter, A. 2012. Cui bono? The selective revealing of knowledge and its
implications for innovative activity. Academy of Management Review.
Amit, R., & Zott, C. 2001. Value Creation in E-Business. Strategic Management Journal, 22(6/7): 493-520.
Arora, A., & Ceccagnoli, M. 2006. Patent protection, complementary assets, and firms’ incentives for
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Becerra, M. 2009. Theory of the Firm for Strategic Management: Economic Value Analysis: Cambridge
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Behrens, J. T., & Yu, C.-H. 2003. Exploratory Data Analysis, Handbook of Psychology: John Wiley & Sons,
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Chesbrough, H. 2006. Open business models: How to thrive in the new innovation landscape: Harvard
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7. Appendix
7.1 VBA Function for Assigning Company Affiliation
Public Function CompanyName(Addresses As String, Optional ReprintAuthor As String) As String Dim CombinedString As String CombinedString = Addresses & ReprintAuthor If InStr(1, CombinedString, "Novartis", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Novartis]" End If If InStr(1, CombinedString, "Pfizer", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Pfizer]" End If If InStr(1, CombinedString, "Sanofi", vbTextCompare) > 0 Or InStr(1, CombinedString, "Aventis", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Sanofi]" End If If InStr(1, CombinedString, "Merck", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Merck]" End If If InStr(1, CombinedString, "Glaxo", vbTextCompare) > 0 Or InStr(1, CombinedString, "SmithKline", vbTextCompare) > 0 Then CompanyName = CompanyName & "[GlaxoSmithKline]" End If If InStr(1, CombinedString, "Abbott", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Abbott]" End If If InStr(1, CombinedString, "Astra", vbTextCompare) > 0 Or InStr(1, CombinedString, "Zeneca", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Astrazeneca]" End If If InStr(1, CombinedString, "Roche", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Roche]" End If If InStr(1, CombinedString, "Lilly", vbTextCompare) > 0 Or InStr(1, CombinedString, "ELIL", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Eli Lilly]" End If If InStr(1, CombinedString, "Bristol Myers", vbTextCompare) > 0 Or InStr(1, CombinedString, "Bristol-Myers", vbTextCompare) > 0 Then CompanyName = CompanyName & "[Bristol Myers]" End If End Function
7.2 VBA Function to Assign Publications to Subject Areas
Public Function CategorizePublication(Category As String, SubjectCategories As String) As Boolean
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Select Case Category Case "Allergy, Respiratory Systems, ENT" If InStr(1, SubjectCategories, "Respiratory System", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Otorhinolaryngology", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Allergy", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Biotechnology & Applied Microbiology" If InStr(1, SubjectCategories, "Biotechnology & Applied Microbiology", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Genetics", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Mycology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Cardiovascular System & Cardiology" If InStr(1, SubjectCategories, "Cardiovascular System & Cardiology", vbBinaryCompare) > 0 Then CategorizePublication = True End If If InStr(1, SubjectCategories, "Hematology", vbBinaryCompare) > 0 Then CategorizePublication = False End If Case "Dermatology" If InStr(1, SubjectCategories, "Dermatology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Endocrinology & Metabolism" If InStr(1, SubjectCategories, "Endocrinology & Metabolism", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Gastroenterology & Hepatology" If InStr(1, SubjectCategories, "Gastroenterology & Hepatology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Hematology" If InStr(1, SubjectCategories, "Hematology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Immunology" If InStr(1, SubjectCategories, "Immunology", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Transplantation", vbBinaryCompare) > 0 Then CategorizePublication = True End If If InStr(1, SubjectCategories, "Respiratory System", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Otorhinolaryngology", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Allergy", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Infectious Diseases", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Parasitology", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Virology", vbBinaryCompare) > 0 Then CategorizePublication = False End If
