Platform Strategies for Open Government Innovation
Brian Cleland, Brendan Galbraith, Barry Quinn, Paul Humphreys
Department of Management and Leadership, University of Ulster, United Kingdom
brian_cleland@yahoo.com
b.galbraith@ulster.ac.uk
b.quinn@ulster.ac.uk
pl.humphreys@ulster.ac.uk
Abstract: The concept of Open Innovation, that inflows and outflows of knowledge can
accelerate innovation, has attracted a great deal of research in recent years (Dahlander and
Gann, 2010; Fredberg et al, 2008). At the same time there has been a growing policy interest
in Open Government, based in part on the assumption that open processes in the public
sector can enable private sector innovation (Yu and Robinson, 2012). However, as pointed
out by Huizingh (2011), there is a lack of practical guidance for managers. Furthermore, the
specific challenges of implementing Open Innovation in the public sector have not been
adequately addressed (Lee et al., 2012). Recent literature on technology platforms suggests
a potentially useful framework for understanding the processes that underpin Open
Innovation (Janssen and Estevez, 2013; O'Reilly, 2011). The paper reviews the literature on
Open Innovation, e-Government and Platforms in order to shed light on the challenges of
Open Government. It has been proposed that re-thinking government as a platform provider
offers significant opportunities for value creation (Orszag, 2009), but a deeper understanding
of platform architecture will be required to properly exploit those opportunities. Based on an
examination of the literature we identify the core issues that are likely to characterise this new
phenomenon.
Keywords: open innovation, e-government, platforms
1. Introduction
1.1 Background
The growth of interest in open innovation since Henry Chesbrough’s publication in 2003 of
Open Innovation: The New Imperative for Creating and Profiting from Technology has been
well documented (Dahlander and Gann, 2010; Fredberg et al, 2008, Huizingh, 2011). While
the majority of the literature focuses on private sector activities, a parallel surge of interest in
the innovation potential of open government has been attracting much attention from policymakers and commentators (Noveck, 2009; Robinson et al., 2009), triggered by renewed
interest in the role of technology in the public sector and by initiatives within the White House,
EU and elsewhere (Yu and Robinson, 2012).
The primary vehicle for the open government agenda has the online publication of public
sector information – the so-called “open data” movement. This internet-centric approach has
meant that the discussion around open government has merged to some extent into the egovernment debate. It has even been suggested that this new emphasis on openness, cocreation and digital technologies represents the next stage in the evolution of e-government
(“e-government 2.0”) (Chun et al., 2010; Baumgarten and Chui, 2009; Mergel 2010).
The question of how these proposed changes to governance might be implemented has
inspired increased interest in the lessons that can be learned from web-based businesses
such as Google, Facebook, Amazon, eBay and Wikipedia (O’Reilly, 2011, Fishenden and
Thompson, 2012). It has been noted that these private sector organisations have adopted a
platform structure in order to sustain a vibrant ecosystem of external innovators. Following
this approach, it has been proposed that e-government might become a platform for private
sector and citizen-centred innovation.
Many issues have yet to be resolved, however. For example, the distinctive characteristics of
public sector platforms have not yet been clearly defined; i.e., in what respect might they
resemble or differ from their industry counterparts? Generally, there appears to be a gap
between the research and the practical guidance required by public sector managers
(Huizingh, 2011; Heeks and Bailur, 2007; Meneklis and Douligeris, 2010). Furthermore, the
platform literature is complex and multifaceted, encompassing as it does research from at
least three diverse fields (i.e., product management, software development and economics).
Finally, the appropriateness of the platform concept as a metaphor for government is not
universally accepted (DiMaio, 2009).
1.2 Structure
The structure of the paper is based on three research streams: open innovation, egovernment and platforms. These topics were selected for their relevance to the issue at
hand (open government innovation) and the breadth and depth of the available literature. For
each field we provide a brief overview and then identify key themes from the research, with a
particular emphasis on recent studies that suggest inter-topic linkages. The order of
discussion is: open innovation, followed by e-government, and finally platforms. We then
discuss the sub-themes which connect these areas of research, and propose a theoretical
framework that allows us to encapsulate the most important findings. Finally, we highlight
gaps in the literature and propose some questions for future research.
