Authur: Mokhtar Amami

Excerpt from from Amami, M., “Open Innovation and Web technologies”. Mediterranean Conference on Information Systems, Samos (Greece), 3-5 September 2015. AIS Library

The Global and dynamic competitive business environment is forcing private and public organizations to look beyond their traditional boundaries for new ideas, new innovations, and reliable and innovative network of suppliers. During the last decade Open Innovation (OI) has been the focus of academia and professionals due to their ever-increasing role in time-based competition, customer satisfaction of tomorrow needs, shrinking innovation cycles and rising customer expectations.

OI is a relatively a new paradigm shift for business enterprises (Chesbrough, 2003; 2007a, 2007b) that aims to seize the potentialities of the web and abandon innovation secrecy paradigm to a kind of paradigm of knowledge sharing. The ultimate goal is to expand markets for external use of innovation (Chesbrough, 2006, 2011), reduce costs of internal innovation and capture the widely distributed knowledge in order to buy/license inventions/Innovations or processes from other businesses.

Although open innovation is attracting more and more researchers, the main problems, however, of creating ideas and sharing them along the supply chain are hard to resolve. In the same token, scanning and capturing new technologies through a web of inventors and startups, or any other channels that can be used as the basis for technology transfer, internal development and joint development exploration and exploitation are even much harder. Granted, a vertical and stable supply chain “à la Toyota, BMW or Walmart” makes the transfer and joint development relatively easy. In fact, the pivot (Toyota, etc.) in this kind of vertical and stable supply chain control the microcosm of process innovation from suppliers to consumers. Suppliers’ involvement in new product development in this type of supply chain is well known and well documented. However, they are still underused, and their innovation process is far from integrated in an open innovation process model.

The open innovation process model is much more challenging than the ecosystem of the vertical and stable supply chain. The pitfalls of this rising model are somewhat numerous.
The new open innovation process model requires new management competencies for managing fuzzy boundaries, inter-organizational relationships, inter-organizational constraints, and bottlenecks. Second, it requires the development of web based OI strategies to scan and channel ideas, knowledge, and innovations from varieties of actors distributed around the globe and integrate them in an open innovation process that expand markets through Licensing/Buying, Spin-off and Joint Development.

There are key central problems that must be analyzed, evaluated, and harnessed in order to seize the opportunities of OI strategies. These are absorptive capacity, complementary assets, intellectual property (IP) and control, networks and the rise of Peer-Production and Network Externalities and Dominant Design.

Absorptive capacity

Absorptive capacity is critical to organizations to open their internal R&D and start transacting ideas, scientific and technological knowledge across their frontiers. Organizations must have the

capability to scan, identify technological opportunities, assimilate, and integrate them in a profitable business model. Cohen & Levinthal (1990) already underlined this capability of absorptive capacity for firms to generate gains from recognizing, assimilating, and adopting external knowledge. Recently other researchers have arrived at similar conclusion. Networked companies with high scientific and technical competencies tend to favor OI. Silicon Valley (SV) is an illustration of this phenomenon. The performance of SV cluster is the concentration of high scientific and technological skills that materialize in intense knowledge exchange and fast innovations and adoption (Saxenian, 1999; Kenny & Burg, 1999; Castilla et al., 2000). Absorptive Capacity can be developed by focusing on the following dimensions:

Awareness: Awareness requires the development of specific processes by which an organization scans for weak signal and uncover knowledge and emerging technologies.

Association: Association requires processes by which an organization uncovers the value of new ideas, prototypes, products, or emerging technologies

Assimilation: Assimilation requires the design of processes that fit organizational design by which the organization dissimulate and debate these new ideas, prototypes, products, or emerging technologies to create, capture and deliver value to customers.

Adoption and Implementation: Adoption and implementation requires the development of processes by which an organization transacts ideas, products, or technologies for competitive sustainability.

Complementary Assets

Complementary assets (CA) are those capabilities (apart from those underpinning the technology) that firms need to exploit the technology (e.g., manufacturing, marketing, reputation, complementary technologies, brand names, supply chain networks, etc.).
The main idea, Teece asserts, that the more complementary assets a company possesses, the more likelihood the company will take advantage of sourcing external scientific and technological knowledge. Teece (1998) distinguished two types of complementary assets: freely available and unimportant and tightly held (kept proprietary) and important. The appropriability regime determines the importance of gains that companies can derive from external knowledge sourcing. Large companies with large assets pool of complementary assets (CA) and tightly held are more oriented toward sourcing external knowledge. The large pool of CA provides potentialities of integrating external knowledge or buying start-ups or buying even large companies. CA, therefore, are important to commercialize innovations and collaborate with other companies.

Intellectual Property: Appropriability and control

Under the traditional innovation paradigm, secrecy, and control of intellectual property (IP) are the driving force for a company’s ability to capture innovation value. Under the new paradigm of organizing Innovation (Open Innovation), the risk for loss of IP control increases particularly when innovation exchange flows are with competitors (Greenhalgh & Rogers, 2010). The dilemma of OI is not easy to overcome if the firm avoids developing a kind of understanding and trust relationships based on adaptability to market and technology shifts and alignment of business interests.
IP control and protection refers to the extent to which technology can be protected from imitation. Control and protection depend on the degree to which scientific and technological

knowledge is tacit (non-codified). IP control and protection depend on the kind of appropriability regimes: “tight” (e.g., Coca-Cola recipe) vs “weak” (e.g., standard consumer electronic).

