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This chapter highlights a particularly challenging arena for knowledge governance, by focussing on the issues associated with large-scale R&D programmes of ‘open innovation’. The chapter develops a theoretical framework for analysing these governance challenges by focussing on the interplay between the knowledge processes and inter-organizational relationships involved. This framework is subsequently applied to a case-study of a major open innovation programme, namely, a major inter-firm research programme sponsored by the European Union (EU) in the aerospace sector. Analysis of this case suggests that the stability and fit of governance mechanisms may be less important than their ability to adapt to the dynamics of the innovation process, and particularly to shifts between the open and closed networks which offer very different routes to appropriating value from that process.

This chapter reviews the core ideas behind Open Innovation, discusses what it is and is not, and shows how it can deliver more value to organizations and to society. Outside-in Open Innovation strengthens the current business and current business model, while inside-out Open Innovation searches for alternative businesses and business models. The chapter explores the connection between technology development and the business model, and examines the use of Open Innovation in intellectual property and in services. However, Open Innovation is not a panacea. Its boundary conditions and limitations must also be acknowledged. As with Chapter 1, the processes of generation in innovation must also be supported by equal attention to innovation dissemination and innovation absorption within the firm, in order for organizations to create and capture value from Open Innovation. Finally, Open Innovation is moving beyond collaborations between two actors, to a broader ecosystem focus that connects many actors together.

The chapter explores the growth, scope, and impact of the academic literature that has arisen since the publication of Open Innovation back in 2003. Moreover, the chapter further clarifies and develop the conceptualization of open innovation, which it defines as a distributed innovation process based on purposively managed knowledge flows across organizational boundaries, using pecuniary and non-pecuniary mechanisms in line with the organization’s business model. On this basis, the chapter then discusses divergent views on open innovation and it calls for greater consistency in future research. Next, the chapter addresses some of the critiques on the notion and development of open innovation as they have emerged in the literature so far. Finally, the chapter considers the progress open innovation research has made, relative to the research agenda identified in Chesbrough, Vanhaverbeke, and West (2006), and extend the possible research subjects and units of analysis.

This chapter integrates the conclusions of the different chapters into a coherent picture. The chapters outlined how open innovation research should evolve in their particular research area. The chapter integrate these ideas and crosslink them to each other, but it also focuses on topics that have not been covered and, in its opinion, still deserve more attention in the future.

Small and medium-sized enterprises (SMEs) have been excluded from the mainstream discussion in open innovation research. However, SMEs can benefit from openness, but existing findings on open innovation in large firms cannot be directly transferred towards the SME sector. This chapter sets the stage for future research on open innovation in SMEs and discusses four key areas of future open innovation research in SMEs: IT-enabled crowdsourcing in SMEs for involving a large number of unknown “outsiders,” the importance of different kinds of networks when SMEs engage in open innovation, the interplay of IP management and open innovation, and the internal dimensions of managing open innovation in SMEs.

This chapter examines the tools, participants, and tensions associated with open innovation projects. It explains three types of the innovators in open innovation: core inside innovators, outside innovators and peripheral inside innovators. It describes innovation contests, innovation markets, communities, toolkits, and technologies that leaders might use to increase smart contributions to their innovation efforts. This chapter also highlights the need for innovative leaders to learn from those who have successfully balances open and closed innovation.

The Introduction discusses the impact of the Great Recession upon innovation spending, and with it, a rethinking of how companies can and should innovate. Open Innovation itself has been affected by the recession, and is sometimes used now as a synonym for outsourcing or cost cutting, which was not the intention of the original concept. A renewed understanding of Open Innovation is needed to unlock its potential to deliver growth, rather than simply cut costs. The role of innovation infrastructure, both for the overall society and for the focal organization, is emphasized as a key to renewing growth through innovation. The Introduction goes on to describe the plan of the book, and introduces the three facets of innovation: generation, dissemination, and absorption. Four possible paths for reading the book are outlined, for practicing managers of innovation, for innovation policy makers, for academic scholars, and for very time-pressed readers.

Open innovation and user innovation share certain key precepts, but differ in key values and assumptions, as well as the phenomena they study. Here this chapter studies an important area of overlap: firms incorporating innovations from individuals. The chapter extend previous conceptions of the “coupled” mode of open innovation to cover such firm-individual interactions, to include interactive co-creation outside the boundaries of the firm. From this, the chapter presents a process model for interactive coupled open innovation that comprises four phases: problem definition, finding participants, external collaboration, and leveraging the collaboration results.

This chapter evaluates the application of open innovation to education. It summarizes the experiences of the University of Erlangen-Nuremberg in helping students overcome the well-known, but still dominant, barriers to innovation and to train them to develop an open innovation mindset. It analyzes what type of teaching methods can be used to support students in becoming open innovation ambassadors and argues that educating students to become open innovation ambassadors requires universities to rethink their own approach to teaching and to open themselves to a new generation of innovators.