2. Open Innovation
2.1 Overview
Much evidence has been provided to support the proposal that innovation is a key driver for
competiveness, profitability and sustainable growth (Drucker, 1988; Christensen, 1997). One
model of innovation management that has gained much attention and popularity in the last
decade is based on the assumption that companies should open up their innovation
processes and integrate the products of internal and external innovation. The concept of open
innovation was first defined by Henry Chesbrough as: “the use of purposive inflows and
outflows of knowledge to accelerate internal innovation, and expand the markets for external
use of innovation, respectively”. (Chesbrough, 2006)
Chesbrough (2003b) illustrates his ideas by contrasting the so-called traditional “closed
innovation model” with the new paradigm of open innovation, stating that factors such as the
increased mobility of knowledge workers and the development of new financial instruments
have caused the boundaries of the innovation process to start breaking up. It has been
proposed that open innovation encompasses a diverse range of practices, such as customer
and supplier integration, innovation clustering, innovation across industries, trading
intellectual property and investing in global knowledge creation (Gassmann and Enkel, 2004).
2.2 Criticisms of Open Innovation
Despite its popularity, Chesbrough’s work has not been without its critics. One of the
criticisms has been that it is merely “old wine in new bottles” (Trott and Hartman, 2009). Trott
and Hartmann point to the history of research in R&D management, where Chesbrough’s
ideas were pre-empted by Alan Pearson and Derek Ball over 30 years ago (Pearson et al.,
1979; Griffiths and Pearson, 1973), and by the network model of innovation management
(Rothwell and Zegveld, 1985) which was developed over 20 years ago. Trott and Hartmann
accuse Chesbrough of erecting a “straw man argument” in the form of “closed innovation
systems” that he can easily demolish and refute. In order to illustrate this, they go through
each of the “principles” of closed innovation and compare them to the literature, thus
attempting to demonstrate that Chesbrough’s “false dichotomy” does not really exist in
industry.
Similarly, Huizingh (2011) states that “it is clear that the roots of open innovation go far back
in history” – a claim supported by Christensen et al. (2005). Mowery (2009) suggests that
closed innovation – assumed by Chesbrough (2003) to be the dominant model - might have
actually been the exception in a history characterized mostly by open innovation practices.
Galbraith and McAdam (2011) point out that a great deal of research still needs to be done to
create a ‘consistent open innovation theory’. They state that Chesbrough’s model is overly
broad in its current form, and on this basis it should be revisited and amended.
2.3 Popularity of Open Innovation
If Chesbrough’s model suffers, as is claimed, from both overly-simplification and a lack of
originality, then how does one explain its current popularity among researchers? After all, his
2003 book gained more than 1,800 citations in just seven years and a wide range of
disciplines, including economics, psychology, sociology, and even cultural anthropology have
shown interest in it (Huizingh, 2011).
According to Dahlander and Gann (2010) there are at four main reasons for its common
currency: (1) it reflects social and economic changes in working patterns; (2) globalisation
allows for an increased division of labour; (3) improved market institutions such as intellectual
property rights, venture capital, and technology standards allow for organisations to trade
ideas; (4) new technologies enable collaboration across greater geographical distances.
Huizingh (2011) explains its attractiveness to scholars and practitioners in the following way:
(1) Chesbrough assigned a single term to a collection of already existing activities; (2) the
timing coincided with the increased interest in outsourcing, networks, core competences,
collaboration, and the internet; (3) Chesbrough’s work offers opportunities for theoretical
extension, which in turn further stimulate proliferation; (4) Chesbrough connected the
processes of acquiring external knowledge and exploiting internal knowledge externally by
placing them both under the open innovation umbrella.
2.4 Free Revealing and Open Innovation
Although Chesbrough remains a key thinker within this field, other researchers have begun to
redefine the concept of open innovation. One important trend is the evolving theory on the
role of intellectual property, and on the various mechanisms of innovation diffusion. While
Chesbrough and much of the early literature focused on intellectual property as a core asset
and its applications within technology transfer and spin-out/spin-in (Fredberg et al, 2008), the
scope of research has broadened in recent years. Ideas drawn from Open Source Software
have become increasingly important (Gruber & Henkel, 2006; West & Gallagher 2006), and
the term itself is still under debate.
One of the more influential ideas has been the concept of "free revealing" as developed by
Von Hippel and Von Krogh (2006) as part of their research into User Innovation. They
suggest that free revealing is practised far beyond the confines of open source software
development. Henkel (2006) argues that smaller firms with less internal resources are more
likely to make use of revealing, and that the "selective revealing" is deployed to minimise
competitive loss. Some, including Badem (2008), have asked whether there is a tension
between openness and the protection of ideas.