Networks and the Rise of Peer-Production

Metcalf’s Law states a network’s value grows proportionately to the square of the number of nodes within the network. Although one can dispute the accuracy of this law, intuitively it can provide the most casual observer with insight into the value of networks. Today, all organizations and individuals recognize the value of networks. In the domain of OI the power of networks to source scientific and technological knowledge (buying and selling) is paramount. The creation and thoroughly designed networks can support the development of a kind of understanding and ultimately a community of trust.

Web technologies-based networks enhance inter-organizational relationships and interpersonal relationships (Johnson & Duxbury, 2010). These relationships are fundamental to cross- organizational frontiers resources exchange. This environment of web technologies-based networks facilitates the strategic roles of OI community drivers. They are external brokers, internal brokers, technology entrepreneurs (P&G), champions (e.g., CEO of P&G) and Capital Venture/Angel entrepreneurs, embodying competencies that allow them to manage cross- organizational relationships to facilitate bidirectional flows of scientific and technological knowledge. These drivers/leaders are key in diffusing technology, mobilizing volunteers, organizing social networks (Castella et al., 2000) and in managing issues such as technology path divergence (forking problems) and fragmentation of innovation process (balkanization problems) (Fleming & Waguespack, 2007). OI environment requires reputation and trust from OI community leaders to create and sustain an Open Innovation Ecosystem. The key roles of these leaders allow them to resolve issues through social brokerage in connecting OI actors and technological boundary spanning through a process of scanning, identifying, translating, and relaying scientific and technological knowledge across organizational frontiers (Fleming & Waguespack, 2007). Because of their key roles as organizational frontiers spanners, OI community hold a higher degree of trust. Because they have an early access to information and knowledge, they have enormous impact on technology diffusion and control. They can develop and implement varieties of strategies to different groups in an effort to hedge on alternative development. Case studies (e.g., P&G, Peugeot, PG, Coca Cola, etc.) and literature review seem to suggest companies that invest in technology gatekeepers not only enhance the flows of scientific and technological knowledge but can immerse themselves in a OI ecosystem that support strategic technological sustainability.

Web technologies fostered a new mode of production system that helped the emergence of the rise of the commons and new mode of producing and channeling information and knowledge. The old alternative modes of production, Markets and Hierarchies, are characterized by either high coordination costs or production costs. Web technologies support groups of individuals collaborate on large-scale projects following a diverse cluster of motivational drives and social signals. This web based emerging collaboration is characterized by both low coordination costs and low production particularly when the object of production is information or culture. Because of web technologies and the wide diffusion of computers, communications capabilities, and increasingly mobile technologies, OI community will play in the future a major role in scientific and technological knowledge exchange among organizations.

The rise of the commons favor peer-participation where community membership is characterized by anti-credentials and there is no a priori selection criteria for participation (Bauwens, 2006).

Low barriers to participate increase the pool of participants and increase the probability of solutions to problems and particularly the new flow of ideas. Moreover, the lower costs (almost null) associated with peer production allow OI community to play fully their roles without organizational financial constraints.
Web technologies-based peer production foster diversity of theories, ideas, and perspectives and consequently improve quality outcomes through interactions in innovation open ecosystem. Peer production system can be characterized by independence, pluralism, representation, decentralized decision-making, and autonomous participation (O’Mahony, 2007). This environment of production can provide scientific and technological contribution to firms that invest in gatekeepers.

Network Externalities and Dominant Design

Network externalities effect occurs when open innovation increases the participation of users which increases the value of products for more users. On the demand side, the telephone service illustrates the network externalities. The benefit that people get from the telephone service depends on the extent to which other people also use this service. In other words, network externalities effect happens when “the attractiveness of a product to customers increases with the use of that product by others” (Fisher & Rubinfeld, 2000). Firms with dominant design (standard system) tend to gain enormously from direct network externalities (when an increase in the size of a network increases the number of others). They tend also to gain from indirect network externalities (when an increase in the size of a network expands the range of complementary products available to the users of the network). The more people who adopt the same standard system, the more services, and applications the user can access, and so the greater the value of that system to each individual user. On the supply side the firm with the largest network tend to achieve increasing returns to scale because the cost of developing and maintaining the network can be spread over a large and increasing growth of the system or product.

In OI environment network externalities or network effects has a profound impact. The dominant design which is the source of network effects tend to favor an open innovation ecosystem to increase the direct and indirect effects. The more users (organizations or individuals) interact with each other, the more ideas and knowledge creation to improve the system and consequently the more the network will increase in value. The increase in the size of network will tend to create an environment of creation of new ideas and knowledge that benefits the creation of more complementary products.

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SSRN: https://ssrn.com/abstract=247520 or http://dx.doi.org/10.2139/ssrn.247520