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Opening Open Innovation:
A Multi-Theoretical Perspective on Intermediaries in Online
Community-Based Innovation
A thesis submitted by
Krithika Randhawa
In partial fulfilment of the requirements for the degree of
Doctor of Philosophy
Management Discipline Group, UTS Business School
University of Technology Sydney
April 2018
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CERTIFICATE OF AUTHORSHIP/ORIGINALITY
I certify that the work in this thesis has not previously been
submitted for a degree nor
has it been submitted as part of requirements for a degree
except as fully acknowledged
within the text.
I also certify that the thesis has been written by me. Any help
that I have received in my
research work and the preparation of the thesis itself has been
acknowledged. In addition,
I certify that all information sources and literature used are
indicated in the thesis.
This research is supported by an Australian Government Research
Training Program
Scholarship.
Signature of Student: Date:
Production Note:
Signature removed prior to publication.
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To my son,
Jeev
my love, my light, my life!
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ACKNOWLEDGEMENTS
“As you start to walk on the way, the way appears”
~ Rumi (1207-1273)
This doctoral thesis marks the culmination of a long journey of
hard work and serendipity a
journey only made possible by the invaluable guidance of my
supervisors and other academic
scholars, as well as the unwavering support and encouragement of
my family. I feel fortunate
to have shared my doctoral journey with such a rich and diverse
set of people, who have
coached, mentored and motivated me along the way each in their
own unique way.
Firstly, I would like to thank Prof. Emmanuel Josserand for
being incredibly
supportive of my research endeavor, and placing enormous faith
in my academic capabilities.
From the choice of topic to publishing of papers, I was given
immense latitude to pursue my
research goals through my dissertation, for which I am very
grateful. Dr. Jochen Schweitzer
has been ever-willing to offer support and assistance, as and
when required during my
doctoral journey. I particularly appreciate Jochen timely help
in providing relevant leads,
which proved useful in finalizing my research site, to help
shape the direction of my
dissertation. I thank Emmanuel and Jochen for their crucial
broad commentary and feedback
on the thesis, especially on the second research paper.
Early in my doctoral journey, a casual conversation with A/Prof.
Ralf Wilden turned
serendipitous resulting in us collaborating on my first thesis
publication, followed by
another study (presented as the third paper in this thesis), and
subsequent research projects. I
have felt intellectually respected in working with, and being
guided by Ralf. I am grateful for
his hands-on, committed mentorship, which has helped me hone
well-rounded research skills
and experience along the way. A/Prof. Danielle Logue got
involved later in my thesis
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journey, following another fortuitous meeting. Danielle has been
very forthcoming with
advice and support, and assistance in attending research
symposiums and workshops, which
have helped expand my horizons. Her timely research guidance,
and in particular, prompt
feedback on the second paper comprising this thesis, is very
much appreciated.
I met Prof. Joel West at the 3nd World Open Innovation
Conference (WOIC), where I
presented my third thesis paper, and was also fortunate to win
the Runner-up Best Paper
Award. Joel shared useful feedback on this paper, and over this
conversation a new research
idea was born. Little did we know that we had sown the seeds of
a new paper, that in exactly
a year's time, would be awarded Best Paper at the 4th WOIC. Over
a chat at the conference,
Prof. Henry Chesbrough described this as a stroke of serendipity
I could not agree more!
I am grateful to Joel for collaborating on this paper. I have
learnt, and continue to learn a
lot, from his meticulous research guidance wisdom.
I would like to thank Dr. Jan Hohberger for working with me on
my first thesis paper.
I have since walked unannounced to his office for many a
friendly conversations. Jan has
been keen to share his research perspectives, and in specific,
his tips and advice for me as a
researcher, that I will always bear in mind. I am grateful to
Prof. Roy Green and Prof. Carl
Rhodes for their ongoing help, and in particular, for their
financial support enabling me to
travel and present at the 3nd WOIC. I also thank A/Prof. Antoine
Hermens for providing
funding support for the 14th Open and User Innovation Conference
and 2015 Australia and
New Zealand Academy of Management Conference.
This dissertation has benefitted from helpful feedback from
participants at various
conferences and workshops in which I presented each paper, in
particular the Academy of
Management (AOM), WOIC, Open and User Innovation Conference,
Druid Society, AOM
Organization and Management Theory Division PDW, AOM Strategic
Management Division
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scholars for their comments at these forums: Prof. Frank Piller,
Prof. Christopher Lettl, Prof.
Lars Frederiksen, Prof. Shaz Ansari, A/Prof. Sonali Shah, Prof.
Natalia Levina, A/Prof.
Alberto Di Minin and Prof. Siegfried Gudergan. The two published
journal articles in my
thesis were improved through feedback from editors and anonymous
reviewers.
I am forever indebted to my family whose undying support has
meant more to me
than I can ever say or reciprocate. I thank my mom and dad for
being the ever-supportive
parents and grand-parents that they are. Their unconditional
love has been the wind beneath
my wings. I am grateful to them for teaching me the value of
hard work and perseverance,
and encouraging me to put my best foot forward in every
endeavor. My husband Ripu has
been my constant through the highs and lows of this journey, and
I thank him deeply for that.
He has been a wellspring of strength, lifting me up every time I
felt overwhelmed. With his
characteristically quiet and selfless love, Ripu has gone out of
his way to enable my
endeavor. I am thankful for the wonderful partner and father
that he is.