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Case "Infectious Diseases, Virology, Parasitology" If InStr(1, SubjectCategories, "Infectious Diseases", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Parasitology", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Virology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Neurosciences & Neurology" If InStr(1, SubjectCategories, "Neurosciences & Neurology", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Psychiatry", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Substance Abuse", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Oncology" If InStr(1, SubjectCategories, "Oncology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Ophthalmology" If InStr(1, SubjectCategories, "Ophthalmology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Rheumatology" If InStr(1, SubjectCategories, "Rheumatology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case "Urogenital & Pregnancy" If InStr(1, SubjectCategories, "Urology & Nephrology", vbBinaryCompare) > 0 Or InStr(1, SubjectCategories, "Reproductive Biology", vbBinaryCompare) > 0 _ Or InStr(1, SubjectCategories, "Obstetrics & Gynecology", vbBinaryCompare) > 0 Then CategorizePublication = True End If Case Else CategorizePublication = False End Select End Function
7.3 VBA Function to Assign Patent Codes to Subject Areas
Public Function CategorizePatent(Category As String, IPCcodes As String) As Boolean CategorizePatent = False Select Case Category Case "Allergy, Respiratory Systems, ENT" If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = True End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then
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CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If Case "Biotechnology & Applied Microbiology" If InStr(1, IPCcodes, "C12N", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "C12P", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "C12Q", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61K-048", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A01H-001/06", vbBinaryCompare) > 0 Then CategorizePatent = True ''' Remove immunology If InStr(1, IPCcodes, "A61P-037/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-037/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-037/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "G01N-033/53", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "G01N-033/54", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "G01N-033/55", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "G01N-033/56", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Cardiovascular System & Cardiology" If InStr(1, IPCcodes, "A61P-009", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology
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If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Dermatology" If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = True End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If Case "Endocrinology & Metabolism" If InStr(1, IPCcodes, "A61P-003", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-005", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-021/06", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If ''' Remove Cardiovascular If InStr(1, IPCcodes, "A61P-009", vbBinaryCompare) > 0 Then CategorizePatent = False
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End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Gastroenterology & Hepatology" If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology
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If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Hematology" If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = True End If Case "Immunology" If InStr(1, IPCcodes, "A61P-037/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-037/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-037/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "G01N-033/53", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "G01N-033/54", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "G01N-033/55", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "G01N-033/56", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology
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If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Infectious Diseases, Virology, Parasitology" If InStr(1, IPCcodes, "A61P-031", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-033", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If
63
'' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Neurosciences & Neurology" If InStr(1, IPCcodes, "A61P-025", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-021/02", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-021/04", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If ''' Remove Rhemuatology If InStr(1, IPCcodes, "A61P-029", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-019", vbBinaryCompare) > 0 Then
64
CategorizePatent = False End If End If Case "Oncology" If InStr(1, IPCcodes, "A61P-035", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Ophthalmology" If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then
65
CategorizePatent = True '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Rheumatology" If InStr(1, IPCcodes, "A61P-029", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-019", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Gastroenterology If InStr(1, IPCcodes, "A61P-001", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Urogenital & Pregnancy If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If Case "Urogenital & Pregnancy"
66
If InStr(1, IPCcodes, "A61P-013", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-015", vbBinaryCompare) > 0 Then CategorizePatent = True '' Remove allergy If InStr(1, IPCcodes, "A61P-037/08", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-011/06", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/16", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Dermatology If InStr(1, IPCcodes, "A61P-017", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Hematology If InStr(1, IPCcodes, "A61P-007", vbBinaryCompare) > 0 Then CategorizePatent = False End If '' Remove Opthalmology If InStr(1, IPCcodes, "A61P-027/02", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/04", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/06", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/08", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/10", vbBinaryCompare) > 0 Or InStr(1, IPCcodes, "A61P-027/12", vbBinaryCompare) > 0 _ Or InStr(1, IPCcodes, "A61P-027/14", vbBinaryCompare) > 0 Then CategorizePatent = False End If End If End Select End Function
7.4 VBA Function to Determine Openness
Public Function JointnessInstitutional(ByVal Addresses As String, CompanyName As String) As Single Dim i As Integer Dim NumberOfInstitutions As Integer Dim SemiColonLocation As Integer Dim BracketLocation As Integer Dim TempAddresses As String Dim ExternalInstitutionCount As Integer ''' Before 2006 no individual author affiliation If Len(Addresses) - Len(Replace(Addresses, "]", "")) = 0 Then NumberOfInstitutions = 1 + Len(Addresses) - Len(Replace(Addresses, ";", "")) If NumberOfInstitutions <> 1 Then For i = 1 To NumberOfInstitutions - 1 SemiColonLocation = InStr(1, Addresses, ";", vbBinaryCompare) TempAddresses = Left(Addresses, InStr(1, Addresses, ";", vbBinaryCompare)) If CompanyName = "Sanofi" Then
67
If InStr(1, TempAddresses, "Sanofi", vbTextCompare) = 0 And InStr(1, TempAddresses, "Aventis", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "GlaxoSmithKline" Then If InStr(1, TempAddresses, "Glaxo", vbTextCompare) = 0 And InStr(1, TempAddresses, "SmithKline", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Eli Lilly" Then If InStr(1, TempAddresses, "Lilly", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Astrazeneca" Then If InStr(1, TempAddresses, "Astra", vbTextCompare) = 0 And InStr(1, TempAddresses, "Zeneca", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If Else If InStr(1, TempAddresses, CompanyName, vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If End If Addresses = Right(Addresses, Len(Addresses) - SemiColonLocation) Next i End If ''' For last address If CompanyName = "Sanofi" Then If InStr(1, Addresses, "Sanofi", vbTextCompare) = 0 And InStr(1, Addresses, "Aventis", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "GlaxoSmithKline" Then If InStr(1, Addresses, "Glaxo", vbTextCompare) = 0 And InStr(1, Addresses, "SmithKline", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Eli Lilly" Then If InStr(1, Addresses, "Lilly", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Astrazeneca" Then If InStr(1, Addresses, "Astra", vbTextCompare) = 0 And InStr(1, Addresses, "Zeneca", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If Else If InStr(1, Addresses, CompanyName, vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1
68
End If End If Else ''' After 2006 Individual Author affiliation NumberOfInstitutions = Len(Addresses) - Len(Replace(Addresses, "]", "")) If NumberOfInstitutions <> 1 Then For i = 1 To NumberOfInstitutions - 1 BracketLocation = InStr(1, Addresses, "]", vbBinaryCompare) SemiColonLocation = InStr(BracketLocation, Addresses, ";", vbBinaryCompare) TempAddresses = Mid(Addresses, BracketLocation + 1, SemiColonLocation - BracketLocation) If CompanyName = "Sanofi" Then If InStr(1, TempAddresses, "Sanofi", vbTextCompare) = 0 And InStr(1, TempAddresses, "Aventis", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "GlaxoSmithKline" Then If InStr(1, TempAddresses, "Glaxo", vbTextCompare) = 0 And InStr(1, TempAddresses, "SmithKline", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Eli Lilly" Then If InStr(1, TempAddresses, "Lilly", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Astrazeneca" Then If InStr(1, TempAddresses, "Astra", vbTextCompare) = 0 And InStr(1, TempAddresses, "Zeneca", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If Else If InStr(1, TempAddresses, CompanyName, vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If End If Addresses = Right(Addresses, Len(Addresses) - SemiColonLocation) Next i End If ''' For last address If CompanyName = "Sanofi" Then If InStr(1, Addresses, "Sanofi", vbTextCompare) = 0 And InStr(1, Addresses, "Aventis", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "GlaxoSmithKline" Then If InStr(1, Addresses, "Glaxo", vbTextCompare) = 0 And InStr(1, Addresses, "SmithKline", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Eli Lilly" Then
69
If InStr(1, Addresses, "Lilly", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If ElseIf CompanyName = "Astrazeneca" Then If InStr(1, Addresses, "Astra", vbTextCompare) = 0 And InStr(1, Addresses, "Zeneca", vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If Else If InStr(1, Addresses, CompanyName, vbTextCompare) = 0 Then ExternalInstitutionCount = ExternalInstitutionCount + 1 End If End If End If JointnessInstitutional = ExternalInstitutionCount / NumberOfInstitutions End Function
7.5 IPC Codes Linked to Subject Areas
IPC Code Description Assigned WoS
Categories
A61P 1/00 Drugs for disorders of the alimentary tract or the digestive
system [7]
Gastroenterology & Hepatology
A61P 1/02 · Stomatological preparations, e.g. drugs for caries, aphtae,
periodontitis [7] Gastroenterology & Hepatology
A61P 1/04 · for ulcers, gastritis or reflux esophagitis, e.g. antacids,
inhibitors of acid secretion, mucosal protectants [7] Gastroenterology & Hepatology
A61P 1/06 · Anti-spasmodics, e.g. drugs for colics, esophagic dyskinesia
[7] Gastroenterology & Hepatology
A61P 1/08 · for nausea, cinetosis or vertigo; Antiemetics [7] Gastroenterology & Hepatology
A61P 1/10 · Laxatives [7] Gastroenterology & Hepatology
A61P 1/12 · Antidiarrhoeals [7] Gastroenterology & Hepatology
A61P 1/14 · Prodigestives, e.g. acids, enzymes, appetite stimulants,
antidyspeptics, tonics, antiflatulents [7] Gastroenterology & Hepatology
A61P 1/16 · for liver or gallbladder disorders, e.g. hepatoprotective
agents, cholagogues, litholytics [7] Gastroenterology & Hepatology
A61P 1/18 · for pancreatic disorders, e.g. pancreatic enzymes [7] Gastroenterology & Hepatology
A61P 3/00 Drugs for disorders of the metabolism (of the blood or the
extracellular fluid A61P 7/00) [7]
Endocrinology & Metabolism
A61P 3/02 · Nutrients, e.g. vitamins, minerals [7] Endocrinology & Metabolism
A61P 3/04 · Anorexiants; Antiobesity agents [7] Endocrinology & Metabolism
