Platform Strategies for Open Government InnovationBrian Cleland, Brendan Galbraith, Barry Quinn, Paul HumphreysDepartment of Management and Leadership, University of Ulster, United Kingdombrian_cleland@yahoo.comb.galbraith@ulster.ac.ukb.quinn@ulster.ac.ukpl.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 BackgroundThe 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 policy-makers 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 e-government debate. It has even been suggested that this new emphasis on openness, co-creation 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 StructureThe structure of the paper is based on three research streams: open innovation, e-government 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 OverviewMuch 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 InnovationDespite 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 InnovationIf 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 commoncurrency: (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 InnovationAlthough 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 non-pecuniary 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 DefinitionsAccording 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 World-Wide-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 GovernmentIt has been suggested that the next stage in the development of e-government (“e-government 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 data-driven 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 PlatformsA 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 govern- ment 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 ContextsThe 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, low-variety "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 RegulationApart 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 ValueThe 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 EvolutionIn 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 ThemesBased 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 InterfacesInformation 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 MechanismsMechanisms 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 CaptureChesbrough (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 PartitioningRelated 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 PracticeThe 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 PlatformsWithin 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 EnvironmentTiwana 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. ConclusionThe 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.

ReferencesAldrich, J., Bertot, J. C., & McClure, C. R. (2002). E-government: initiatives, developments, and issues. Government Information Quarterly, 19, 349-355.Alexander, C. (1964). Notes on the Synthesis of Form (Vol. 5). Harvard University Press.Antikainen, M., Mäkipää, M., Ahonen, M., (2010). Motivating and supporting collaboration in open innovation. European Journal of Innovation Management 13, 100–119.Badem, D. (2008) Selective Revealing in Open Innovation Processes: The Case of Embedded Linux, <ww.ai.wu-wien.ac.at/~koch/lehre/user-innovation-pi-ws-08/presentations/selective.pdf> Retrieved on: 29/04/09.Bakici, T., Admirall, E., & Wareham, J. (2010). The underlying mechanisms of open innovation intermediaries. In R&D management conference.Baldwin, C.Y., Clark, K.B., (1997). Managing in an age of modularity. Harvard Business Review 75 (5), 84–94.Baldwin, C. Y., & Clark, K. B. (2000). Design rules: The power of modularity (Vol. 1). MIT Press.Baldwin, C. Y., & Woodard, C. J. (2009). The architecture of platforms: A unified view. Platforms, markets and innovation, 19-44.Baldwin, C., & Von Hippel, E. (2010). Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Harvard Business School Finance Working Paper, (10-038).Baldwin, C., & Von Hippel, E. (2010). Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Harvard Business School Finance Working Paper, (10-038), 4764-09.Bannister, F. (2001) Dismantling the silos: extracting new value from IT investments in public administration. Information Systems Journal, 11, 65–84.

