Unpacking Open Innovation

Highlights From a Co-Evolutionary Inquiry

Kenneth A. Loparo, Kenneth A. Loparo, Manlio Del Giudice, Maria Rosaria Della Peruta

• Publisher: Palgrave Macmillan
• Year: 2013
• Print ISBN: 9781137359322
• eBook ISBN: 9781137354372
• Topic: Negocios y empresa
• Subtopic: Estrategia empresarial

Disintegrated or distributed innovation, collaborative innovation, collective invention, collegial innovation, free innovation, open knowledge disclosure, free knowledge disclosure: are these all the same thing? This shows us there is some confusion regarding open innovation, or at least there is a need to cast a wider net around what open innovation is all about. The prevailing thought is that open innovation allows organizations to simultaneously expand their breadth of ideas, opportunities, and know-how while minimizing the technical and market risks associated with innovation. As a result, open innovation appears to come with little down side. Del Giudice, Della Peruta, and Carayannis fill the gap in our understanding of this emerging research field of open innovation. Their work depicts the major tendencies of publications through identifying the main themes in literature and investigating the research frontier. It also discusses potentially important fields of investigation that are still left rather unexplored.

CHAPTER 1

OPEN INNOVATION IN MANAGEMENT SCIENCE

Elias G. Carayannis

There are different sources of open innovation. A classical one is knowledge spillovers, which arise when firms can capture knowledge or information “in the air,” as Marshall put it. Recently, there has been an upsurge in the so-called “open source” phenomenon whereby knowledge and information are distributed openly by their producers, in a context where the production and distribution of knowledge are governed by well-defined norms (e.g., Lerner and Tirole, 2002). An “old” form of open source is open science, which is again based on clear norms of production and diffusion of knowledge (Dasgupta and David, 1994). Open science, and particularly the proximity of firms to universities or other scientific institutions, have themselves been considered sources of knowledge spillovers (e.g., Alcacer and Chung, 2007).

(Gambardella, 2010, p. 85)

The concept of open innovation was introduced by UC Berkeley professor Henry Chesbrough, who has become famous worldwide due to his work Open Innovation—The New Imperative for Creating and Profiting from Technology, which was published in 2003. The scholar showed how, in the past century, highly innovative ideas were generated by firms that strongly invested in internal research and development and hired top professionals. These ideas were protected by an effective intellectual property (IP) strategy. Generally, a virtuous circle of innovation was activated, since profit was reinvested in R&D (Chesbrough, 2003a) (figure 1.1).

In the old model of closed innovation, enterprises adhered to the following philosophy: Successful innovation requires control. In other words, companies must generate their own ideas, then develop, manufacture, market, distribute and service those ideas themselves. For most of the 20th century, that model worked well, as evidenced by the spectacular successes of central R&D organizations such as AT&T’s Bell Labs.

Today, though, the internally oriented, centralized approach to R&D is becoming obsolete in many industries. Useful knowledge is widely disseminated, and ideas must be used with alacrity. If not, they will be lost. Such factors create a new logic of open innovation, in which the role of R&D extends far beyond the boundaries of the enterprise. Specifically, companies must now harness outside ideas to advance their own businesses while leveraging their internal ideas outside their current operations.

H. W. Chesbrough (2003b) “Open Innovation: The New Imperative for Creating and Profiting from Technology”

Figure 1.1 Going beyond to the innovation

Nevertheless, in the last years of the twentieth century, innovation management changed due to several reasons, in particular, (1) the number of knowledge workers increased together with their mobility and (2) venture capital became increasingly available. As a result, the closed innovation process in companies started to fall apart (Chesbrough, 2003a).