A61P 3/06 · Antihyperlipidemics [7] Endocrinology & Metabolism
70
A61P 3/08 · for glucose homeostasis (pancreatic hormones A61P 5/48)
[7] Endocrinology & Metabolism
A61P 3/10 · · for hyperglycaemia, e.g. antidiabetics [7] Endocrinology & Metabolism
A61P 3/12 · for electrolyte homeostasis [7] Endocrinology & Metabolism
A61P 3/14 · · for calcium homeostasis (vitamin D A61P 3/02; parathyroid
hormones A61P 5/18; calcitonin A61P 5/22; osteoporosis
A61P 19/10; bone metastasis A61P 35/04) [7]
Endocrinology & Metabolism
A61P 5/00 Drugs for disorders of the endocrine system [7] Endocrinology & Metabolism
A61P 5/02 · of the hypothalamic hormones, e.g. TRH, GnRH, CRH,
GRH, somatostatin [7] Endocrinology & Metabolism
A61P 5/04 · · for decreasing, blocking or antagonising the activity of the
hypothalamic hormones [7] Endocrinology & Metabolism
A61P 5/06 · of the anterior pituitary hormones, e.g. TSH, ACTH, FSH,
LH, PRL, GH [7] Endocrinology & Metabolism
A61P 5/08 · · for decreasing, blocking or antagonising the activity of the
anterior pituitary hormones [7] Endocrinology & Metabolism
A61P 5/10 · of the posterior pituitary hormones, e.g. oxytocin, ADH [7] Endocrinology & Metabolism
A61P 5/12 · · for decreasing, blocking or antagonising the activity of the
posterior pituitary hormones [7] Endocrinology & Metabolism
A61P 5/14 · of the thyroid hormones, e.g. T3, T4 [7] Endocrinology & Metabolism
A61P 5/16 · · for decreasing, blocking or antagonising the activity of the
thyroid hormones [7] Endocrinology & Metabolism
A61P 5/18 · of the parathyroid hormones [7] Endocrinology & Metabolism
A61P 5/20 · · for decreasing, blocking or antagonising the activity of PTH
[7]
Endocrinology & Metabolism
A61P 5/22 · · for decreasing, blocking or antagonising the activity of
calcitonin [7] Endocrinology & Metabolism
A61P 5/24 · of the sex hormones [7] Endocrinology & Metabolism
A61P 5/26 · · Androgens [7] Endocrinology & Metabolism
A61P 5/28 · · Antiandrogens [7] Endocrinology & Metabolism
A61P 5/30 · · Oestrogens [7] Endocrinology & Metabolism
A61P 5/32 · · Antioestrogens [7] Endocrinology & Metabolism
A61P 5/34 · · Gestagens [7] Endocrinology & Metabolism
A61P 5/36 · · Antigestagens [7] Endocrinology & Metabolism
A61P 5/38 · of the suprarenal hormones [7] Endocrinology &
71
Metabolism
A61P 5/40 · · Mineralocorticosteroids, e.g. aldosterone; Drugs increasing
or potentiating the activity of mineralocorticosteroids [7] Endocrinology & Metabolism
A61P 5/42 · · for decreasing, blocking or antagonising the activity of
mineralocorticosteroids [7] Endocrinology & Metabolism
A61P 5/44 · · Glucocorticosteroids; Drugs increasing or potentiating the
activity of glucocorticosteroids [7] Endocrinology & Metabolism
A61P 5/46 · · for decreasing, blocking or antagonising the activity of
glucocorticosteroids [7] Endocrinology & Metabolism
A61P 5/48 · of the pancreatic hormones [7] Endocrinology & Metabolism
A61P 5/50 · · for increasing or potentiating the activity of insulin [7] Endocrinology & Metabolism
A61P 7/00 Drugs for disorders of the blood or the extracellular fluid
[7]
Hematology
A61P 7/02 · Antithrombotic agents; Anticoagulants; Platelet aggregation
inhibitors [7] Hematology
A61P 7/04 · Antihaemorrhagics; Procoagulants; Haemostatatic agents;
Antifibrinolytic agents [7] Hematology
A61P 7/06 · Antianaemics [7] Hematology
A61P 7/08 · Plasma substitutes; Perfusion solutions; Dialytics or
haemodialytics; Drugs for electrolytic or acid-base disorders,
e.g. hypovolemic shock (artificial tears A61P 27/04) [7]
Hematology
A61P 7/10 · Antioedematous agents; Diuretics [7] Hematology
A61P 7/12 · Antidiuretics, e.g. drugs for diabetes insipidus (ADH A61P
5/10) [7] Hematology
A61P 9/00 Drugs for disorders of the cardiovascular system [7] Cardiovascular System & Cardiology
A61P 9/02 · Non-specific cardiovascular stimulants, e.g. drugs for
syncope, antihypotensives [7] Cardiovascular System & Cardiology
A61P 9/04 · Inotropic agents, i.e. stimulants of cardiac contraction; Drugs
for heart failure [7] Cardiovascular System & Cardiology
A61P 9/06 · Antiarrhythmics [7] Cardiovascular System & Cardiology
A61P 9/08 · Vasodilators for multiple indications [7] Cardiovascular System & Cardiology
A61P 9/10 · for treating ischaemic or atherosclerotic diseases, e.g.
