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Virtual communities as a vehicle for science-based external knowledge sourcing
Cand merc. (MIB) Management of Innovation and Business Development Copenhagen Business School
Academic advisor: Finn Valentin, Dep. of Innovation and Organizational Economics
113 Pages + Appendix STU count: 271.249
2011-11
Dan Herlin 070184-2901
Benedikta Hedegaard-Knudsen 231283-1778
Abstract Over the past decade the world has witnessed a dramatic development of information and
communication technologies (ICT), and one of the most profound manifestations of online
communication is that of virtual communities (VCs). VCs are proliferating across the Internet in
various forms, and companies have become increasingly interested in utilizing VCs as a tool for
external knowledge sourcing and innovation. In the literature, we find that most work on this
topic predominantly relates to market-‐focused crowdsourcing through user-‐ or challenge-‐driven
VCs. In this light, this paper aims to investigate the benefits that a research-‐based VC holds for
science-‐based R&D intensive firms in acting as a vehicle for unguided search of scientific
opportunities, as to ultimately enhance their innovative capacity. Our research takes point of
departure in the combinatorial view of innovation where we recognize that external sources of
knowledge hold great potential for innovating firms. We take an exploratory and multi-‐
disciplinary approach where we combine literature of cognitive economics, sociology,
innovation, ambidexterity and network theory. Moreover, we conduct a prospective single-‐case
study of Novozymes (NZ) -‐ a leading biotechnology firm in the industrial enzyme business. Here,
we assess NZ’ R&D organisation and its current innovation model to conclude that NZ is to
certain extent is trapped in sub-‐optimal routinized exploitative R&D strategies. While NZ’
current innovation model has proved highly efficient in the past, looming challenges in the
enzyme market places Novozymes in a position to benefit from more explorative R&D strategies.
We identify a set of enabling properties that makes virtual communities particularly conducive
for overcoming a number of barriers found in real life (IRL) communities. More specifically, we
highlight how VCs can overcome barriers of time and geographical proximity as well as barriers
of cognitive-‐, disciplinary-‐ and organizational separation. We conclude that VCs hold potential to
act as a brokerage mechanism for bridging structural holes and facilitate external knowledge
sourcing, and ultimately make out a keystone in the development of ambidextrous
organisational capabilities. As a result, we suggest that NZ can engage in more explorative R&D
strategies by means of a VC set-‐up, without compromising the efficient model if innovation
currently in place in the organization.
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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Table of Contents List of Abbreviations ...................................................................................................................................................... 3
1. INTRODUCTION .......................................................................................................................................... 5 1.1. PROBLEM STATEMENT .............................................................................................................................................. 8 1.2. CLARIFICATION OF RESEARCH .................................................................................................................................. 8 1.3. DEMARCATION ............................................................................................................................................................ 9 1.4. MOTIVATION ............................................................................................................................................................ 10 1.5 RELEVANCE ................................................................................................................................................................ 10 1.6. DISPOSITION ............................................................................................................................................................. 11
2. METHODOLOGY ....................................................................................................................................... 12 2.1. RESEARCH STRATEGY AND DESIGN ..................................................................................................................... 12 2.2. DATA COLLECTION .................................................................................................................................................. 14 2.2.1. Qualitative research methods .................................................................................................................... 14 2.2.2. Method of verification ................................................................................................................................... 17 2.2.3. Quantitative research method ................................................................................................................... 18
2.3. CRITIQUE OF METHODOLOGY ................................................................................................................................ 18 2.3.2. Limitations ......................................................................................................................................................... 18 2.3.3. Reliability ............................................................................................................................................................ 20 2.3.4. Validity ................................................................................................................................................................. 20 2.3.5. Generalizability ................................................................................................................................................ 21
2.4 DELIMITATIONS ........................................................................................................................................................ 21 2.5. CENTRAL CONCEPTS ............................................................................................................................................... 22
3. LITERATURE REVIEW ............................................................................................................................ 24 3.1. COGNITIVE ECONOMICS .......................................................................................................................................... 25 3.2. BRIEF HISTORY OF ICT AND THE INTERNET ...................................................................................................... 26 3.3. VIRTUAL COMMUNITIES ......................................................................................................................................... 27 3.4. A TYPOLOGY OF VIRTUAL COMMUNITIES FOR EXTERNAL KNOWLEDGE SOURCING ..................................... 29 3.4.1. User-‐driven community ................................................................................................................................ 30 3.4.2. Challenged-‐Based Community ................................................................................................................... 31 3.4.3. Research-‐based community ........................................................................................................................ 31
3.5. RESEARCH GAP ........................................................................................................................................................ 32 4. THEORETICAL DISCUSSION .................................................................................................................. 33 4.1. COMBINATORIAL INNOVATION ............................................................................................................................. 33 4.1.1. The linear-‐ and the chain-‐linked model -‐ The role of science and innovations .................... 35 4.1.2. Exploitation and Exploration ..................................................................................................................... 39 4.1.3. The Ambidexterity Hypothesis ................................................................................................................... 40 4.1.4. Combinatorial Innovation: Models and application of theory .................................................... 41
4.2 NETWORKS, KNOWLEDGE AND STRUCTURAL HOLES ........................................................................................ 45 4.2.1. The Social Structure of Networks ............................................................................................................. 46 4.2.2. Structural Holes ............................................................................................................................................... 48 4.2.3. Structural holes and opportunities in segmented networks ........................................................ 49 4.2.4. Brokerage and Innovation .......................................................................................................................... 50 4.2.5. Cognitive Distance ........................................................................................................................................... 51 4.2.6. Social Capital and Innovation .................................................................................................................... 52
4.3. VIRTUAL COMMUNITIES AND KNOWLEDGE SOURCING .................................................................................... 54 4.3.1. Knowledge Sharing and Information Exchange in ‘virtual worlds’ .......................................... 54
4.4. THEORETICAL SYNTHESIS AND APPLICATION .................................................................................................... 55 5. NOVOZYMES -‐ CASE COMPANY PROFILE .......................................................................................... 58 5.1. NOVOZYMES R&D ORGANIZATION ....................................................................................................................... 59
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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5.2. LOOMING CHALLENGES .......................................................................................................................................... 61 6. ANALYSIS .................................................................................................................................................... 62 6.1. PART I -‐ NOVOZYMES’ INNOVATION MODEL ....................................................................................................... 63 6.1.1. R&D in transition at Novozymes ............................................................................................................... 64 6.1.2. Novozymes’ innovation model ................................................................................................................... 66 6.1.3. R&D at Novozymes: basic vs. applied scientific research ............................................................... 68 6.1.4. R&D project groups at Novozymes .......................................................................................................... 69 6.1.5. Novozymes and The Long Tail of R&D ................................................................................................... 71 6.1.6. The emergence of revolutionising technologies for enzyme research ..................................... 73 6.1.7. Conclusion: analysis part I ........................................................................................................................... 75
6.2 ANALYSIS PART II – VIRTUAL INNOVATION BROKER ....................................................................................... 76 6.2.1. A great place to start ..................................................................................................................................... 76 6.2.2. Structural holes and combinatorial innovation ................................................................................. 77 6.2.3. The Virtual Innovation Broker .................................................................................................................. 78 6.2.4 Enabling and inhibiting properties of virtual communities .......................................................... 80 6.2.5. Trends in community life online ................................................................................................................ 83 6.2.6. Conclusion: analysis part II ......................................................................................................................... 86
6.3 ANALYSIS PART III – THE AMBIDEXTROUS INNOVATION MODEL .................................................................. 87 6.3.1. Optimal Scope Continuum ........................................................................................................................... 87 6.3.2. Overcoming obstacles to ambidexterity ................................................................................................ 90 6.3.3. Ambidextrous innovation ............................................................................................................................. 93 6.3.4. Conclusion: analysis part III ....................................................................................................................... 95
6.4. CONCLUSION: ANALYSIS PART I, II, II .................................................................................................................. 96 7. DISCUSSION OF FINDINGS AND FUTURE PERSPECTIVES ........................................................... 99 8. BIBLIOGRAPHY ..................................................................................................................................... 105 8.1. BOOKS AND ARTICLES ......................................................................................................................................... 105 8.2. ONLINE SOURCES .................................................................................................................................................. 113
9. APPENDIX ................................................................................................................................................ 114 APPENDIX 1: INTERVIEW SUMMARY ......................................................................................................................... 115 APPENDIX 2: ONLINE QUESTIONNAIRE SUMMARY ................................................................................................. 146 APPENDIX 3: NOVOZYMES SALES DATA AND GLOBAL ENZYME MARKET ............................................................ 151 APPENDIX 4: ONLINE TRENDS – EMERGING SCIENTIFIC COMMUNITIES ............................................................. 153 APPENDIX 5: ENABLING AND INHIBITING PROPERTIES OF A VIRTUAL COMMUNITY ........................................ 159
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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List of Abbreviations
B-‐2-‐B Business to Business
B-‐2-‐C Business to Consumer
FtF Face to Face
ICT Information and Communication Technology
IRL In Real Life
LM Linear Model of Innovation
NZ Novozymes
R&D Research and Development
VC Virtual Community
VIB Virtual Innovation Broker
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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“The value of an idea lies not its origin, but in its delivery”
-‐ Ronald Burt, 2001
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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1. Introduction Do you have a good idea? A sudden spark of inspiration? A memory? Where did it come
from? We are often led to believe that ideas pop out of nowhere. Famous tales suggest
that great ideas are the result of epiphanies, such as Archimedes who supposedly while
lying comfortably in his bathtub suddenly realized that ‘any object, wholly or partially
immersed in a fluid, is buoyed up by a force equal to the weight of the fluid displaced by
the object’1; or of Isaac Newton who, when the apple fell from the tree, suddenly grasped
that the ‘…gravitational force is proportional to the product of the two masses
and inversely proportional to the square of the distance between them’2. In the light of
the notion of combinatorial innovation, the ‘Eureka!’ moment metaphor and Edison’s
light bulb allegory are reduced to romanticized versions of the truth. The point is that
most great ideas have a historical record, and first see the day of light after being
processed iteratively by a number of actors; often as result of collective effort of
‘connecting the dots’ (Burt, 2001). Similarly, innovations emerge through the
recombination of the technological components and processes that lie along the
contemporary technology frontier (Fleming & Sorensen, 2004). Through collaboration
and connectivity, the combination of pools of knowledge in due course leads up to a
moment of breakthrough.
The traditional view of creative processes, is that these are the result of a genetic
precondition or personal trait, but creativity is an import-‐export game -‐ not a creation
game (Burt, 2004). Hence, “the value in an idea lies not in its origin, but in its delivery” (Ibid.:1).
But how can the delivery of ideas be facilitated? It becomes important to understand
what circumstances that are required to facilitate the emergence of ideas? Behavioural
sciences holds part of the answer. A generic notion from sociology is that information
circulates more within groups of people than across groups of people (Lin et al., 2001).
With the notion of combinatorial innovation in mind, many scholars suggest that multi-‐
disciplinarity opens up for novel and more radical combinations. Nevertheless, since the
composition of groups often takes a homogenous character, it has been proved
challenging to reach out to actors who reside in distant networks and disciplines. What
1 Archimedes discoveries in the bath: http://www.mlahanas.de/Greeks/ArchimedesBath.htm 2 How Newton Built on Galileo Ideas: http://galileo.phys.virginia.edu/classes/109N/lectures/newtongl
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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could possibly incentivize people who do not naturally come together, to meet and share
knowledge and experiences?
Over time the mechanisms or ‘enabling spaces’ for connecting and facilitating
collaboration and mediation of information across people have taken many forms. In the
Age of Enlightment3, enabling spaces took the form of coffee houses. According to Cowan
“…the coffeehouse was a place for individuals to congregate, to read, as well as to learn
from, and debate with each other” (2005:89). Over the years more sophisticated enabling
spaces have emerged, such as schools and universities, and today’s counterpart of the
coffeehouses during the Enlightment is indisputably the Internet. Human social
interaction has changed dramatically over the past decade, much as a result of
developments in communication technology and the emergence of the Internet. The
central utility of the Internet is to facilitate connectivity and the notion of ‘sharing’ is the
substance of online interaction. The applications of the Internet found in in human life
today are countless. Social and public life is increasingly mediated through Internet
technology, essentially reframing our everyday experiences and changing the very fabric
of society. Since the emergence of the Internet in the late 1990’s, it has brought about
profound impacts on the world economy, on politics, on culture and social progress, and
promoted the transformation of social production and information dissemination
(Xinhua, 2010). The proliferation of low cost access to the Internet has made way for
new means by which inter-‐organizational and inter-‐personal interaction can take place,
allowing connections to be made and networks to be built, earlier unimaginable.
Essentially it has grown to become an integrated facet of life for people, organizations
and businesses -‐ a given piece of our information and communication landscape -‐ and
not the least a major source and catalyst for innovation.
One of the most profound manifestations of online communication technology is that of
virtual communities (VC). The mode for online communication has moved from
monologue to dialogue, i.e. from ‘one-‐to-‐many’ to ‘many-‐to-‐many’ (Brandtzæg et al.,
2010). VCs have soured in numbers over the past decade, and online ‘connections’ are
multiplying at a phenomenal rate. Today, the multiplicity of VCs is growing from broad
to narrow in scope and VCs are to be found within almost any area of interest, industry
3 Timespan: 1650-1796 (Frost, 2011)
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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or field of study. A VC can establish linkages and facilitate interaction between
geographically dispersed actors, and act as a vehicle for information exchange and
knowledge sharing (Füller et al., 2004). The interest for how online communication
technologies can accommodate new knowledge creation and enhance innovation is
growing among companies (Brandtzæg et al., 2010).
One such company is Novozymes (NZ) -‐ a Danish biotechnology firm and world leader in
industrial enzymes. The business of industrial enzymes is highly R&D-‐intensive, and
16% of NZ’ workforce is employed in R&D, and about 14% of revenue is re-‐invested in
research (Annual Report, 2010). The constant search for new knowledge is an integral
part of NZ’ business agenda, and the R&D organization is always seeking new leads for
application areas of its enzyme technologies. Along with developments of information
and communication technologies (ICT), the R&D organization at NZ has turned their
interest towards opportunities that can be realized by means of external knowledge
sourcing through the use of virtual community technologies. More specifically, they have
asked us to investigate to what extent a virtual community can help facilitate efficient
external knowledge sourcing and make R&D activities more explorative.
Innovating firms are said to face two conflicting processes of organizational learning:
exploration and exploitation. Exploitation deals with static efficiency and relates to
refinement of existing products and procedures and incremental innovation, whereas
exploration relates to dynamic efficiency and involves search for new options in distant
fields and more radical innovation (March, 1991). We know that managing the scope of
exploration and exploitation comprise a paradoxical challenge, and to do so successfully
is said to require ambidextrous organizational capabilities (Tushman & O’Reilly, 1996).
We draw upon the notion of ambidexterity and seek to understand the extent to which a
VC can support an ambidextrous model of innovation to emerge, as we seek to uncover
potential opportunities that can be realized by leveraging particular qualities of VCs to
help manage exploitation and exploration simultaneously.
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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1.1. Problem Statement In this thesis we explore the following research question: How can a virtual community
facilitate external knowledge sourcing so as to enhance the innovative capacity of
Novozymes’ R&D organization?
In this effort, we conduct a three-‐pronged analysis in which the three below sub-‐
questions are explored, respectively:
Q1: To what extent is the current innovation model at Novozymes conducive for
effective external knowledge sourcing?
Q2: How can virtual communities support the facilitation of external knowledge
sourcing for science-‐based firms?
Q3: Can a virtual community make way for an ambidextrous innovation model?
1.2. Clarification of research Q1: The first sub-‐question serves to address the extent to which the current innovation
model at NZ is conducive for external knowledge sourcing. Here we analyse NZ’ the
scope of R&D activities and its current innovation model. We investigate the
characteristics of the enzyme research environment at NZ and develop arguments for
why distant search is deemed a critical element in the development of novel and
revolutionary applications in enzyme technology. Ultimately we conclude that NZ
suffers from a local search bias and indeed hold to benefit from external knowledge
sourcing.
Q2: Secondly, mechanisms for external knowledge sourcing are reviewed, where we
take a particular interest in the role of virtual communities for facilitating external
knowledge sourcing. Here, existing literature and case-‐examples of virtual communities
are revised, and a set of enabling properties for how virtual communities can act as a
vehicle for external knowledge sourcing is identified. We further expand the second part
of the analysis and take pragmatic approach. Here we highlight a number of trends in
online community life as well conduct an online survey, where we find supporting
arguments for VCs in research-‐based environments.
Q3: Thirdly, we explore the notion of cognitive distance and explorative strategies to
shed light on the implications of too distant sources of knowledge. We furthermore
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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highlight the notion of ambidextrous innovation and address how a virtual community
holds potential to reinforce a balance between exploitative and explorative R&D
strategies.
In summary, Q1 helps us identify a problem, Q2 proposes a solution and Q3 assesses the
proposed solution in the light of scope of exploration and ambidextrous organisational
capabilities. Thus, in reaching our succeeding conclusions, this paper follows two logics
of reason. In exploring Q1 a practical and diagnostic approach is taken and our
subsequent findings are largely based on the case analysis of Novozymes through
empirical data from a set of interviews. Our case provides a context in which the
phenomenon of VC can be discussed and exemplified. In Q2 and Q3, our concluding
remarks are the result of inference from extant literature and application and
reconstruction of prevailing theory and concepts, and thereby of a more general nature.
Altogether, we hope to shed light on the emerging phenomenon VC with regards to
innovation and external knowledge sourcing.
1.3. Demarcation It is important to note that there is more to the story of building virtual communities for
external knowledge sourcing than what is covered over the course of this thesis. A large
number of factors must be assessed before a decision to build and employ a virtual
research community can be taken. This paper merely tells the story of how a (particular)
firm could potentially to benefit from an initiative like this. We thus take a specific
interest in gaining a contextual understanding of Novozymes, a company that wishes to
establish a virtual community, how a virtual community can facilitate external
knowledge sourcing, and the implications of this. Given the scope of a Master Thesis we
have chosen to omit analysis of how a possible implementation can take place, and
thereby refrain from addressing how knowledge are to be transferred, internalized or
absorbed into the real world setting of the organization from the virtual community.
Another important note on this paper is that it should not be seen as a cost-‐benefit
analysis of the utility of virtual communities in the given context, but rather as a benefit
analysis. While we touch upon both enabling and inhibiting properties of virtual
communities, we choose to delimit our thesis to unravel potential benefits encompassed
by this technology as opposed to its limitations. While this might indicate an asymmetric
emphasis, it seems justified by the scope and objective of the paper. Thus, we delimit our
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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focus on two dimensions. We place our research in the upper left quadrant of figure 1.1
below, yet we want to highlight the there are other important dimensions that needs to
be studied in order to gain a more complete comprehension of the phenomenon in
question.
Figure 1.1: Demarcation
Source: Own model
1.4. Motivation We, the authors of this paper, are fascinated by opportunities arising from the fast
developments of information and communication technology (ICT), and in particular,
online tools for communication and collaboration. Furthermore, given our pronounced
specialization in the field of management of innovation, we wanted to conduct a study of
how online tools hold potential to enhance innovative capacity of firms. Two facets of
innovation have driven our research forward. As highlighted in the introduction the
combinatorial perspective of innovation provides an appealing take on understanding
the emergence of ideas, and consequently how and where innovations transpire. Second,
a movement emphasizing the value to be reaped by firms through exploring external
sources of knowledge has emerged in the economic literature under the term open
innovation. Inspired by the principle proposed by Bill Joy, cofounder of Sun
Microsystems, “No matter who you are, most of the smartest people work for someone else”, we
find models for distributed (open) innovation an intriguing aspect of innovation worth
studying further.
1.5 Relevance Given the rapid emergence of new applications of ICT for the purpose of knowledge
sharing and collaboration we find the topic of our study highly relevant. Virtual
communities are today increasingly being used as a tool for crowdsourcing knowledge,
?
?
Implementation
Contextual understanding !
?
Costs Benefits
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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yet we find that the underlying elements for why online technologies provide such a
useful tool is understudied. In particular, we find that science-‐based firms who aim to
engage in unguided search of scientific opportunities by means of online technologies
have been largely omitted from the academic discourse. It is proposed here that science-‐
based firms to a larger extent can take advantage of online networks in their R&D
efforts; hence the present paper aims to provide supportive arguments and theory for
better understanding how to take an active role along the emerging trend of virtual
communities in the light of innovation. Moreover, it is believed here that in studying the
phenomenon of virtual communities through the lens of innovation-‐ and network theory
with point of departure in cognitive economics and sociology discourse, we wish to
provide a more nuanced picture of the utility of such technologies in the management of
R&D strategy and innovation. (See section 3 for literature review and research gap
identification).
1.6. Disposition Figure 1.2. Disposition of Thesis
Source: Own illustration
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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2. Methodology The aim of the methodology section is to provide the reader with an overview of the
overall research approach, collection and treatment of data, limitations, delimitations
and critique of chosen methods.
2.1. Research Strategy and Design We are conducting an exploratory case study of Novozymes, and highlight the benefits of
a virtual community for external knowledge sourcing in that context. Exploratory
studies focus on finding new insights, to ask questions and to assess a phenomenon in a
new light, and the advantage of exploratory studies is the degree of flexibility and
adaptiveness that the approach provides the researcher with (Saunders et al., 2007).
The exploratory researcher does not approach their project according to any set formula,
hence we set out to generate hypotheses for later investigation rather than illustrating
an actual occurrence of events. As such our case does not tell a story of how, but rather
asks how, and this paper can thereby be seen as an initial effort to shed light on the role
of virtual communities in a particular context that in turn can open up for future
research.
We are inspired by the abductive theory of method, which emphasizes no a priori
hypotheses or presuppositions before initiating the research (Levin-‐Rozalis, 2000; Haig,
2005). Drawing on an exploratory approach, we sat out to uncover and establish a
research hypothesis on the basis of initial project meetings with NZ (February 2011).
Based on this, we identify current and novel concepts that we find to be of assistance in
substantiating our hypothesis (Haig, 2005). In our particular case, we are not only
dealing with a hitherto unknown and completely new initiative at Novozymes, but
theory and literature on the topic is also scarce. We take this circumstance as an
opportunity to further explore the research phenomena; a circumstance that the
abductive logic supports by calling for a cyclical process of checking and rechecking
against observations made, widening and modifying our hypothesis through the process
(Levin-‐Rozalis, 2000). The movement between theorizing and data collection is reflected
in the shift that our research topic has gone through over course of our research. We
started out by looking into design attributes of an online platform to assess how such an
open innovation platform should be constructed. We soon came to realize that there
were other important underlying issues that would need to be addressed prior to
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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assessing implementation and architectural attributes of the platform. We turned our
interest to the notion of network structures-‐ as well as types of scientific research (basic
vs. applied scientific research) and its impact on different types of innovation. We thus
experienced a slight shift in our focus area, and began to theorize and collect data to
further assess these theoretical constructs in the light of a virtual community. Here
where we found that current literature and theory inadequately address the particular
intersection of the topics of network structures, innovation and virtual communities.
Figure 2.1. Abductive research method
Source: Own model
As a result of scant elaborative data, literature and theory, to explain this particular
topic of research, our research design was structured to encompass abductive reasoning.