Some other reasons pointed out by Chesbrough (2003b) are as follows:

• Widespread circulation of useful knowledge

• Firms’ inadequate exploitation of available information

• Loss of ideas that are not immediately used

• An unsupportive business model, on which the importance of an idea or a technology depends

• Alteration of the innovation process by the presence of venture capital

• The need for firms to be active sellers and buyers of IP

Hence, an open innovation model was developed, according to which companies commercialize both external and internal ideas by implementing specific routes that lead to and from the market. In Chesbrough’s words (2003a, p. 37), “the boundary between a firm and its surrounding environment is more porous, enabling innovation to move easily between the two.” In a similar process, projects can ensue from internal or external sources and new technology may be deployed in different phases. Moreover, the ways projects reach the market can vary; besides the classical sales channels, it is possible to start up a spinoff venture or resort to out-licensing (Chesbrough, 2003b).

PRINCIPLES OF OPEN INNOVATION

According to Chesbrough (2003a), open innovation is founded on the following principles:

• Intelligent people do not all work in-house and therefore external knowledge is required.

• Significant value may be created by external R&D.

• Research profitability is not exclusively associated with internal work.

• “First to market” is less important than a strong business model.

• Both external and internal ideas are fundamental to win.

• For a company it is important to capitalize on its own IP and purchase external IP when necessary (figure 1.2).

West, Vanhaverbeke, and Chesbrough (2006, p. 286) defined open innovation as “both a set of practices for profiting from innovation and also a cognitive model for creating, interpreting and researching those practices.” Chesbrough (2006a) has argued that two anomalies in previous research on innovation have been overcome by open innovation. First, the spillovers are no longer considered as something to avoid but as a direct result of the business model; second, the IP rights are no longer deemed as a tool for protection but as a new class of assets. The current business model may benefit from both.

Moreover, five key themes in research were identified (Chesbrough, 2006b):

• The business model—value is generated within the value chain and captured in part by focal firms due to its two important functions, discussed in the next section.

• External technologies—they fill the gaps and enable the manufacture of complementary products that allow technology to be more rapidly accepted, so the company’s business model is leveraged.

• Complexity of knowledge identification, evaluation, and incorporation—knowledge management and connections appear increasingly relevant.

• Start-ups—they represent experiments with business models, as they carry new technologies and allow exploration of new markets.

• IP rights—by this means ideas and technologies can be easily transferred.

In the industry of open source software development (OSS), some open innovation models were initially developed and later transferred to more general open innovation practices. An OSS project involves a decentralized community of volunteer developers who collaborate to produce a software product using Internet-based tools such as e-mail, mailing lists, Web-based concurrent versioning systems (CVS), and bug-reporting software. To date, OSS researchers and practitioners have been primarily interested in three sub-areas of research: (1) individual developer participation; (2) competitive dynamics; and (3) innovation processes, governance, and organization [see von Krogh and von Hippel (2006) for a summary of these areas] (figure 1.3).

“Open Innovation follows a long tradition of studying the processes of innovation, and stands on the shoulders of many previous scholars” (Chesbrough 2006a, p. 5).

As Pavitt (2002, pp. 119–120) emphasized:

So far, this writer has been unable to find a simple or elegant theoretical framework to encompass the richness of the empirical material on corporate innovative activities. However, in organising this material, it has proved useful to divide the processes of innovation into three, partially overlapping, processes each of which is more closely associated with contributions from particular academic disciplines.

• Producing scientific and technological knowledge: since the industrial revolution, the production of scientific and technological knowledge has been increasingly specialised, by discipline, by function and by institution. Here, history and social studies of science and technology have been the major academic fields contributing to our understanding

• Transforming knowledge into working artefacts: in spite of the explosive growth in scientific knowledge in this period, theory remains an insufficient guide to technological practice, given the growing complexity of technological artefacts, and of their links to various fields of knowledge. Technological and business history has made major contributions here and, more recently, so have the cognitive sciences.

• Matching working artefacts with users’ requirements: the nature and extent of the opportunities to transform technological knowledge into useful artefacts vary amongst fields and over time, and determine in part the nature of products, users and methods of production. In the competitive capitalist system, corporate technological and organizational practices therefore co-evolve. These processes are central concerns of scholars in management and economics.