antianginal drugs, coronary vasodilators, drugs for myocardial
infarction, retinopathy, cerebrovascula insufficiency, renal
arteriosclerosis [7]
Cardiovascular System & Cardiology
A61P 9/12 · Antihypertensives [7] Cardiovascular System & Cardiology
A61P 9/14 · Vasoprotectives; Antihaemorrhoidals; Drugs for varicose
therapy; Capillary stabilisers [7] Cardiovascular System & Cardiology
A61P 11/00 Drugs for disorders of the respiratory system [7] Respiratory System
A61P 11/02 · Nasal agents, e.g. decongestants [7] Respiratory System
A61P 11/04 · for throat disorders [7] Respiratory System
A61P 11/06 · Antiasthmatics [7] Respiratory Systems;
72
Allergy
A61P 11/08 · Bronchodilators [7] Respiratory System
A61P 11/10 · Expectorants [7] Respiratory System
A61P 11/12 · Mucolytics [7] Respiratory System
A61P 11/14 · Antitussive agents [7] Respiratory System
A61P 11/16 · Central respiratory analeptics [7] Respiratory System
A61P 13/00 Drugs for disorders of the urinary system (diuretics A61P
7/10) [7] Urology & Nephrology
A61P 13/02 · of urine or of the urinary tract, e.g. urine acidifiers [7] Urology & Nephrology
A61P 13/04 · for urolithiasis [7] Urology & Nephrology
A61P 13/06 · Anti-spasmodics [7] Urology & Nephrology
A61P 13/08 · of the prostate [7] Urology & Nephrology
A61P 13/10 · of the bladder [7] Urology & Nephrology
A61P 13/12 · of the kidneys [7] Urology & Nephrology
A61P 15/00 Drugs for genital or sexual disorders (for disorders of sex
hormones A61P 5/24); Contraceptives [7]
A61P 15/02 · for disorders of the vagina [7] Obstetrics & Gynecology
A61P 15/04 · for inducing labour or abortion; Uterotonics [7] Obstetrics & Gynecology
A61P 15/06 · Antiabortive agents; Labour repressants [7] Obstetrics & Gynecology
A61P 15/08 · for gonadal disorders or for enhancing fertility, e.g. inducers
of ovulation or of spermatogenesis [7] Reproductive Biology
A61P 15/10 · for impotence [7] Reproductive Biology
A61P 15/12 · for climacteric disorders [7] Reproductive Biology
A61P 15/14 · for lactation disorders, e.g. galactorrhoea [7] Obstetrics & Gynecology
A61P 15/16 · Masculine contraceptives [7] Reproductive Biology
A61P 15/18 · Feminine contraceptives [7] Reproductive Biology
A61P 17/00 Drugs for dermatological disorders [7] Dermatology
A61P 17/02 · for treating wounds, ulcers, burns, scars, keloids, or the like
[7] Dermatology
A61P 17/04 · Antipruritics [7] Dermatology
A61P 17/06 · Antipsoriatics [7] Dermatology
A61P 17/08 · Antiseborrheics [7] Dermatology
A61P 17/10 · Anti-acne agents [7] Dermatology
A61P 17/12 · Keratolytics, e.g. wart or anti-corn preparations [7] Dermatology
A61P 17/14 · for baldness or alopecia [7] Dermatology
A61P 17/16 · Emollients or protectives, e.g. against radiation [7] Dermatology
73
A61P 17/18 · Antioxidants, e.g. antiradicals (preparations for protection
against sunlight A61Q 17/00) [8] Dermatology
A61P 19/00 Drugs for skeletal disorders [7] Rheumatology
A61P 19/02 · for joint disorders, e.g. arthritis, arthrosis [7] Rheumatology
A61P 19/04 · for non-specific disorders of the connective tissue [7] Rheumatology
A61P 19/06 · Antigout agents, e.g. antihyperuricemic or uricosuric agents
[7] Rheumatology
A61P 19/08 · for bone diseases, e.g. rachitism, Paget's disease [7] Rheumatology