Data are systematically collected and analysed, and re-‐evaluated to allow the initial
theoretical assumptions to evolve in the process of further data collection and analysis
(Strauss & Corbin, 1998). We furthermore re-‐construct prevailing theoretical constructs
and thus our identified hypotheses according to data collected – a reoccurring process of
movement between theorizing and conducting empirical research (Wallace, 1971). This
approach is, furthermore, in line with the paradigm of social constructivism, which
acknowledges that knowledge is generated in the context of social interaction between
the interviewer and the interviewee (Kvale, 1996). In light of a social constructivist
epistemological approach we primarily rely on heuristic reasoning as guidance
throughout the thesis. As opposed to logic reasoning, heuristic reasoning cannot
demonstrate the truth or falsity of a theorem; it can merely augment or diminish our
confidence in a theorem (Polya, 1941). Thus, while logic reasoning is objective, heuristic
reasoning is subjective. In turn, a heuristic proof is provisional rather than absolute, and
it may be completely reasonable yet come to change tomorrow. Consequently, our
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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conclusions are the best that can be obtained in the light of an explorative case study
and given the actual state of our knowledge.
2.2. Data Collection To address the identified research question we have utilised both primary and
secondary sources of information, and qualitative and quantitative research methods.
Secondary sources of information play an important role in the forming of this thesis,
and the MIB4 curriculum has inspired us in structuring our research. We take a
multidisciplinary approach to the literature that is assessed and employed, such to cover
cognitive economics, sociology as well as innovation-‐ and network theory, and literature
on Information and Communication Technology and virtual communities. Across these
topics we emphasise and elaborate upon a selected group of theoretical constructs that
we find useful in highlighting essential elements of our research.
2.2.1. Qualitative research methods Qualitative data collected and applied in this thesis are gathered through interviews.
The purpose with qualitative research interviews is to examine the perceptions of the
world from the point of view of the interviewee and thus to comprehend the meaning of
their experiences of a given subject (Kvale, 1996). Opponents of the qualitative method
argue that research interviews may not lead to objective information (Kvale, 1996). But
this can be partly explained by the ontological point of view of these researchers. They
will predominantly be represented within the positivistic paradigm, and therefore claim
that quantitative methods are the only viable and scientifically sound methods (Kvale,
1996). The ontological point of departure for this thesis is that of social constructivism
and we thus understand that interviews will never represent the definitive truth;
information of an objective nature is not possible to achieve, neither is it the aim of our
research method.
Interviews The objective of this section is to shed light upon the type and structure of interviews
conducted. We have primarily relied on in-‐depth semi-‐structured interviews (approx. 1-‐
2 hours per interview), as such interviews are of value for seeking new insights to a given
issue (Saunders et al., 2007). Inspired by McCurdy et al. (2005) we have commenced
4 MIB: ‘Management of Innovation and Business Development’, a M.Sc. degree program at CBS
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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interviews by asking grand tour questions based on a range of topics that we sat out to
identify. These allow the informant to describe a ‘regular day at the office’ and gives the
researcher an idea of what the informant perceives to be the most important to stress; a
valuable technique that avoids imposing interviewer bias. Subsequent questions such as
mini-‐tours-‐ and story question methods have built upon preceding questions, to ensure
that we gain the perspective of the informant (Ibid.).
In exploring our research question we identified four overall focus areas that we sat out
to address through out our research and interviews.
1. Open innovation in the context of Novozymes. The initial interviews conducted with key
employees at NZ, took a predominant focus in understanding what is meant with open
innovation at NZ and which relation it has to company core values.
2. Novozymes R&D Organization. The focus here is to gain an understanding of the current
research processes at NZ’ R&D organization, their current model of innovation and
advantages and challenges that the current structure exhibits.
3. Characteristics of enzyme research. The aim is to understand how enzyme research is
carried out, how scientists interact with other scientists and what types of information is
discussed or shared.
4. Online interaction and the potential of a virtual community set-‐up. We address the
potential utility of a virtual community set up in the context of enzyme research where
we discuss opportunities and disadvantages of a virtual community set up.
Interviewee group Table 2.1 provide an interview summary of all interviews conducted as well as an
indication of which focus area that each interviewee has contributed to. Interviews
conducted have been divided up into two categories: 1. Internal, (NZ employees)
including: biotechnology engineers, enzyme researchers and employees from the
innovation office, marketing, sales excellence, customer solutions, corporate branding
and business development. 2. External (enzyme researchers and innovation
management specialists) including: bachelor-‐ master-‐, Ph.D. level engineering students,
and innovation managers and professors. The column named Company indicates which
company the interviewee is from, and in the case of NZ, 2C Novozymes refers to the R&D
Organization, whereas 8X Novozymes refers to the HQ departments at NZ.
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Table 2.1: Interviewee List Internal
Name: Position: Company: Initials Area of In-‐ vestigation
1 2 3 4
1 Thomas Lykke Sørensen
Front End Champion 2C, Novozymes TLS
2 Thomas Rasmussen Business Development Manager
8X, Novozymes TRMU
3 Jesper Duus Nielsen Senior Department Manager 2C, Novozymes JDUN
4 Erik Gromsen Vice President 2C, Novozymes ERG
5 Martin Simon Borcher Senior Department Manager 2C, Novozymes MTBO
6 Carsten Lauridsen Project Director 2C, Novozymes CLAU
7 Sune Sauer Lobedanz Senior Department Manager 2C, Novozymes SULO
8 Mads Bjørnvad Senior Manager 2C, Novozymes MAEB 9 Martin Barfoed Director 2C, Novozymes MAB
10 Henriette Draborg Innovation Platform Manager 2C, Novozymes HDRA
11 Henrik Lund Senior Department Manager 2C, Novozymes HLU
12 Torben Bochlet Senior Director 2C, Novozymes TVB
13 Henrik Bisgård-‐Frantzen Senior Director 2C, Novozymes HBF
14 Thomas Lenhard Senior Department Manager 2C, Novozymes TLHD
15 Sara Landvik Senior Scientist 2C, Novozymes SALK
16 Steen Krogsgaard Senior Department Manager 2C, Novozymes STKH
17 Espen Friis Protein Engineering 2C, Novozymes EPF
18 Jesper Frederiksen Corporate Brand Manager 8X, Novozymes JFRE
19 Mads Madsen Corporate Positioning, Head of Branding
8X, Novozymes MSMS
20 Lars Christian Hansen President, Novozymes Europe 8X, Novozymes LACH
21 Anett Lund-‐Nielsen Colstrup
Head of Sales Excellence 8X, Novozymes ALN
22 Anders Ohmann Global Customer Solutions Director 8X, Novozymes AOH
23 Sebastian Søderberg Business Development and Marketing Director
8X, Novozymes SESQ
24 Kristian Ebbensgaard New Business Development Director
8X, Novozymes KEBB
25 Anders Lund Senior Director Marketing 8X, Novozymes ALUN
26 Peter Stenbak Executive Assistant to CEO 8X, Novozymes PSTB
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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External
Name: Position: Company: Initials Area of In-‐ vestigation
1 2 3 4
27 Jovita Ivanaviciute Global Research & Innovation Vestas JIV
28 Anders Bech Bruntse M.Sc Student DTU Bruntse
29 Jakob Skjold-‐Jørgensen M.Sc. Student KU Skjold
30 Rasmus Marvig Ph.D. Student DTU Marvig 31 Hans Genee M.Sc. Student DTU Genee 32 Johan Fuller CEO HYVE Fuller 33 Peter Kragh Innovation Manager Coloplast Kragh 34 Jacob Bøtter Partner, Author Wemind Bøtter
35 Lars Bo Jeppesen Professor Università Commerciale Luigi Bocconi
Jeppesen
2.2.2. Method of verification
Qualitative data comprise the majority of our data input, and our research approach is
built to overcome the inherent drawbacks of qualitative methods. We recognize that it
can be difficult to determine the number of interviews needed to validate findings, yet
we draw upon the concept of triangulation5 in achieving consistency of inputs from
informants. I.e. we investigate the extent to which information given by one informant
does in fact provide a realistic picture of the situation. Thus multiple sources of data is
utilised to crosscheck the information provided by informants internally at Novozymes
and external to the company. Furthermore, we consult informants after interviews to
check whether he/she agrees with our interpretations and if conclusions made
represent his/her explanations. The objective of applying the method of triangulation is
to increase both the validity, i.e. checking for causality; and reliability, i.e. checking for
observer bias (Saunders et al., 2007). Through applying these methods of verification,
we experienced that interviewees were content with the conclusions and
interpretations that had been made. And in circumstances where a divergence was
found, we were able to elaborate and discuss findings with the interviewee to reach
mutual understanding of our interpretations.
5 Triangulation refers to the use of two or more independent sources of data or data collection within one study in order to ensure that the data is telling you what you think it is telling you, i.e. ensuring validity (Saunders et al., 2007:614)
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2.2.3. Quantitative research method
The aim of this thesis is to explore how a virtual community can act as brokerage
function and to facilitate external knowledge sourcing. We are analysing the potential of
a hypothetical virtual community, thus qualitative data pertaining to records of an actual
case does not exists. Quantitative data has in this paper has been gathered through a
structured online questionnaire (appendix 2 for online questionnaire). The
questionnaire is formulated on the basis of what we learned during our interviews and
the survey was sent out to approximately 100 people, where we have received 42
responses. As we draw on the social constructivist paradigm, our aim with the online
survey has been to gain more generalizable and comparable insights with regards to
utility of a virtual community in the context of science-‐based firms who seek to explore
external sources of knowledge. The responses given through the online survey are
applied in part II of the analysis where we explore how a virtual community can be
understood as a platform for external knowledge sourcing.
2.3. Critique of methodology
2.3.2. Limitations The key objective in this paper is to shed light on the phenomenon of virtual
communities as a tool for science based firms to expand their exploratory scope. Given
the nature of our case, we are not able to analyse an actual virtual community and the
results and implications of such. In that respect we are to a limited to a prospective
research approach, where we by means of empirical data and theory aim to anticipate
future outcomes. As such, we cannot make use of the benefits of a retrospective study
that looks backwards and examines the actual outcome of a given phenomenon at work.
Moreover, we seek to identify the potential utility of virtual communities in a new
context where this phenomenon has not yet been studied (to our knowledge), and
acknowledge that our subsequent concluding remarks are to a certain extent speculative.
Yet, there are a number of methodological benefits from taking a prospective case study
approach that we wish to highlight. One issue with the post hoc, or retrospective case
study approach is that the awareness of the outcomes of the case gives the researcher a
temptation to “cherry-‐pick” a case that supports a given hypothesis or theoretical claim
and leave out propositions and factual data that does not fit with the author’s plan
(Bitekhtine, 2007). As mentioned, hypothesizing in this paper has taken place over the
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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course of the research process and is thus less contaminated by such bias. Nonetheless,
we as authors of this paper are certainly not free from bias. The leading hypothesis of
this paper is that virtual communities indeed exhibit opportunities for science based
firms to engage in external knowledge sourcing, hence our preconceived ideas regarding
the utility of virtual communities in this context has played a role during the formation
of the paper at hand.
We recognize the limitations of single-‐ case study, where a multiple case study could
provide more generalizable results. Nevertheless, we believe that as the first study of its
kind, it is important to promote depth over scope in order to unravel the underlying
mechanisms in place. Moreover, much of the input used to delineate a set of enabling
properties of VCs for acting as a vehicle for external knowledge sourcing are based on
inference from existing literature and casework on the use of VCs in related contexts.
In taking an exploratory approach our empiric input plays an important role in opening
up for further questions to be considered. In identifying interviewees as well as
respondents in our online survey, we have used a method of pyramiding. I.e. we have
identified appropriate interviewee candidates in a sequential fashion based upon
recommendations from our preliminary round of interviews. We recognize the risk of
interviewee and respondent bias, however we wish to assert that random selection
would not have been viable in this study, given that extensive knowledge of the subject
matter was deemed a prerequisite to receive qualified answers. Furthermore, we
understand that even with the method of random selection, fully unbiased responses are
not completely achievable.
Finally, Novozymes is known as the world leader of enzyme technology and as a
company that has the capital to make investments in projects, as one interviewee
mentioned, “I don’t think any top-‐level manager at NZ has felt that he didn’t have the funds to
engage in a project of need or interest” (TRMU, 2011). There is thus a great deal of prestige
from being associated with NZ, and many students from engineering universities see
great opportunities in working there. Although interview contacts made with master
degree and Ph.D. level students where initiated by ourselves, the informants became
aware of the sponsor behind the project, namely NZ, through the course of the
discussion. Consequently this can have an impact on the data gathered through the
interviews and online questionnaire resulting in biased responses. For the interviews
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conducted internally at NZ, the initial contacts for the first round of interviews was
made through the project group at NZ, and thereby had an impact on the responses
given. This can all have had a limiting impact on the information given, however, we
have to the extent possible focused on interview verification methods and been aware of
the potential bias while evaluating data for the analysis.
2.3.3. Reliability Reliability refers to whether the data collection methods yield consistent findings. Three
areas are emphasised here: firstly, if measures taken will yield the same results on other
occasions, secondly, if similar observations could be reached by others, and lastly, if
there is transparency in how sense was made from the raw data (Saunders et al., 2007).
Throughout our research we therefore pay attention to the three threats of reliability,
namely time error, subject error and observer influence (Wilson, 2010). We have
gathered data over the course of nine months and conducted interviews in rounds,
ensuring reliability of answers of respondents, and to provide us with an awareness of
the changing contexts related to the case. This inherently increases our chance to reduce
threats of time error and subject error. With regards to observer influence we have
focused on introducing ourselves as Master Degree students from Copenhagen Business
School, and emphasized that the objective of our research has no risk of harming
respondents’ professional standing. Nevertheless, we recognize that we cannot
guarantee that we have successfully overcome the three threats of reliability.
2.3.4. Validity Validity refers to the extent that the methodological approach allows the researcher to
investigate the problem at hand, and is concerned with the level of truth in the data with
regards to the specific problem (Kvale, 1996). Yin (2003) emphasizes the importance of
constructing validity, both in the research design itself, as well as during the data
collection process. Yin points out that this may be especially important to stress in a case
study research, as people often criticize case study researchers for using ‘subjective’
judgments during data collection. In order to increase construct validity, he suggests
three tactics: multiple sources of evidence, chain of evidence, review by key informants
(Yin, 2003).
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In order to fully grasp the context that we are researching, we have tried to utilize
multiple sources of evidence to help build and substantiate our findings. We draw upon
qualitative both quantitative research methods where we use interviews, and online
survey as well as literature and theory as sources of input. Furthermore, we take an
interdisciplinary approach to provide a more nuanced assessment of the problem at
hand. While we recognize that there is trade-‐off of depth and scope we have favoured a
broad perspective over a narrow with regards to the literature that we draw upon. The
research process in this paper can be characterised as an incremental chain of evidence
build-‐up, where our hypotheses undergo modifications throughout the process.
Together with key contacts at NZ (TLS & TRMU), we identified an overall assumption of
a positive causal relationship between the notion of distant sources of knowledge inputs
and innovative capacity for NZ. We find support for this claim by combining network-‐
and combinatorial innovation theory that allows us to understand the importance of
distant search and the potential value that lies in networks beyond the reach of the
organisation. Hence, through our interviews we have aimed to focus on a variety of
topics as to cover virtual communities, combinatorial nature of innovations and
structural holes. Lastly, in the previous section on qualitative research method, we
addressed how we have arranged for review by key informants throughout the interview
process by allowing respondents comment on their input.
2.3.5. Generalizability
Generalizability is the degree to which findings can be applicable to other research
settings, also referred to as external validity (Saunders et al., 2007). External validity is
more difficult to attain in a single-‐case study (Yin, 2003), however, as suggested by Stake
(2003), a better understanding of a single case could lead to a better theorizing about a
still larger collection of cases. The degree of generalizability of findings is elaborated
upon the in the discussion and future perspectives section (section 7) following the
analysis and concluding remarks.
2.4 Delimitations Delimitations define and narrow the scope of the study in question, and here we present
exclusionary and inclusionary decisions that have been made throughout the thesis.
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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• The case analysis is anchored in the R&D organisation at NZ, meaning that
research is conducted with focus on the structure and processes that reside
within R&D. We will therefore not assess or include how other functions present
at Novozymes that could provide support for external knowledge sourcing or act
to enhance of innovative capacity, such as marketing-‐ and business development
departments etc.
• The social structure of networks theory discusses both community-‐ and
individual dimensions of networks. We are particularly interested in the
underlying notions of the theory and the effect networks, structural holes and
bridging has on innovation. Thus we omit from distinguishing the community-‐ vs.
individual dimension level network structures.
• We take a particular interest in assessing the potential of a science-‐based virtual
community for researchers that is initiated by a B-‐2-‐B firm. The analysis will
therefore not encompass other forms of virtual communities often employed by
B-‐2-‐C companies such as lead-‐user-‐ or challenge-‐based communities.
Further delimitations that are of interest for the research scope will be elaborated upon
in Literature Review and Research Gap (section 3).
2.5. Central Concepts A number of concepts are employed throughout this thesis. Many concepts are adopted
from prevailing theory and literature and have been outlined in the subsequent
literature review and theoretical discussion sections. Nevertheless, we develop and
make use of several terms and concepts that we wish to describe here in more detail.
Technological vs. organisational innovation We acknowledge that is there is a distinction between technological and organisational
innovation. The former relates to how firms commercialise new technological
knowledge and ideas that result in new products or processes, while the latter referrers
to changes to organisational structures and administrative processes (Poole & Van de
Ven, 1989). We draw on both of these definitions as we address both the impact that a
VC as on the organizational design of our case company, as well as capacity for
producing commercial innovations in the light of exploitative-‐ and explorative R&D
strategies.
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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Innovative capacity The concept of innovative capacity provides a way to understand and measure
fundamental aspects of the ability of a firm to research and produce innovation. While
we do not set out to measure innovative capacity, the term is used to denote the
aptitude of a firm (in our case Novozymes) for producing innovation by means of its
R&D efforts. In behavioural science literature we find evidence of use of the term in
addressing how innovative capacity often is obtained through networks. In other words,
networks can increase the innovative capacity of experimental firms by helping them
secure advantages that they would not be able to obtain on their own (Suarez-‐Villa,
1990). This paper echoes this view of networks and innovation, and recognizes the
importance of networks to ensure innovative capacity.
Incremental vs. radical innovation Incremental innovation can be understood as the continuous learning and development
of existing technology, whereas radical innovation can be understood as the exploration
of new technology that departs from existing practices and structures (Orlikowski,
1991). The view taken on incremental and radical innovation in this thesis is not to be
understood as separate categories but rather as placed on either end of a continuum
representing the degree to which new knowledge (novel combinations) is embedded in
an innovation (Ibid.).
External knowledge sourcing We use the notion of external knowledge sourcing in defining our research question. In
the literature we find that external knowledge sourcing is said to be crucial for
innovation processes, and has been defined as the ability of a firm to recognize,
assimilate and transform knowledge available from dispersed external sources such as
customers, suppliers, other firms, universities, online communities, and industrial
designers is (von Hippel, 1988; Chesbrough, 2003). We define this concept as the ability
of a firm to expand and replenish its knowledge base by means of sources of knowledge
residing external to the organization.
Virtual Innovation Broker The virtual innovation broker (VIB) is a concept used to denote the capacity of a virtual
community to act as a mechanism for bridging structural holes. This concept is
introduced in more detail in the forthcoming theoretical discussion and analysis part II.
Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin
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Discipline Throughout this thesis the term discipline is thoroughly utilized. In the context of our
thesis a discipline is used to denote a particular branch of scientific knowledge or field of
study. Subsequently, cross-‐disciplinary work involves two or more disciplines.
Science-‐based firm Throughout this thesis we use the term science-‐based firm to indicate a company that
uses scientific research as its main input for R&D and technological innovation.
Ambidextrous Innovation We use the notion of ambidextrous innovation to highlight the ability of a firm to carry
out both exploitative and explorative innovation strategies concurrently.
3. Literature Review The literature review section is aimed at identifying a research gap in the current
literature in which the present paper aims to make a contribution. We have set out to
investigate the notion of a virtual community as a mechanism for facilitating external
knowledge sourcing for science-‐based firms. In this effort we review literature on the
topics of Information and Communication Technology (ICT) and Virtual Communities
(VCs) to determine to what extent contributions in the field have addressed our
particular topic of research. On the one hand, the literature review outlined here is a
summary in that we revise extant literature within the field to familiarize the reader
with what has been written on the topic, and to identify a gap in which to position the
present paper. On the other hand, it is just as much a synthesis by way of re-‐organizing
previous findings and claims from extant literature, to give way for new interpretations
that can shed light on the phenomenon under scrutiny. We aim to pinpoint that the
phenomenon of VCs -‐ understood as a mechanism for firms to engage in unguided
search for scientific input to R&D in the external research environment -‐ has been
largely understudied, in particularly through the lens of cognitive economics and
innovation and network theory. First, we position our paper in the field of cognitive
economics, and thereafter move on to revise literature regarding the utility of
incorporating VCs to promote organizational learning. We find that extant literature
inadequately has addressed how science-‐based R&D-‐intensive firms with a strong B-‐2-‐B
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orientation can utilize VCs as a mechanism for unguided search as a means for external
knowledge sourcing.
3.1. Cognitive Economics A cognitive approach to understanding human activities in the economic arena has
become a fundamental area of inquiry. The field of cognitive economics is developing
into a discipline which is bearing a new theory of human behaviour in economics,
strongly rooted into a cognitive approach to human action (Egidi & Rizzello, 2003).
Cognitive economics can be defined as “…the study of reasoning operations and adaptation
processes implemented by economic agents in their interactions” (Walliser, 2001:3). We adopt
the cognitive approach to economics given the notion that the “...choices people make are
determined not only by some consistent overall goal and the properties of the external world, but
also by the knowledge that decision-‐makers do and don’t have of the world, their ability or inability
to evoke that knowledge when it is relevant…” (Simon, 2000:25). Along the lines of cognitive
economics we take a multidisciplinary approach to our study and concede that the
context in which our research takes place is characterized by structural uncertainty6. In
this particular paper, the notion of search for scientific knowledge in human problem
solving is a central topic, and the conception of innovation lies at heart of our research.
March and Levintahl (1993) point out that firms often find themselves in cognitive traps
in which a strong focus on success may induce them to persist excessively in the use of
procedures and actions associated with success in the past. This tends to anchor firms in
exploitative sub-‐optimal routinized strategies to the detriment of research and
innovation (Ibid.). The central area of interest in this paper is to investigate how firms
can avoid, or escape, such cognitive traps. Our focus is mainly to explore the hypothesis
that a virtual community can act as vehicle for exploration and external knowledge
sourcing and subsequently relieve firms of such ‘traps’. We study the underlying
processes of a particular firm’s (NZ’) R&D activities and its current innovation model to
find that it is to a certain degree trapped in sub-‐optimal exploitative strategic routines.
We further draw on literature in sociology, and on the notions of combinatorial
innovation and network theory, in order to establish that the external knowledge
sources hold opportunities for enhancing the innovative capacity of our case company.
What is of particular interest here, are mechanisms for getting access to unexplored
6 Structural uncertainty: Probability of the occurrence of an unanticipated event due to a particular configuration of a system such as an economy, market or organization (businessdictionary.com)
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pools of knowledge, and we have chosen to pay specific attention to the role of virtual
communities understood as an ‘enabling space’ or ‘bridge’ between a firm and its
external environment.
There are intense academic debates both regarding more ‘open’ innovation activities,
combinatorial innovation, structural holes theory and around the exploitation-‐
exploration dichotomy, however very few scholars have combined these streams of
literature (one exception is found in Danzinger & Dumbach, 2008). We suggest that an
integrated approach can enrich theory and the workability of these concepts, and in
particular shed new light on the phenomenon of virtual communities. We revise
literature and theory on VCs to determine where in the literature our paper fits.
3.2. Brief history of ICT and the Internet The IT era started in 1971 and transformed society mainly by spurring radical
improvements in computation capacity (see Mores law7) (Jovanovic & Roussea, 2005).
IT has given rise to a successive wave of new technologies including the semi-‐conductor,
and most notably the Internet. While the semi-‐conductor can be thought of as
computational extrapolation of IT, the Internet can be viewed as the communicational
arm of IT. Since the late 1990s the notion of ICT8 (information and communication
technology) is often used to denote these two facets of IT, and in this paper we
predominantly take an interest in the communicational externalities of IT; henceforth
we employ the term ICT.