My son Jeev has been the most serendipitously tied to every
milestone in my doctoral
journey. A week before he was born, I submitted my first thesis
paper to the Journal of
Product Innovation Management, where it eventually got
published. Jeev was almost one,
when I presented the preliminary (conceptual) version of my
second thesis paper at the
Academy of Management. A month after he turned two, the
empirical version was submitted
to (and ultimately published in) the Journal of Knowledge
Management. In parallel, I
submitted my third thesis paper to the 3rd WOIC, where in fact a
new paper that extends my
thesis was conceived. The year Jeev turned three; I continued to
balance motherhood with
my doctoral dissertation, along with full-time research and
teaching. Yet, through it all, my
son has evinced nothing but endless patience and love and for
this, I am eternally grateful.
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TABLE OF CONTENTS
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INTRODUCTION
Innovation has long been acknowledged as a key to organizational
competitiveness and a way
to drive economic development. Much of the early research
promoting this view was centered
on industrial innovation, with an emphasis on the role of
science and technology in spurring
growth and change (Rogers, 1995; Schumpeter, 1934). Common to
these classical
conceptualizations is an understanding of innovation as a linear
process occurring through in-
house research and the development of new technologies, which is
later commercialized into
the market (Freeman, 1982). Organizations were believed to
appropriate value and gain
competitive advantage through tight control of this technical
innovation process (Chandler,
1977; Teece, 1986), and exclusive ownership of related
intellectual property (Chesbrough,
2003c). For most of the 20th century, such a closed approach to
innovation saw heavy
investment in internal research and development, which
subsequently formed the primary
basis of commercial success for many industrial giants such as
AT&T and DuPont
(Chesbrough, 2003a).
By the end of the 20th century, however, organizations began to
adopt
Innovation thus moves
from a location internal to the organizatio
external partners (Bogers and West, 2012; Chesbrough, 2006).
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OI research has focused on manufacturing and product-based
organizations (Mina et al., 2014) investigating the firm-level
implementation of OI (Chiaroni
et al., 2011; Dahlander and Piezunka, 2014; Laursen and Salter,
2006; van de Vrande et al.,
2009), knowledge exchange and technology transfer across
inter-firm dyads (West and
Bogers, 2014). tudies have uncovered how organizations can
collaboratively develop innovations with suppliers, customers,
and partners via R&D
alliances and technology partnerships
through the search and integration of external knowledge (e.g.,
Cassiman and Veugelers,
2006; Hughes and Wareham, 2010), as well as patent and IP
portfolio management
ultimately
Role of Intermediaries in Open Innovation and Crowdsourcing
Previous OI research has also highlighted the crucial role of
intermediaries in enabling
external collaboration and knowledge exchange between entities
(Chesbrough, 2003c;
Colombo et al., 2015; Howells, 2006) agent or broker in [some]
aspect of the
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innovation proc (Howells, 2006, p. 720), an innovation
intermediary is known to accelerate access to external
resources, ideas and solutions
(Chesbrough, 2006), and help search, integrate and transfer
knowledge for OI (Diener and
Piller, 2013; Howells, 2006; Lopez-Vega, 2009). Over time,
studies have used a variety of
terms to refer to innovation intermediaries: third parties
(Mantel and Rosegger, 1987),
consultants/bridgers (Bessant and Rush, 1995), superstructure
organizations (Lynn et al.,
1996), brokers (Hargadon and Sutton, 1997), knowledge brokers
(Hargadon, 1998), bridge
builders (Lagnevik et al., 2010), boundary organizations
(Guston, 2001), and innovation
brokers (Klerkx et al., 2009). The literature has provided
various classification schemes for
intermediaries, but in general their functions can be summarized
as: (1) facilitating
collaboration between organizations, (2) connecting actors, (3)
providing service for
stakeholders, (4) scanning and gathering information, and (5)
facilitating communication and
knowledge exchange (Diener and Piller, 2013; Howells, 2006;
Lopez-Vega, 2009). As such,
the majority of research has examined the role of innovation
intermediaries in enabling
technological transfer and diffusion at the level of systems and
networks (Howells, 2006),
with relatively limited focus on their activities and processes
in helping organizations
implement OI (Lauritzen, 2017; Sieg et al., 2010).
More recently, increasing digitization and the advent of
web-based technologies have
considerably reduced the transaction costs of brokering
distributed knowledge (Chesbrough,
2006; Sawhney et al., 2005), giving rise to new ways for
intermediaries to facilitate OI
(Bogers et al., 2017; West et al., 2014). Crowdsourcing has
emerged as such a mechanism
through which intermediaries provide digital platforms to enable
organizations engage an
to feed into their
innovation initiatives (Afuah and Tucci, 2012; Boudreau and
Lakhani, 2009; Howe, 2006;
Howe, 2008) (Zogaj et al., 2014)
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extend the reach of client
organization (seekers) to a large number of individuals
(solvers), thus helping organizations
in overcom tap into new and previously disconnected sources
of
knowledge (Jeppesen and Lakhani, 2010; Verona et al., 2006).