An idea closely-related to free revealing, that appears in the literature on business networks
and clusters, is that of “knowledge sharing between firms through the medium of untraded
interdependencies - knowledge exchanged informally and without explicit compensation”
(Tallman et al., 2004). Storper (1993,1995,1997) introduced the idea of “untraded
interdependencies” as “socially driven exchanges” which no market mechanism exists. Kogut,
et al. (1994) suggest that firms and their suppliers share not only tradable resources, but they
also share knowledge that is integral to the social community - a “public good” for all
members. It is notable that von Hippel’s conception of free revealing also requires than
information is treated as a “public good” (Baldwin and von Hippel, 2010; Harhoff and von
Hippel, 2003).
Dahlander and Gann (2010) recognise this dimension of open innovation research by suggest
that open innovation practises can be either pecuniary or non-pecuniary, where nonpecuniary open innovation is defined as that which presents no immediate financial rewards.
They thus present an analysis of open innovation in two dimensions: inbound versus
outbound, and pecuniary versus non-pecuniary. These two dimensions of open innovation
are used to produce a framework with four types of openness: acquiring, selling, sourcing and
revealing.
Where, then, do the research gaps exist? A review of the literature shows that the primary
focus to date has been on open innovation in the private sector, with limited research having
been been done on the public sector (Lee et al., 2012). To understand the context in which
such research might take place, the following section will consider how the e-government has
evolved to embrace openness as a driver for public sector innovation.
3. E-Government
3.1 Background and Definitions
According to Yildiz (2007), early researchers into government technology treated
technological factors as “peripheral”, outside of the primary management function. The role of
technology from this perspective was to support improved decision-making (Simon, 1976).
Independent adoption of technology by government bodies lead to a “stovepipe” architecture
(Aldrich et al., 2002). While academic interest in this area continued to grow throughout the
1970s and 80s (Danziger et al., 1982; Bozeman and Bretschneider, 1986), it was not until
internet access became commonplace that the e-government concept really emerged (Ho,
2002).
It has been argued that the events of September 11, 2001 triggered a change in perception of
e-government – whereby the role of technology in strengthening national security became a
core focus (Halchin, 2004; Seifert & Relyea, 2004). A number of authors have pointed out the
tension between this security-focused approach and the original principles of e-government
(Doty and Erdelez, 2002; Halchin, 2004; Hernon, 1998).
Perhaps unsurprisingly, no single definition for e-government has been universally adopted
(Halchin, 2004). E-government is defined by the UN as “utilizing the Internet and the WorldWide-Web for delivering government information and services to citizens” (UN & ASPA,
2002). Hernon describes it as “simply using information technology to deliver government
services directly to the customer 24/7”, where “the customer can be a citizen, a business or
even another government entity” (Duffy, 2000). Brown and Budney (2001) have broken down
e-government actions into three categories: Government- to-Government (G2G),
Government-to-Citizen (G2C), and Government-to-Business (G2B). Yildiz (2003) adds two
more categories: Government-to-Civil Societal Organizations (G2CS) and Citizen-to-Citizen
(C2C).
3.2 From E-Government to Open Government
It has been suggested that the next stage in the development of e-government (“egovernment 2.0”) involve adopting the principles of open innovation and user participation
(Baumgarten and Chui, 2009; Chun et al., 2010). It is worth pointing out, however, that the
concept of “open government” predates the internet era. Yu and Robinson (2012) argue that
the idea of open government emerged as a result of the American “peacetime dividend“
following World War 2.
The first published explanation of the term open government was Wallace Parks’ 1957 article,
The Open Government Principle: Applying the Right to Know Under the Constitution. Almost
ten years later, in 1966, the US Congress passed the Freedom of Information Act, and in
1974 it noted that “[o]pen government has been recognized as the best insurance that
government is being conducted in the public interest.” (Yu and Robinson, 2012). The current
resurgence of interest in open government has largely been driven by the information-sharing
potential of the internet. Yu and Robinson (2012) suggest that recent policy has been
characterized by a tendency to use the term open government in an ambiguous way – so that
it refers to both technological innovation (as exemplified by the “open data” movement) and to
political accountability (the original meaning of the phrase) - and that this ambiguity threatens
to undermine both ideals.