A61P 19/10 · · for osteoporosis [7] Rheumatology
A61P 21/00 Drugs for disorders of the muscular or neuromuscular
system [7]
A61P 21/02 · Muscle relaxants, e.g. for tetanus or cramps [7] Neurosciences & Neurology
A61P 21/04 · for myasthenia gravis [7] Neurosciences & Neurology
A61P 21/06 · Anabolic agents (androgens A61P 5/26) [7] Endocrinology & Metabolism
A61P 23/00 Anaesthetics [7] Anesthesiology
A61P 23/02 · Local anaesthetics [7] Anesthesiology
A61P 25/00 Drugs for disorders of the nervous system [7] Neurosciences & Neurology
A61P 25/02 · for peripheral neuropathies [7] Neurosciences & Neurology
A61P 25/04 · Centrally acting analgesics, e.g. opioids [7] Neurosciences & Neurology
A61P 25/06 · Antimigraine agents [7] Neurosciences & Neurology
A61P 25/08 · Antiepileptics; Anticonvulsants [7] Neurosciences & Neurology
A61P 25/10 · · for petit-mal [7] Neurosciences & Neurology
A61P 25/12 · · for grand-mal [7] Neurosciences & Neurology
A61P 25/14 · for treating abnormal movements, e.g. chorea, dyskinesia [7] Neurosciences & Neurology
A61P 25/16 · · Anti-Parkinson drugs [7] Neurosciences & Neurology
A61P 25/18 · Antipsychotics, i.e. neuroleptics; Drugs for mania or
schizophrenia [7] Neurosciences & Neurology; Psychiatry
A61P 25/20 · Hypnotics; Sedatives [7] Neurosciences & Neurology; Psychiatry
A61P 25/22 · Anxiolytics [7] Neurosciences & Neurology; Psychiatry
A61P 25/24 · Antidepressants [7] Neurosciences & Neurology;
74
Psychiatry
A61P 25/26 · Psychostimulants, e.g. nicotine, cocaine [7] Neurosciences & Neurology; Psychiatry
A61P 25/28 · for treating neurodegenerative disorders of the central
nervous system, e.g. nootropic agents, cognition enhancers,
drugs for treating Alzheimer's disease or other forms of
dementia [7]
Neurosciences & Neurology; Psychiatry
A61P 25/30 · for treating abuse or dependence [7] Neurosciences & Neurology; Psychiatry; Substance Abuse
A61P 25/32 · · Alcohol-abuse [7] Neurosciences & Neurology; Psychiatry; Substance Abuse
A61P 25/34 · · Tobacco-abuse [7] Neurosciences & Neurology; Psychiatry; Substance Abuse
A61P 25/36 · · Opioid-abuse [7] Neurosciences & Neurology; Psychiatry; Substance Abuse
A61P 27/00 Drugs for disorders of the senses [7]
A61P 27/02 · Ophthalmic agents [7] Ophthalmology
A61P 27/04 · · Artificial tears; Irrigation solutions [7] Ophthalmology
A61P 27/06 · · Antiglaucoma agents or miotics [7] Ophthalmology
A61P 27/08 · · Mydriatics or cycloplegics [7] Ophthalmology
A61P 27/10 · · for accommodation disorders, e.g. myopia [7] Ophthalmology
A61P 27/12 · · for cataracts [7] Ophthalmology
A61P 27/14 · · Decongestants or antiallergics [7] Ophthalmology; Allergy
A61P 27/16 · Otologicals [7] Otorhinolaryngology
A61P 29/00 Non-central analgesic, antipyretic or antiinflammatory
agents, e.g antirheumatic agents; Non-steroidal
antiinflammatory drugs (NSAIDs) [7]
Rheumatology
A61P 29/02 · without antiinflammatory effect [7] Rheumatology
A61P 31/00 Antiinfectives, i.e. antibiotics, antiseptics,
chemotherapeutics [7]
Infectious Diseases
A61P 31/02 · Local antiseptics [7] Infectious Diseases
A61P 31/04 · Antibacterial agents [7] Infectious Diseases
A61P 31/06 · · for tuberculosis [7] Infectious Diseases
A61P 31/08 · · for leprosy [7] Infectious Diseases
A61P 31/10 · Antimycotics [7] Infectious Diseases; Mycology