Through an
line intermediaries allow organizations to
R
. Within this context, studies have
(Chesbrough, 2003c; Colombo et al., 2013; Colombo
et al., 2015; Howells, 2006), which is typically achieved by
demonstrated the effectiveness of such OI intermediaries in
solving complex, tournament-
based crowdsourcing
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Key Research Gaps and Research Question
Although existing crowdsourcing studies have significantly
advanced this relatively young
domain within OI, they focus almost exclusively on
intermediaries facilitating tournament-
based crowdsourcing for technical problem-solving, and have
seemingly ignored other modes
of intermediation (Colombo et al., 2013). As a result, we know
far less about how
organizations
those involving users or
consumers
. Furthermore, research on
Consider the case of Edmunds, an online intermediary that
enables its clients, based in
the automobile industry, to obtain ideas, opinions, and feedback
from a community of users
or consumers of automobiles. Here, the newly obtained knowledge
feeds into a range of
internal innovation processes, such as launching a new model
into the market. In this way,
Edmunds acts as a
helping auto manufacturers integrate the market- and/or
customer-based knowledge
through online communities into their OI processes. To do so,
Edmunds provides its clients
with infrastructure in the form of a digital platform, tools,
and access to the community, and
helps them become competent in running their own community
projects to directly
collaborate and integrate user-based knowledge into their OI
process (Diener and Piller,
2013; Verona et al., 2006). Edmunds is only one of many such
online intermediaries serving
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clients across a wide array of industries. B
(Mele and Russo-Spena, 2015; Sawhney et al., 2003;
Verona et al., 2006) Unlike crowdsourcing through innovation
contests and tournaments,
such community-based crowdsourcing is rooted in collaboration:
members interact with one
another and work together to contribute to the innovative
output. In this context, OI involves
iterative knowledge exchanges between the organization and the
community, and amongst
members of the community (Bogers et al., 2017; Chesbrough and
Bogers, 2014), resulting in
an increasingly complex role undertaken by intermediaries in
managing these OI
relationships and dynamics.
Studies have investigated how
Surprisingly, few studies have explored the crowdsourcing
process from the
perspective of the seeker or client, and out of those that have,
nearly all
Far less research has studied the seeker-intermediary
relationship from the perspective
of the intermediary (Alexander and Martin, 2013; Howells, 2006;
Pittaway et al., 2004;
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Verona et al., 2006). The literature has identified the
potential benefits of intermediaries for
clients such as efficiency in knowledge search (Diener and
Piller, 2013), integration of
technical expertise (Jeppesen and Lakhani, 2010) and customer
knowledge (Verona et al.,
2006), resolving conflicts and competing interests (O'Mahony and
Bechky, 2008), and
reducing uncertainty in the innovation process (Zogaj et al.,
2014); and has highlighted the
importance of maintaining close and continuous interactions with
client organizations
(Bessant and Rush, 1995; Howells, 2006), including in virtual
settings (Verona et al., 2006).
However, there is limited knowledge on precisely how online
intermediaries engage with
seeker organizations to enable successful outcomes from
crowdsourcing, particularly in the
context of community-based OI (Lauritzen, 2017; Zogaj et al.,
2014)
Beyond the lack of attention to the role of intermediaries in
online community-based
OI, research on how organizations can leverage communities for
OI is also limited
(Dahlander et al., 2008; Dahlander and Magnusson, 2005; West and
Lakhani, 2008). Other
research streams have investigated the importance of online
communities as an external
source of innovation; see, for example, research on user
innovation (e.g., Füller et al., 2008;
von Hippel and von Krogh, 2003), co-creation (e.g., Nambisan and
Baron, 2009), and
community-based innovation (e.g., Dahlander and Frederiksen,
2012). Yet these streams have
largely examined aspects within communities, such as
peer-to-peer assistance in open-source
software (e.g., Lakhani and Von Hippel, 2003) and sporting goods
(e.g., Franke and Shah,
2003; Shah, 2006). Other studies have focused on individual
members; for instance, their
willingness to participate in different online communities, such
as brand communities (e.g.,
Füller et al., 2008), firm-hosted user communities (e.g., Wiertz
and de Ruyter, 2007), and
virtual customer environments (e.g., Nambisan and Baron, 2009).
However, we know little
about the collaboration and knowledge exchange between
organizations and online
communities for OI, and even less so on the role of
intermediaries in supporting client
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organizations in this process. Yet, this is important because
communities are largely
autonomous entities that fall outside the hierarchical realm of
the organization (Lee and Cole,
2003; O'Mahony and Bechky, 2008). Tensions arise from the
organization and the
community being driven by competing goals and motives that need
to be tackled (Dahlander
et al., 2008; Faraj et al., 2011; Lauritzen, 2017). Therefore,
to enable an efficient transfer of
knowledge between the client organization and the online
community (Colombo et al., 2015;
Sawhney et al., 2003; Sawhney et al., 2005; Verona et al.,
2006), intermediaries need to help
clients overcome internal barriers, and intervene as required to
increase client capacity in OI.
How can
intermediaries facilitate clients in engaging in online
community-based OI?
Thesis Approach and Theoretical Perspectives
Noting the
I start my doctoral thesis with a systematic bibliometric review
of the OI literature in the first
research paper. Such a review is
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The key insight, which I address
further in the subsequent papers that comprise my thesis, is
that while studies have
predominantly investigated the firm-centric aspects of OI, with
a particular focus on the role
of knowledge, technology, and R&D from the innova
has been paid to the role of users and communities in OI. In
fact, findings show that this is
the least researched area within the OI literature,
substantiating the need to focus on it as part
of my thesis.
uncover key research
gaps and set an agenda that suggests how theoretical lenses from
external fields, such as
organizational behavior (e.g., Communities of Practice) and
marketing (e.g., Service-
dominant logic), are pertinent to more comprehensively explore
multiple facets of the OI
phenomenon. pursue these as research avenues in my thesis.