Baumgarten, J., Chui, M., (2009). E-government 2.0. McKinsey Quarterly 4, 26–31.Belenzon, S., & Schankerman, M. (2008). Motivation and sorting in open source software innovation. LSE STICERD Research Paper No. EI47.Borins, S., (2001). Encouraging innovation in the public sector. Journal of Intellectual Capital 2, 310–319.Boudreau, K., & Hagiu, A. (2008). Platform rules: Multi-sided platforms as regulators. Available at SSRN 1269966.Boudreau, K., 2010. Open Platform Strategies and Innovation: Granting Access vs. Devolving Control. Management Science 56, 1849–1872.Boudreau K.J., Lakhani, K.R., (2009). How to Manage Outside Innovation. MIT Sloan Management Review 50.Bozeman, B., & Bretschneider, S. (1986). Public management information systems: Theory and prescription. Public Administration Review, 46, 475-487.Bresnahan, T. F., & Greenstein, S. (1999). Technological competition and the structure of the computer industry. The Journal of Industrial Economics, 47(1), 1-40.Brown, M. M., & Brudney, J. L. (2001, October). Achieving advanced electronic government services: An examination of obstacles and implications from an international perspective. Paper presented at the National Public Management Research Conference, Bloomington, IN.Baldwin, C., & Von Hippel, E. (2010). Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Harvard Business School Finance Working Paper, (10-038), 4764-09.Chesbrough, H.W., Teece, D.J., (2002). Organizing for innovation: when is virtual virtuous? Harvard Business Review 80 (8), 127–136.Chesbrough, H (2003a). Open Innovation: The new imperative for creating and profiting from technology, Boston, MA: Harvard Business School Press.Chesbrough, H., (2003b). Open platform innovation: Creating value from internal and external innovation. Technology Journal 7, 5.Chesbrough, H. W. (2006). The era of open innovation. Managing innovation and change, 127(3), 34-41.Christensen, C.M.( 1997). The innovator’s dilemma, Harvard Business Review Press, Boston, US.Christensen, J. F., Olesen, M. H., & Kjær, J. S. (2005). The industrial dynamics of Open Innovation—Evidence from the transformation of consumer electronics. Research policy, 34(10), 1533-1549.Chun, S.A., Shulman, S., Sandoval, R., Hovy, E., (2010). Government 2.0: Making connections between citizens, data and government. Information Polity 15, 1–9.Cochrane, A., (2000). Local government: Managerialism and Modernisation. In New Managerialism, New Welfare?, ed. John Clark, Sharon Gewirtz, and Eugene McLaughlin, 122-136, London: Sage.Dahlander, L. and, Gann, D. (2010). How open is innovation?, Research Policy, Volume 39, Issue 6, Pages 699-709Danziger, J. N., Dutton, W. H., Kling, R., & Kraemer, K. L. (1982). Computers and politics: High technology in American local governments. New York: Columbia Univ. Press.Deci, E.L., Koestner, R., Ryan, R.M., (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological bulletin 125, 627.DiMaio, A. (2009). Government 2.0: A gartner definition. Industry Research, ID, (G00172423).Doty, P., & Erdelez, S. (2002). Information micro-practices in Texas rural courts: Methods and issues for E- government. Government Information Quarterly, 19, 369-387.Duffy, D. (2000). Q&A: Balancing the role of e-Government: Interview with Mike Hernon, vice president of e-government for New York City-based GovWorks. [Online]. Available at: http://www.cnn.com/2000/TECH/computing/11/13/qna.egov.idg/. Accessed January 7, 2001.Dunleavy P., & Margetts, H. (2010). The Second Wave of Digital Era Governance. American Political Science Association Conference, 4 September 2010, Washington DC, USA (unpublished), available at http://eprints.lse.ac.uk/27684/1/The_second_wave_of_digital_era_governance_(LSERO).pdf . (Accessed May 1, 2011).Dunleavy, P., Margetts, H., Bastow, S., & Tinkler, J.. 2005. New Public Management is dead & long live digital-era governance. Journal of Public Administration Research and Theory 16: 467-494.