Figure 1.2 On processes of innovation

OSS communities are open in the sense that their outputs can be used by anyone (within the limits of the license) and anyone can join merely by subscribing to an e-mail list. Openness in terms of membership leads, in turn, to transparency in the development process, since communication about projects and their direction largely occurs in public. Thus, project leadership is accountable to the wider community for its growth and future direction, and everyone is aware of shortfalls and issues. Transparency also affords individuals self-determination with respect to the level of effort they choose to expend and awareness of others’ efforts that they might be able to fold into their own (Gulati, Puranam and Tushman, 2012, p. 579).

Figure 1.3 The emergence of OSS communities

According to West and Gallagher (2006), three fundamental challenges of open innovation may be identified: motivation, integration, and exploitation of innovation. These were examined by the two scholars through a qualitative and quantitative analysis of OSS development.

Four generic open innovation strategies were detected:

• Pooled R&D and shared R&D, for which a cultural change is required

• Spinouts, which are a means of bypassing large companies’ bureaucracies

• Selling complements, which means agreeing to commoditization or developing different types of products according to different commodities

• Using donated complements, which means that differentiated products can be developed by users thanks to the availability of general-purpose technologies

The open innovation model is becoming widely adopted in many industries nowadays. For example, in the pharmaceutical industry, open innovation has become one of the most significant trends. In the area of pharmaceutical research, Henderson and Cockburn (1994, p. 67) have shown that the ability to “encourage and maintain an extensive flow of information across the boundaries of the firm” is important to the productivity of the process of drug discovery. In fact, pharmaceutical firms have realized that it is too expensive to have all competences in-house, so they have begun to focus on the most important, including technology platforms and therapy areas, and collaborating at the same time with the right partners.

In their study on pharmaceutical firms, Bierly and Chakrabarti (1996) uncovered four generic knowledge strategy groups— “explorers,” “exploiters,” “loners,” and “innovators”—and found that firms with a good balance of both internal and external learning with a tendency toward more radical learning (i.e., “innovators” and “explorers”) exhibited consistently higher levels of profitability (figure 1.4).

Different interesting implications result from the issue of whether a company gains its knowledge from sources inside or outside the organization, and how the different acquisition behaviours affect the propensity to innovate. A number of researchers have analyzed the knowledge sourcing schemes implemented by companies, reaching the conclusion that both internal and external sources of knowledge are on the same level of importance. Iansiti and Clark (1994) studied the automobile and mainframe computer industries, finding that considerably high performing companies were actively involved in internal and external integration. In their research on the lithotripsy industry, Nagarajan and Mitchell (1998) revealed that the methods of knowledge acquisition were responsible for different types of technological shifts. This means that for encompassing and complementary changes the companies relied on inter-organizational relationships, while for incremental shifts they trusted in internal Research and Development. Nobel and Birkinshaw (1998) analyzed communication and control in international R&D operations, revealing that international creators, who were more responsible for innovation than improvement and adjustment, preserved effective internal and external networks of relationships. This means that they were able to acquire knowledge from external sources, and implement coordination and communication across organizational sub-units. In their study on the retail food industry, Rulke et al. (2000) ascertained that store managers based their organizational self-knowledge on both internal and external sources of information. In their research on the optical disk industry, Rosenkopf and Nerkar (2001) discovered that technological developments were highly influenced by explorations extended along both organizational and technological boundaries.

Figure 1.4 Knowledge sourcing schemes and inn...

Table of contents

• Cover
• Title Page
• Copyright
• Contents
• List of Figures
• Introduction
• 1. Open Innovation in Management Science
• 2. Open versus Closed Innovation: Speculating about the Future of Technology Management
• 3. Invention, Inventiveness, and Open Innovation
• 4. Open Innovation or Collective Invention? Conceptualizing the Debate
• 5. Openness That Matters: Net Generation, Higher Education, and Student Entrepreneurship
• 6. On the External Dimension of Business Knowledge Flows: “Markets for Knowledge Resources”
• 7. What Open Innovation Is: Local Search, Technological Boundaries and Sustainable Performance in Biopharmaceutical Experimentation
• Index