Stemming from these insights, the remainder of my thesis is set
up to develop a
comprehensive account of intermediary-mediated, community-based
OI by transcending the
perspective of the focal innovating firm. I incorporate the
perspectives of multiple actors to
study the engagement of intermediaries with the seeker
organizations in facilitating
community-based crowdsourcing. In doing so, and following
recommendations discussed in
the first research paper, I draw on
Community of Practice (
They are relevant when
address the relationship between
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intermediaries and client organizations. Beyond helping extend
the firm-centric approach
dominant in extant OI studies, t
and thus aid a novel theoretical exploration of the role of
intermediaries in
facilitating clients deploy online community-based OI.
y thesis
he interaction
between intermediaries and seeker organizations, in
implications for intermediaries hoping to build
client capacity in community-based OI. In a similar way, seeker
organizations can also
benefit from improved ways to select the right intermediaries
when seeking support for the
implementation of community-based crowdsourcing. These can
ultimately translate into
better OI outcomes.
Thesis Outline
My thesis comprises three research papers that address specific
gaps in the OI literature,
revolving around the role of intermediaries in facilitating
online community-based
innovation.
with my supervisors and other scholars, and present these as
chapters in this
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document. All articles have been published and/or are under
review for publication in top-tier
academic journals. Articles under review have been previously
published as peer-reviewed
papers in leading academic conferences. Table 1 provides an
overview of the research papers
that form part of this thesis, including the title, contributing
authors, publication outlets, and
my contribution, as well as other work related to my thesis that
further extends my doctoral
research. I shall now outline the structure of my thesis, and
how each chapter (research paper)
contributes to the development of my research agenda.
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Table 1: Overview of Research Output Research Paper Key Research
Question Contributing
Authors Published/Under-review in My
contribution Research Paper 1: Bibliometric Review of Open
Innovation: Setting a Research Agenda
What are the theoretical roots and key themes underpinning the
existing OI research? What are the key gaps in extant OI
literature, and how can these be addressed?
Krithika Randhawa A/Prof.Ralf Wilden Dr. Jan Hohberger
Published in the Journal of Product Innovation Management (ABDC
- A*) Previous versions of this paper were presented at the: 2014
Academy of Management Annual Meeting, Philadelphia 2014 Strategic
Management Society, Madrid 2014 Druid Society Conference,
Copenhagen
75%
Research Paper 2: Knowledge Collaboration between Organizations
and Communities: The Role of Open Innovation Intermediaries
What mechanisms do OI intermediaries deploy to facilitate
knowledge collaboration at the organization-community boundary?
Krithika Randhawa Prof. Emmanuel Josserand Dr. Jochen Schweitzer
A/Prof. Danielle Logue
Published in the Journal of Knowledge Management (ABDC - A)
Previous versions of this paper were presented at the: 2015 Academy
of Management Annual Meeting, Vancouver 2015 Australia New Zealand
Academy of Management, Queenstown (Best Paper Award) 2016 Open and
User Innovation Conference, Boston 2016 Academy of Management
Meeting, Anaheim
85%
Research Paper 3: Open Service Innovation: The Role of
Intermediary Capabilities
How do intermediaries, in general, and those with digital
service platforms specifically, engage with clients to assist
clients innovate their services?
Krithika Randhawa A/Prof Ralf Wilden
Under review in an ABDC - A* ranked journal Previous versions of
this paper were presented at the: 2016 World Open Innovation
Conference, Barcelona (Runner-up—Best Student Paper) 2017 Open and
User Innovation Conference, Innsbruck 2017 Academy of Management
Annual Meeting, Atlanta
80%
Additional Research Paper and Book Chapter: Randhawa, K.,
Wilden, R. & West, J. (2018 Role of the Seeker in Open Social
Innovation (under review in an ABDC A-ranked journal) A version of
this paper was presented at 2017 World Open Innovation Conference,
Barcelona (Best Student Paper Award) Randhawa, K and Scerri, M.
(2015) Service Innovation: A Review of the Literature in Agarwal,
R., Green, R. & Roos, G. (Eds.) Handbook of Service Innovation
(pp 27-51). Springer: London
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Chapter One presents my first research paper. In this paper, my
co-authors and I
conduct a systematic review of the literature on OI (including
previous research on
crowdsourcing) to gather a consolidated understanding of the
theoretical roots and key
themes underpinning this rapidly expanding (and increasingly
scattered and diverse) field
(Huizingh, 2011; Van De Vrande et al., 2010; West and Bogers,
2017).
What are the theoretical roots and key themes underpinning
existing OI research?
What are the key gaps in extant OI literature, and how can these
be addressed?
My co-authors and I address these questions by combining two
complementary
bibliometric methods of co-citation analysis and text mining of
321 core journal articles on
OI. Through such a structured empirical analysis of both the
structure and content of the
field, we uncover that OI research draws mainly from within
rather than across fields,
research has predominantly focused on the firm-
centric aspects of OI, with an emphasis on examining aspects
relating to knowledge,
technology, and R&D, from the perspective of the innovating
firm. The role of users and
communities in OI has received the least attention in the
literature. We identify other research
gaps in the existing research, leading to future research
avenues of: (1) Developing a more
comprehensive understanding of OI by including diverse
perspectives; (2) Increasing focus
-
on customer co- , and (3) Directing
more attention to OI strategy formulation and implementation. We
provide recommendations
on how hitherto unused or underused organizational behavior,
marketing, and management
theories can be applied to explore each of these avenues.
