Part III Open Innovation Strategy of Firm
7 Dynamics of Open Innovation
7.2 Model Building
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at knowledge and technology in the knowledge-based age. In other words, what is required is a direct analysis of concrete dynamic processes at a corporate level.
Thus, this chapter seeks to identify how evolutionary technology management and strategy, i.e., open innovation technology management strategy at the corporate level evolves in a complex adaptive system.
For these reasons, we need to develop a theoretical concept model that can explain the processes from open innovation of new ideas or technology, to the appearance of dominant design, and the evolution of national innovation system, RIS, or SIS. The growing body of literature on strategic alliances, the virtual corpo-ration, buyer-supplier relations, and technology collaboration indicate the impor-tance of external integration and sourcing (Teece et al. 1997). Namely, there is a growing necessity to analyze the dynamic process of open innovation, and that is the subject of this study.
Corporate open innovation goes through evolutionary stages in the market, blooming into various types and levels of emergence or being influenced by strange triggers, under complex adaptive systems. The basic locus of evolution is a market.
Corporate open innovation shows up as dominant design thanks to various evolu-tionary factors (e.g., economies of scale and scope, economics of networks, and open business models). After all, corporate open innovation creates market lock-in, by initiating path dependence and forming the technology regime.
The degree of corporate open innovation creates a variety of evolutionary effects according to the degree of complexity of the complex adaptive system.
In the case of A in Fig. 7.2, the degree of corporate open innovation is high, and the degree of complexity of the complex adaptive system (CAS) is high as well. The degree of complexity of the CAS is high and has two meanings. One is that the openness to a new product is great, because customer fascination with such prod-ucts is high. The other is that the production and distribution of new knowledge and technology are brisk, because the capacity for research and development (R&D), as well as the technology of various agencies in the system, is great. In other words, the openness of the innovation system itself is great, because the strange trigger of the CAS is robust. In the case A firm in Fig. 7.2, a firm fully commits to global open innovation, which brings about continuous evolutionary change.
In the case of B in Fig. 7.2, though the degree of corporate open innovation is high, the degree of complexity in the CAS is not as great. Here, there are consider-able difficulties in connecting the fruit of corporate open innovation with evolution-ary change. In this case, firms are gradually confronted with limits to performing open innovation activities at a high level of energy. Here also the fruit born by the
Evolutionary Change - Locus: Market
- Momentum of Evolution Economics of Scale and Scope: Supply Economics of network: Demand
Open Business Model: Supply and Demand - Result of Evolution
Dominant Design, Technology Regime Open Innovation
- Agent: firm, institution Etc.
- Channel: collaborating, licensing
acquiring, merging etc.
- Direction: inbound, outbound - Degree: incremental, radical
Complex Adaptive System - Entity: NIS, RIS, SIS
- Degree of Emergence Differentiation
Changing of dominant design and firms Emerging of new sector
- Strange trigger
Fig. 7.1 OCE model concept
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open innovation activities of the firm are neither acknowledged by the customers of the innovation system itself nor supported by technological capability, and the firm faces difficulties owing to the discord between the products of the firm and its mar-ket. In this regard, a firm needs to develop an open innovation system appropriate for it, and concentrate on it, or it needs to adapt its own open innovation for the CAS in which it is involved.
In the case of C in Fig. 7.2, not only the level of corporate open innovation but also the degree of openness of the CAS is low. There is little reason to hope for enhancement of the corporate open innovation and openness of the innovation sys-tem, without external stimulus or institutional change. In this case, a corporate strat-egy aimed at enhancing the degree of open innovation should be developed and political measures taken at the same time to increase the openness of the CAS.
Specifically, R&D programs should be developed to directly improve corporate open innovation, to establish cooperative research with university and national research institutes, and to promote the employment of excellent research personnel.
Further, at the level of national innovation, it is also necessary to introduce various technologies and to invite excellent R&D personnel from abroad, to promote par-ticipation in global R&D programs, and to concentrate on nurturing domestic R&D personnel through attendance at famous foreign universities with a focus on research. In addition, at the level of sectorial and regional innovation, it is necessary
Fig. 7.2 The relationship between open innovation and complexity of system 7.2 Model Building
to prepare political measures to enable improvements in system openness and complexity.
The situation indicated by D in Fig. 7.2 is typical of most current, cutting-edge enterprises, corporate giants, and technology-based small and medium-sized enter-prises (SMEs). The openness of the innovation system is low, and the degree of its complexity is high. For this reason, new corporate products fall into the commodity trap so that the life cycles of new technology are already very short or they face the danger that the technology life cycle will be shortened. Such firms have no option other than to keep creating new knowledge, technologies, or ideas, through continu-ous, active open innovation. As the openness of an innovation system is low and the degree of its complexity is high, it is impossible for firms to make technology inno-vation sufficient to keep rival firms from overtaking them or to completely protect their own technologies with patents. Firms have no choice but to form corporate organizations, to develop corporate strategies, to build a corporate production sys-tem aimed at continuous open innovation, and to build open innovation into the entire product life cycle.
As mentioned above, open innovation creates evolutionary change through cor-porate activity and coevolution with the CAS. Corcor-porate open innovation activities influence the innovation system itself and, at the same time, are influenced by the innovation system, which brings about resonance and coevolution with other firms influenced by the innovation system.
The OCE model can be proved and analyzed by using documents, case studies, surveys, and social experiments (e.g., ultimatum game or iterated prisoner dilemma).
Further, the OCE agent-based model (ABM) can be built to simulate real situations.
Normally, agent-based models occasion the problem of validity inevitably (Carcia et al. 2007). Such approaches as a conjoin analysis have traditionally been used to secure the validity of agent-based marketing models.
Using the OCE model, more accurate analyses can be made of the long tail phe-nomena gradually increasing in online and mobile markets (e.g., e-books and music). It is possible not only to make a direct analysis and explanation of open innovation of firms related to crowd sourcing, or of the gradual increase in collec-tive intelligence in diverse fields (e.g., Wikipedia, Quirky, Threadless), but also the increasing profits occurring at App Store and the like. The OCE model is also very useful for analyzing major fields in which open innovation of firms is occurring (e.g., smartphones, e-books, online music, pharmaceuticals, and consumer electron-ics). Open innovation in all the industries is gradually being strengthened thanks to continuous development of the knowledge-based economy. For this reason, it is expected that industries or sectors for which open innovation analysis of firms using the OCE model is intended will continue to increase in the future.
We will now assemble the OCE model in three stages. First, we will build up open innovation factors, processes, and their connections with complex adaptive systems (Yun and Mohan 2012a). Second, we will build up diverse complex adap-tive system factors and their relationships with open innovation and evolutionary change (Yoon and Lee 2009; Yun and Mohan 2012b). Third, we will construct
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evolutionary change resulting from the complex adaptive system and its interaction with open innovation (Malerba et al. 1999a, Malerba et al. 2008).
7.3 Construction of OCE Model