Since the early days of the Internet era, sceptics and traditionalists have ascribed a
number of risks to the phenomenon of the Internet. It has been said to be potentially
detrimental for the traditional sense of in-‐real-‐world (IRL) social relationships (Dreyfus,
2001). Online social relationships have been described to be less profound, valuable and
durable than offline relationships, and that such communication is often less expressive
and authentic than face-‐to-‐face (FtF) communication. Furthermore, online
communication has been feared to water out human social life dispatching us to the
realms of virtual worlds (Ibid). However, most contemporary research shows that the
Internet has not alienated us from the real world. On the contrary, the Internet has been 7 Moore's law describes a long-‐term trend in the history of computing hardware, i.e. the number of transistors that can be placed on an integrated circuit doubles approx. every two years (Moore, 1965) 8 ICTs and the Internet are used to address a broad range of computer technologies including web browsing, email, chat/instant messaging, online communities, blogs etc.
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shown to stimulate social and civic engagement and has been said to be the major
catalyst for globalization and the continued progress of the human race (Song, 2008). As
a matter of fact, people are found to be remarkably resourceful in waving the Internet
into existing practices of everyday human life, and instead of abandoning prior social
practices people engage in media multiplicity – the act of using several mediums for
building and maintaining social relationships (Wellman & Haythornthwaite, 2002;
Howard et al. 2004). Essentially the Internet has shrunken the world, yet significantly
enlarged social life, by juxtaposing remote actors online and boosting information and
knowledge sharing. Yet, the literature around this field is nascent and dispersed, and
theorizing-‐ and conceptualizing processes are at work continuously. One of the most
solid concepts to have emerged is that of the virtual community9. The Internet revolution
has evoked an unprecedented proliferation of virtual communities across the web
(Fernback, 1999; Hiltz & Wellman, 1997). The notion of VC is employed as a central
concept in this paper referring to an online ‘space’ where reciprocal interaction takes
place between individuals and groups.
3.3. Virtual Communities The concept of the ‘virtual community’, first introduced by Rheingold (1993), has today
become the pigeonhole for describing ‘places’ where social interaction takes place
virtually through some sort of media, as opposed to in real life (Lavián & Guinalíu, 2005).
While the virtual community concept is as old as the concept of the Internet, its
exponential growth began in the late 1990s due to developments in ICTs such as
electronic mail (e-‐mail), chat rooms and instant message systems (Ibid.). The
justification to this expansion is found in the advantages generated by virtual
communities. Computers send and receive data across remotely located servers that, by
means of a shared interface, facilitate a sense of belonging, collective action and
interpersonal intimacy for humans (Andersen, 2005). Online, people can experience the
benefits from communal life, while avoiding most of its burdens. An individual can
participate in a public ‘place’ while physically being in a private place, and share
thoughts without running the risk of immediate narrow-‐minded judgement. And, in case
conversations grow dull or relationships complicated, a virtual community is always
easy to leave.
9 > 3 million hits on google.com / > 50,000 hits on scholar.google.com
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Many definitions of the concept of virtual community have appeared in the literature,
but traditionally this concept has been defined from a social point of view. In Reigngold’s
definition, virtual communities are the “…social aggregations that emerge from the ‘Net’ when
enough people carry on those public discussions long enough, with sufficient human feeling, to form
webs of personal relationships in cyberspace” (1993:5). Similarly, Ridings et al. (2002) expose
that a VC is a group of people with a common interest that interact regularly in an
organized way over the Internet. Following Besser online communities are more
narrowly defined as “groups of people with a shared interest in a hobby, profession, or a product
who get and share ideas online. The sharing is done at the convenience of the participant and not
at a specific time of the week or month, and the "meetings," as a result, tend to be ongoing”
(2000:159). It can be inferred that one of the main advantages of VCs is that these
communities can overcome the space, time and physical barriers to interaction that exist
in traditional in-‐real-‐life (IRL) communities (Andersen, 2005). As such, virtual
rendezvous in the form of online groups, networks or communities, challenge the
traditional notion of a community understood as something physically embodied and
dependent on geographical proximity of interacting members. Even so, virtual
communities encompass many of the attributes of IRL communities. Muñiz and O’Guinn
(2001) point out that virtual communities encompass three core components:
• Consciousness of kind: Refers to the feeling that binds every individual to other community
members and the community brand.
• Rituals and traditions: Processes carried out by community members who help to reproduce
and transmit the community meaning in and out of the community.
• Sense of moral responsibility: Reflects the feelings that create moral commitment among the
community members.
While the above highlights many of the characteristics of VCs, little is said regarding the
reason for why individuals choose to engage in communities online. Hagel and
Armstrong (1997) point out that virtual communities can help to satisfy three types of
needs:
• Sharing resources: VCs enable individuals to share information on topics they may be
interested in.
• Establishing relationships: In VCs we may find people with similar problems, interests and
experiences.
• Trading: Some VCs also allow us to carry out economical transactions.
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While the above list is far from exhaustive, the notion of ‘sharing’ is a reoccurring theme
in most definitions, and can be identified as the substance of online interaction. In
determining how VCs can comprise a source of external knowledge, and potentially
enhance an organization’s innovation capacity, sharing of information, knowledge and
ideas become key components. The proliferation of online communities and interactive
places for collaboration hold the potential to extend the scope of, and access to, relevant
knowledge sources available to an organization (Zhang & Ackerman, 2005). Given that
VCs have enabled new dimensions of interaction and interconnection among
individuals, documents and data, and have become places for people to seek and share
expertise (Ibid.), they have proved to be useful tools for firms in pursuit of new
expertise and knowledge. However the extant literature regarding this topic is quite
scattered and we find that the above definitions and typologies are overly broad in their
scope as they include almost any kind of relationship that takes place across the virtual
space. While they are useful in providing a basic understanding of the concept, they fail
to acknowledge the diverse nature of how and why a VC can be useful, particularly
taking a business perspective. For the purpose of this thesis it becomes important to
differentiate between different kinds of online communities and to consider the
objective that a business may have for facilitating a VC.
3.4. A typology of virtual communities for external knowledge sourcing The diversity of virtual communities (VC) for external knowledge sourcing is quite
remarkable and VCs are today found to meet a plethora of needs unthinkable just ten
years ago. The utility of VCs for knowledge sharing and idea generation has been
illustrated in a large number of studies, and by means of identifying a set of VC
attributes we wish to provide a comprehensive overview. In turn, this will help us to
better pinpoint where in the literature we find our research gap. We identify a set of
community architectures that are fundamentally different, yet all sharing the quality of
acting as catalysts for external knowledge sourcing. We introduce a three-‐pronged
typology of VCs, namely: the user-‐driven-‐, the challenge-‐based-‐, and the research-‐driven
VC. We then pinpoint that the type of community that this paper has set out to study
belongs to the third category. Finally, we highlight in which way this study is different
than other studies of its kind.
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In order to develop a VC typology, inspiration has been drawn from Pisano & Verganti
(2008) and their classification of modes of collaborative innovation. While this article
does not specifically address ‘virtual’ communities, it acts as a good guiding framework
for understanding different kinds of external networks of innovating firms.
Figure 3.1: Modes of external collaboration
Source: Pisano & Verganti (2008)
3.4.1. User-‐driven community
User-‐, power-‐user-‐ or lead-‐user communities have been recognized to support
innovation and product development across a large number of firms. Von Hippel (2005)
defined lead users as users whose needs significantly anticipate the requirements of the
broader market. However lead users are found to be useless to companies unless they
find a way to communicate and form relationships (Moeini et al., 2006). The phenomena
of VCs have made the lead-‐user innovation concept more widely accepted and exploited;
a number of such successful VCs have seen the light of day. As provided by the
terminology, ‘user-‐driven’ suggest that it is the users of the final products that take part
in product development and the innovation process. This type of community has been
found to be particularly useful for B-‐2-‐C oriented firms (Antikainen, 2011). Two
successful VCs of this kind include Coloplast’s Stoma-‐innovation and Lego’s
Mindstorms.com. This kinds of VC resonates the characteristics of the “elite circle”
outlined by Pisano and Verganti (2008).
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3.4.2. Challenged-‐Based Community
The challenged-‐based community architecture is structured around pre-‐defined
problem statements or challenges that might be facing a particular firm. In the lingo of
Pisano and Verganti (2008) the challenged-‐based community would resemble that of
the Innovation Mall. Examples of such communities range from one-‐time product design
competitions to extensive expert networks solving complex puzzles. E.g. Henkel
advertised an online challenge called the Henkel “Adhesive Packaging Design Contest”10
where solvers from all over the world submitted their proposals, and a winner was
selected and rewarded. Netflix, the world’s largest online movie rental service provider,
hosted a challenge for developing a logarithm to improve its video recommendation
system. Teams of mathematicians, programmers and software engineers were given
three years to solve the challenge with a subsequent reward of US$1 million. The most
renowned challenged-‐based community is that of Innocentive.com: an online
intermediary innovation broker who broadcasts challenges with accompanying rewards
to a vast network of experts (Lankhani, 2008). We have found that both B-‐2-‐C and B-‐2-‐B
oriented firms utilize this kind of VC.
3.4.3. Research-‐based community In our definition, the research-‐based VC is aimed to source knowledge and expertise
from a global network of a broad mix of industry and university scientists, but also other
individuals interested in the topics addressed by the community ‘owners’/moderator.
The overall goal is to expand the innovation capacity of the firm who choses to establish
the platform. In Pisanos & Verganti (2008) this community bears resemblance to the
Innovation Community in that anyone who is interested are welcomed to join and the
‘search’ is unguided, i.e. not steered by means of predefined problems or queries. The by
far most famous example of a research-‐based community would be that of Procter and
Gamble’s (P&G) Connect & Develop (C&D). It was estimated that for every P&G scientist
there were at least 200 other scientists at least as good elsewhere in the world. Hence,
in 2004 the C&D innovation model was created. C&D is an online initiative based on
global R&D network of scientists and other professionals external to the organization,
who by means of having a clearer sense of consumer needs, work towards identifying
promising ideas and products for the world market (Huston & Sakkab, 2006). In 2010
10 http://www.packdesign-‐contest.com/start.php
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more than a thousand successful products had been launched with the involvement of
external innovators. Over the years, research productivity has been dramatically
improved at P&G through reliance on a global collaboration platform with people
external to the organization (P&G Annual Report, 2010).
3.5. Research Gap Virtual communities (VC) can be viewed as a relative new phenomenon, dating back less
than two decades. The literature around VCs is embryonic with loosely connected
contributions sprouting up across disciplines. Furthermore, along with new technology
advancements in ICT the phenomenon of VCs is under constant development, making it
a moving target thus difficult to study. By using the typology outlined in below, we can
better isolate our literature gap.
Figure 3.2: Virtual Community Typology
We find that existing literature and case studies examining the utility of virtual
communities as catalysts for external knowledge sourcing to be inadequate. Our
literature gap is two-‐fold, practical and theoretical: Firstly, we find that one of our
identified categories of VCs, namely the research-‐based VC as established in the above,
has been largely understudied. Whether it takes the form of academic papers and case
studies, we find that contemporary work addressing both user-‐driven-‐ and challenge-‐
based VCs occur frequently in the literature with a number of illustrative studies, while
science-‐based research focused communities are close is lacking. Moreover, most
studies on research-‐based VCs relate to initiatives taken by B-‐2-‐C oriented firms, in turn
resulting in a strong end-‐consumer focus. We find that virtual solutions utilized by
science-‐based firm with a B-‐2-‐B orientation to be particularly unaddressed. In this light,
through investigating opportunities of a VC for our case company Novozymes (a B-‐2-‐B
oriented science-‐based firm), we add valuable insight to a new dimension of use of VCs
not yet illuminated. Secondly, we have not come across any piece of literature taking a
User-‐driven VC Challenged-‐based VC Research-‐driven VC • Lead-‐user innovation • Innovation of “use” • Virtual customer environment
• Broadcasting • Solutions seekers and solvers
• Pre-‐defined challenges and rewards
• Virtual research environment
• Knowledge sharing • Collaboration • Unguided Search
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cognitive economics perspective in addressing research-‐based VCs, neither combining
the theoretical lenses of innovation-‐, network-‐ and ambidexterity theory in this effort.
Finally, we believe we are first to postulate that VCs can by means of certain attributes
overcome obstacles of ambidexterity and thereby ease the often difficult balance of
exploitation and exploration.
In other words, we find that the current literature, by using prevailing concepts and
theory, does not sufficiently address how science-‐based B-‐2-‐B-‐oriented firms can
facilitate a VC as part of unguided search for new scientific knowledge and expertise
with the ultimate goal to ambidextrously enhance innovative capacity. Furthermore, we
test the use of prevailing theory and concepts in explaining the emerging phenomenon
of VC and its implication for external-‐ search, knowledge sourcing and collaboration. It is
our intention to elucidate the phenomenon of the VC in the given context.
4. Theoretical Discussion In this paper we take an exploratory multidisciplinary approach, where we draw upon
and combine literature from sociology, cognitive economics, innovation, and ICT. We
integrate a range of theoretical constructs including: innovation theory, network theory,
structural holes, search, social capital, ambidexterity and virtual communities. The
objective of the theoretical discussion is to provide an understanding of the theoretical
notions and the application of these in the analysis. We have structured the theoretical
discussion into three sections: 1) Combinatorial innovation; 2) Networks, knowledge
and structural holes; 3) Virtual communities and knowledge sharing. On the basis of our
theoretical discussions, we wish to highlight key takeaways with the aim to place our
thesis in the context of these theoretical viewpoints, and to build a conceptual
foundation on which the forthcoming analysis will be conducted. Furthermore, we wish
outline how theory will be applied in the subsequent analysis (section 4.4). Given the
interdisciplinary nature our research and the scope of our thesis, we make reservations
as to how exhaustive the below theoretical discussion is, provided that we have
subjectively chosen theory and concepts.
4.1. Combinatorial Innovation The notion of combinatorial innovation provides an underlying understating of how and
where innovations emerge. It is widely recognised that innovation spurs technological
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advancements consequently leading to economic growth (Fleming and Sorensen, 2004,
McDaniel, 2000, Klevorick et al. 1993, etc.). According to Schumpeter (1934), innovation
can be understood as “new combinations of productive means,” (in Varian, 2003:1), that,
among others, includes the introduction of a new good. We know that innovation
involves a degree of novelty, however, what exactly is implied by novelty in this context?
Since Schumpeter, the science of ‘innovation’ has received the attention of numerous
scholars (e.g. Henderson; Utterback; Teece; Tushman; Forster; Christensen), all of which
helped define innovation (McDaniel, 2000). The novelty of innovations can be viewed
upon as relative to the overall technological frontier, as well as to the previous
experiences associated with the adoption of an innovation. Novelty thereby refers to the
application of a known technology to a new purpose (Abernathy & Clark, 1985; Afuah,
2004; Fleming & Sorensen, 2004). Afuah (2004) further states that an innovation can be
characterised as invention plus development and commercialization, ultimately opening
up for the recombination of existing technological components and processes -‐ a
combinatorial approach towards innovation (Fleming & Sorensen, 2004).
Re-‐combinations of technological components and processes can take various forms and
produce different results. Freeman and Soete elaborated upon the impact innovations
have, as certain innovations “…involve big changes and discontinuities (‘radical’ innovations)
and others involve many small improvements (‘incremental’ innovations),” (1997:21-‐22). The
notion of combinatorial innovation not only refers to large recombinations of
components but also that smaller alternations in fact can have an impact on the
technological advancement that follows, as well as by spanning way for a transition of
what is perceived to be possible and achievable (Ibid.). Clarifying this idea, we draw
upon Fleming & Sorensen’s (2004) discussion of innovation as the novel
reconfigurations made to a given component or process, ultimately opening up for
technology, product or process advancement. In this thesis we acknowledge the
combinatorial view on how innovations emerge.
How can we understand the origin of combinatorial innovations? And furthermore,
under which circumstances do they arise? Many scholars have sought to provide
insights to this by drawing upon the processes that support the emergence of
combinatorial innovations. In the following, we have identified a number of theoretical
constructs that we find useful in highlighting the notion of combinatorial innovation,
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and how they apply in the context of our research. Here we take point of departure in
the concepts of the linear model and the chain-‐linked model in highlighting the
importance of science in supporting innovative activities within science-‐based firms. We
then bring in the concepts of exploitation and exploration, and that of ambidexterity to
assess the degree to which NZ is in a position to engage in and incorporate a more
explorative approach in its aim to enhance innovative capacity.
4.1.1. The linear-‐ and the chain-‐linked model -‐ The role of science and innovations Within the fields of innovation management and organisational learning, the notion of a
strong link between scientific progress, technological change and overall economic
development has been emphasised (Bush, 1945; Furnas, 1948; Fleming & Sorensen,
2004). Technological change has furthermore been argued to have an impact on the
competitive structure of many industries, where technological advancements have
driven the growth of industries. As a result industry players non-‐responsive of
technological change and the potential it holds are pushed out of the market (Ernst,
2003). Bush (1945) also emphasises that technological advancements, (i.e. new
products, processes, new industries, etc.) would not come about if it were not for a
deeper understanding and an extensive knowledge-‐base of the laws of nature and the
application of such for practical purposes: “We will not get ahead unless we offer new and more attractive and cheaper products…The answer is clear. There must be a stream of new
scientific knowledge to turn the wheels…” (Bush, 1945: chp.3.5). The focus of Bush’s (1945)
statement is on how to ensure economic development at the societal level and he
emphasises the importance of scientific research that is performed without emphasis on
practical or applied ends. This results in general knowledge and an underlying
understanding of nature and its laws, ranging across scientific fields (Bush, 1945;
Balconi et al, 2010). The findings from conducting basic science are said to substantiate,
and feed into, applied scientific research, thereby supporting the search for a complete
solution that results in a practical application (Ibid). The distinction between basic and
applied science is of importance in understanding the contributions of each, as well as
understanding the interlocked relationship between the two. Bush emphasises that
applied science would eventually stagnate if basic scientific research was neglected
(Ibid). In context of our thesis we find the basic-‐ vs. applied science dichotomy is useful
for understanding the importance of facilitating unguided search for scientific
opportunities as part of NZ’ ambition to enhance its innovative capacity.
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Below, the linear model and the chain-‐linked model are outlined and discussed. We find it
important to distinguish that the unit of analysis of the two models is quite different,
where the former takes a societal level unit of analysis and the latter takes the
organisation. By juxtaposing the two models we enhance our understanding of firm’s
innovation model. In the context of NZ, we wish to understand to which degree its
internal R&D organisation can be characterised according to the chain-‐linked model.
Furthermore, through understanding the underlying thoughts behind the linear model,
we wish to assess the potential to expand NZ’ current innovation model given insights
provided by the linear model.
Figure 4.1. The linear model
Source: Bush, 1949
Bush (1949) and Furnas (1948) are considered the founding fathers behind the linear
model of innovation (Balconi et al., 2010). The linear model (LM) illustrates the process
of innovation moving from research to marketing (Bush, 1949), or from exploratory and
fundamental research to sales (Furnas, 1948) (see figure 4.1). The LM has been applied
as an influential tool in a broad range of circumstances, such as academics lobbying for
research funds or economists providing expert assertions for governmental policy-‐
makers, justifying financial support for science through the application of the model
(Godin, 2005).
Despite the influential role the linear model of innovation has had, it has stirred much
criticism over the past 50 years. Many scholars proclaim that the linear model
disregards the actual reality of an innovation process. The grounds for such critique
relate to numerous studies that show that the process of innovation is “not smooth nor
linear, nor often well behaved”, implying that the LM is an over-‐simplification of a rather
complex process (Kline & Rosenberg, 1986:285). Kline and Rosenberg (1986) called the
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linear model into question and introduced the chain-‐linked model as an alternative
model for illustrating an innovation process.
Figure 4.2. The chain-‐linked model
(Source: Kline and Rosenberg, 1986)
They state that the main concerns that the linear model presents is the lack of feedback
loops and the impact on the process of innovating. The process of innovation is in many
cases unforeseeable and characterised by a high degree of uncertainty, may that be
technical, functional or market uncertainty. Radical innovation processes are said to
thrive in environments that allow for the influence of multiple sources of information.
Incremental innovation thrives best where iterative processes open up for new learning
and development, thereby emphasizing the importance of such feedback loops in the
either innovation process (Kline and Rosenberg, 1986). As such feedback loops and
external pieces of information are important drivers for the innovation process:
“innovation in this substance frequently occurs in the processes for producing them –
recombination of existing manufacturing steps” (Fleming & Sorensen, 2004:910). Kline and
Rosenberg (1986) indicate that the linear model, where the completion of one-‐step
ultimately leads to the initiation of the next step, has difficulty in supporting drivers of
innovation.
However, it becomes questionable whether the critique of the LM is in fact valid,
especially if we take a historical perspective of the LM to shed light on what the actual
origin and objective of the model was. The LM was originally designed to support
governments in their pursuit to enhance the economic development after the Second
World War (Bush, 1945). It states that basic or fundamental scientific research is the
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main and unique source of knowledge for technical innovations hence economic growth,
and the underlying idea takes point of departure in the distinction between basic and
applied scientific research. Private, profit-‐driven organisations are said to lack
motivations for engaging in basic science. Bush stated that it was the responsibility of
the government to ensure that basic scientific research would flourish, and that public
funding would be the driver for such (Balconi et al., 2010), hence he introduced the LM.
However, by direct comparison of the two models we learn that the unit of analysis for
each model is notably different. The chain-‐linked model emphases the innovation
process within a firm, i.e. an innovation process that is characterised by an applied
scientific research approach: technological-‐, application-‐ and industrial oriented
research. The linear model, however, does not refer to the daily processes of
incremental learning and development at the firm level. It looks into the role of science
in enhancing the long-‐term developments of the economy, with particular focus on
science-‐based industries (Bush, 1949; Furnas, 1949). Moreover, it takes a long-‐term
perspective as its unit of analysis; the process of innovation cannot be viewed upon as a
“generalised co-‐occurrence of concomitant tasks” (Balconi et al., 2010:8). In the light of this
thesis, we wish to highlight the importance of distinguishing between the two models
given that the chain-‐linked model does not adequately recognize the importance of pure
basic science, providing important insights that highlight the actual scope of R&D
activities at Novozymes I.e. by understanding science as something that can be
consulted iteratively throughout an innovation process, hence guided by the questions
that arise in that very process, the inventor inherently will suffer from ‘inculcation11 of
the mind’. In other words, the idea behind ‘pure’ science in the discovery of new
knowledge is that “…it is not contaminated by any other value than those relating to the
acquisition of knowledge” (Raucek, 1971:306).
The process of innovation is complex, however, a distinction between basic and applied
scientific research provides insights to the value that can be gained from understanding
the innovation process as provided by the linear model and the chain linked model.
There is furthermore an interconnectedness between basic and applied science; the
success of firm-‐level exploitation strategies might well depend upon population-‐level
investments in exploration strategies (Balconi et al., 2010). It first becomes valid to ask 11 To impress (something) upon the mind of another by frequent instruction and repetition or indoctrination (The Online Dictionary, 2011)
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to which degree can a firm engage in or establish its own explorative strategies as a
supplement to prevailing exploitative strategies already in place within a firm? In the
forthcoming analysis we aim to elaborate upon the above, through assessing the degree
to which NZ can simultaneously engage in both exploitation-‐level strategies and
exploration-‐level strategies. In pursuit to gain insight to this, the following section
addresses the notion of exploitation and exploration.