The two subsequent empirical papers (presented in Chapters Two
and Three) pursue
two of the three research avenues emanating from the
bibliometric review Further, I follow
recommendations laid out in this study to integrate the
CoP view from organizational behavior and the S-D logic of
marketing to explore the role
of In
this way, my first research paper (Chapter One) serves as a
Functioning as the second research paper, Chapter Two addresses
a key gap revealed
in Chapter One to develop a more comprehensive understanding of
OI from a wide range of
perspectives. Based on the findings of Chapter One, it is
evident that OI research has
predominantly adopted a firm-centric approach to study knowledge
inflows. This has been
done by drawing upon s
how organizations acquire external knowledge in the form of
technology or IP as R&D resources to boost internal
innovation outcomes. In the empirical
paper presented in Chapter Two, my co-authors and I highlight
the need for different
approaches in addressing the complex, interactive nature of
knowledge exchange in
intermediary-mediated, community-based OI (Bogers et al., 2017;
Chesbrough and Bogers,
2014). We focus on the perspectives of multiple actors to
explore the ways in which OI
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intermediaries mediate knowledge collaboration between client
organizations and online user
communities. Specifically, the research question we pose is:
What mechanisms do OI intermediaries deploy to facilitate
knowledge collaboration
at the organization-community boundary?
We draw on the CoP perspective of knowledge (Brown and Duguid,
1991; Lave and
Wenger, 1991; Wenger, 1998) (Carlile, 2002;
Carlile, 2004). In doing so, we respond to a specific call
raised in my first research paper to
explore the usefulness of this theoretical lens in combining
organizational with extra-
organizational perspectives (West and Lakhani, 2008), thus
extending the firm-centric
theorization of knowledge dominant in extant OI research
(Randhawa et al., 2016) The CoP
lens acknowledges the socially situated, relational nature of
knowledge as something beyond
the well-defined, easily transferable stocks of IP and
technology (Brown and Duguid, 1998;
Lave, 1988). Thus, the CoP perspective regards knowledge
exchange for OI as embedded in
socio-material practices of actors in the OI ecosystem
(Orlikowski and Scott, 2015), as
opposed to traditional knowledge theories that view OI as an
outcome of transfer of discrete
knowledge stocks between actors (Lee and Cole, 2003; Swan,
2007). This theoretical
perspective is hence useful to examine the complex, social
nature of knowledge collaboration
at the organization-community boundary (Claude Paraponaris et
al., 2015; Kimble and
Hildreth, 2005), making it particularly well-suited for our
research question.
The perspectives of both the intermediary and the clients are
analyzed to lay out a
relational framework of the knowledge boundary management
mechanisms (and associated
practices) used by intermediaries to enable organizations to
engage in online community-
(Verona et al., 2006) playing a role that goes
, in becoming more involved in facilitating
-
(Dahlander et al., 2008;
Dahlander and Magnusson, 2005; West and Lakhani, 2008).
addresses an additional research avenue identified in Chapter
One, that
is, to enhance focus on customer co- .
Despite the important role that OI can play in services, Chapter
One revealed that only a
limited amount of research explicitly examines this aspect,
which is
(Chesbrough, 2011a; Chesbrough, 2011b). In the empirical
paper
presented in Chapter Three, my co-authors and I recognize that
studies on service innovation
have discussed the importance of engaging with customers and
other external partners (e.g.,
Alam, 2002; Moeller, 2008), and the increasing role of
innovation intermediaries that provide
digital service platforms in driving engagement with online
customer communities (Lusch
and Nambisan, 2015; Mele and Russo-Spena, 2015; Sawhney et al.,
2003; Verona et al.,
2006). Yet, there is lack of research on how service
organizations engage in OI mechanisms
such as crowdsourcing to co-innovate with customer communities
across the service
ecosystem (Ostrom et al., 2015; Vargo and Akaka, 2012).
Furthermore, although previous OI
research has investigated what online intermediaries do, only
limited research has explicitly
investigated how precisely they help seekers leverage
community-based OI processes in
general (Lauritzen, 2017; Verona et al., 2006), and to innovate
services (rather than products)
in particular (Mina et al., 2014). Consequently, the
capabilities OI intermediaries need to
deploy to enable clients implement open service innovation
through community-based
crowdsourcing also remains underexplored. Recognizing this gap,
we ask the research
question:
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How do intermediaries, in general, and those with digital
service platforms
specifically, engage with clients to assist clients innovate
their services?
We focus on developing a framework of intermediary capabilities,
which are required
to support seeker clients overcome internal barriers to
implementing open service innovation
through online community-based crowdsourcing. To do so,
accentuate the role of
service ecosystems, and collaboration between value chain
entities that belong to these
ecosystems (Vargo et al., 2015), thus
occurring on service platforms in co-creating value and
innovation (Lusch and Nambisan,
2015; Ordanini and Parasuraman, 2010; Perks et al., 2012). Thus,
th
to advance our understanding of open service innovation as
emerging from the
application of service
Drawing on this relational view to
a theoretical framework of the capability portfolio of OI
intermediaries in enabling
clients to
-
leverage e
(Ostrom et al., 2015).
Both empirical papers (Chapters Two and Three) are based on one
exploratory case
study (Eisenhardt, 1989; Yin, 1984; Yin, 2003) of an OI
intermediary referred to here as
Nexus, and its 18 service-providing client organizations based
in the public sector. In this
instance, clients were able to with online communities
.