Drucker, P.F. (1988). The Coming of the New Organization, Harvard Business Review, 66(1):45-53.Eisenmann, T. R. (2008). Managing proprietary and shared platforms. California Management Review, 50(4), 31-53.Gassmann, O., & Enkel, E. (2004). Towards a theory of open innovation: three core process archetypes. In R&D management conference (pp. 1-18).Enkel, E, C Kausch & O Gassmann (2005). Managing the risk of customer integration. European Management Journal, 23(2), 203–213.Evans, D. D. S., Hagiu, A., & Schmalensee, R. L. (2006). Invisible engines. MIT Press.Farrell, J., & Katz, M. L. (2000). Innovation, rent extraction, and integration in systems markets. The journal of industrial economics, 48(4), 413-432.Fichman, R.G., (2004). Real Options and IT Platform Adoption: Implications for Theory and Practice. Information Systems Research 15, 132–154.Fishenden, J., Thompson, M., (2012). Digital Government, Open Architecture, and Innovation: Why Public Sector IT Will Never Be the Same Again. Journal of Public Administration Research and Theory.Fredberg, T., Elmquist, M., & Ollila, S. (2008). Managing Open Innovation - Present Findings and Future Directions. VINNOVA - Swedish Governmental Agency for Innovation Systems.Frey, K., Lüthje, C., Haag, S., (2011). Whom Should Firms Attract to Open Innovation Platforms? The Role of Knowledge Diversity and Motivation. Long Range Planning 44, 397–420.Galbraith, B., McAdam, R. (2011) The promise and problem with open innovation, Technology Analysis & Strategic Management Vol. 23, Iss. 1Gassmann, O., Enkel, E., & Chesbrough, H. (2010). The future of open innovation. R&D Management, 40(3), 213-221.Gassmann, O., & Enkel, E. (2004). Towards a theory of open innovation: three core process archetypes. R&D management conference (pp. 1-18).Gawer, A., & Cusumano, M. A. (2002). Platform leadership (pp. 252-254). Boston: Harvard Business School Press.Griffiths, D and AW Pearson (1973). The organisation of applied research and development with particular reference to the customer – contractor principle. R&D Management, Vol. 3, pp. 121–124.Gruber, M. & Henkel, J. (2006). New ventures based on open innovation - an empirical analysis of start-up firms in embedded Linux. International Journal of Technology Management, 33(4): 356-372.Hagiu, A. (2009). Two‐Sided Platforms: Product Variety and Pricing Structures. Journal of Economics & Management Strategy, 18(4), 1011-1043.Halchin, L. E. (2004). Electronic government: Government capability and terrorist resource. Government Information Quarterly, 21, 406-419.Harhoff, D., Henkel, J., & Von Hippel, E. (2003). Profiting from voluntary information spillovers: how users benefit by freely revealing their innovations.Research policy, 32(10), 1753-1769.Heeks, R., & Bailur, S. (2007). Analyzing e-government research: Perspectives, philosophies, theories, methods, and practice. Government Information Quarterly, 24, 243-265.Heeks, R. (1999) Reinventing Government in the Information Age. Routledge, London.Henkel, J. (2006) Selective revealing in open innovation processes: The case of embedded Linux. Research Policy, 35(7): 953-969.Hernon, P. (1998). Government on the Web: A comparison between the United States and New Zealand. Government Information Quarterly, 15(4), 419!443.Ho, A. T. (2002). Reinventing local governments and the e-government initiative. Public Administration Review, 62(4), 434-441.Hogge, B., (2010). Open data study. A report commissioned by the Transparency and Accountability Initiative, available for download at: http://www. soros. org/initiatives/information/focus/communication/articles_publications/publications/open-data-study-20100519.Huizingh, E. K. (2011). Open innovation: State of the art and future perspectives. Technovation, 31(1), 2-9.Iansiti, M., & Levien, R. (2004). The keystone advantage: what the new dynamics of business ecosystems mean for strategy, innovation, and sustainability. Harvard Business School Press.