A61P 31/12 · Antivirals [7] Infectious Diseases;
75
Virology
A61P 31/14 · · for RNA viruses [7] Infectious Diseases; Virology
A61P 31/16 · · · for influenza or rhinoviruses [7] Infectious Diseases; Virology
A61P 31/18 · · · for HIV [7] Infectious Diseases; Virology
A61P 31/20 · · for DNA viruses [7] Infectious Diseases; Virology
A61P 31/22 · · · for herpes viruses [7] Infectious Diseases; Virology
A61P 33/00 Antiparasitic agents [7] Parasitology
A61P 33/02 · Antiprotozoals, e.g. for leishmaniasis, trichomoniasis,
toxoplasmosis [7] Parasitology
A61P 33/04 · · Amoebicides [7] Parasitology
A61P 33/06 · · Antimalarials [7] Parasitology
A61P 33/08 · · for Pneumocystis carinii [7] Parasitology
A61P 33/10 · Anthelmintics [7] Parasitology
A61P 33/12 · · Schistosomicides [7] Parasitology
A61P 33/14 · Ectoparasiticides, e.g. scabicides [7] Parasitology
A61P 35/00 Antineoplastic agents [7] Oncology
A61P 35/02 · specific for leukemia [7] Oncology
A61P 35/04 · specific for metastasis [7] Oncology
A61P 37/00 Drugs for immunological or allergic disorders [7]
A61P 37/02 · Immunomodulators [7] Immunology
A61P 37/04 · · Immunostimulants [7] Immunology
A61P 37/06 · · Immunosuppressants, e.g. drugs for graft rejection [7] Immunology; Transplantation
A61P 37/08 · Antiallergic agents (antiasthmatic agents A61P 11/06;
ophthalmic antiallergics A61P 27/14) [7] Allergy
A61P 39/00 General protective or antinoxious agents [7]
A61P 39/02 · Antidotes [7] Toxicology
A61P 39/04 · Chelating agents [7] Not assigned
A61P 39/06 · Free radical scavengers or antioxidants [7] Not assigned
A61P 41/00 Drugs used in surgical methods, e.g. surgery adjuvants for
preventing adhesion or for vitreum substitution [7]
Not assigned
A61P 43/00 Drugs for specific purposes, not provided for in groups
A61P 1/00-A61P 41/00 [7]
Not assigned
76
7.6 Overlap Matrices
Table 12: Initial overlap matrix of patents. Bright yellow indicates an overlap larger than 20%. Dark yellow indicates an overlap larger than 30%.
77
Table 13: Initial overlap matrix of patents. Bright and dark yellow indicates overlap greater than 20% and 30% respectively
78
7.7 Summary of Value Capture Data
Company Patents Interfirm alliance
Openness patents
Abbott 4152 0.20% 11.70%
Astrazeneca 2380 1.00% 7.50%
Bristol Myers 1913 1.30% 8.80%
Eli Lilly 1266 12.40% 14.60%
GlaxoSmithKline 3286 0.50% 4.40%
Merck 5364 3.20% 10.40%
Novartis 3098 0.60% 12.50%
Pfizer 2603 0.70% 12.40%
Roche 2774 0.80% 7.60%
Sanofi 2988 0.30% 11.20%
Table 14: Total number of patents, share of interfirm alliances and openness
Disease Area Total patents
Relative share
Openness of patents
Allergy, Respiratory Systems, ENT 947 4.3% 6.9%
Biotechnology & Applied Microbiology 3223 14.7% 12.9%
Cardiovascular System & Cardiology 1242 5.7% 9.2%
Dermatology 1560 7.1% 10.1%
Endocrinology & Metabolism 1098 5.0% 6.7%
Gastroenterology & Hepatology 883 4.0% 10.4%
Hematology 2012 9.2% 9.2%
Immunology 1824 8.3% 12.1%
Infectious Diseases, Virology, Parasitology
1702 7.8% 12.3%
Neurosciences & Neurology 1840 8.4% 6.3%
Oncology 2153 9.8% 9.4%
Ophthalmology 1346 6.1% 12.0%
Rheumatology 1126 5.1% 8.1%
Urogenital & Pregnancy 942 4.3% 8.7%
Not assigned 11712 n/A 10.1%
Table 15: Total number of patents, relative share and openness per disease area.