(Hilgers and Ihl, 2010; Nambisan, 2008). O
(Eisenhardt and Graebner, 2007; Silverman, 2006), and thus
pertains to the foci
of both my empirical papers, that is, to investigate: (1) the
mechanisms of OI intermediaries
in facilitating knowledge collaboration between organizations
and online communities, and
(2) the capabilities of OI intermediaries in enabling
organizations to co-create services with
online communities.
to shed light on different aspects of the phenomenon. In doing
so, my thesis
opens up OI to external intellectual streams in advancing a
robust theorization of how
.
-
Since standalone research articles form
the chapters of my thesis, there is some overlap in content
between the chapters. Nonetheless,
the articles are unique in that they address separate research
questions, draw upon different
theoretical lenses, and make distinctive contributions to the
literature. Each chapter of this
thesis begins with a preface that links it to the previous
chapter, and provides a summary of
the
emanating from my
doctoral study (presented in Table 1) in which I
explore one of my identified research opportunities, that is, to
examine the role of the seeker
more avenues that future research can pursue in continuing to
advance a holistic
understanding of OI and community-based .
-
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34
CHAPTER ONE
PREFACE
co-citation analysis text mining
firm-centric aspects of
OI
role of users and communities in OI
behavior, marketing, and management
offer Thus, this paper lays the foundation for
opening OI up to other intellectual streams, which is a useful
way to capture the richness of the
phenomenon, and move the field forward.
-
35
A Bibliometric Review of Open Innovation: Setting a Research
Agenda
Introduction
co-citation analysis text mining (unstructured ontological
discovery)
-
36
co-citation analysis
Text mining
The Evolution of Open Innovation Research
-
37
-
38
co-citation analysis text mining (unstructured ontological
discovery)
Methodology
-
39
i
(72), co-creation (48) and
-
40
crowdsourcing (31). iii After accounting for articles that
appear in two or more lists, this was
reduced to 405 unique focal articles. Fourth, all three authors
independently reviewed the
abstracts to determine the relevance of the articles to OI. This
review process led to the exclusion
of articles that are unrelated to the OI field. For example,
some articles on crowdsourcing deal
with the use of crowds in a way that does not clearly qualify as
an innovation, such as an online
information labor market (e.g., Gonen et al., 2013) or as a
source of online news and information
(e.g., Castillo et al., 2013). Also, not all articles that deal
with collaborative innovation are
centered on OI in the way the concept was defined by Chesbrough
(2003a, 2003c, 2006a). For
example, many co-creation articles predominantly revolve around
customers, consumers and/or
services (Alexander et al., 2009; Bolton and Saxena-Iyer, 2009)
in a way that has more to do
with user innovation, service-dominant logic or service
innovation than OI. This iterative process
of reconciling and validating resulted in the final set of 321
focal articles .
co-citation
analysis
-
41
vi
-
42
Text mining
viii
-
43
ix
Results
Management Decision California Management Review
Management
Science
-
44
European Planning Studies
Table 1: Top 15 journals publishing the focal articles and their
references
1 40 Research Technology Mgt 1 183 Research Policy2 32 Research
Policy 2 151 Technovation3 31 R and D Mgt 3 123 R and D Mgt4 30 Int
J of Technology Mgt 4 100 Int J of Technology Mgt5 24 Technovation
5 92 J of Product Innovation Mgt6 15 Tech Forecasting and Social
Change 6 90 Industrial Marketing Mgt7 12 J of Product Innovation
Mgt 7 89 Int J of Innovation Mgt8 12 Tech Analysis and Strategic
Mgt 8 60 European J of Innovation Mgt9 9 Innovation: Mgt, Policy
and Practice 9 60 J of Business Research
10 8 Management Decision 10 56 Tech Forecasting and Social
Change8 California Mgt Review 11 56 Tech Analysis and Strategic
Mgt
12 7 MIT Sloan Mgt Review 12 49 Organization Science13 6 J of
Business Research 13 44 Innovation: Mgt, Policy and Practice
6 Organization Science 14 43 Industry and Innovation15 5 Mgt
Science 15 42 J of Technology Mgt and Innovation
Note: N = Number of articles
-
45
Table 2: Top 15 m
1 843 Laursen K, Salter A, 2006 1 180 Chesbrough H, 2003c2 692
Chesbrough H, 2003a 2 115 Cohen W, Levinthal D, 19903 339 Huston L,
Sakkab N, 2006 3 97 Laursen K, Salter A, 20064 318 Chesbrough H,
Crowther A, 2006 4 72 Chesbrough H, 2006a5 267 Dahlander L, Gann
D.M, 2010 5 57 Lichtenthaler U, 20086 264 Laursen K, Salter A, 2004
57 Chesbrough H, Crowther A, 20067 248 Enkel et al., 2009 57 March
J, 19918 235 Van De Vrande et al, 2009 8 56 Chesbrough H, 2003a9
228 Sawhney et al., 2005 56 Von Hippel E, 1988
228 Caloghirou et al., 2004 10 53 Teece D, 198611 224 Perkmann
M, Walsh K, 2007 11 50 Gassmann O, 200612 216 West J, Gallagher S,
2006 12 49 Von Hippel E, 200513 215 Ritter T, Gemunden H.G, 2003 13
47 Chesbrough et al., 200614 201 Dodgson et al., 2006 14 43 Huston
L, Sakkab N, 200615 197 Piller F.T, Walcher D, 2006 15 41 Arora et
al., 2001
197 Chesbrough H, Appleyard M.M, 2007
Among the references (that is, the intellectual roots) of the
focal articles, Chesbrough
(2003c) is most cited (Table 2). It is also clear that the
majority of the focal articles cite
publications belonging to the OI field. Absorptive capacity
(Cohen and Levinthal, 1990),
exploration and exploitation (March, 1991) and user innovation
(von Hippel, 1988) are the only
research domains external to OI that appear in the Top 15
citation statistics. This indicates that
OI research draws more heavily from within rather than across
fields.