4.1.2. Exploitation and Exploration Whether the goal is to take advantage of internal knowledge and developments or to
search for inputs from more distant sources, potentially across disciplines, the concepts
of exploitation and exploration provide valuable insight to the ways in which inventors,
organisations, etc. can engage in such search processes (March, 1991; Fleming and
Sorensen, 2004). In the context of this thesis, the concepts will assist in shedding light
upon the nature of the R&D activities at Novozymes (NZ). Through understanding the
structure of the R&D activities we are able to assess the degree to which NZ is engaging
in exploitation-‐ versus exploration-‐oriented activities, and more importantly the affect
this has on the overall innovative capacity of the firm in light of its aim to expand the
overall enzyme market globally.
According to March exploitation covers elements of search such as refinement, choice,
production, efficiency, selection, implementation, and execution (1991:71). Fleming and
Sorensen (2004) refer to this type of activity as local search. Here the emergence of
input to the innovation process comes from the incremental changes that are made to
one component at a time, either through reconfiguration or replacement of a given
component (Ibid.). The term local indicates that developments are based upon previous
research activities and developments that have taken place, thereby exhausting only the
potential possibilities that lie right in front of the inventor. The benefit of local search is
the possibility to take full advantage of prior research. It also provides the inventor with
a higher degree of reliability in the innovation process drawing on past insights to what
and what does not, act as valuable information in the process of future exploitations
(Fleming & Sorensen, 2004). However, the downside of exploitation is known as
cognitive bias, i.e. by focusing only on familiar components and combinations the
inventor refrains from investigating more distant and potentially more valuable sources
of input. The iteration of exploitation processes can result in a decrease of variability of
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outcomes, hence slowing down the advancement of innovation as local search
combinations are exhausted over time (Ibid.).
To overcome such cognitive bias, the concept of exploration provides valuable insights.
March states that, different from exploitation, exploration covers elements of search that
indicates variation, risk taking, experimentation, flexibility and discovery (1991:71). The
exploration of new possibilities in an innovation process can provide insights beyond
what local search can open up for. Although exploration can lead to less certain and
systematic inputs as compared to exploitation it can still be of great value, as exploration
leads to inputs that are more distant (March, 1991), thus providing insights to
disciplines that hold potential to produce more novel combinations.
4.1.3. The Ambidexterity Hypothesis
As outlined above, two broad types of qualitatively different learning activities between
which firms divide attention and resources -‐ exploration and exploitation -‐ have been
proposed in the literature (Van de Ven 1996, March 1991). Many studies have shown
that exploration and exploitation require substantially different structures, processes,
strategies, capabilities, and cultures to pursue and may have different impacts on firm
adaptation and performance (e.g. Holmqvist, 2004; Van den Bosch et al. 1999; He &
Wong, 2004). In general, exploration is said to be associated with organic structures,
loosely coupled systems, improvisation, autonomy, and emerging technologies.
Exploitation on the other hand has been referred to relate to mechanistic/bureaucratic
structures, tightly coupled systems, path dependence, routinization, control and
bureaucracy, and stable markets and technologies (Ancona et al. 2001; Brown &
Eisenhardt 1998; He & Wong, 2004). To capture the capacity of managing both these
activities Tushman and O’Reilly (1996) introduced the premise of ambidexterity, which
suggest that firms needs to that firms need to achieve a “balance” between the two to
achieve superior performance. The notion of ambidexterity signifies a firm’s ability to
operate complex organisational designs that provide for short-‐tem efficiency and long-‐
term innovation (Ibid.). Essentially, the two activates compete for firms’ scarce
resources, resulting in the need for firms to manage the trade-‐offs between the two (He
& Wong, 2004). As argued by Levinthal and March, “The basic problem confronting an
organization is to engage in sufficient exploitation to ensure its current viability and, at the same
time, to devote enough energy to exploration to ensure its future viability” (1993:105). Tushman
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and O’Reilly (1996) use the “juggler” metaphor to describe an ambidextrous firm that
has the capabilities to both compete in mature markets (where cost, efficiency, and
incremental innovation are critical) and develop new products and services for
emerging markets (where experimentation, speed, and flexibility are critical); in other
words to exploit and explore simultaneously. The ambidexterity hypothesis can also be
found in between the lines of Eisenhardt and Martin (2000) who propose that dynamic
capabilities require a blend of both the logic of exploration and exploitation.
In this paper we take a particular focus on innovation processes, and Ancona et al.
argued that dynamic capabilities “are rooted in different streams of innovation—in
simultaneously exploiting and exploring” (2001:658). The literature further highlights that
adopting only one of these methods of innovation would produce insufficient results due
to the shortcomings of each. What is characterised as being good and valuable in the
long-‐term may not be good in the short-‐term and vice verse (March, 1991). This is
elaborated on in Tushman, Anderson & O’Reilly (1997) stating that firm’s face
difficulties in extending their existing competences to develop innovations that would
create new markets. In this light we infer that firms may benefit from separating
activities relating to incremental-‐ and radical innovation respectively.
In this thesis, we employ the notion of ambidexterity to highlight a lacking focus on
explorative R&D activities of our case company. Moreover, we seek to assess the
potential of a virtual community to act as a vehicle for explorative unguided scientific
search without interfering with current R&D practices. In other words, we explore to
what extent a virtual community can make way for an ambidextrous innovation model.
To our knowledge, this is the first study that links the construct of ambidexterity to
virtual community and innovative performance.
4.1.4. Combinatorial Innovation: Models and application of theory Many parallels can be drawn between the concepts discussed up until now. The
concepts of exploitation and exploration are deeply rooted in the discussion of basic
versus applied scientific research, and of the linear model versus the chain-‐linked model.
In the context of exploitation, we therefore recognize a link between the chain-‐linked
model and applied scientific research. We furthermore see an opportunity to congregate
the concepts of exploration, the linear model and the value of basic science. The notions
of exploration and distant search, i.e. gaining input from basic science and cross-‐
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disciplinary interactions (March, 1991; Fleming & Sorensen, 2004), provides insights to
how a firm can benefit from external sources of knowledge. We infer that the optimal
solution is a combination of both exploitation and exploration, referred to as the
dynamic organizational capability of ambidexterity. In the forthcoming analysis, we
wish to apply these notions and concepts to the case of NZ. Here we emphasize three
models that well capture the notion of combinatorial innovation to help analyze NZ’
R&D activities.
1. The Long Tail of R&D
The long tail of R&D provides an indication of the scope and scale of an organization’s
R&D activities (see figure 4.3). Along the y-‐axis we find the total amount of capabilities
that an organization is able to leverage relative to how cross-‐disciplinary the
organization’s activities are. I.e. the further out on the x-‐axis you move the higher the
degree of cross-‐disciplinary capabilities is captured by the organization. The columns
along the x-‐axis indicate this degree of multi-‐disciplinary engagement of the firm:
• Internal R&D: In-‐house R&D capabilities in targeted disciplines
• External Collaborations: include key customer-‐ and university collaborations
• Multi-‐disciplinary networks: Capabilities leveraged across a broad number of
previously untargeted disciplines
• Unusual Suspects: Unanticipated valuable input found across non-‐targeted
disciplines
• Figure 4.3: The Long Tail of R&D
Source: Own Model (Inspiration: The Long Tail, Anderson 2004)
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However, due to obstacles to ambidexterity, many firms fail to leverage multi-‐
disciplinary networks and reach out to unusual suspects, to the detriment of more
explorative driven innovation. The model highlights a negative relationship between
depth and scope of the disciplines that a firm leverages and can be understood as the
trade-‐off in balancing exploitation and exploration as pointed out in ambidexterity
literature. By the same token, ambidextrous firms are able to manage capabilities
available across the long tail hence a firm is to be understood as encompassing a range
of the activities on the x-‐axis, as opposed to a simply point on the curve. In the
subsequent analysis, we apply the Long Tail of R&D to map the scope of Novozymes
exploitative vs. explorative activities. The goal is to define NZ’ innovation model and
assess how diverse NZ is given the disciplines leveraged.
2. The external sourcing continuum
An adapted version of the external sourcing continuum introduced by Nambisan &
Sawhney (2007) is outlined below (figure 4.4). The model suggests that firms can “shop”
for innovations ranging from raw ideas to market-‐ready products. The continuum
highlights that there are both benefits as well as trade-‐offs at either end of the
continuum: sourcing for raw ideas takes an explorative focus and provides a company
with a higher degree of reach, i.e. the number of options available, however, it also
implies a higher degree of risk and uncertainty. Sourcing for market-‐ready products
takes an exploitative focus on the refinement of product solutions with a high speed to
market.
Figure 4.4: The External Sourcing Continuum
Source: Adapted model, Nambisan & Sawhney, 2007
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We propose that focus on applied science, incremental innovation and local search leads
to “shopping” for market-‐ready products at the innovation bazaar, whereas basic
science, radical innovation and distant search result in more raw ideas.
In the forthcoming analysis, we would like to shed light upon this trade-‐off and this
model helps to concretize the dynamic interplay between focus and scope that any
innovation model struggles to balance. We will use this model as part of multi-‐pronged
framework to illustrate the extent of external knowledge sourcing of our case-‐company
and the opportunities that lie in utilizing a virtual community as tool to align
exploitation and exploration.
3. The Chain-‐Linked vs. Linear Gamut
The linear model provides insights to how basic scientific research can be of value for a
science-‐based firm in fuelling applied research activities. We infer that there lies value in
taking basic-‐scientific/linear model approach as complement to applied
scientific/chain-‐linked model reasoning (figure 4.5). In the analysis, we draw upon the
findings of the linear model of innovation and the chain-‐linked model of innovation, and
assess how these provide insights for understanding the advantages and shortcomings
NZ’ current innovation model. More specifically, we investigate the extent to which the
market-‐orientation of the chain linked model inhibits NZ’ to develop novel combinations,
and whether following the reasoning behind the linear model can open up for new front-‐
loading of opportunities to the current R&D organization at NZ.
Figure 4.5: The chain-‐linked vs. linear model gamut
Source: Own Model
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4.2 Networks, Knowledge and Structural Holes In this section we bring in the notion of networks and structural holes to the theoretical
discussion. In the above section, a number of theoretical constructs have been addressed
as to shed light on the important interplay between basic and applied science, the
process of innovation, and the tradeoff in scope between exploitative and explorative
R&D activities. The network perspective provides important insights that help us to
understand and substantiate the rationale for why Novozymes should engage in external
knowledge sourcing. A thorough understanding of how the social structures of networks
are organized, we are furthermore able to emphasize the value that can be gained from
bridging network structures, which thus opens up for the potential to grasp novel inputs
for combinatorial innovations. The concept of brokerage becomes increasingly
important in this context, as we propose that the virtual community can facilitate the
brokerage of different network structures, a notion that will be elaborated upon in the
sequential section.
In Lahkani and Panetta (2007) principles of distributed innovation is explored,
suggesting that R&D labs can benefit from seizing opportunities residing across
networks external to the organization. The idea is based on Benbya & Belbaly in
postulating that “…knowledge is unevenly distributed in society, and that centralized models for
economic planning and coordination are prone to failure due to an inability to aggregate this
distributed knowledge” (2007:7). We expand Benbya and Belbaly’s notion to suggest that
due to the prerequisite of economic planning of R&D activities in profit oriented science-‐
based firms, such firms generally fail to embrace the full range of distributed knowledge
available to them. In the high-‐tech industry the notion of Joe’s law is prevalent:
“No matter who you are, most of the smartest people work for someone else” (Lahkani & Panetta,
2007:97). Thus, provided that potentially valuable knowledge resides across individuals
and networks outside the boundaries of any organization, taking a network perspective
becomes a critical element in understanding how to best get access to such pools of
knowledge. Essentially, the network dimension of this paper constitute the intersection
between the theoretical constructs previously outlined in the theory section and the
notion of a virtual community in acting as knowledge broker and catalyst for external
knowledge sourcing.
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In this section we will focus on the concept of networks, structural holes and brokerage
of structural holes (Burt, 1992). To set the foundation in which the remaining discussion
takes point of departure, we begin with a short discussion on the notion of networks,
where the concepts of open and closed network structures is emphasized. Sequentially
we introduce the notion of structural holes that leads to a discussion of the
opportunities and implications to be found, and which affect this can have on innovation.
The aim is to highlight the obstacles and opportunities that arise from structural holes.
4.2.1. The Social Structure of Networks
The notion of social networks has attracted much attention over the past decades from
both the fields of social and behavioral science (Wasserman and Faust, 1994). Building
upon the sociological ideas of Simmel (1955) and Merton (1968), scholars have explored
the concepts of networks, looking into the structure of ties between individuals,
organisations and communities (Granovetter, 1973); the centrality of betweenness
(Freeman, 1977); the power of having exclusive exchange partners (Cook and Emerson,
1978); and the structural autonomy that is created by network complexity (Burt, 1980).
The social network analysis approach also has deep ties within network theory, as it
assumes the importance of relationships between agents. It refers to a set of actors (also
called 'nodes') who are tied to one another through social relations, and therefore takes
point of departure in the relationships that arise among entities, and on the patterns and
interactions of such relationships (Wellman & Berkomitz, 1988). Scholars have
recognized the benefits of applying a social network perspective in leveraging new
insights to standard social and behavioral questions within the fields of political,
economic, or social structural environment (Wasserman & Faust, 1994).
4.2.1.1 Closed versus Open Networks Burt (1997) categorises a number of network benefits according to three main
elements: firstly, a network’s ability to provide an individual with access to information
beyond what he/she could possess alone; secondly, it provides such information early,
which can be advantageous in being the first to act upon it; finally, the network allows
for referral benefits, meaning that the information received through a network is often
considered more reliable as it comes from a credited source (Ibid.). However, it becomes
questionable under which circumstances such ‘information benefits’ are viable. As we
shall see, depending upon the characteristics of the network, and the extent to which it
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is closed or open, ultimately has an impact on the information benefits to be reaped
from the network (Burt, 1997).
In the social network literature disputes have arisen over which network structure,
closed or open, appropriates the most benefits to the network (Ahuja, 2000). Closed
networks are characterized by strong mutual ties across entities, creating a homogenous
community where everyone knows everyone; the greater the network closure the more
interconnected the network. Coleman (1990) argues that networks with higher closure
generate high trust, which in turn facilitates cooperation. From Coleman’s (1988)
perspective, the optimal social structure of a network is thus one generated from
building dense, well-‐connected networks. Contrary to this, Burt’s (1992) perspective is
that constructing networks of disconnected nodes is the most optimal strategy.
Following this, Burt (1992, 2001) states that there are negative affects of closure: the
high degree of interconnectedness between the members in a closed network results in
the creation of norms in such network structures that make groups less heterogeneous,
thus constraining social behaviors. Burt (1997) goes so far as to say that the structure of
homogeneous closed networks are associated with a redundancy of information benefits,
i.e. no new information is infused into the network. This is echoed by Putman (2000)
who postulates that closed networks are great in helping its members get by, but not
ahead. Due to the homogeneity of the contacts in a closed network, knowledge revolves
within the network without gaining new insights and input to further challenge the
structure (Burt, 1992). Thus non-‐redundant contacts, i.e. unknown contacts and
knowledge can provide information benefits of value to the network itself (Granovetter,
1973; Burt, 1992). A valid remark here is that if a firm’s R&D activities have a strong
internal orientation, the organisation (network) may suffer from what Burt refers to as
redundant information benefits. In the context of this paper, the effect that network
structures (open vs. closed) may have on knowledge sourcing thus becomes important
to consider.
What is particularly interesting in the context of our thesis is the affect that the
characteristics of a network (open vs. closed) have on innovation of NZ’ R&D
organization, and the potential there lies in external sources and networks. Network
structures are said to have an impact on innovation, and it has been is found that small
homogenous communities more quickly introduce incremental improvements in
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technology (Lynn et al., 1994). Burt (2005) takes this point further in stating that closed
networks might actually work to inhibit innovation (Burt, 2005), while networks with
heterogeneous substructures will produce more radical innovations. NZ seeks to
enhance its innovative capacity through external knowledge sourcing, and therefore the
types of network structures that a virtual community aims to encompass is of
importance. Scholars suggest that open networks hold potential to produce more radical
innovations, and thus it becomes a motivating factor for the remaining discussion to
grasp how heterogeneity of networks and the bridging of networks can be a driver for
innovation.
4.2.2. Structural Holes
A generic research finding in sociology and social psychology is that information
circulates more within groups of people than in between groups of people (Lin et al.,
2001). In other words, in any kind of grouping or cluster of people, such as divisions,
industries and disciplines of research etc., information flows are more vigorous within
than across. This does not necessarily imply that people are not aware of what takes
place in other groups or networks, rather that they focus on the activities taking place in
their particular group, and simply attend less to the activities of people in other groups.
Information flows within groups are results of the cognitive constructs of the individuals
in that group, thereby curbed to fit the cognizance of that group. By the same token, new,
yet ‘unchallenged’ information will circulate more across groups that within, giving rise
to opportunities to emerge in between groups (Ibid.). This idea has been explored more
in depth through the conceptualization of structural holes and the opportunities that lie
in bridging structural holes.
Supporting arguments of the theory of structural holes draws upon network-‐related
theories emerging in the 1970’s. The term structural hole can be characterised as the
social gap between two groups (Parjanen et al., 2011); the weak connections between
clusters of densely connected individuals (Granovetter, 1973, 2005); and as the gaps
between non-‐redundant contacts (Burt, 1997). This element of disconnectedness, in
other words holes in the structure of the networks, may result in ignorance towards the
benefits that could be gained as assets and behaviours get locked in suboptimal
exchanges (Burt, 1980). Thus, potential benefits lie in identifying structural holes across
networks and in taking action in order to attempt to bridge them. In the forthcoming
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analysis, the research environment of our case company Novozymes (NZ) is analysed,
and we draw upon the concept of structural holes to highlight the rational for why NZ
stand to benefit from engaging in more cross-‐disciplinarily collaborations. In the
following we will review whether structural holes hold opportunities vis-‐à-‐vis
disadvantages, and which role ‘bridging’ and ‘closure’ plays in this respect.
4.2.3. Structural holes and opportunities in segmented networks
Following March’s (1991) idea of exploitation versus exploration, Fleming and
Sorensen’s (2004) notion of local versus distant search, and the notion of social
structures of networks, we come to understand that opportunities lie in distant and
more heterogeneous social structures of networks and that benefits can be reaped
through brokerage (Granovetter, 1974, Burt, 2001, Parjanen et al. 2011). However,
benefits of brokerage are not without limitations and we infer that it becomes vital to
ask: when are structural holes too distant for brokerage to provide fruitful results? In
other words, is there an optimal cognitive distance between structural holes? Following
Nooteboom we learn that “…outside sources of knowledge "require a "cognitive distance" which
is sufficiently small to allow for understanding but sufficiently large to yield non-‐redundant novel
knowledge" (2000: 72). Scholars argue that network structures should optimally hold a
mixture of brokerage and closure (Narayan, 1999). Brokerage of structural holes implies
the existence of brokerage function bridging relationships across heterogeneous actors.
On the other hand, network closure of structural holes results in creating trust and
stronger ties in between previously disconnected agents. There are strengths and
limitations of both closure and brokerage, but “…while brokerage ... is the source of added
value, closure can be critical to realizing [that] value' (Burt 2001:52).
Individuals who are accustomed to interacting with individuals across groups possess
an intuitive ability to accept alternative ways of thinking and behaving and are therefore
able to foresee potential opportunities that lie in bridging activities across various
groups. This notion builds upon fundamental ideas within sociology and economics and
as Adam Smith noted: “when the mind is employed about a variety of objects it is some how
expanded and enlarged.” (Smith, 1982:539). There lies great value in opening up for
discussions between different disciplinary areas, exposing them to means of being and
doing that is unfamiliar to them. Empirical studies further support this notion, as Burt
(2004) noted through an in-‐depth study of a French chemical giant Rhône-‐Poulenc,
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where the CEO stated that his scientists received great value for new ideas and products
from inputs provided to them from individuals of other disciplinary fields.
4.2.4. Brokerage and Innovation The above discussion sheds light upon the benefits that can be reaped from bridging
structural holes, in that new opportunities arise from connecting unknown areas of
interest, disciplines, etc. The impact that this has with regards to innovation is of due
importance in the context of the given thesis; the objective being to highlight the impact
that distant and unforeseen sources of external knowledge can have on the prevailing
innovation model of a science-‐based company such as Novozymes.
Scholars in innovation and organisational learning discourse has emphasised the
linkages and the outcome of collaborative networks as being the vehicle by which
organisations gain access to external information (Ahuja, 2000). The field of sociology
has long studied the relationship between network structures and innovation, however,
focusing more on the adaption and diffusion of innovation rather than the outcome of
network structures on the generation of innovation (Ibid.). Other scholars have paid
more attention in this area (Shan et al., 1994; Podolny & Stuart, 1995; Powell et al.,
1996). Areas that have been studied range from external factors determining whether
an innovation becomes a technological dead-‐end or if it serves as the basis for
subsequent innovations (Podolny & Stuart, 1995). Moreover, collaborative network
relationships are found positively correlated to innovation output (Shan et al., 1994).
The network perspective on innovation emphasises the importance of the connectivity
of heterogeneous groups of actors as well as the importance of exploring and exploiting
weak ties and structural holes (Parjanen et al., 2011). Networks rich in structural holes
open up for more opportunities for new combinations of knowledge and ideas, and we
thus infer that brokers, or the bridging of structural holes, support innovation by
connecting, recombining and transferring sources of information, knowledge or ideas
that would otherwise be disconnected (Burt, 2004.). Innovation primarily happens at
the boundaries between disciplines or specialisations, and it is therefore evident that
working across boundaries or distances is an important driver supporting innovation
(Parjanen et al., 2011). Hence, the notion of distance plays an important role whether we
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are talking about cognitive, communicative, organisational, social, cultural, functional or
geographical distance.
Figure 4.6: Bridging network structures across disciplines
Source: Own Model
4.2.5. Cognitive Distance
The concept of cognitive distance supports the notion of structural holes in that it
addresses the degree of “difference” across individuals or groups. Cognition is
developed in the interaction of the physical and social environment and it can be
identified based on prior knowledge, which “…confers an ability to recognize the value of new
information, assimilate it, and apply it to commercial ends” (Cohen & Levinthal, 1990:128).
Following Simon (2000:33), “…cognitive capabilities of human agents are bounded by… the
limits imposed by the frames of reference, value systems and modes of symbolic representation
prevailing in the epistemic communities to which they belong”. This highlights the idea that in-‐
group idiosyncrasies may constrain the cognitive capacity of the group. Nooteboom et al.
(2005) state that the term cognitive in this sense denotes a broad range of mental
activity, perception, sense making, categorization, inference, value judgments, emotions,
and feelings, which all build on each other. Furthermore, as different categories of
cognitive meaning are constructed through the experiences that follow individuals, it is
inferred that individuals inherently interpret, understand and evaluate their
surroundings differently (Nooteboom et al., 2005:3).
Oberoi and Saviotti (2010) introduced the notion of cognitive distance to denote the
dissimilarity in knowledge bases between firms. We thus infer that similarity of
knowledge bases would imply cognitive closeness, likely to prevail within homogenous
networks. The notion of cognitive distance can therefore be understood as the space in-‐
between social structures of networks characterized by structural holes. Conclusively,
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the diversity of ‘distance’ is to be considered a source of innovation (Harmaakorpi et al.,
2006). In the succeeding analysis (section 6.3.1) we elaborate upon the notion of
optimal distance between structural holes where we place NZ in this context.
4.2.6. Social Capital and Innovation The notion of social capital is a relevant topic to address in the light of this thesis. Given
that we take a network perspective to knowledge creation, the ways in which value is
created by means of relationships becomes a central issue. Moreover, the concept of
social capital can help us to better understand how, and under what premises,
information is shared and knowledge is created. We find that the value of social capital
for knowledge creation is not as straightforward as most authors propose; rather the
value is contingent on context and the type of knowledge one intends to produce. We
come to question if novel combinations (radical innovation) derive benefit from high
social capital, or if in fact the lack of high social capital makes way for this type of
innovation to emerge.