The innovation potential of open government has been strongly promoted by the Obama
administration. The administration’s emphasis on technology and innovation may be
connected to a presidential campaign that successfully leveraged online networks and datadriven fundraising methods (Kreiss, 2012). In recent years the open government / open data
policy agenda has been promoted within the US through the Open Government Directive, and
internationally through the Open Government Partnership (OGP, 2013). Related efforts, such
as the European Union’s 2003 Directive on the Re-use of Public Sector Information (Janssen,
2011) and the UK government’s Power of Information Taskforce Report (Mayo and Steinberg,
2007) demonstrate that other governments also recognise the value of open government
data.
3.3 Open Government Platforms
A related trend, identified by Dunleavy and Margetts (2010), has been the shift within
government away from new public management (NPM) (James and Manning, 1996;
Cochrane, 2000; McNulty and Ferlie, 2004) towards what some have called digital era
governance (DEG). A key aspect of DEG is the digitisation of government - including
technological innovations such as cloud computing, social networks and open data (Dunleavy
et al., 2005). Fishenden and Thompson (2012) argue that an open platform architecture will
be required to deliver DEG, and that inspiration should be drawn from platform businesses
such as Google and Facebook.
The theme of open government platforms has also been explored by O’Reilly (2011), who
argues that “government is, at bottom, a mechanism for collective action” and that
government 2.0 should be “an open platform that allows people inside and outside government to innovate. O’Reilly (2011) presents the platform model as an alternative to “vending
machine government” (Kettl, 2002). Similarly, the core principles of what Janssen and
Estevez (2013) call “lean government” include public involvement, platforms and
orchestration. They argue that government’s role as orchestrator is to “control the platform
and associated resources to coordinate the activities of the many stakeholders”. Others,
however have pointed out potential flaws in the “government as platform” model, including
issues related to the regulatory environment, public sector motivations, and the dual role of
government as both platform provider and platform consumer (DiMaio, 2009).
This recent focus on government platforms for open innovation suggests that we need to
consider in more detail the extensive literature on platform architectures. This topic defines
the third and final research stream for our study.
4. Platforms
4.1 Theoretical Contexts
The platform concept has been used to inform theoretical analysis in at least three distinct
fields: product development (Wheelwright and Clark, 1992; Kogut and Kulatilaka, 1994; Kim
and Kogut, 1996; Sawhney, 1998), software-based business strategies (Bresnahan and
Greenstein, 1999; Gawer and Cusumano, 2002) and economics (Rochet and Tirole, 2003;
Parker and Van Alstyne, 2005; Evans, et al., 2006; Eisenmann, 2008; Hagiu, 2009). Baldwin
and Woodard (2009) have argued that the term has a consistent meaning across these
different domains - whereby a platform is a system defined by three aspects: (1) a stable, lowvariety "core", (2) a changeable, high-variety set of "complements", and (3) the interfaces
which allow core and complements to operate as a single system. In this section we review
some of the key concepts that have emerged from the literature.
4.2 An Architecture for Innovation?
The term "platform architecture" has been interpreted in various ways by different authors.
Ulrich (1995) defined product architecture as "the scheme by which the function of a product
is allocated to physical components", and specifically included interfaces within this definition.
In their discussion of modular systems, Baldwin and Clark (2000) consider architecture as a
description of the relationship between modules and functions, and suggest that architecture,
interfaces and standards together comprise the "design rules" of such a system. Whitney et
al. (2004) state that architecture includes (1) a list of functions, (2) the components required
to carry out those functions, (3) the connections and interfaces between the components and
(4) a description of the system's operation under changing conditions. Tiwana et al (2010)
define platform architecture as "a conceptual blueprint that describes how the ecosystem is
partitioned into a relatively stable platform and a complementary set of modules that are
encouraged to vary, and the design rules binding on both".
A common rationale for platform architectures is that such structures enable higher rates of
innovation. It has been argued that modular systems in general are particularly supportive of
innovation (Baldwin and Clark, 1997) by allowing for more rapid trial-and-error-learning
(Nelson and Winter, 1977) and greater autonomy (Chesbrough and Teece, 2002), although
the generalisability of such claims have been challenged by Miozzo and Grimshaw (2005).
Furthermore, Kirschner and Gerhart (1998) argue that the conservation of core processes in
biological systems facilitates evolution by supporting complementary processes that allow for
variation and adaptation. Baldwin and Woodard (2009) argue that this biological principle
should apply to platform designs generally, and that partitioning should reduce the cost of
innovation in man-made systems.