To delve deeper into the intellectual roots of OI, a co-citation
network of the references
of the focal articles was mapped (Figure 1).
-
46
-
47
Figure 1: Co-citation network
Note: To increase the readability, this Figure only shows
publications with more than 20 citations, a degree range >3 and
a co-citation strength of >10. Publication size indicates number
of citations received, connections between publications are
co-citations linkages, and the darkness of these connections
denotes the number of co-citations (darker = more
co-citations).
references
cited
-
48
Figure 2: Dispersion of Open Innovation concepts
Note: To increase readability, this study only shows
publications with more than 75 citations, a degree range >3, and
a co-citation strength >20. Publication size indicates the
number of citations received, connections between publications are
co-citation linkages, and the darkness of connections denotes the
number of co-citations (darker = more co-citations).
7
6
83
9
5
2
4
1
1. Open innovation 2. Absorptive capacity/Exploration &
exploitation/Knowledge-based view3. Search strategies and
R&D co-
operation4. Resource-based view and dynamic
capabilities5. Networks and alliances6. User innovation and
co-creation7. OSS communities8. Methodology I9. Methodology II
-
49
-
50
et al.
Focal articles
Firm-centric aspects of OI; (2) Management of OI networks, Role
of
users and communities in OI
firm-centric aspects of OI
-
51
firms
development
Management of OI networks
industry management,
-
52
network
management
firms
management network
network
role of users and communities in OI
development
ideas
participants
-
53
software
importancedistance
C
A
B
-
54
Differences between early and current research
firm-centric aspects of OI
customer
-
55
Figure 4: Time period 2003-2008 (55 articles)
importancedistance
knowledge
-
56
importancedistance
Management
-
57
network
policy
customer
ideas
-
58
Discussion
Firm-centric aspects of OI; Management of OI networks; Role of
users and communities in
OI.
firm-centric aspects of OI
-
59
mainly to investigate
how the focal firm can develop resources and capabilities for
knowledge exchange and
technology transfer
OI networks
users and communities
-
60
Table 3: Summary of key results from text mining and co-citation
analysis
Research Area Themes Concepts 2003-2008 2009-2013 Related
research streams Key authors & publications1 firms firms strong
strong Open innovation
development technology strong strongr&d strong
strongknowledge strong strongcapacity non-existent strongsearch
strong strongcollaboration non-existent strongdevelopment strong
strongresources strong strongcapabilities strong
non-existentstrategy strong strongperformance non-existent
strong
2 management network medium mediumnetwork ip medium
non-existentindustry patent medium medium
venture non-existent medium Networks and alliancesgovernment
non-existent mediumpublic non-existent mediumpolicy non-existent
mediumsocial weak mediumlearning non-existent mediumcustomers
medium weak
3 participants individuals weak weaksoftware users weak weak
User innovation and co-creationprojects participants non-existent
weakideas community weak weak OSS communities
members weak weakOSS non-existent weak
Henkel (2006); Lakhani & von Hippel (2003); Lerner &
Tirole (2002); von Hippel & von Krogh (2003)
Resource-based view and dynamic capabilities
Absorptive capacity/Exploration and exploitation/Knowledge-based
view
Role of users and communities in OI von Hippel (1986, 1988,
2005); Piller & Walcher (2006);
Prahalad & Ramasamy (2004); Sawhney et al., (2005)
Search strategies and R&D co-operation
Laursen & Salter (2006); Rosenkopf & Nerkar (2001);
Cassiman & Veugelers (2002); Perkmann & Walsh (2007)
Cohen & Levinthal (1990); Zahra & George (2002); March
(1991); Kogut & Zander (1992); Nonaka (1994)
Barney (1991); Eisenhardt & Martin (2000); Penrose (1959);
Teece et al.(1997); Wernerfelt (1984)
Management of OI networks
Ahuja (2000); Burt (1992); Granovetter (1973); Powell et al.
(1996); Uzzi (1997)
Text mining results Co-citation resultsResearch emphasis
Firm-centric aspects of OI
Chesbrough (2003c); Chesbrough & Crowther (2006b); Dodgson
et al. (2006); West & Gallagher (2006)
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61
generate a more holistic
and robust understanding of OI, and thus advance the research
domain.
Although
beyond the scope of this article, such integration of ideas also
paves the way for OI concepts to
enrich research in these external domains, in turn enabling OI
to have a more significant impact
on the wider business community.
1. Develop a more comprehensive understanding of OI from diverse
perspectives
The network perspective:
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62
Finally, studies on international alliances (e.g.,
Hohberger,
2014; Narula and Duysters, 2004) can be useful in examining the
benefits and challenges of
international OI networks.
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63
Table 4: Research gaps and future research directions
Research Gap Potential Research Questions Theories / Concepts
that can be applied
1 Develop a more comprehensive understanding of OI by including
diverse perspectives
The network perspectiveHow can collaborative learning processes
be managed across open innovation networks?