Irani, Z., Love, P.E., Elliman, T., Jones, S., Themistocleous, M., (2005). Evaluating e-government: learning from the experiences of two UK local authorities. Information Systems Journal 15, 61–82.James, O., and Manning, N., (1996). Public Management Reform: A Global Perspective. Politics 16(3): 143-149.Janssen, M., Estevez, E., (2013). Lean government and platform-based governance—Doing more with less. Government Information Quarterly 30, S1–S8.Janssen, K. (2011). The influence of the PSI directive on open government data: An overview of recent developments. Government Information Quarterly, 28(4), 446-456.Kettl, D. F. (2002). The transformation of governance: Public administration for twenty-first century America. Johns Hopkins University Press.Kim, D. J., & Kogut, B. (1996). Technological platforms and diversification. Organization Science, 7(3), 283-301.Kirschner, M., & Gerhart, J. (1998). Evolvability. Proceedings of the National Academy of Sciences, 95(15), 8420-8427.Kogut, B., & Kulatilaka, N. (1994). Options thinking and platform investments: Investing in opportunity. California.Kreiss, D. (2012). Taking our country back: The crafting of networked politics from Howard Dean to Barack Obama. OUP USA.Langlois, R.N., (2002). Modularity in technology and organization. Journal of Economic Behavior & Organization 49, 19–37.Layne, K., & Lee, J. (2001). Developing fully functional e-government: A four stage model. Government Information Quarterly, 18, 122!136.Lee, S.M., Hwang, T., Choi, D., (2012). Open innovation in the public sector of leading countries. Management Decision 50, 147–162.Lim, E.T.K., Tan, C.-W., Cyr, D., Pan, S.L., Xiao, B., (2011). Advancing Public Trust Relationships in Electronic Government: The Singapore E-Filing Journey. Information Systems Research 23, 1110–1130.Linders, D., Wilson, S.C., (2011). What is open government?: one year after the directive, in: Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times. pp. 262–271.Mayo, E. and Steinberg, T. (2007). The Power of Information: An Independent Review, available at http://www.epractice.eu/files/media/media1300.pdf;McNulty, Terry, && Ewan Ferlie. (2004). Process transformation: Limitations to radical organizational change within public service organizations. Organization Studies 25: 1389- 1142.Meneklis, V., Douligeris, C., (2010). Bridging theory and practice in e-government: A set of guidelines for architectural design. Government Information Quarterly 27, 70–81.Mergel, I. (2010): Government 2.0 Revisited: Social Media Strategies in the Public Sector, American Society for Public Administration, Vol. 33, No. 3, p. 7 & 10.Miozzo, M., Grimshaw, D., (2005). Modularity and innovation in knowledge-intensive business services: IT outsourcing in Germany and the UK. Research Policy 34, 1419–1439.Moore, M. H. (2005). Break-Through Innovations and Continuous Improvement: Two Different Models of Innovative Processes in the Public Sector. Public Money & Management, 25 (1): 43-50Mowery, D.C., (2009). Plus ca change: industrial R&D in the ''third industrial revolution''. Industrial and Corporate Change 18, 1-50.Nelson, R.R., Winter, S.G., (1977). In search of more useful theory of innovation. Research Policy 5, 36–76.Noveck, B. S. (2009). Wiki government: How technology can make government better, democracy stronger, and citizens more powerful. Washington, DC: Brookings Institution Press.O’Reilly, T., (2011). Government as a Platform. Innovations: Technology, Governance, Globalization 6, 13–40.Open Government Partnership (Sept. 2011), http://www.open govpartnership.org/sites/www.opengovpartnership.org/files/page_files/OGP_Declaration.pdf.Orszag, P. Exec. (2009) Office Of The President, Memorandum No. M-10-06, Open Government Directive, Available at: http://Www.Whitehouse.Gov/Sites/Default/ Files/Omb/Assets/Memoranda_2010/M10-06.pdf.