The benefits of platform design generally come at a price, however - as Langlois (2002)
points out, “there is no free lunch". According to Baldwin and Clark (1997), "modular systems
are much more difficult to design than comparable interconnected systems". A major
challenge for the platform architect is knowing where the boundary between core and
complements should lie - in other words, "which components should remain stable and which
should vary" (Baldwin and Woodard, 2009). Langlois (2002) highlights the difficulty of defining
encapsulation boundaries in a dynamic environment, where it is impossible to effectively
partition tasks in advance due to the fact that knowledge is constantly changing (von Hippel,
1990).
4.3 Platform Regulation
Apart from the partitioning problem, a key challenge in platform design is the effective use of
regulation in order to influence participants and thereby drive value generation and capture. A
number of studies have referred to the regulatory role of platform owners (Rochet and Tirole,
2004; Iansiti and Levien, 2004; Farrell and Katz, 2000). Boudreau and Hagiu (2008) consider
in detail at the use of non-price instruments in a variety of multi-sided platforms (MSPs) and
conclude that regulation involves a wide range of legal, technical, informational and other
instruments, often applied in concert. Tiwana et al (2010) propose that platform governance
can be considered from three distinct perspectives: (a) decision rights partitioning, (b) control,
and (c) proprietary versus shared ownership. In their analysis of government platforms,
Janssen and Estevez (2013) suggest that "orchestration" is key, by which they mean the
"arrangement, coordination, and management of complex networks in which public and
private parties conduct tasks".
Effective regulation (or governance/orchestration) requires an understanding of the dynamics
of user communities. Boudreau and Lakhani (2009) state that a key question for platform
owners is whether external innovators should be organised as a competitive market or a
collaborative community, and identify three factors for consideration in this decision. Issues of
motivation are also considered by Antikainen et al (2010), who note that the majority of
existing reward mechanisms appear to increase participation but not collaboration. It is
important to note that motivational mechanisms must be chosen carefully. For example, Frey
et al (2011) suggest that intrinsic motivation leads to more substantial contributions than
extrinsic rewards. Inappropriate reward systems may be counter-productive, or even
damaging. There is strong evidence, for example, that extrinsic rewards can have a negative
effect on intrinsic motivation (Deci et al 1999).
4.4 Ownership and Value
The issue of ownership has also been identified as an important concern for platform
providers (West, 2003). Tiwana et al. (2010) point out that decision rights for the platform
need not belong exclusively to the owner, and that decision rights for modules need not
belong exclusively to module developers. The challenge, they suggest, is to balance
autonomy for external innovators with the need for a coordinated ecosystem. Decisions
around access and control can also affect the type of user that is attracted to the platform
(Belenzon and Schenkerman, 2008), and the overall rate of innovative activity (Boudreau
2010).
Connected to the idea of ownership is the question of how to ensure that value generated by
the platform can be suitably appropriated. Chesbrough (2003b) states that platforms can
"combine internal and external innovations in ways that create value". He claims that just as
value creation is vital for platform adoption, so value capture is necessary for platform
sustainability. According to Baldwin and Woodard (2009), the ability of platforms to generate
value depends on the "option potential" in the complementary modules. It is argued that
external innovators will be drawn to the platform is there is option value in the complements,
unless excessive appropriation of value occurs. Iansiti and Levien (2004) describe excessive
value capture as a "dominator strategy" which runs the risk of starving and destroying the
platform's ecosystem.
4.5 Platform Evolution
In their review of platform-based innovation models, Boudreau and Lakhani (2009)
emphasise that strategies should not be "cast in stone", highlighting the example of the
iPhone App Store, which achieved success by converting a community of external innovators
into a centralised and controlled marketplace. Tiwana et al (2010) propose a detailed
framework for analysing platform evolution. Specifically, they consider the impact on platform
evolution of three coevolving factors: (1) platform design, (2) platform governance and (3)
environmental dynamics. Evolution is not solely the responsibility of the platform owner,
however, and the role of customers in co-creating modules and driving platform evolution is
highlighted by Pekkarinen and Ulkuniemi (2008). It is also worth bearing in mind that the most
attractive and durable systems often develop through an "unselfconscious" process, where
"the rules are not made explicit, but are, as it were revealed through the correction of
mistakes" (Alexander, 1964).