Network learning (e.g., Powell et al.,1996; Ahuja, 2000)
Alliance learning (e.g., Kale & Singh, 2007)
What is the role of network structure and strength of social
tiesbetween network entities in open innovation outcomes?What
relational capabilities and governance mechanisms drivevalue
creation and capture in open innovation networks?
The user perspective How do users co-construct identities
through their engagement inthe open innovation process?Identity
theory (e.g., McAdams, 1996, 2006; Brown, 2006; Watson, 2009;
Kleine III et al., 1993; Mittal, 2006)
How can user identity formation act as an intrinsic motivator
forusers to co-innovate with firms?
User innovation concepts (e.g., von Hippel,1986, 1988, 2005;
Piller & Walcher, 2006)
What is the role of users' motivation in shaping their
participationbehaviour in open innovation activities?
The community perspective How do open innovation communities
relate to the canonicalprocedures and rules of engagement laid by
the host firm?
Communities of practice (e.g., Brown & Duguid, 1991; Lave
& Wenger, 1991; Wenger, 1998)
What kind of self-governing practices emerge through
relationalparticipant interactions in open innovation
communities?
Social practice theory (e.g., Reckwitz, 2002; Schatzki et al.,
2001; Gherardi, 2008)
How do communal dynamics feed back into organizationalpractices
of open innovation?
2 Direct increased attention to open strategy formulation and
implementationHow can firms align open business models with the
outcomes ofvalue creation and value capture?
Business model innovation (e.g., Zott & Amit, 2010)
Strategic innovation and value capture (e.g., Afuah, 2009; Afuah
& Tucci,
What are the collective processes of developing open
strategyacross open innovation networks?
Strategy-as-practice (e.g., Whittington, 1996; Jarzabowski &
Spee, 2009) Dynamic capabilities (e.g., Eisenhardt & Martin,
2000; Teece et al.,1997)
What organizational capabilities are required for the
sustainedimplementation of open strategy?
3How can firms leverage customer resources to co-create
valueacross various stages of open service innovation?
Service dominant logic (e.g., Vargo & Lusch, 2004; Lusch
& Vargo, 2006) Service (eco-)system (e.g., Vargo & Akaka,
2012)
How can service value networks be structured to enable
openservice innovation?
Co-creation (e.g., Prahalad & Ramasamy, 2004; Sawhney et
al., 2005) Service innovation concepts (e.g., Miles, 1993;
Magnusson et al., 2003)
What kind of collaborative processes are involved between the
firm and customers in open service innovation?
Social network theory (e.g., Burt, 1993; Uzzi, 1997)
Alliance-portfolio management (e.g., Aggarwak & Hsu, 2009; Wang
& Rajagopalan, 2015)
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64
The user perspective:
engage and incentivize user
innovators in the OI process.
-
65
The community perspective:
-
66
2. Direct increased attention to OI strategy formulation and
implementation
-
67
3. Enhance focus on customer co-creation and conceptualize ‘open
service innovation’
-
68
Conclusion and Limitations
co-citation analysis text mining
-
69
behavior (e.g.,
communities of practice), management (e.g., dynamic
capabilities) and marketing (e.g., service-
dominant logic) offer
will aid researchers to more comprehensively
capture the richness of the OI phenomenon. Although outside the
scope of this study, this
suggested amalgamation will also allow the OI concept to
permeate into other research domains.
This will help to address theoretical and empirical challenges
in fields outside of OI, and thereby
increase the impact of OI on the broader business community.
The resulting broader perspective on OI will ultimately benefit
managerial decision-
making. For example, integrating service-dominant logic into OI
research will inform managers
on how to better establish organizational conditions for value
co-creation, such as an open
service innovation orientation and culture, which treat external
partners as integrated, active, and
value creating. Insights from service-dominant logic will also
provide managers with guidelines
to better design OI processes for better collaboration across
the entire value chain including
customers, suppliers and other partners. Furthermore, adopting a
community of practice
perspective will shed light on how managers can foster
communities as external sources of
innovation by addressing the social, interactive practices that
underpin intra-community and
firm-community relationships. Managers can draw on these
insights to orchestrate community
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70
engagement and governance practices toward better firm-community
collaboration, and thus spur
the creation and capture of value through community-based OI.
Finally, incorporating dynamic
capability thinking into an OI framework will help managers to
better identify market
opportunities for OI and effect organization-wide business model
reconfigurations to capture
value from these opportunities. Implementing open business
models require high organizational
responsiveness and broad market understanding particularly in
highly dynamic environments.
Through the use of a systematic research
methodology, this study reduced the bias often associated with
traditional literature reviews and
expert surveys. findings are influenced by the scope and nature
of the
underlying research design and methods. First, the restriction
to certain keywords and/or journals
while building the sample may have had an impact on the results.
To minimize sampling bias,
this study employed a rigorous sample selection procedure by
choosing multiple keywords and a
wide range of journals and articles belonging to all business
domains. Second, the empirical
results are a representation of existing research (published and
in-press articles), and exclude
ongoing and not-yet-published debates (e.g., working articles
and conference proceedings).
Finally, as is the case with any bibliometric analysis, the
results are the outcome of the algorithm
employed by the analytic software. Hence a detailed methods
description is provided for the
reader. Additionally, to guide and strengthen the interpretation
of the software-produced outputs,
the research team read the contextual text excerpts and
abstracts of the related articles/citations,
thereby supplementing the objective examination of the
literature with qualitative and
interpretative analysis.
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71
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