Over the two past decades ‘social capital’ is notably the most successful concept
exported from sociology to other social sciences and to the public discourse (Portes,
2000). Social capital has often been used to address how interpersonal relations can
improve community life and solve social problems. It is a relational asset that exists
across people in a given group, community, organization or society, and that by means of
fostering trust, mutual obligation and cooperation becomes the mortar of civic
engagement (Nelson et al., 2003). I.e., when social capital is high, people feel empathy
with one another and sense of belonging, and they take on responsibilities and
motivation for solving problems (Ibid.).
Social capital represents the gains to an individual, a group of people, or a community,
acquired from the establishment of relations with other individuals or groups. This has
been captured eloquently by Portes: “…whereas economic capital is in people's bank accounts
and human capital is inside their heads, social capital inheres in the structure of their relationships”
(1998:7). Social capital is created when a relationship is established, and appreciates
over the course of repeated interaction (Ibid.). Most scholars agree that social capital
value surplus accrue to both the individual and the collective. Bourdeiue & Wacquant,
define social capital as “…the sum of resources, actual or virtual, that accrue to an individual or
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group by virtue of possessing a durable network of more or less institutionalized relationships of
mutual acquaintance and recognition” (1992:119).
Social capital: a liability or a virtue? Most literature addressing the notion of social capital seem to praise the emergence of
social capital, and point out a strong positive relationship between social capital and
knowledge creation (Canella & McFayden, 2004). However, high degrees of social capital
have also been seen as a constraint for knowledge creation and innovation.
Interpersonal networks can, over time, produce strong norms and mutual identification
among network members, thus limiting openness to new information and diverse views.
Burt (2001) for example, claims that when high social capital is realized by a group,
norms emerge from such network structures making the group less heterogeneous, thus
constraining social behavior -‐ which from a business perspective can be understood as
inhibiting the innovative capacity of the group. This is echoed by Gabbey & Leenders in
proposing: “When networks are too durable they may yield obstacles for novel combinations of
radical innovation” (2001:203). Nooteboom (1999) recognizes that in the light of radical
innovation (exploration of novel combinations) systemic linkages are not required. In
other words, with novel combination, strong social ties (i.e. high social capital) become a
liability rather than a virtue. Following Lynn et al. (1994), small homogenous
communities are said to more quickly introduce incremental improvements in
technology while innovation communities with more heterogeneous substructures will
produce more radical innovations. This suggests that the value of social capital is
contingent on the circumstances in which knowledge is created, and more importantly,
on the objective of the specific collaborative exertion. In other words, the value that
accrues to a network aimed to produce novel combinations (radical innovation) might
become depressed at expense of high social capital. Walker et al. captures these two
facets of social capital: “Social capital is a means of enforcing norms and behaviour of
individuals or corporate actors and thus acts as constraint as well as a resource.” (1997:111).
From the above, we understand that social capital can be both a virtue and a liability for
a given innovation process, and drawing on this we add depth to our understanding of
network structures and its affect on the outcome of radical vs. incremental innovations.
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4.3. Virtual Communities and Knowledge Sourcing The structure of networks provides an indication of the opportunities that lie in bridging
structural holes and distant sources of knowledge. We have shown that the structure of
networks is essential for the way in which knowledge can be shared. In the following we
highlight structural characteristics of “virtual” networks, and move on to suggest that as
a result of the properties of a virtual community, it holds the potential to broker
structural holes and distant sources of knowledge. Drawing upon findings of
combinatorial innovations, networks and structural holes, we wish to illustrate how a
virtual community can act to enhance the innovative capacity of Novozymes.
The distance between networks, structural holes and sources of knowledge may come in
different forms such as cognitive, communicative, organisational, functional, social or
cultural. Often the distances are so great that a special brokerage function is needed – a
means by which information exchange and translation can take place between structural
holes (Burt, 2004). In the context of this thesis, we propose that such a special brokerage
function can be facilitated through the means of virtual community, and we introduce
the concept of a virtual innovation broker. We thus proceed to discuss the nature of
information exchange and knowledge sourcing in the context of a virtual community set-‐
up.
4.3.1. Knowledge Sharing and Information Exchange in ‘virtual worlds’
To locate expertise and knowledge sources to solve problems is often a social and
collaborative endeavor (Bian et al., 2008). While performing an online search (using e.g.
‘Goolge.com’) sometimes is an efficient way to answer a particular question, today’s
search engines are not capable of answering queries that require deep semantic
understanding of the query or the document in question (Ibid). Hence, asking a person is
often the only way to get a satisfying answer. One good place to start is then to review
ones own professional network in hope of leads that provide a solution, but sometimes
the right source of knowledge lies beyond the reach and grasp of one’s own network and
‘resources’. The proliferation of online communities and interactive places for
collaboration hold the potential to extend the scope and access to relevant knowledge
sources available to an individual or organization. Virtual communities enable new
levels of interactions and interconnections among individuals, documents and data, and
have become places for people to seek and share expertise (Zhang & Ackerman, 2005).
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In order to understand how a VC can act as vehicle for external knowledge sourcing,
information exchange and knowledge sharing become important elements to consider.
Researchers have recently positioned social capital as a key factor for understanding
knowledge creation (Nahapiet & Ghoshal, 1998). Here, one important question to
consider is: Why does someone choose to share information or knowledge with
somebody else? Two main rationales or logics come to mind, positioned at two extremes
of a spectrum. First, take the barter economy logic: a pragmatic view of exchange where
an information package is shared in between two individuals just as any other good on a
market, but it is not paid for with money but with the exchange of another good (piece of
information). In the case that interaction repeats itself, a social relationship might
emerge allowing for a social logic to guide the forthcoming exchange. Here, principles of
trust, mutual reciprocity and norms of action allow for information and knowledge to be
exchanged based on principles of social life, as opposed to principles of market exchange
(Bullen, 2007). The two logics of information exchange suggest that information and
knowledge can be shared in both the presence and absence of social capital, but the
characteristics of the exchange is inherently different. The previous point made
regarding the liability of high social capital also bears relevance when addressing
information exchange. We infer that in the absence of social capital, information
exchange follows a more mechanistic/market logic whereas high social capital results in
a more spontaneous exchange following a social logic. Yet, we have learned that high
social capital may run the risk of hampering novel combination to emerge from the
exchange due to the formation of norms and constraints in social behaviour as a result
of group dynamics (Burt, 2001). Thus, there seems to be a trade-‐off between high vs.
low social capital, where the optimal level seems to be balanced level, i.e. neither too
high nor too low, as it fosters an exchange of information that supports the emergence of
both incremental and radical innovations.
4.4. Theoretical synthesis and application In the above discussion a broad number of concepts and theoretical constructs are
introduced and revised, each representing particular dimensions of our topic of research.
Across these concepts we have identified subtle analogies that suggest a relationship in
the context of networks and innovation. We find that many of these, given their
dichotomous nature, can be bifurcated onto a continuum (figure 4.7).
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Exploitation Local Search
Low Cognitive Distance Closed Networks Closure / Bonding High Social Capital
Incremental Innovation
Exploration Distant Search
High Cognitive Distance Open Networks
Brokerage / Bridging Low Social Capital Radical Innovation
Figure 4.7: Conceptual dichotomy continuum
We find support in Binz-‐Scharf for our claim that exploration and exploitation can be
placed on a continuum and that certain network structures are better suited for each of
the two: “exploration and exploitation…move along a continuum…given by the configuration of
ties in the networks employed. The network is sparse in the exploration phase and dense in the
exploitation phase, corresponding to weak ties during exploration and strong ties during
exploitation” (2003:8). We also infer that the above spectrum falls under the umbrella of
ambidexterity theory, where the balance of each dimension comprises an essential
element for a firm to be ambidextrous. It is at the intersection of the concepts outlined in
figure 4.7, combined with the phenomenon of virtual communities, that the concept of
the virtual innovation broker emerges. Thus, one important contribution of this thesis is
to highlight the utility of virtual communities for science-‐based firm for external
knowledge sourcing, in the light of the relationship between the aforementioned
theoretical constructs. In addition, we find that the models we employ in the subsequent
analysis share a similar pattern. Below we introduce three models that guide us in our
analysis.
Drawing on literature, we understand that firms often find themselves in cognitive traps
in which strong profit-‐orientation may induce firms to persist excessively in the use of
procedures and actions associated with success in the past (March & Levinthal, 1993).
This often leads firms into sub-‐optimal exploitative strategies that impede the
emergence of innovation of a radical nature. One objective of the first part of the analysis
is to analyse to which extent our case company, NZ, is trapped in such sub-‐optimal
exploitative strategies. In doing so, we employ the Long Tail of R&D where we analyse
the external scope of NZ’ current innovation model (see point 1, figure 4.8). Moreover,
although we postulate that firms should be explorative in their R&D strategies, we also
find evidence in the literature suggesting that there is a limit to the value of distant
sources (e.g. Nooteboom et al., 2005).
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Figure 4.8 Elements of External Knowledge Sourcing
1. The Long Tail of R&D
2. Optimal Scope Continuum
3. Ambidexterity trough a virtual innovation broker
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This leads us to hypothesize that there is an inverted U-‐shaped relationship between
cognitive-‐, disciplinary-‐ and organisational distance and the degree of valuable input for
radical innovation (see point 2, figure 4.8). Moreover, from the ambidexterity literature
we know that activities relating to the extremes of the continuum (figure 4.7) are often
difficult to combine. In other words, firms often lack the organisational capabilities
enabling a simultaneous focus on exploitative and explorative strategies. It is in this light
that we in the second part of the analysis introduce and apply the concept of the virtual
innovation broker and propose that it can act as a bridge between NZ’ R&D organisation
and more distant sources in the external environment (see point 3, figure 4.8). In sum,
the first illustration places our case company NZ in the context of external knowledge;
the second illustration highlights that resource heterogeneity is valuable, but only to a
certain degree; the third shows that it is not only a matter of scope but also of balancing
exploitation and exploration, and that this can potentially be achieved by means of a
virtual innovation broker.
Given that the second and third part of the forthcoming analysis is of a conceptual
nature, with point of departure in theory and literature, additional theoretical
constructs and how they are applied will be introduced there and then as we see fit.
5. Novozymes -‐ Case Company Profile Novozymes (NZ) is a biotechnology-‐based company headquartered in Copenhagen,
Denmark. The company was founded in 2000 as a result of a de-‐merger12 with Novo
Nordisk, a world leading pharmaceutical company. NZ’ core business areas are
industrial enzymes (94%), microorganisms (4%) and biopharmaceuticals (2%) (Annual
Report 2010). NZ’ products are used in a broad range of process industries including
agriculture, bioenergy, food & beverages, household care, leather, pulp & paper, textiles
and wastewater solutions (NZ Corporate Website, 2011). In large tanks inside the
laboratories of NZ, tiny enzymes are produced using microbiological processes and
fermentation technology. Sustainability lies at the heart of NZ’ business agenda, and
since sustainable solutions have become acknowledged to make sound business sense
by other businesses, NZ profits from delivering green solutions ultimately reducing
energy consumption and climate impact of its customers. NZ is well recognized, both by
12 The split was aimed to bring about a stronger focus on the emerging business of industrial enzymes.
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the general public due to its green profile, as well as by its customers. In 2010 NZ helped
customers reduce CO2 emission by 40 million tons. Furthermore, the company has
received a number of acknowledgements and rewards: Dow Jones named NZ the
sustainability sector leader in the biotech area and Procter & Gamble appointed NZ its
“Supplier of the Year” for the third year in a row out of more than 80,000 suppliers
(Annual Report 2010). NZ heavily relies on R&D and invests 14% of its turnover in R&D,
and out of its 5400 employees across 30 countries 16% work in R&D (Annual Report
2010). Correspondingly, a strong IPR and patenting strategy is exemplified by an
extensive patent portfolio of more than 6500 granted or pending patents (Annual
Report 2010). After the split with Novo Nordisk and becoming a separate company in
2000, Novozymes (NZ) has experienced steady growth rates. By 2010 NZ had a 47%
market share, compared with 43% in 2000. This makes NZ the world’s leading producer
of industrial enzymes, with generated sales of DKK 9,724 million and EBIT of DKK 2,117
million in 2010 (Annual Report 2010). Given the global economic slowdown, these
results are quite remarkable.
5.1. Novozymes R&D organization The R&D organization at NZ is structured around two functional areas: Applied
Discovery Unit (ADUs) and Molecular Biotechnology (MBs). The ADUs are structured in
divisions along each industrial application area such as textiles, food & beverage,
What is an Enzyme?
An enzyme is a protein that works as a catalyst in naturally occurring processes. Catalysis is defined as the acceleration of a chemical reaction by some substance, which itself undergoes no permanent chemical change. This means that once the biological process is complete, the enzymes are neither used up in the reaction nor do they appear as byproducts.
Enzymes are mostly found in microorganisms such as fungi and bacteria. These are then further developed to improve desired characteristics of the enzyme and prepare it for mass production.
There are a plethora of different enzymes, with highly varying characteristics. Some are good at “chopping up” dirt and fats, suitable for detergents, others prolong life of food, while yet others are specialized at “chopping” starch, helping the fermentation process in ethanol production. When used for industrial applications, enzymes can usually speed up production processes at a lower cost than chemicals due to reduced raw material and utility use.
Source: Novozymes Talent Search, 2011
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bioenergy, etc. (figure 5.1). The MBs on the other hand are expected to carry out, what
NZ characterizes as basic scientific research and act as a support function the ADUs in
the development of enzymes for each given application area.
Figure 5.1 Overview of R&D activities at Novozymes
Source: Own illustration
The MBs set up project groups that work within each application area, and based on
inquiry from the ADUs, the MBs return to the labs to improve or change characteristics
of the enzyme in question. Most work is centered on optimization and customization of
current products. Such activities include improving enzyme performance and stability
(e.g. to make enzymes in detergents work just as well in low temperatures); improve
process compatibility, i.e. how should the enzymes be applied; and reduce enzyme
production costs (SULO; TRMU, 2011).
A large share of product developments at NZ take place within the four walls of the
organization inside closed labs and protected by a strong IPR policy. Nevertheless, the
R&D organization at NZ has been recognized for its strong focus on external
collaborations (e.g. in Knudsen & Nielsen, 2008). NZ takes an active role in trying to be
more open, as stated on the company website: “One important means of staying ahead is
through mutually beneficial collaborations with universities and other partners around the
world.”13. The collaborative scope of NZ’ R&D efforts can be structured around the
following three activities:
13 http://www.novozymes.com/en/careers/students/how-‐we-‐work-‐with-‐universities/Pages/default.aspx
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• Internal R&D: A number of in-‐house R&D resources are leveraged. In 2009 the
Innovation Office was set up to manage the front-‐end pipeline across the company’s
businesses, and a number of interactive forums have been created. An intra-‐
organizational communication and connection tool has been set up to make way for
bringing together the company’s employees. Furthermore, a number of group
collaborations have been set up including: NZ' Radical Innovation Catalysts (RIC) and
cross-‐functional group collaboration for idea qualification.
• Strategic partnerships and key customer collaborations: NZ relies on development
projects carried out in close collaboration with external strategic partners as a part
of its growth strategy. Allying with partners in the research process is no longer only
an R&D related decision it is just as much a corporate strategic objective (Knudsen &
Nielsen, 2008).
• University Collaboration: Over the past decade a number of University collaborations
have been initiated by NZ in e.g. the United States, China, Brazil and Denmark. On the
company website it is stated that “By working so closely with universities we get fresh ideas
and talent that help us look into tomorrow to prepare industries for what’s coming”4.
5.2. Looming Challenges The long-‐term targets are set to an annual organic sales growth of 10%, an EBIT margin
of 20% and ROC of 22%, and future projections show that Novozymes (NZ) will hold
50% of the market in couple of years (Annual Report, 2010). Given the current market
situation these targets are to be considered ambitious. While NZ demonstrates an
impressive record, the future holds a new set of challenges that must be dealt with. After
studying the financial numbers more carefully we found that NZ has been outgrowing
the market over the past decade -‐ by a rate of 29%14 (appendix 3). In the long run this
implies that unless total market expansion accelerates, NZ has to grow at the expense of
current market assets, making it increasingly difficult to reach growth targets.
Furthermore, industry concentration is relatively low, with the presence of only a few
manufacturers able to cater to the needs of clients (Frost & Sullivan, 2009). In addition,
the industrial enzyme business is characterised by strong barriers of entry due to
expensive technology and the complex nature of enzyme producing technologies (Ibid.).
Competition is thereby moderate across most enzyme application areas; expect the
14 Novozymes growth divided by total market growth
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pharmaceutical enzyme market that is highly competitive. Competition is known to
grow markets, and in low concentration industries market growth is highly dependent
on the actions of a small set of competitors (Ibid.). Hence, measures taken by NZ to
ensure market growth are deemed vital for NZ in the future. In this light, innovation and
development of new industrial application areas for enzyme technologies becomes very
important strategic objectives for NZ. Technological change has been argued to have a
great impact on the competitive structure of many industries, where technological
advancements drive the growth of industries (Ernst, 2003). For NZ this calls for constant
development of new applications to meet growth targets, and it is deemed vital to move
beyond existing industries and application areas. NZ has been recognized for its strong
innovative capacity, yet, with future challenges comes greater pressure for pioneering
and radical innovation. As a response, NZ is investigating opportunities to increase its
scope of external knowledge sourcing in order to broaden its horizon in search for new
knowledge. In 2011, a new corporate value pillar was introduced: “Connect to create –
because the world is full of ideas” 15. Furthermore, a “we-‐know-‐it-‐all” corporate culture is
being called into question, which indicates a new direction in which the organization is
moving. NZ is progressively looking for ways in which it can ensure to explore external
sources of knowledge potentially valuable to the organization and the future of enzyme
business.
6. Analysis We conduct a three-‐pronged analysis that combines valuable insights to assist us in
exploring the identified problem statement: How can a virtual community facilitate
external knowledge sourcing so as to enhance the innovative capacity of Novozymes’ R&D
organization? We draw upon empirical evidence, as well as concepts, theory and
literature, as outlined in previous sections of the paper, to support our subsequent
claims and findings. For each part of the analysis a brief part-‐conclusion is outlined, to
be followed by our overall concluding remarks at the end of the analysis.
In the first part of the analysis we aim to gain an understanding of Novozymes current
innovation model and identify the extent and scope of its current R&D activities. Here,
we draw upon empirical findings from our in-‐depth interviews. We conclude that
15 http://www.novozymes.com/en/about-‐us/vision-‐and-‐values/touch-‐the-‐world/Pages/Our-‐values.aspx
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Novozymes’ innovation model is focused on the exploitation of known sources of
knowledge to the detriment of radical innovation. Ultimately we provide arguments for
why external knowledge sourcing hold potential to benefit the organization.
For the second part of the analysis, emphasis is placed on the concept of a virtual
community, where we develop a rationale behind establishing a research-‐based virtual
community for external knowledge sourcing. We highlight some enabling and inhibiting
properties of virtual communities for acting as a mechanism for unguided distant search
for scientific opportunities. Moreover, we develop the concept of a virtual innovation
broker to highlight that a virtual community holds potential to bridge structural holes.
Here we primarily make inference based on prevailing theory and literature, and also
include findings from an online survey. We conclude that a virtual innovation broker
theoretically holds potential to facilitate an explorative arm of NZ’ innovation model.
In the final part of the analysis we address the notion of scope in unguided search for
scientific opportunities. We bring in the notion of upper limits of ambidexterity and
place emphasis on implications of balancing exploitation vs. exploration-‐oriented R&D
activities in the light of the virtual community set-‐up. Here we suggest that the virtual
innovation broker holds potential to overcome a number of obstacles to ambidexterity
found in the literature. Here we predominantly employ prevailing theoretical constructs
highlighted in the theory section. We conclude that a VC can be viewed as an add-‐on to
NZ’ innovation model with the potential to expand innovation activities to become more
explorative, without harming current exploitative capabilities.
6.1. Part I -‐ Novozymes’ innovation model The objective of the first part of the analysis is to answer the first sub-‐question (Q1) of
the problem statement, namely: To what extent is the current innovation model at
Novozymes conducive for effective external knowledge sourcing? We take point of
departure in the R&D organisation at NZ and aim to identify how R&D activities are
structured with regards to research and new product development. A mapping of the
process of innovation at NZ is conducted, where we draw upon the notion of
combinatorial innovation, concepts of basic vs. applied scientific research and as well as
exploitation vs. exploration. We find that the R&D activities at NZ has a strong in-‐house
focus but also covers a number of external collaborations with key customers and
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universities. A mapping of these provides insights to the scope of NZ’ current innovation
activities transcending organizational boundaries of the firm. Drawing upon the notions
of market-‐pull and technology-‐push and its affect on innovation, the objective is to
address the balance of exploitative and explorative activities in the current process of
innovation.
A mapping of NZ innovation model covers three main focus areas assessed throughout
this section. We begin by looking into the transition that NZ’ R&D organization has gone
through over the past 20 years. This is done in order to illustrate how Novozymes has
moved from carrying out more explorative R&D activities to becoming more exploitative
over recent years. Before concluding on the model of innovation we assess how R&D
project groups are organised at Novozymes to shed light on the degree of cross-‐
disciplinary interactions in R&D projects.
6.1.1. R&D in transition at Novozymes
Innovation is an important driver for economic development for corporations,
industries and society in general (Ernst, 2003). Like most firms, NZ is dependent on
innovation for performance. An innovation model illustrates the mechanisms that act to
support the innovation process, whether it is a result of technology push, market pull or
a combination of the two. In our study of NZ we find that its model of innovation is
currently characterised by the mechanisms of market-‐pull, however, this has not always
been the case. Traditionally, NZ’ model for innovation was characterised by a
technology-‐push orientation where the organisation focused on new inputs emerging
from research (SULO, 2011). This is illustrated by the following assertion: “…when we
found an enzyme and understood why and how it worked, we would then ask if there was a market
that could use it.” (SULO, 2011). R&D activities thus revolved around exploration of
enzyme technologies to discover new enzymes, through working with unknown
components to understand how they worked together (Ibid). The role of marketing and
business development was a secondary activity that followed sequentially after findings
were made in R&D, in order to assess the market opportunities and to commercialise
the product.
The innovation process characterised by technology-‐push did not face much change
until NZ’ product portfolio began to encompass a broad number of product categories
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and application areas. Soon the role of market-‐pull became more crucial, and
optimisation of the current product portfolio was prioritized. Marketing and business
development began to take an active role in determining which industries and markets
were of particular interest for NZ to target, and consequently also where the R&D
organisation was to place its focus (SULO, 2011.). According to employees and managers
at NZ, the shift in this direction has taken place over the last five year, and it
characterises the way in which NZ engages in R&D at present (TLS; TRMU; SULO; MTBO;
SALK, 2010). It is Business Development, Marketing and Customer Solutions that dictate
the direction of the enzyme technology that R&D is researching. This has been further
indicated through our interviews with employees at NZ “…it is business development and
marketing that indicate that there is a particular market with a high potential for enzyme
products, and then we [MB’s and ADU’s in R&D] alter a current enzyme product to meet these
needs” (SULO, 2011). Where R&D activities previously revolved around exploring new
enzymes and solutions, the current model is deemed to be of a more exploitative nature.
R&D today takes point of departure in known enzymes and exploits capabilities built up
internally to deliver optimised products. Innovation at NZ can thus be characterised as
incremental in nature, as most innovations emerge by combining known knowledge and
components to alter current products and build new solutions. Hence we find evidence
that NZ’ innovation model used to be more radically oriented in its approach to R&D
using input from basic scientific research to create new solutions. It seems that over
time the growth of NZ’ product portfolio has influenced a shift in focus of R&D activities,
as indicated through an interview “we [NZ] have such a large palette of products to offer, to
alter, and development further such as to meet the needs of our customers” (SULO, 2011). This is
not to say that the current model of innovation is insufficient16, however it brings to
mind some of limitations in being able to meet future growth projections as discussed in
the company profile above (section 5). Through an assessment of NZ innovation model,
we will shed light upon the extent to which current innovative activities are conducive
for optimally supporting the innovative capacity of NZ in the face of looming challenges
in the future of enzyme business.