5. Emerging Themes
Based on our research we have identified four cross-cutting themes that are likely to influence
the design and governance of open government platforms:
5.1 Information Flows and Interfaces
Information flows are central to the definition of open innovation (Chesbrough, 2003a).
Directionality is important - flows can be inside-out, outside-in or coupled (Gassmann and
Enkel, 2004). Similarly, the development of e-government models has been defined by the
direction of communications (Layne and Lee, 2001; Schelin, 2003) between various
categories of stakeholder (Brown and Budney, 2001; Yildiz, 2003). Multi-sided platforms can
be said to mediate transactions between stakeholders (Rochet and Tirole, 2003; Baldwin and
Woodard, 2009).
5.2 Regulatory Mechanisms
Mechanisms for identifying the best solutions to a given problem and for rewarding
contributors,have been explored by various authors in the context of open innovation
(Terweisch and Xu, 2008; Antikainen et al., 2010; Bakici et al., 2010). Mechanisms for
promoting trust, participation and communication have also been addressed within studies on
e-government (Linders and Wilson, 2011; Lim et al., 2011; Fishenden and Thompson, 2012).
Platform researchers have examined related issues in depth (Tiwana et al., 2010; Parkes,
2007).
5.3 Value Generation, Measurement and Capture
Chesbrough (2003b) focuses on the importance of the open innovation business model to
ensure that value can be captured and that the innovation process is sustainable. It has been
claimed that platforms create value through the provision of real options (Fichman, 2004) and
that they can capture value through various appropriation mechanisms (Baldwin and
Woodard, 2009; Iansiti and Levien, 2004). In the context of e-government, questions relating
to measuring and capturing value are arguably more complex, as evidenced by debates over
the meaning of public sector value (Irani et al., 2005; Heeks, 1999; Bannister, 2001) and the
role of government-owned intellectual property rights (IPR) (Reichman and Samuelson, 1997;
Suber, 2009).
5.4 Ownership and Partitioning
Related to the debate over IPR and value capture is the question of ownership. Platforms for
open government need not be government-owned – they may be community-owned (e.g., as
an open source project) (Hogge, 2010) or privately owned (e.g., by a commercial open data
platform provider). Indeed, open innovation studies indicate that the intermediary function is
often carried out by a third party (Gassman et al., 2010). One justification for open
government platforms is that they partition the stable, government-controlled core from the
dynamic ecosystem of private innovators (O’Reilly, 2011), but defining natural boundaries is a
challenge for any platform architect, particularly in a changing environment with limited
knowledge (Langlois, 2002). For public sector platform designers, the difficulty may be
compounded by controversies over the proper size and scope of government (O’Reilly, 2011;
Janssen and Estevez, 2013).
6. Further Research
6.1 Theory vs Practice
The gap between theory and practice in e-government has been highlighted by a number of
studies (Yildiz, 2007; Heeks and Bailur, 2007; Meneklis and Douligeris, 2010). Huizingh’s
review of the literature on open innovation emphasises the need of managers for practical
frameworks (Huizingh, 2011). Future investigations into government platform strategies
should consider addressing this gap.
6.2 Public vs Private Platforms
Within the literature on both open innovation and platforms, the focus has been predominantly
on the private sector. The public sector provides a very different context, including regulatory
requirements (DiMaio, 2009), cultural norms (Borins 2001), questions around value
measurement (Irani et al., 2005) and value capture (Reichman and Samuelson, 1997), and
other factors. Empirical research on the differences between emergent e-government
architectures and established industry models would cast a useful light on these issues.
6.3 Design, Governance and Environment
Tiwana et al. (2010) describe a tripartite model of interacting dynamics – design, governance
and environment - that influence platform evolution. A distinctive mixture of endogenous and
exogenous factors will shape the development of government-owned platforms in ways that
have yet to be fully explored. Questions of how to match architecture to governance (internal
fit) and internal decisions to external conditions (environmental fit) will be important to ensure
government platforms provide sustainable public value (Moore, 2005).
7. Conclusion
The aim of this analysis was to understand the issues affecting platform strategies for open
government from three distinct theoretical perspectives. These perspectives were chosen
based on relevance to the core topic and the depth of existing research. We explored the
major themes from each research area and subsequently identified four key questions for
academics and practitioners. We also highlighted three important gaps in the literature where
further research might contribute to both theory and practice. By drawing together these
perspectives and highlighting emergent issues we hope to facilitate a deeper analysis of the
role of government as an active participant in innovation ecosystems.
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