Open Innovation can be a powerful engine for growth, if properly managed. P&G was an early, powerful trendsetter in achieving growth from Open Innovation. Open Innovation also can be valuable as a tool to enable environmental sustainability, as seen by Enel and Carlsberg However, even organizations who embody effective Open Innovation practices can have trouble sustaining growth over time. Practices that initially led to strong growth have been followed by periods of declining revenue, or even bankruptcy. Both Qwirky and P&G have struggled to sustain growth via Open Innovation. Open Innovation requires a certain mindset to sustain growth over time. Following the best practices alone may not keep the company ahead of its competitors. Following Open Innovation principles may prove more enduring.

This chapter examines the role of open science and open innovation in the sourcing of knowledge by firms, through interactions with universities. Three main modes of such interaction are identified: IP licensing, research services, and research partnerships. These interactions highlight the importance of relationship-based modes of interaction. Some of these relationship-based interactions enable appropriation via intellectual property rights, while others are more aligned with the norms of open science and create benefits for firms by generating basic knowledge, creating skills and enabling follow-on innovation.

Open science is a powerful way to discover and disseminate new knowledge. But the very norms that animate open science can sometimes inhibit its subsequent commercialization. There exists a Valley of Death between the culmination of a scientific project, and the later commercial use of that science. While a fundamental knowledge of how a technology works may have been achieved, there is far too little known for businesses to invest in developing that knowledge further. And the best use of a new discovery often is unknown to those who first discover it. This is where open science must start to give way to Open Innovation. IMEC and CERN’s ATTRACT project provide two examples wherein a strong culture of open science co-exists with a thriving Open Innovation culture as well to traverse the Valley of Death

This introductory chapter discusses the theme of this volume which is about open innovation (OI). This volume explores OI’s search for smart people who might expand the space for innovation and describes the broad canvas of OI practices, its participants, and future promise. It identifies five trends that lie behind OI as an important strategic option and discusses the proposed prerequisites of contemporary OI projects. It also explains the distinction of OI from invention and explains the two types of OI. The first is self-organized and self-motivated collaborative activity to achieve a common goal and the second is organizational strategy to broaden innovation boundaries.

This chapter examines issues concerning open innovation users. It analyzes user innovation in different organizations and shows that innovations occur in many different settings. It contends that people responding to their own and others’ needs can be the source of smart ideas but it is the “lead users” that are often more visionary and more effective in helping organizational leaders understand trends in the market. This chapter also suggests that open user innovation is an institution that competes with and can displace producer innovation in many parts of the economy.

Open innovation and open business models are two concepts that have been launched by Henry Chesbrough (2003a; 2006a; 2007b). The chapter develops a classification scheme through the combination of open–closed innovation and traditional vs. open business models. Furthermore, the chapter considers new product development or new business development as just one specific driver for competitive advantage. Product innovations may not be an option for companies producing commodities but their competitive drivers may be affected by product innovations of their (technology) partners. Reframing open innovation in this way allows us to shed light on innovation networks in which the instigators of the network are for instance customers or complementors (but not the innovators themselves) are benefitting. This approach results in a general classification scheme for open innovation research. The simplicity of the structure should make it attractive as a starting point for new developments or application areas in the open innovation literature.

In spite of the rapid expansion of the open innovation phenomenon in business and the great research interest in this topic over the past decade, only limited attention has been paid to the international dimension of open innovation. Such a gap is a surprise given that large numbers of firms engaged in open innovation are multinational corporations (MNCs). Although recent international R&D literature sheds light on the role of location-specific factors in the global open innovation cycle, i.e., the sourcing and leveraging of globally dispersed knowledge, the research streams on global R&D and open innovation have typically been treated as two separate intellectual endeavors. We argue a need to incorporate insights gained from the global R&D literature and suggest how open innovation literature can contribute to the research on global R&D management in the future.

There are many similarities in how firms pursuing an open innovation strategy can utilize crowds and communities as sources of external innovation. At the same time, the differences between these two network forms of collaboration have previously been blurred or overlooked. In this chapter, we integrate research on crowds and communities, identifying a third form—a crowd–community hybrid—that combines attributes of both. We compare examples of each of these three network forms, such as open source software communities, gated contests, crowdsourcing tournaments, user-generated content, and crowd science. We then summarize the intrinsic, extrinsic, and structural factors that enable individual and organizational participation in these collaborations. Finally, we contrast how these collaborative forms differ regarding their degree of innovativeness and relevance to firm goals. From this, we identify opportunities for future research on these topics.