16 NZ is clearly able to meet profit targets year after year.
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6.1.2. Novozymes’ innovation model
Taking point of departure in Novozymes (NZ) current R&D focus addressed above, we
assess the degree to which NZ’ innovation model can be characterised in the light of the
chain-‐linked model. We model the process of internal product development given the
frame of the chain-‐linked model to better understand its advantages and drawbacks.
Finally we wish to shed light upon the implications that arise as a result of the chain-‐
linked model in a firm’s pursuit to expand its innovative capacity. On NZ corporate
website it is emphasized how the organization’s innovation model supports incremental
and radical innovative processes with the aim to ensure a solid pipeline of products for
current market needs as well as to ensure long-‐term growth (NZ Corporate17, 2011). We
find reason to call this position into question by means of our assessment of the actual
scope of NZ’ R&D activities. We uncover insights that indicate that NZ model of
innovation is overly geared for exploitation and incremental innovation with a strong
reliance on applied science as the main input.
The combinatorial perspective of innovation highlights that a broad range of inputs from
external sources, feedback on current processes, and organizational learning by
iteration, together act as drivers for innovation. The combinatorial approach is
characterised by re-‐combination of given components, technologies and processes that
in turn accelerate the innovative process (Kline and Rosenberg, 1986). The structure of
the chain-‐linked model supports the combinatorial approach to innovation as it opens
up for both feedback loops and moving back and forth in the process if innovation (Ibid.).
The feedback loops in turn make way for multiple sources of information to influence a
given innovation process – something Kline and Rosenberg argue is beneficial and
supportive of radical innovation (1986). Furthermore, the iteration of processes
supports incremental innovation (Ibid.). Another important characteristic of the chain-‐
linked model is that it supports the design of the innovation process. Initiating a
technological innovation process calls for an overview of what is needed or expected
from the process, and the sequential redesigns that are essential in reaching a successful
outcome (Kline and Rosenberg, 1986).
17 http://www.novozymes.com/en/investor/sustainability-‐investment-‐facts/Pages/rd-‐and-‐innovation.aspx
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Figure 6.1: NZ’ innovation along the Chain-‐linked model
Source: Kline & Rosenberg (1996)
At Novozymes, a market-‐pull approach to innovation takes point of departure in the
needs and opportunities in the market. Our interviews with employees in the MB-‐ and
ADU departments indicate that a large majority of projects are characterised as product-‐
oriented, where the aim is to either work towards finding a solution or to understand a
given solution better; ultimately to produce a better product (SULO, MTBO 2011). When
further asked whether the organisation was involved in other types of projects that
were not pre-‐defined by the market, interviewees from both MB and ADU departments
re-‐emphasised that a vast majority of R&D projects revolved around tailoring a solution
for the market (SULO, SALK, MTBO, 2011).
We infer that processes of development are initiated on the basis of what the potential
market holds of opportunities for a given product, much along the lines of the chain-‐
linked model. Based on a given requirements of the project, the MB project groups work
closely with the ADU division in each given industrial application area in carrying out
continuous re-‐adjustments and refinements until predefined requirements are met
(MTBO, 2011). We draw a parallel between the R&D organisational structure and the
chain-‐linked model, and infer that NZ internal innovation model resembles the
underlying notions of the chain-‐linked model. The process of product development
follows along the path of the chain-‐linked model (Figure 6.1). It takes point of departure
in the potential market, thereby maintaining a strong focus on producing and providing
application and industrial oriented solutions. NZ’ core competences lie within
researching and producing enzymes for industrial purposes, and consequently it heavily
relies on a thorough scientific understanding within the field of biotechnology in being
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able to meet the demands of the market. As outlined in the theory section, the chain-‐
linked model assumes science to be a knowledge domain open for consultation
iteratively over a given innovation process. This implies that science is aimed to answer
questions that arise during the innovation process, which in turn uses identified market
potentials as point of departure. However, developing arguments for why Novozymes
should engage in more explorative R&D, the linear model becomes a useful frame of
reference (see theory section, figure 4.1). The linear model takes a long-‐term
perspective on science in enhancing the lasting developments of the economy with
particular focus on science-‐based industries. The key contributions of this model can
provide valuable insights for NZ in its quest for becoming more explorative. In pursuing
an innovation model that resembles the fundamentals of the chain-‐linked model, we
infer that NZ does not adequately recognize the importance of pure basic science. By
developing mechanisms that invite more basic scientific input, NZ can faster incorporate
emerging developments taking place out in the broader scientific community (figure
6.2). In the following section we assess the role of basic vs. applied science at NZ’ R&D
organization in more depth.
Figure 6.2: Linear Model vs. Chain-‐linked model
Source: Own Model
6.1.3. R&D at Novozymes: basic vs. applied scientific research In the theoretical discussion we established that both basic and applied scientific
research are of great value for an innovation process. Basic science revolves around
generating a general understanding of a phenomenon, and applied scientific research
looks into providing solutions to technological and industrial problems or issues
(Balconi et al., 2010). Through our interviews with scientists at NZ we discovered that
the way in which NZ utilizes these concepts is rather different from the above definition.
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NZ indicates that its two main R&D departments, MB’s and ADU’s, focus on basic
research and applied research respectively. Yet, taking a theoretical viewpoint a
different story emerges. Novozymes, being a profit-‐driven organization, aims to
strategically focus all R&D and product development activities on delivering market-‐
ready products. It is therefore strategically focused on applied research where all
departments in fact take an application-‐oriented approach to support the necessary
activities throughout the entire pipeline; from early discovery to market launch. This is a
strategic approach that is common for science-‐based profit-‐driven firms, who are often
reluctant to allocate large investments in basic research without a clear future market
value (Balconi et al., 2010). By taking a more thorough look into the activities that these
two departments are engaged in, it becomes clear that the classical definition of basic-‐
and applied research does not apply at Novozymes. As indicated by a Senior Department
Manager for MB Bio-‐Diversity, Martin Borchert, “all research is in fact application oriented,
the differentiation between MB’s and ADU’s merely lies in how early stage we are” (MTBO, 2011).
The relationship between MBs and ADUs is of importance in that both departments
work closely to provide the most efficient products for the industry. Sune Lobedanz,
Senior Department Manager for MB at NZ stated that “the aim of the MB department is not
to investigate a fundamental scientific problem in that sense; a biological problem. We act to
support the ADUs and to bring new insights to the product portfolio” (SULO, 2011). Novozymes’
R&D organisation is structured such that it holds the scientific competences necessary
to substantiate and support the business of the company, and holds the competences to
develop product applications accordingly (SULO, 2011). We therefore call into question
whether the MB department can in fact be characterised to works with basic research,
and therefore also whether the firm is in a position to grasp the value that stems from
more basic oriented scientific research.
6.1.4. R&D project groups at Novozymes A mapping of R&D activities with regards to project formation and the competences that
are utilised indicates a high degree of cross-‐disciplinarily interaction between particular
members of a project group. As illustrated in figure 6.3 the MB department is made up of
a set of sub-‐divisions18, and when projects are initiated, a cross-‐disciplinary group from
18 The MB department is comprised of the following sub-‐divisions: bioinformatics, bioprocess technology, cloning, metabolic engineering, protein chemistry, protein optimization, recombinant expression and screening (NZ Corporate Website, 2011).
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MB is formed to work with the particular ADU division19. The level of cross-‐disciplinary
interaction that takes place internally at NZ is therefore confined to the MB department;
ADU researchers only work within their given industrial application area and not across
(SULO, 2011). Despite this organisational structure, the majority of interviewees
indicated that it would be beneficial for the ADUs to be more cross-‐disciplinary in their
approach, working together in groups across industrial applications (STKH, TLHD 2011).
E.g. people engaged in detergents research could potentially benefit from sharing
experiences and knowledge with people in other application areas such as food or
biofuels.
Figure 6.3: Project groups at Novozymes
Source: Own illustration
When project teams encounter difficulties in finding a solution to a given task, project
groups primarily draw on two means by which they can gain input. They exploit the
internal competences through consulting colleagues and previous research on the area.
Or in the case that the project is in collaboration with an external key customer, the
group has the possibility to consult the collaborating partner for additional input or
guidance (SULO, 2010). NZ collaborative partnerships therefore also play a crucial role
in providing insights to the demands in the market as well as providing guidance with
alternative inputs and suggestions for potential solutions. However, an important
implication is that although the MB department takes point of departure in more early
19 The ADU department covers the following industrial applications: Agriculture, bioenergy, biopharma, food & beverages, household care, leather, pulp & paper, textile, wastewater solutions (NZ Corporate Website, 2011).
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stage research, all activities are nonetheless centered on industrial applications (MTBO,
2011). And the same holds true for projects that involve the collaboration with key
customers. Thus, we find support for our argument that the entire process of innovation
is pre-‐defined to meet a given industrial application outcome, thus limiting the degree of
radical innovations that emerge.
Innovation literature tells us that innovation primarily happens at the boundaries
between disciplines or specialisations, and that working across boundaries or distances
is an important driver in supporting innovation (Parjanen et al., 2011). Following the
notions of combinatorial innovation and structural holes, we have learnt that novel
combinations often emerge across disciplines (from bridging structural holes) and that
there is an incentive to spur interdisciplinary research. In this light we reason that NZ
suffers from a degree of cognitive bias by primarily relying on local search and
exploitation of internal competences in finding input to a given project.
Keeping the above in mind, we infer that there is a continuous flow of knowledge
sharing within the organisation, as well as with collaborative partners in the case that
projects involve their expertise. Along the lines of the chain-‐linked model, R&D at
Novozymes supports feedback loops and iterative processes that enable NZ to
effectively make use if its internal competences, while exploring more distant solutions
is limited to pre-‐defined collaborations with external partners. However, before
concluding on Novozymes innovation model another important point must be
emphasised, which refers to the explorative activities characterised by the above-‐
mentioned collaborative partnerships with key customers and universities. In the
following we draw upon the Long Tail of R&D model to assess the external scope of NZ’
current innovation model.
6.1.5. Novozymes and The Long Tail of R&D Based on numerous interviews with employees and managers at NZ, and by drawing
upon the Long Tail of R&D introduced in the theoretical section, we have developed an
adapted model to illustrate the scope and diversity in NZ’ R&D activities (see figure 6.4).
We use the model to highlight possible limitations of NZ’ current innovation model.
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Figure 6.4: Novozymes and The Long-‐Tail of R&D
Source: Adapted model, inspiration Anderson 2004
The Long Tail of R&D provides an overview of how cross-‐disciplinary R&D activities of a
firm are. The further out the x-‐axis you move the more diverse becomes the set of
disciplines that you leverage. NZ is considered to efficiently exhaust a large degree of its
capabilities along defined and specific lines of enzyme business. While work indeed is of
a cross-‐disciplinary nature, it resides within strategically targeted disciplines as to fulfil
NZ’ objective of supplying products that meet the demands of the market. We have
mapped NZ’ internal R&D as the first pillar along the x-‐axis. External collaborative
agreements with key customers and universities come next. Here, work takes place
across a variety of disciplines some of which are new to NZ, hence these activities are
categorised further out along the x-‐axis. Considering the market circumstances and the
growth projections set for NZ, innovation and the development of new industrial
application areas for enzyme technology are two crucial strategic objectives for the firm.
However, although NZ’ external collaborations indicate a higher degree of diversity of
the disciplines accessed, collaborations are nonetheless close to targeted disciplines
relative to NZ business (TLS, TRMU, 2011). For example, external collaborations with
key customers are conducted within current industrial areas such as collaborative
partnerships with P&G20 on optimizing detergents, or with Schulstad21 on optimizing
20 http://www.pg.com/
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enzymes for baking (Ibid.). University collaborations may indicate that NZ gets access to
more basic oriented scientific research. However, given NZ current focus aimed towards
industrial applications, university collaborations too are found to predominately take
place within known industrial application areas (TLS; TRMU, 2011.). It becomes
questionable whether the current innovation model, characterised by high reliance on
internal competences and external collaborations limited to analogous disciplines, can
in fact support NZ in its goal to expand the market through opening up for more and
new industrial applications.
Explorative and distant search relates not only to acquiring knowledge and ideas
outside a company’s four walls, but more importantly it invites knowledge and ideas
from distant, unique and often unanticipated sources or connections. We infer that there
is a lack of diversity in the input NZ receives and incorporates in its innovation process.
In other words, a vast majority of activities lies within the comfort-‐zone of known
application areas. Furthermore, a strong R&D organisation revolving around the
methods of the chain-‐linked model acts to reinforce NZ’ position in this comfort-‐zone. As
an internal driver for innovation, the model is currently sufficient in fulfilling NZ’
objectives as it supports the development of products for the market. However, the
model is deemed inadequate for enhancing innovative capacity beyond current activities.
We suggest that Novozymes finds itself in a cognitive trap of suboptimal routinized
exploitative strategies. Moreover, we claim that there lies an opportunity in moving
further out along the long tail of R&D to seek and appropriate distant and more diverse
sources of knowledge.
6.1.6. The emergence of revolutionising technologies for enzyme research
To further assess why Novozymes is to benefit from explorative and more distant
sources of knowledge and ideas, it is of interest to understand where revolutionary
technological advancements utilized by Novozymes has come from in the past.
Advancements within research can be said to fall into two categories: advancements
within basic science and advancements within applied science. We have found that a
number of revolutionary technologies that have radically impacted the way, in which
research is conducted across a broad range of fields, also have had a significant impact
on the way enzyme research is conducted today. One such example is that of human 21 http://www.schulstad.dk/
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genome sequencing technology, which was initially developed to understand genetic
codes in humans. Following the notion presented by Bush (1945) this type of research
can be classified as basic scientific research for two reasons. Firstly, government funds
where the supporting backbone of the research initiative -‐ an investment that very few
profit-‐motivated companies would be willing to bear due to the uncertainty of outcomes.
And secondly, the aim of human genome project was to gain an understanding of a
particular scientific phenomenon. The result of this research project starting in the
1960’s turned out to revolutionise the scientific field of medicine through gaining a
better understanding of diseases and cures for human beings (SULO, 2011). In the
beginning 21st century the technology became more accessible and a wider range of
scientific fields started to incorporate the method for the sequencing of other biological
organisms.
Since the year 2000 genome sequencing has played a vital role within the field of
enzymes and biotechnology (SULO, 2011). Sequencing is a commonly applied
technological process at NZ, which has dramatically eased the process of finding
upcoming enzyme candidates, and opened up for the ability to sequence
microorganisms, fungi and bacteria. One response from our interviews stated, “…it has
changed the way we work with micro biotechnology the most” (Ibid.). This technological ability
is of great value to both the way in which NZ works and the external enzyme
environment; it is said that we only know a small share of microorganism what can
actually do. However with the sequencing technology researchers have the potential to
grasp the full potential of these organisms (SALK, 2011).
Another important revolutionising technological change that NZ has encountered is that
of the polymerase chain reaction method (PCR). Originally developed to detect the
mutation causing sickle cell anemia in whole genomic DNA (History of PCR, 2011). The
PCR method replaced an unreliable and inconsistent method that had been developed
internally at NZ, ultimately opening up for more efficient and reliable processes for
cloning microorganisms with consistent outcomes (SALK, 2011). The above examples
shed light on the close relationship between findings in basic science and its ultimate
impact on application-‐oriented research. From interviews conducted we have found that
significant advancements within the field of enzymes have come from unanticipated
sources within basic scientific research (SULO; TRMU; SALK, 2011).
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Furthermore, in the theory section we introduced the linear model to highlight that the
emergence of new scientific knowledge, originating from basic scientific research, is a
driver for initiating application-‐oriented research (Balconi et al., 2010). We find that this
notion holds true in the case of NZ as incorporation of basic scientific inputs as a tool in
application oriented scientific research has been shown to comprise an essential
element in enhancing NZ innovative capacity to date. Thus, it seems important that an
innovation model can exploit both internal capabilities as well as tap into the external
scientific environment.
6.1.7. Conclusion: analysis part I
The objective of the first part of the analysis has been to assess the extent to which the
current innovation model at Novozymes is conducive for effective external knowledge
sourcing. The following concluding remarks are based on what we have learned about
the processes and procedures of R&D at NZ. While NZ claims to be engaged in both
incremental and radical innovation processes, our findings indicate that NZ today is in
fact rather limited to an incremental scope of innovation, and less explorative than seen
in the past. Moreover we find that NZ predominantly relies on market-‐pull logic with
regards to new product development. As a result we find that both MBs and ADUs are
engaged in market captive R&D with a strong application orientation. Nevertheless,
some of our findings also support the presence of exploration activities, such as the way
in which project groups are formed with emphasis on cross-‐disciplinary teams, and by
means of the external collaborations that NZ in fact engages in. Yet, the majority of
research and collaboration with external sources reside within targeted disciplines and
known industrial applications areas. With the challenges confronting NZ, the current
model of innovation plays havoc with the development of more radical innovation with
regards to enzyme technology. We thus infer that NZ is trapped in an exploitative model
of innovation geared for incremental innovation. By drawing upon the notions of the
linear model, we propose that Novozymes is to benefit from unguided search of
scientific opportunities, thereby front-‐loading the R&D organisation through expanding
the current innovation model to leverage basic science and become more explorative.
However, it is deemed a complex challenge to engage in more exploration and basic-‐
science oriented research without compromising the present, very efficient yet
exploitative model of innovation.
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6.2 Analysis Part II – Virtual Innovation Broker In Part II of the analysis we explore the second sub-‐question of our research (Q2) to
understand how a virtual community (VC) set-‐up can support the facilitation of external
knowledge sourcing. The aim is to determine the extent to which a VC can extend NZ’
innovation model to take on a more explorative quality. We develop a set of theory-‐
based arguments for how a number of VC properties can help facilitate an enabling
space for exploration. In the first part of the analysis we reached an empirical and
evidence-‐based conclusion with point of departure in the case of NZ; in the second part
of the analysis we mainly deduce our findings from theory and secondary case-‐
observations. First, by combining theoretical constructs from sociology, network theory
with the perspective of combinatorial innovation we provide an underlying rationale for
why it is valuable to tap into knowledge pools and opportunities that lie external to the
organization. Secondly, by combining our understanding of social structures and its
impact on combinatorial innovations in the light of the idiosyncratic environment of VCs,
we arrive at a set of enabling and inhibiting properties of VCs for acting as a vehicle for
external knowledge sourcing. The guiding hypothesis in this paper is that a VC can act as
a brokerage function between a firm and its external environment. Based on this notion
we introduce our exposition of a VC in this context by developing the concept of the
virtual innovation broker. Ultimately, we conclude that VCs hold potential for acting as a
virtual innovation broker.
6.2.1. A great place to start Novozymes (NZ) is renowned for its strong innovative capacity, yet as outlined in the
first section of the analysis we find evidence suggesting that NZ finds itself in a cognitive
trap of sub-‐optimal exploitative R&D strategies. Given its current model of innovation,
NZ becomes increasingly less likely to produce innovations on the radical side of the
innovation continuum22. Two broad conceptualizations of innovation are considered
important in the light of this paper: open innovation and combinatorial innovation.
Through our interviews at NZ we have come across two statements that illustrate these
two notions well. Per Falholt, CSO23 at NZ said that “…Only 1% of enzyme people work at
Novozymes” (HDRA, 2011). Understanding that most smart people work for someone else
is somehow the essence of open innovation. Thus, just as Procter & Gamble (P&G) in 22 The innovation spectrum refers to the continuum that spans from incremental to radical innovation. 23 CSO: Chief Scientific Officer
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developing the Connect & Develop platform established an understanding that for every
scientist employed at P&G there were at least 200 equally competent scientists
elsewhere (Huston & Sakkab, 2006), NZ have reached a similar conclusion. Second,
Anders Ohmann, Director of Global Customer Solutions at NZ illustrated a way to
understand the notion of discontinuous (radical) innovation: "…the next generation of cars
will likely be developed with the help of the car industry or similar and related industries, however,
if the horse carriage industry had been responsible for the development of the next mode of
transportation, the car would never have been invented” (AOH, 2011). A famous Henry Ford
quote similarly goes “If I'd asked my customers what they wanted, they'd have said a faster
horse." In other words, distant and often unanticipated knowledge pools often contribute
to deliver profound innovations. By the same token, Anders Ohmann pointed out that
while NZ needs radically new industrial application areas for its enzyme technology,
these are not likely to emerge from the innovation model that NZ currently pursues.
From the above we can understand that NZ is aware of two important notions: first that
external sources are plenty and important, and secondly, that agents from distant
disciplines and fields will most likely be those who can provide the most radical inputs
for innovations.
Nevertheless, while it is a great start, few rewards will come from simply knowing that
valuable competences reside external to one’s organization and that distant sources
often hold unforeseen inputs. The true value lies in knowing how to attract and explore
such resources. A first step in this direction is to understand the underlying reasons
manifested in the emergence of social structures, and the nature of how ideas come
about. Secondly, a mediating mechanism of some sort must be developed; where in this
paper we have decided to investigate the potential opportunities that lie in using a
virtual community set-‐up as a medium for realizing external knowledge sourcing.
6.2.2. Structural holes and combinatorial innovation In the theory section we established that the flow of information is more vibrant within
than across groups of people, such that people develop similar views of their history, of
behaviors today, and of how to move into the future. Over time information within
groups group often becomes sticky (von Hippel, 1994), which makes structural holes
appear in the social fabric of communication. These holes are missing relations that
inhibit information to flow between groups. The logic behind structural holes is that
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holes emerge as a result of weaker connections between groups. Moreover, such holes
separate non-‐redundant sources of information, i.e. on either side of a structural hole
different flows of information circulate (Burt, 2001). From understanding this, it
becomes clear that disconnected people are more likely than connected people to
operate with different ideas and practices. Furthermore, the more disconnected the
contacts are the more likely it is that a structural hole exists in between. Nevertheless, it
is in the act of bridging structural holes that things turn complicated, but also where the
value of the hole shows itself. In the book Ten Faces of Innovation, authored by IDEO’s
General Manager Tom Kelley (2005), he introduces the notion of cross-‐pollinators, who
are human agents who “…draw associations and connections between seemingly unrelated ideas
or concepts to break new ground”. Cross-‐pollination reverberates the notion of
combinatorial innovation in that it draws upon the principle of combining or
reconfiguring distributed ideas and turning them into innovations. Thus, novel
combinations can be understood to potentially emerge through bridging structural holes.
The bridge relation that spans structural holes is however not to be understood as a
guarantee, it is a probability; given the right contextual circumstances a connection can
bear fruits. I.e. connecting across structural holes can increase the propensity of a
‘productive accident’; or of encountering a new opinion or practice not yet familiar to e.g.
colleagues; or of envisioning a new synthesis of existing opinion or practice (Burt, 2011).
Furthermore, to bridge is not a forthright endeavor and the literature often point out
that a certain brokerage function is key for bridging the holes -‐ a function that will be
elaborated upon in the following section in the context of a virtual communities.
