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

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.

To my son,

Jeev

my love, my light, my life!

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

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

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.

TABLE OF CONTENTS

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).

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

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)

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

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

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;

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

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

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

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

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.

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

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

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:

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 .

References

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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)

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:

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.

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)

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

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.

71

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