Parker, G. G., & Van Alstyne, M. W. (2005). Two-sided network effects: A theory of information product design. Management Science, 51(10), 1494-1504.Parkes, D. C. (2007). Online Mechanisms. In N. Nisan, T. Roughgarden, E. Tardos, V. Vazirani, (Eds.), Algorithmic Game Theory. Cambridge, U.K.: Cambridge University Press.Pearson, A.W, Green, T., & Ball, DF (1979). A Model for Studying Organizational Effects of an Increase in the Size of R&D Projects. IEEE Transactions on Engineering Management, EM-26(1), 14–21.Pekkarinen, S., Ulkuniemi, P., (2008). Modularity in developing business services by platform approach. International Journal of Logistics Management, The 19, 84–103.Reichman, J.H., Samuelson, P., (1997). Intellectual property rights in data. Vand. L. Rev. 50, 49.Robinson, D., Yu, H., Zeller, W., & Felten, E. (2009). Government data and the invisible hand. Yale Journal of Law & Technology, 11, 160.Rochet, J. C., & Tirole, J. (2003). Platform competition in two‐sided markets. Journal of the European Economic Association, 1(4), 990-1029.Rochet, J. C., & Tirole, J. (2004). Two-sided markets: an overview. Institut d’Economie Industrielle working paper.Rothwell R & Zegveld, W. (1985). Reindustrialisation and Technology, London: Longman.Sawhney, M. S. (1998). Leveraged high-variety strategies: from portfolio thinking to platform thinking. Journal of the Academy of Marketing Science, 26(1), 54-61.Schelin, S. H. (2003). E-Government: An overview. In G. David Garson (Ed.), Public information technology: Policy and management issues (pp. 120!137). Hershey, PA: Idea Group Publishing.Seifert, J. W., & Relyea, H. C. (2004). Do you know where your information is in the homeland security era. Government Information Quarterly, 21, 399!405.Simon, H. A. (1976). Administrative behavior (3rd ed.). New York, NY: The Free Press.Storper, M. (1993) Regional "worlds" of production: Learning and innovation in technology districts of France, Italy and the USA. Regional Studies, 27: 433-456.Storper, M. (1995). The resurgence of regional economies, ten years later: The region as a nexus of untraded interdependencies. Journal of European Urban and Regional Studies, 2(3): 191-221.Storper, M. (1997) The regional world: Territorial development in a global economy. New York: Guilford Press.Suber, P., (2009). Open access in 2008. Journal of Electronic Publishing 12.Tallman, S., Jenkins, M., Henry, N. & Pinch, S. 2004. (2004) Knowledge, Clusters and Competitive Advantage, Academy of Management Review, 03637425, Apr2004, Vol. 29.Terwiesch, C., Xu, Y., (2008). Innovation contests, open innovation, and multiagent problem solving. Management Science 54, 1529–1543.Tiwana, A., Konsynski, B., Bush, A.A., (2010). Research Commentary--Platform Evolution: Coevolution of Platform Architecture, Governance, and Environmental Dynamics. Information Systems Research 21, 675–687.Trott, P., Hartmann D. (2009) Why “open innovation” is old wine in new bottles, International Journal of Innovation Management, 13 (4), pp. 715-736Ulrich, K. (1995). The role of product architecture in the manufacturing firm. Research policy, 24(3), 419-440.United Nations, & American Society for Public Administration (ASPA). (2002). Benchmarking e-government: A global perspective. New York, NY: U.N. Publications.Von Hippel, E. (1990). Task partitioning: An innovation process variable. Research policy, 19(5), 407-418.Von Hippel, E. (2005). Democratizing innovation: The evolving phenomenon of user innovation. Journal für Betriebswirtschaft, 55(1), 63-78.Von Hippel, E. & Von Krogh, G. (2006) Free revealing and the private-collective model for innovation incentives. R & D Management, 36(3): 295-306.West, J. (2003). How open is open enough?: Melding proprietary and open source platform strategies. Research Policy, 32(7), 1259-1285.West, J. & Gallagher, S. (2006). Challenges of open innovation: the paradox of firm investment in open-source software. R & D Management, 36(3): 319-331.Wheelwright, S. C., & Clark, K. B. (1992). Creating project plans to focus product development. Harvard Business School Pub..

Whitney, D. (chair) and the ESD Architecture Committee (2004). The influence of architecture in engineering systems. Engineering Systems Monograph, MIT Engineering Systems DivisionYildiz, M. (2003). A general evaluation of the theory and practice of e-government (In Turkish). In M. Acar & H. Ozgur (Eds.), Cagdas Kamu Yonetimi-1 (pp. 305!328). Istanbul: Nobel Publications.Yildiz, M., (2007). E-government research: Reviewing the literature, limitations, and ways forward. Government Information Quarterly 24, 646–665.Yu, H., Robinson, D., (2012). The New Ambiguity of’Open Government’. Princeton CITP/Yale ISP Working Paper.