6.2.3. The Virtual Innovation Broker
In the context of structural holes, the notion of brokers or brokerage functions have been
introduced to address that certain agents, connected to multiple and distributed
networks, are able to act as intermediaries and potentially broker information and
aggregate ideas arising across different/distant networks (Kleinberg et al., 2008). In
other words, the bridging of structural holes is often understood to occur by means of
brokerage (Burt, 2000). In the literature brokerage functions have traditionally been
anthropomorphized, i.e. taken the shape of human agents. Given that most people
require nudging before realizing the value of, or even discussing ideas from, outside
their regular work group, a few people do (Burt, 2001). Such individuals are often better
connected across networks and can act as natural brokers of information. To our
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knowledge the idea of a virtual brokerage function has not yet been proposed in extant
literature. In this part of the analysis we would like to explore the notion of what we
refer to as the virtual innovation broker (VIB) -‐ a virtual community that intrinsically
acts as a broker of information and innovation across remote actors or networks. While
the term virtual suggest that any digital communication device or platform for
interacting virtually is captured by this concept, we have delimited the scope of our case
study to investigate the role of a VC in this context. After all, the notion VC has been
identified as the most profound manifestation of communication taking place across the
Internet. In using the term VIB we wish to emphasize the intermediary role that a VC can
play in acting as a bridge between NZ’ current innovation model and the external, more
distant research environment not currently covered.
Should virtual worlds be seen as a completely new context in which familiar social
processes take place, or merely as an odd context in which social processes play out in a
way not generalizable to the real world? Following Burt (2011), we see no obvious
reason for why networks should operate very differently in VC than across a variety of
in-‐real-‐life (IRL) networks, in which their effects have been reported. In Bakshy, Arrer &
Adamic (2009) (on network contagion effects, gesture diffusion, social trends, fashion in
online vs. offline networks) many attributes of social networks are found to be similar in
both virtual-‐ as well as IRL communities. Moreover, Burt (2011) shows in a study of two
virtual communities that the underlying mechanisms for structural holes and network
closure are the same in both online communities and in offline communities. Thus for
the purpose of this paper we assume similarity between how structural holes are
bridged and combinatorial innovations emerge in IRL communities and in virtual
communities, i.e. understood as familiar social processes that take place in a new
context.
In developing the concept of the virtual innovation broker we study the phenomenon of
virtual communities and some of its properties that support more radical oriented
innovative processes. These findings are essential for the case of NZ, where we propose
that a VC holds the potential to facilitate a brokerage function thus opening up for more
radical innovations to emerge. The following subsections highlight different dimensions
and properties of virtual communities that are of particular interest for our research.
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Virtual communities: structural holes vs. social capital It has been found that recent developments in ICT and the Internet have rapidly changed
the effect of space and time on social capital networks (Social Capital Research, 2011). A
plethora of virtual communities has over recent decades emerged, essentially
compressing the space-‐time continuum by offering cheap and fast connectivity across
remote actors. It has be disputed to what extent an online community actually promotes
or facilitates a place for social capital to grow. Following Wellman (1999) and Cummings
et al. (2002), online communities are not considered to be “intimate groups” due to
geographical dispersion of participants, and such dispersal of social networks should
come to decrease social capital (Putman, 2001). Moreover, the structural holes
argument claims that highly clustered networks are bad for innovative performance
while the social capital position argues the opposite. By extension, the structural holes
argument states that un-‐clustered, or more open networks can enhance innovative
capacity. To explain this discrepancy, one must understand that it takes dramatically
different processes and network structures for producing mature (incremental) as
opposed to young (radical) innovation. For continuous mature innovation, a dense
group of agents addressing similar issues are required to create the critical mass for
further innovation along the ‘chosen path’ (Pyka, 2009). However for a young
innovation to emerge redundant ties are less valuable and it is important to have rapid
access to distant information (geographically, technologically and cognitively) (Ibid.).
Conclusively, structural holes are more important and high social capital less important,
for exploration/radical innovation than for exploitation/incremental innovation, and
vice verse. Thus, what a VC may lack in capacity to ensure intimacy across its members
(i.e. high social capital), it holds in scope and distance across its members (structural
holes). In the light of the virtual innovation broker and opportunities to facilitate
unguided search, exploration and radical innovation, the above discussion further
supports the use of a VIB for this purpose.
6.2.4 Enabling and inhibiting properties of virtual communities
It is argued in this paper that VCs hold a number of enabling as well as inhibiting
properties for supporting external knowledge sourcing. In the literature we find
examples of both skeptics and enthusiasts with regards to how virtual communities
influence social life, knowledge sharing and innovation. The utility of a VC is commonly
assessed by juxtaposing occasions in virtual communities to analogous occasions in real-‐
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life (IRL) communities. First of all, in real-‐life communities geographical dispersion is
often seen an obstacle, however in virtual communities it is rather understood as an
opportunity, where diverging ideas and viewpoints of remote actors can convene and
synergize (Leary & Fontahina, 2007). Furthermore, in case that the mutual topic of
interest is narrow, a large scope is often required as local reach would not be enough for
a community to take form. Take for example ‘Savvyauntie.com’ that gathers thousands
of aunties from across to world online to share experiences, and offers tools such as an
‘Auntiepedia’. It has been described as a modern approach to share and celebrate aunt-‐
hood (Savvyauntie.com, 2011). Such a community is quite unlikely to prosper in a real
life setting. Secondly, virtual communities hold potential to overcome some of the
asocial effects of social interaction. E.g. prejudice is less likely to limit formation of
relationships, as interactions are of a more anonymous nature online. Thirdly, in virtual
communities the impact of differing demographic attributes across members (such as
gender, class, ethnicity, age etc.) is less likely to inflict relationships and ultimately also
information and knowledge sharing, as sometimes seen in traditional “in real life”
communities (Leary & Fontahina, 2007). Fourthly, from the literature we know that
physical communities more often than not suffer from cognitive, disciplinary and
organizational separation. I.e. people tend to group with likeminded people, from within
those disciplines and organizations (workplace, school, etc.) to which they belong. Given
the nature of social interaction in virtual communities, such barriers are to a certain
extent evaded. Finally, according to Rheingold (1993), the main advantage of online
communities is that they hold potential to bring social, intellectual, professional, and not
the least political, leverage to ordinary citizens at low cost. As we see, virtual
communities hold a number of positive attributes for overcoming challenges that often
arise in real-‐life communities.
Nevertheless, while much of the literature address the many positive externalities of
virtual communities, not all literature portrays virtual communities (VCs) in such a
positive light. Fernback wittily argues "…the term virtual community is more indicative of an
assemblage of people being 'virtually' a community than being a real community in the nostalgic
sense" (1999:217). A number of barriers have been identified that VCs have a hard time
to overcome. First, in certain fields, such as the sciences, cutting edge knowledge may be
difficult to disseminate to large groups since it may require specialised expertise and
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may be difficult to aggregate or represent (Olson & Olson, 2000; Bos et al, 2007). As
highlighted by Nooteboom, “new distant-‐shrinking technologies [i.e. ICT] are unlikely to
undermine the value of proximity, because the diffusion of codified knowledge amplifies rather
than devalues the significance of local tacit knowledge” (1999:136). Due to the complex
nature of tacit knowledge, direct and close face-‐to-‐face interaction is essential for new
technological development (Ibid.). A second barrier is the unpredictable shifts in
memberships of a VC. Wenger et al. (2002) pointed out that membership is fluid in its
composition, thus hard work is required for the community to develop and grow -‐ to
maintain energy and a high degree of participation. Thirdly, all large-‐scale, multi-‐user
communities and online social networks that rely on users to contribute content or build
services have been found to share one universal property: a tiny minority of users
usually accounts for a disproportionately large amount of the content and participation,
while a large majority lurk in the background. This phenomenon of online participation
inequality was first studied by Hill et al. (1992) and has been confirmed in a number of
more recent studies (e.g. McConnell & Huba, 2006). Findings from such studies have
resulted in the 90-‐9-‐1 rule: 1% of people create content (creators), 9% edit or modify
that content (contributors), and 90% view the content without contributing (lurkers).
Figure 6.5: Online Participation Inequality
We recognize that virtual communities comprise a set of both enabling and inhibiting
properties for creating and implementing a successful virtual community (appendix 5
for an exhaustive list). Nonetheless, as highlighted in the delimitation of our research,
we take a particular interest in the enabling properties for facilitation of external
knowledge sourcing. We wish to highlight that VC are found to have the capacity to
overcome three fundamental barriers that are of particular interest in the light of our
research:
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1. Temporal barriers
2. Spatial barriers
3. Barriers of cognitive-‐, disciplinary-‐ and organizational separation
By overcoming obstacles of time and space, connections and interactions amongst
members can to a larger extent take place at the convenience of the individual member.
While, IRL communities are constrained by the prerequisite that members must
physically meet at a particular time and place (Burt, 2011), a VC can span geographical
distance and bridge distant networks. This supports the function of potential brokerage
of previously inconceivable structural holes, as these connections in the network would
not naturally have emerged. Furthermore, as we are exploring the potential to grasp
more distant sources of knowledge to spur the emergence of radical innovations, the
dimension of cognitive-‐, disciplinary-‐, and organizational separation are of importance.
In the theoretical section we established that network structures characterized by a
higher degree of heterogeneity might in fact open up for more radical innovations (Lynn
et al., 1994; Burt, 2005). This is because more heterogeneous communities are not to
such a large extent confined by mutual ties, established norms or redundancy of
information benefits, otherwise characterized as being supporting factors for the
emergence of incremental innovations (Burt, 1997). In the case of a VC, we see the
opportunity overcoming barriers of cognitive, disciplinary and organizational
separation, potentially stimulating the emergence of more radical innovation. We follow
up on this discussion in part II of the analysis in the light of obstacles of ambidexterity.
6.2.5. Trends in community life online Thus far, we have introduced theoretical arguments for why a virtual innovation broker
can act to facilitate the brokerage of structural holes and thereby open up for new inputs
for combinatorial innovations. However, it is also important to assess whether the
notion of a VC fits into the context of a firm that resides in a science-‐based industry. In
doing so we have identified a number of generic trends regarding the use of VCs as well
as gained insights through an online survey where we asked a group of researchers and
biotech students about their habits and preferences for interacting online. Our data
suggests that online interactions are not just a frivolous social endeavor but that it is
becoming a professional act, as researchers increasingly seek to share knowledge and
collaborative partners online.
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Based on the ever-‐increasing number of members of large VCs we sat out to investigate
if the adoption rate is also increasing on a generic level. This would point out that VC life
on a macro level is becoming a more integrated part of peoples’ lives. By comparing the
time it took for the four largest virtual communities today, we found intriguing evidence
of a dramatic increase in the rate of adoption. Calculating the days it took from when
these communities were founded until they reached 20 million users, we identify an
exponential development in rate of adoption (see figure 6.5). LinkedIn founded in 2003
took nearly 2000 days to reach 20 million users, whereas Google+ launched in 2011 only
took 24 days. While there certainly are many variables in play for this development, it
hard to neglect that user adoption rates most positively have increased over the years.
Figure 6.5: Time to reach 20 million users
Source: www.mashable.com
A second finding from browsing a number of blogs and other social media news
websites is that social media is increasingly becoming a popular instrument among
scientists. Niche communities are sprouting up all over the web (Appendix 4 for
exhaustive list of identified of niche science and related VCs). We can thus infer that the
scientific community24 is becoming more responsive towards interaction across VCs. A
plethora of communities is emerging with devoted interests in particular fields of
research. Many of these are also of a rather cross-‐disciplinary nature where scientists
meet from across broad array of fields.
24 The scientific community consists of the total body of scientists, its relationships and interactions (http://en.wikipedia.org/wiki/Scientific_community)
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In summary, two supporting arguments are put forward in the above: 1) Virtual
community rate of adoption is increasing dramatically on a macro level and 2) the
scientific community is becoming more prone to engage in online community life,
substantiated by the emergence of more niche-‐online communities within the field of
scientific research.
Online survey A historical and well-‐documented notion is that a scientist’s motivation for doing
research to a large extent is intrinsic, i.e. “it cannot be enforced…it must come as product of
enthusiasm that an individual feel towards his work” (Glaser, 1965:1). Findings from our
online survey provide indications that substantiate the above statement by Glaser. Here
we found that a large majority of our online survey respondents showed a high sense of
professional pride in their line of work (i.e. researching). More than 80% indicated that
they enjoy being able to help others, that they took pride in assisting others with
problem solving and idea development. More than 70% indicated that being able to
discuss and elaborate on research findings and contemplations with other researchers
drives them. Responses related to the scientist motivation for engaging in research
further reflect the findings of Glaser. 35% replied that it was their passion for the field
and 27% stated that it was their interest in expanding the pool of knowledge that
motivated them (appendix 2). Our online survey provides indications that scientists
aspire to interact with likeminded people who share their enthusiasm, and that they also
value such activities in an online context. Furthermore, amongst the respondent group
from our online survey we were able to spot similar trends as highlighted in above. Our
results point out that researchers and biotech students increasingly use the Internet as a
source for networking, collaboration and knowledge (Appendix 2). Furthermore, with
regards to the online behavior of the respondents, more than 70% saw value in
contributing on online platforms, and more than 60% indicated that they could see
themselves actively partake in discussions and problem-‐solving activities online.
Findings from our online survey indicate that researchers see value in being able to
collaborate with other like-‐minded people, and furthermore, to do so through a virtual
community. In the light of this thesis these arguments are important as they indicate
that virtual communities are increasingly adopted as a knowledge sharing and
collaboration tool, also used by researchers. We thus infer that this behavior on part of
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the researchers further supports our hypothesis that a virtual community hold potential
to act as vehicle for external knowledge sourcing.
6.2.6. Conclusion: analysis part II In the second part of the analysis the objective has been to explore the phenomenon of
virtual communities in the context of innovation and external knowledge sourcing. By
drawing upon notions of social capital, structural holes and brokerage in combination
with a number of virtual community attributes we point out that VCs hold the potential
to bring together remote actors, that would not otherwise naturally meet. In this light,
we develop the concept of the virtual innovation broker to highlight the enabling
properties of a VC in acting as a mechanism for bridging structural holes across
dispersed networks. In this effort we highlight the social context and point out that VCs
can overcome temporal and spatial barriers as well as barriers of cognitive, disciplinary
and organizational separation, all commonplace in in-‐real-‐life communities. We find
supporting evidence of general trends in online community life further suggesting that
virtual communities are becoming a more integrated part of people’s life. Moreover,
niche communities centred on particular areas of interest is yet another emerging trend.
Here we find that researcher-‐oriented communities are finding the Internet increasingly
useful as tool for carrying out research, to collaborate, share and receive knowledge
input. In an effort to quantify these trends we conducted an online survey, where
respondents to a large extent confirmed our claims. Thus, by combing theory, literature
and illustrative cases we find support for our hypothesis, i.e. that the utility of a virtual
innovation broker in the given context is potentially high. In light of taking an
explorative research approach, we find reason to be optimistic with regards to the
potential of a virtual community in acting as a virtual innovation broker and opening up
for more distant and explorative inputs to the current innovation model at Novozymes.
Nevertheless, we recognize that our arguments are inadequate in order for us to
conclude with certainty that a VC can become an explorative arm of Novozymes
innovation model. To provide a more comprehensive view of VCs and explorative R&D,
in the third and final part of the analysis we address the VIB in the light of the notion of
optimal scope in external knowledge sourcing and obstacles of ambidexterity.
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6.3 Analysis Part III – The Ambidextrous Innovation Model Through the first and second part of the analysis we confirm that the current innovation
model at Novozymes is limited in its explorative scope, and that literature and theory
support our notion of the virtual innovation broker as possible tool to expand the scope
of NZ’ innovation model through facilitation of an enabling space for external knowledge
sourcing.
With support from literature and theory we argue that the propensity to produce more
radical innovation increases with distance or separation of actors. However too much
distance may render information irrelevant and incomprehensible (Parjanen, 2011).
Thus there seems to be a limit to the scope of explorative R&D activities. We raise two
issues to be addressed in the third and final part of the analysis: how can the notion of
optimal scope be understood, and how can the virtual innovation broker (VIB) be
illustrated as tool for ambidextrous innovation? We confine our argumentation in this
section to a conceptual level, i.e. we do not aim to address specific functional-‐ and design
attributes of a potential VC-‐platform, but rather by utilizing prevailing concepts in
network-‐ and innovation theory highlight the notion of scope in unguided distant search
for science-‐based firms, such as NZ. Here we seek to illustrate the notion optimal scope
in the presence of virtual communities and unguided search. In the light of the
exploitation-‐exploration dichotomy, literature on ambidexterity provides evidence of
how balancing exploitative and explorative strategies often are found difficult for firms
to achieve. Given the set of properties identified in the second part of the analysis, here
we assess the degree to which a virtual community can be understood as a tool that can
make way for an ambidextrous innovation model.
6.3.1. Optimal Scope Continuum In the theoretical discussion section we highlighted that diversity of distance, cognitive,
disciplinary and organisational, is seen as a source of innovation (Harmaakorpi et al.,
2006) and often emphasised as a precondition for novel combinations to emerge
(Parjanen, 2011). Similarly, too high proximity is said to induce a lack of openness and
flexibility towards new or unknown sources of knowledge (Boschma, 2005; Parjanen,
2011). By the same token, too much distance may render information irrelevant or
incomprehensible. Nonetheless, while high distance holds the merit of novelty (greater
variety), it also holds a problem of communicability from a lack of common ground of
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experience, skills and norms. It is thus important to understand that cognitive distance
must be sufficiently small to allow understanding, but sufficiently large to generate non-‐
redundant novel knowledge. The implication of this in the context of the virtual
innovation broker implies that there is a given limit to the degree of resource
heterogeneity -‐ a limit to the value of the information sourced. We infer that there is an
inverted U-‐shaped relationship between resource heterogeneity and input for radical
innovation. In the Optimal Scope Continuum (figure 6.6) below, we have show that as
cognitive distance increases it has a positive effect on learning by interaction because it
yields opportunities for novel combinations of knowledge and information. Diverse sets
of known and unknown information (i.e. semi-‐redundant information) are necessary for
the potential of novel combinations to emerge in such settings. However, at a certain
Figure 6.6: The Optimal Scope Continuum
Source: Own model
point the cognitive distance becomes so large, inherently rendering the mutual
understanding needed to utilize such opportunities obsolete, in other words, resulting in
redundancy of information. A similar logic can be applied to the notion of exploitation
and exploration. Innovation processes that are characterized by a lower degree of
cognitive distance, i.e. similar to those of NZ’ innovation model, are prone to be more
geared towards exploitation. On the other hand, innovation processes that are
characterized by more distant sources (high cognitive distance) of information by means
of explorative activities open up for more radical innovations.
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Drawing on our findings from part I of the analysis, we understand that the information
and knowledge that NZ’ has access to, both internally through the R&D organization and
externally through its collaborative partnerships, although cross-‐disciplinary in its
nature, nonetheless lie within already targeted disciplines. We therefore infer that NZ
mainly leverages sources characterized by a relatively low degree of cognitive-‐,
disciplinary-‐ and organizational distance, and we map NZ at the far left end of the
optimal scope continuum (see figure 6.6). The information here is of a non-‐redundant
character, which places NZ in a position to conduct primarily market captive R&D. We
infer that information and knowledge that resides further out along NZ’ long tail of R&D
(see analysis part I, figure 6.4) in the external environment provides information that is
of a semi-‐redundant and redundant character. Such information is of value to an
organization in producing novel input for innovation. In the past where NZ’ model of
innovation was more driven by a technology-‐push and explorative approach, NZ gained
access to more basic scientific oriented input. One example highlighted was the DNA
sequencing technology, which ultimately had an important impact on the processes of
innovation at NZ. The technology was originally developed to sequence human genomes
in 1960’s, and at the time it could be categorized as redundant relative to NZ. When the
technology was adapted to fit other fields of research information, became semi-‐
redundant and later non-‐redundant, so that NZ in 2000 was in a position to assimilate
the technology into its R&D processes. We know from theory and from the analysis part
I of NZ, that basic scientific inputs are of value to application oriented R&D, however,
such information must reside within the optimal cognitive-‐, disciplinary-‐ and
organizational distance, i.e. of a non-‐redundant, or preferably and semi-‐redundant
nature to be of value for a firm such as NZ. It is argued here, that by being more
explorative, a science-‐based firm can gain realize the value from developments in basic
science at a faster rate.
What the precise optimal scope of distance is can be very difficult to assess. However,
the optimal scope can be defined according to when information moves from being
semi-‐redundant to being completely redundant, i.e. when the mutual understanding
needed to assimilate new information is no longer apparent, and therefore not of value
for the given innovation process. Hence, the optimal scope continuum recognises that
both exploitation and exploration are of value for a given innovation process, and that
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once distant and more explorative information becomes redundant in the given context,
it provides an indication of where outer limits of exploration resides, hence also where
the optimal scope is be identified. We thus conclude that although it holds great
potential to draw in more explorative and distant sources of knowledge, there is
essentially a limit to the value of exploration. Bearing this finding in mind, in the
following section we on to address how an organisation can balance the two activities of
exploitation and exploration and the role a VIB can play in this context.
6.3.2. Overcoming obstacles to ambidexterity
Ambidexterity can be understood as the interplay between exploitation
(stability/incremental innovation) and exploration (flexibility/radical innovation).
According to March, exploitation includes such things as refinement, choice, production,
efficiency, selection, implementation, and execution. Exploration on the other hand
includes things captured by terms such as search, variation, risk taking, experimentation,
play, discovery, and discontinuous innovation (1991:71). Levinthal and March state that,
“an organization that engages exclusively in exploration will ordinarily suffer from the fact that it
never gains the returns of its knowledge” (1993:105). In contrast, firms mainly in pursuit of
exploitation usually achieve returns that are proximate and predictable, but not
necessarily sustainable. March (1991) proposes that exploitation and exploration are
two fundamentally different learning activities between which firms divide their
attention and resources. Furthermore, given the profit-‐seeking nature of firms,
exploitation is often chosen over exploration, much as seen in the case of NZ. Similarly, a
one-‐sided focus on exploitation is said to enhance short-‐term performance, but may
result in ending up in competency trap (Ahuja & Lampert, 2001).
Exploitation and exploration are also said to require fundamentally different
organizational structures and contexts in which different types if innovation can be
expected to emerge (Raisch & Birkinshaw, 2008). Tushman & Smith (2002) describe
incremental innovations (designed to meet existing customers’ needs) as exploitative,
and radical innovations (designed to meet the needs of emergent customers) as
explorative. Levinthal and March conclude that long-‐term survival and success depend
on an organization’s ability to “engage in enough exploitation to ensure the organization’s
current viability and to engage in enough exploration to ensure future viability” (1993:105).
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The above notions are important to understand when assessing a virtual community as
a mechanism to balance exploration and exploitation of R&D activities. In the literature
we find primarily two suggestions of how organizations can balance and synchronize
exploitative and explorative strategies. The first proposes that firms should externalize
either exploitative or explorative activities (Lavie & Rosenkopf, 2006; Rothaermel &
Deeds, 2004). The second argue that it is crucial to carry out the two activities at a
different time and place so they do not plow into one another (Venkatraman, Lee, & Iyer,
2007). Nevertheless, March’s (1991) position is that exploitation and exploration are
two facets of organizational learning that are inseparable, and some scholars argue in
favor of creating loosely coupled organizations in which the explorative units are
strongly buffered against the exploitative units (Levinthal, 1997; Weick, 1976). Echoing
this, other scholars propose that maintaining exploration and exploitation as parallel
activities is not enough to bring value to the firm (Jansen et al., 2009). Furthermore, it
has been stated that it is necessary to integrate these two activities in order to achieve
"unity of effort among the various subsystems in the accomplishment of the organization's task"
(Lawrence and Lorsch, 1967:123).
On the contrary Christensen et al. (1998) postulate that exploratory activities need to be
‘completely separated’ from exploitative units to be able to pursue disruptive innovation.
This notion is further supported by Raisch et al. who emphasize the importance of
"subdivision of tasks into distinct units that tend to develop appropriate…contexts for exploitation
and exploration" (2009: 686). I.e. if boundaries are too permeable between explorative
and exploitative units, constraints imposed by exploitation may “…stifle exploration and
reduce its radius” (Ibid.) Conversely, variations and changes involved by exploration may
destabilize exploitative processes (Raisch et al, 2009).
It seems as though it can be argued whether the two activities should be integrated or
not. We believe that both arguments hold merit in their own right. Separation of
activities is crucial to avoid interference, yet in order to realize the value of novel
combination that emerges in explorative structures, information and knowledge must
somehow be internalized into a process of market captive R&D where
commercialization can take place. As pointed out, we have delimited our paper not to
address how knowledge is to be internalized, appropriated or absorbed and we thereby
pay particular attention to how activities can be separated.
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Obstacles to ambidexterity has been well documented in extant literature, but he
essential challenge resides in dealing with both exploration and exploitation in amore
balanced way, without interference between the two. In Raisch & Birkinshaw (2009) we
learn about two solutions for overcoming obstacles to ambidexterity. The first is a
balance-‐type solution assuming the development of a hybrid of strategies that can
accommodate for both activities simultaneously. The second lies in achieving spatial and
temporal separation of activities through formation of parallel structures. The latter is
often addressed by the theory of punctuated equilibrium that states that organizations
can oscillate between exploitation and exploration in an iterative fashion to avoid
interference by parallel activities, yet allow for both to take place recursively. This,
however, requires an unusual capacity for swift organizational shifts, which is not very
commonplace among larger organizations (Raisch & Birkinshaw (2009). Nevertheless,
the above is of high interest in the light of this thesis, as we infer that a VC set up can be
viewed upon as an explorative arm (add-‐on to the current innovation model at NZ) thus
opening up for such parallel structures of innovative activity. If we recall part II of the
analysis where a set properties of virtual communities was outlined, we emphasized
three key enabling factors of virtual communities for acting as a vehicle for external
knowledge sourcing and search: virtual communities overcome temporal and spatial
barriers, as well as barriers of cognitive-‐, disciplinary-‐ and organizational separation.
Basically, this thesis is exploring the utility of a virtual innovation broker to overcome
obstacles to ambidexterity, and based on the above we suggest that on a conceptual level
there seems to be room for a fit. The solution called for in the literature can be
interpreted as a mechanism for carrying out explorative activities without disturbing
exploitative actives and routines. As such, we find that VIB to be particularly well suited
for the task. In a sense, the VC can be thought of as a second order function that
safeguards the dynamics of the organization by overcoming the contradictory challenge
of stability (exploitation) vs. flexibility (exploration). In the light of our case company, by
means of having access to a network that exists virtually the idea is that NZ can be more
able to balance the countervailing processes of exploitation and exploration and thus
able to capitalize on a more ambidextrous innovation model. Moreover, through a VIB
NZ can potentially rely on virtual and sparse networks during exploration and utilize in-‐
real-‐life teams or tightly bounded groups during exploitation. In addition, the virtual
innovation broker can be hibernated if activities on the virtual platform interfere with
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(steal attention from) the exploitative strategies carried out by the in-‐house R&D
organization, providing a means to oscillate as proposed by Raisch & Birkinshaw (2009).
March (1991) points out that whereas hierarchical structures are more efficient in
exploitation, one should rely on external networks during exploration. We echo March
(1991) in that external networks are key in exploration and move on to suggest that
such networks can be successfully leveraged by means of a virtual innovation broker. In
this respect, given the choice of architectural attributes, a virtual community can
function as a considerably ‘flat’ network. Similarly, following Tushman & O'Reilly (1996),
we learn that while exploitation is better served by bureaucratic structures, exploration
is better supported by organic structures. In this light, the notion of NZ utilizing a virtual
community for exploration receives further support, assuming that structure and
development of a virtual researcher community is more organic than the structure
found at NZ’ R&D organization.
In support of our claim, along the lines of Danzinger & Dumbach (2008), we propose
that ambidextrous organizational attributes indicate that a possible way to create
discontinuous innovation lies in what is referred to as open innovation instruments. A
plethora of open innovation instruments exists (e.g. virtual communities), and such
instruments are said to be suitable for supporting ambidextrous organizational
capabilities (Ibid.). In sum, we infer that a VC indeed holds potential to can act as a tool
to overcome obstacles of ambidexterity.
6.3.3. Ambidextrous innovation A virtual innovation broker (VIB) is a complex socio-‐technical structure, and its
underlying architecture relies on a fundamental understanding of the interaction
between people and technology. In this paper, we go beyond addressing interface-‐ and
communication tools design, and turn to the question of scope. In the case of Novozymes
the VIB is by definition earmarked to act as tool for integrating human agents who are to
some extent cognitively distant from one another, as to produce broader inputs to NZ
R&D organization. In the light of structural holes and ambidexterity theory, we
hypothesize that the scope of distance is a fine balance between being either being too
close to current R&D activities or too distant rendering knowledge inputs redundant.
Thus, the socio-‐technical infrastructure must accommodate for the complex task of
balancing the exploitative and explorative capacity of the platform.
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Below we introduce a model that was outlined in the previous theory section (figure
6.7). In the model, the virtual innovation broker (VIB) is illustrated as a mechanism to
ease the process of concurrent engagement in the two activities of exploration and
exploitation, i.e. widen the scope of engagement along the exploitation-‐exploration
continuum (x-‐axis). The idea is that an organization is unlikely to be able to switch into
forms of full flexibility, and we thereby propose given previously identified enabling
properties of VCs, that a more explorative facet of R&D activities can take place by
means of a VIB.
Figure 6.7: Ambidextrous innovation through a VIB
Source: Own model
By the same token, a VIB can act as a virtual search medium for unguided scientific
discovery, and in our case enable NZ to engage in basic science while keeping its current
applied science-‐based and exploitative oriented innovation model. As pointed out in
part I of the analysis, NZ’ current innovation model has been proved very successful in
the past. It is therefore important that introducing a more explorative scope does not
interfere too much with current activities. Moreover, it is further believed that the
current innovation model provides an important element in realizing the value that
potentially can come to transpire from a successful VC set-‐up. It is believed here, that
such interference will be reduced, given that the nature of interactions in the virtual
world takes place in another dimension (i.e. both temporally and spatially), and can thus
be said to occur separated from present activities of NZ. Finally, we recognize that our
claim is limited to what we know from literature about obstacles to ambidexterity and
our interpretation of the above-‐mentioned VC properties in overcoming those obstacles.
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6.3.4. Conclusion: analysis part III
In part III of the analysis we address the question of whether a virtual community can
make way for a more ambidextrous innovation model. Here we address two important
issues relating to the underlying understanding of external knowledge sourcing: the
notion of optimal scope with regards to cognitive, disciplinary and organizational
distance/separation, and the notion of obstacles to ambidexterity. In this light we
suggest that a virtual innovation broker (VIB), given a set of properties identified in part
II of the analysis, constitute a particularly compelling alternative to facilitate a bridge
between a science-‐based R&D organization such as Novozymes’ and its external
research environment. As such, the VIB can act as a parallel structure in which
explorative activities can take occur without directly interfering with in-‐house R&D
activities.
The optimal scope continuum allows us to understand that while distant sources of
knowledge are of value to an innovation process, there is nonetheless a limit to how
distant and redundant such sources of knowledge can become without rendering the
value obsolete. With the optimal scope continuum we infer that an innovation process
that balances both exploitation and exploration activities holds the potential to provide
inputs of a semi-‐redundant nature, thus opening up for novel combinations to emerge.
Moreover, many scholars have contributed to the discussion of difficulties in balancing
exploitation and exploration. While there are opportunities at either end of the
exploration-‐exploitation continuum, literature and theory highlights that engaging in
both ends of the continuum often renders opportunities at one end superfluous. In this
context we highlight that if formation of groups and interaction across human agents
takes place virtually, barriers of time and space, and barriers of cognitive-‐, disciplinary-‐
and organizational separation can be surmounted. This implies that, in theory, the
explorative domain of R&D can be run as a parallel structure to the exploitative domain,
thereby mitigating issues of that often arise when combining exploitation and
exploration in the same domain (dimension). Ultimately this may lead to more
ambidextrous innovation, assuming that a successful implementation of a virtual
innovation broker can be achieved.
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6.4. Conclusion: Analysis part I, II, II The overall research objective of this thesis has been to explore how a virtual community
can facilitate external knowledge sourcing so as to enhance the innovative capacity of
Novozymes’ R&D organization? In this effort we delimited our paper to take a particular
interest in: (Q1) the current R&D activities at Novozymes; (Q2) a set of enabling
properties of virtual communities for external knowledge sourcing; and (Q3) the
implications of scope with regards to distant search of scientific opportunities and
resource heterogeneity, and ultimately highlighted ways in which a virtual community
platform can overcome obstacles of ambidexterity. Before reaching our final concluding
remarks, we will outline the main contributions from the three parts of the analysis.
Q1: To what extent is the current innovation model at Novozymes conducive for effective
external knowledge sourcing?
We can conclude that Novozymes R&D organization is geared towards producing
market ready products by leveraging strong internal competences centred on
application-‐oriented research. In this light we found that the chain-‐linked model
presents a useful illustration of the current innovation model at NZ. Moreover, we
pointed out that NZ’ model of innovation can be understood as a product of “strong ties”
across the R&D organization and involves a limited set of external collaborations. In
other words, NZ’ current innovation model is successfully exhausting benefits of
localness, high social capital, network closure, exploitation; but is limited in its scope of
explorative activities involving more uncertainty, basic scientific input, distant search
across open networks and raw ideas. While we find evidence that project groups at NZ
are of a cross-‐disciplinary nature, we can conclude that NZ to a certain degree is trapped
in sub-‐optimal routinized exploitative R&D strategies. All R&D activities, ranging from
MB’s to ADU’s as well as external collaborations are limited to cover already targeted
disciplines and industries. The degree of basic scientific research is not adequately
prioritised, despite past examples indicating its vital impact on innovative processes
within R&D of enzyme technology. This is further reflected in the transition of the R&D
organisation, moving from an explorative focus drawing on basic research in the past
towards an exploitative focus, driven by market captive R&D. We conclude that NZ’
innovation model is not particularly conducive for effective external knowledge
sourcing, and suggest that opportunities for frontloading the R&D organisation lie in
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increasing the scope of external networks leveraged with focus on resource
heterogeneity by moving further out along the long tail of R&D.
Q2: How can virtual communities support the facilitation of external knowledge sourcing
for science-‐based firms?
In part II of the analysis we introduced the central phenomenon under investigation in
our thesis, the virtual community (VC). Here we draw on theory and literature to
highlight the rationale for why external knowledge sourcing is of importance so as to
enhance innovative capacity. Following the notion, that bridging structural holes can
result in more novel combinations (radical innovation), we highlight that a special
brokerage mechanism often is needed to create valuable connections across structural
holes. In the context of a virtual community, we expose the concept of the virtual
innovation broker as such a mechanism to support the facilitation of external knowledge
sourcing for science-‐based firms. In view of the context of social interaction in a virtual
world, we understand that virtual communities hold a set of enabling properties, that
are of particular value in the light of our research objective. More specifically, we
highlight the capacity of VCs to overcome barriers of time and space, as well as
cognitive-‐, disciplinary-‐ and organisational separation. Evidence from general trends of
online community life, and results from our online survey, suggest that VCs hold
potential to facilitate an enabling space conducive for external knowledge sourcing.
Virtual communities are becoming an integrated medium for communication and
interaction within the scientific community, and researchers strongly indicate openness
towards the utility of a virtual community for knowledge sharing and collaboration. In
sum, our arguments draw on theory, literature and empirical input, and support our
claim of how a virtual community can facilitate external knowledge sourcing by the
means of a virtual innovation broker. Nevertheless, given the explorative nature as well
as the scope of our paper, we note that in order to confirm with certainly that the value
of a VC is high in the given context, additional success criteria not addressed in this
particular study are necessary to include.
Q3: Can a virtual community make way for an ambidextrous innovation model?
In part III of the analysis the above notion of the virtual innovation broker is taken one
step further and placed under the light of optimal scope of ‘distance’ and ambidextrous
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innovation. While exploitation and exploration activities are important for an innovation
process, there is a limit to the extent to which exploration is of value. Through the
optimal scope continuum we propose that as information moves from being semi-‐
redundant to redundant provided an indication of the outer bounds of the optimal scope.
Obstacles to ambidexterity are addressed through recognizing that exploitation-‐ and
exploration activities require different organisational structures. Where exploitation is
supported through bureaucratic and hierarchical organisational structures; exploration
is supported through organic and flat structures. We infer that by facilitating a VC as a
parallel structure in concurrence with a more exploitation oriented innovation model,
can open up for several benefits. We highlight these by means of our case company,
where we postulate that such an initiative hold potential to enhance the innovative
capacity of NZ, without hampering the internal organisational structure. I.e. in theory,
and provided a number of assumptions regarding opportunities to absorb novel
combinations emerging on the VC platform, a virtual innovation broker can make way
for NZ to surmount obstacles of ambidexterity. Here we point out that due to a set of
enabling properties, VCs can overcome barriers of time and space, and cognitive,
disciplinary and organisational separation -‐ thereby making way for an ambidextrous
innovation model.
In exploring our identified research question we draw upon findings from part I, II and
III of the analysis. We find that, in the context of NZ, a virtual community holds potential
to act as a brokerage function and vehicle for external knowledge sourcing. Specifically,
it can bridge dispersed actors along five dimensions: temporal-‐, geographical-‐, cognitive-‐,
disciplinary-‐ and organisational, in a more effective way than what can be achieved
through an IRL community setting. Not only does it provide NZ with the access to distant
sources of information across previously untargeted disciplines, it also supports
opportunities to gain input from valuable basic oriented research, thereby opening up
for exploration activities transcending the reach of NZ’ current innovation model. In the
light of obstacles to ambidexterity, we have reason to believe that a VIB can play an
important role for balancing more explorative R&D activities along with Novozymes
current exploitative, however remarkably efficient, innovation model. As a result, a VC
holds potential to comprise a cornerstone in developing ambidextrous organizational
capabilities at Novozymes. These are deemed vital given the looming challenges facing
Novozymes in the future of industrial enzyme business.
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Nevertheless, the actual result of VC set-‐up with regards to enhancing NZ’ innovative
capacity remains to be seen after a successful implementation has been carried out. As
of now, we are bound to merely hypothesize that facilitating a VC can indeed enhance
innovative capacity at Novozymes, yet our research provides an optimistic outlook for
why Novozymes should take on an initiative as the one presented in this paper.
7. Discussion of findings and future perspectives Efficient diffusion of knowledge and information is considered the hallmark of a healthy
modern economy (Pyka, 2009). By means of our research we wish to highlight the utility
of ICT in general, and VCs in particular, for making the knowledge economy more
efficient, ultimately resulting in different forms of innovation. The overall message in
this paper is that there is reason to be optimistic about the potential that VCs holds in
facilitating external knowledge sourcing for science-‐based firms. Nevertheless, it
becomes relevant to discuss the implications of our findings, as well as future
perspectives that our research opens up for. Moreover, it is pertinent to ask to what
extent we have contributed to the identified research gap, we initially sat out to address.
Given the embryonic stage of research relating to VCs in the context of innovation, and
the absence of literature regarding research-‐based virtual communities of the kind that
we address in this paper, our case is of a prospective and explorative nature. This has
had both limiting and advantageous bearing on our subsequent findings. We have been
limited to study a hypothetical virtual community set-‐up, thus not been able to provide
empirical evidence with regards to the precise nature and effects of a virtual community
to promote exploration and radical innovation. We are confined to infer only on the
potential opportunities that the phenomenon of VCs holds in the given context, in which
we predominantly rely on inference from theory and literature to reach our concluding
remarks. On the other hand, our approach has allowed us to freely hypothesize and
theorize regarding the use of VCs as to enhance innovation capacity. Moreover, by
combining a pragmatic and theoretical approach, we were able to take a take broad
perspective to our research and use theory and literature in order to shed light on the
phenomenon in question. In this effort we have successfully addressed our pre-‐defined
research gap. Given the lack of studies promoting virtual communities as a tool to be
used by science-‐based firms to broaden their scope and R&D activities, our paper can be
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seen as a preliminary exertion towards highlighting the potential of virtual communities
to facilitate external knowledge sourcing and to overcome obstacles of ambidexterity.
Subsequently, our findings are generalizable on two levels, a pragmatic and a theoretical
level. First, through our case study of Novozymes we find evidence of a predominant
exploitative focus of R&D activities suggesting a lack of exploration. In this light, and
provided that NZ is a firm celebrated for its innovative capacity, our analysis of NZ’
innovation model indicates that (conceivably) other science-‐based R&D intensive firms
may suffer from similar biases. Secondly, our findings are to a certain extent
theoretically generalizable. At the intersection of network-‐, ambidexterity-‐ and
innovation theory and the phenomenon of virtual communities, we present a number of
theoretical claims for why virtual communities hold potential to contribute to
exploration and ambidextrous innovation. An integrated approach of this kind has not
been found in extant literature, and we hold that it provides a nuanced and
comprehensive overview of the mechanisms and dynamics in play regarding the utility
of VCs in the given context. As such, our paper has a positive bearing on the usefulness of
prevailing theoretical constructs in a new setting.
Nonetheless, our paper holds a number of apparent limitations. We only address one
dimension out of many, for understanding how to make use of VCs in the given context.
In order to provide a more comprehensive picture of the utility of VCs for knowledge
sourcing, we envision a number of future research areas that has bearing on our
particular study. We find it important to note, that we recognize that along the line of
most literature regarding opportunities of ICT and virtual communities for knowledge
sourcing and innovation, we too are guided by optimistic suppositions. Thus, in order to
ensure a more nuanced and symmetric debate, more critical perspectives could favour
discourse on the topic of virtual communities in science-‐based innovation. Furthermore,
we are limited to rely on theory on which we base our inferences, thus concrete case
studies presenting the actual effects of VCs should more precisely be able confirm or
reject our claims.
Additionally, in our paper we highlighted that there are strengths and limitations of both
closure and brokerage, but “…while brokerage ... is the source of added value, closure can be
critical to realizing [that] value' (Burt 2001:52). In this light, our paper can be understood
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as an effort to highlight the role of brokerage, i.e. the source of added value that can
come from utilizing virtual communities as a brokerage function en route for remote
and distant actors and knowledge pools. Yet, our study merely touches upon the first
dimension of a two-‐fold inquiry. Correspondingly to Burt’s statement above, following
brokerage comes closure. In that respect it becomes relevant to address how to capture
the value that may transpire. Ensuing research should therefore assess how external
knowledge, captured on the VC, can be effectively internalized as well as commercialized.
It would be of interest to take an intra-‐organizational perspective and analyze how firms
effectively can appropriate, absorb and make use of knowledge emerging from a
successful VC set-‐up. Such research endeavors is favorably carried out in the light of a
retrospective case study, allowing for empirical analysis of knowledge transfer
processes. Exploitation of external knowledge sources is an essential element of a firm’s
innovative capacity, and the notion of absorptive capacity provides a useful concept in
this context with regards to how external knowledge is internalized. Cohen and
Levinthal (1990) state that the absorptive capacity of a firm is the ability to recognize
the value of new information, to integrate it, and to apply it in a commercial context.
Here, current knowledge bases in a firm play an essential role in appropriating external
knowledge; basic skills, experience and the understanding of a particular field provides
a solid foundation by which to evaluate new knowledge. Moreover, absorptive capacity
is said to enhance the ability of a firm to realize the value of the new scientific knowledge
(Cohen and Levinthal, 1990). It is the prior possession of knowledge that supports
creativity through opening up for new associations and linkages between pieces of
knowledge that may not have been obvious before. Thus, the diversity of knowledge
bases internally in the organization is also a crucial role with regards to the assimilation
of novel combinations, i.e. the integration of more radical external knowledge.
Drawing upon the above, future research can be also extended to include development
of strategic recommendations required to successfully implement a VC set-‐up. Our paper
can be considered to provide the underlying rational for undertaking the initiative,
opening up for a more precise plan to be outlined. Here, it would be of interest to take an
operational perspective on the case, where relevant areas to assess would include e.g.:
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platform design-‐ and architecture attributes, platform ownership25 strategies, cost
structures and procedures to ensure user attraction and retention.
Sir Ken Robinson, a well known education researcher, said during a talk at TED26:
“Human resources are much like natural resources, they are buried deep and you have to go
looking for them, they are not just lying around on the surface. And you have to create the
circumstances in which they can show them selves.” By the same token, the architecture of a
VC will to a certain degree define its members and delimit activities that take place.
People tend to cluster into groups as result of interaction opportunities defined by the
places people meet (Pyka, 2009); e.g. the neighborhoods in which they live, the projects
in which they are involved, their workplace as well as the online forums in which they
participate. We infer that just as the architecture of a certain neighborhood is part of
defining the type of people who choose to live there, the architecture of a virtual
community will come to define its members as well as the type of interaction that may
take place in between those members. Through an interview with Peter Kragh, Director
of Front End Innovation at Coloplast27 (founder of innovaiotnbyyou.com), he stated that
a primary recommendation for VC building was to ensure that a learning-‐by-‐doing
principle is employed. He said that one can control the interface design, the
communicative tools and the scope of the focus areas one wish to address etc., but one
cannot control the members. Who is to join only time will tell, and what members will
‘talk’ about is very hard to anticipate. Nonetheless, actions can be taken to influence
what kind of community one is seeking to build. Research drawing upon the above
notions would be highly relevant to take our study one step further.
The phenomenon of virtual communities is becoming an increasingly fascinating target
for social and behavioral science as well as cognitive economics and innovation
literature. One reason for this is, that as a result of advancement of the underlying
computer-‐ and Internet technology supporting the proliferation of virtual communities,
VCs are becoming easier to measure (Burt, 2011). Thus, VCs are to be seen as networks
rich in data available for analysis, which furthermore can come to help improve our 25 Ownership can range from either no ownership where external moderators manage the platform (as seen in the case of Coloplast’s ww.stomainnovation.com) to sponsorship where the firm is a sponsor of the initiative but allow the milieu to grow organically, to full ownership where the firm takes full control and responsibility of implementation, design and content. 26 TED is a nonprofit devoted to Ideas Worth Spreading. It started out (in 1984) as a conference bringing together people from three worlds: Technology, Entertainment, Design. (ted.com) 27 Coloplast is a Danish healthcare firm with focus on products in the ostomy care sector
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understanding of networks in the real world. We echo Burt who urges the entire
academic discourse to “explore virtual worlds as a research site” and “…make virtual
communities legitimate research laboratories to better understand network mechanisms of
innovation…the potential is enormous” (2011:3). In such efforts it becomes important to
establish a clearer link for translating research results between real worlds and virtual
worlds (Ibid.). This further highlights the importance of future research to make use of
retrospective case studies to better concretize and quantify research findings.
Ultimately, we hope that our paper can encourage scholars to take a deeper interest in
virtual communities in the context of innovation.
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“Thanks to the Internet companies that move now can leverage a global pool of talent,
ideas, and innovations that vastly exceeds what they could ever hope to marshal internally”
-‐ USA Today’s editor, Kevin Maney
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9. Appendix The appendix consists of documents, graphs and tables that contain supplementing
information, as well as compilation of interview summaries and meeting notes from our
empirical data.
Appendix: Table of Contents 9. APPENDIX ................................................................................................................................................ 114 APPENDIX 1: INTERVIEW SUMMARY ......................................................................................................................... 115 APPENDIX 2: ONLINE QUESTIONNAIRE SUMMARY ................................................................................................. 146 APPENDIX 3: NOVOZYMES SALES DATA AND GLOBAL ENZYME MARKET ............................................................ 151 APPENDIX 4: ONLINE TRENDS – EMERGING SCIENTIFIC COMMUNITIES ............................................................. 153 APPENDIX 5: ENABLING AND INHIBITING PROPERTIES OF A VIRTUAL COMMUNITY ........................................ 159