Prospects for the development of innovation networks. Prospects for the development of innovation networks An innovation network is characterized by
The openness of innovation networks of a matrix structure inevitably draws the surrounding innovation space into its orbit, strengthening regional component. This will transform regional competitive advantages. The latter are now associated with a movement of interspecific resources that consolidates hidden, informal knowledge, competencies, and corresponding networks. Regional competitive advantages now reflect not static, but dynamics of regional fundamental competencies, relevant technologies. The movement of knowledge in a special regional information space is characterized by a synergistic effect.
Pattern. The value of a creative intangible asset increases with the development of an appropriate network of informal creative relationships and communications.
Axiom. Informal knowledge moves through informal communications, which provide the shortest path for the movement of information and knowledge, relevant experience and its high speed. As a result, internal “transaction” costs are minimized.
Axiom. Dismantling chains of informal connections, informal communications, and the movement of information destroys the connectivity and diversity of network structures, and therefore the foundations of a network organization.
Axiom. A network leader is a professional who is in informal networks and constructs them.
Axiom. The presence of informal networks is a property of living knowledge and should be supported by discussion, respectively, the exchange of information and its interpretations.
Pattern. In the process of this exchange, new explicit and hidden knowledge is born, technological and organizational priorities are adjusted and new informal networks are self-organized. In the informal information space the movement of a resource itself is a process of its mutual enrichment.
Pattern. The high dynamism of innovation processes and their interdisciplinary nature lead to a gradual growth of informal knowledge and innovative action and with a high level of innovative connectivity to their predominance over the formal. This provides sustainability of competitive advantages and makes the innovation process open. As a result, it is possible to maintain and acquire competitive advantages only within the framework of an open innovation process and open innovation networks.
Open innovation networks presented various degrees connectivity. This can be an equal and multi-level partnership. Open networks are developing in two dimensions: the development of R&D and the commercialization of innovations.
Axiom. The transition to a new stage of the life cycle of an open innovation network involves a transformation of connectivity and involves new actors in it.
Pattern. Working in such networks allows you to gain skills and experience in solving project problems. Therefore, the involvement of regional organizations in such networks makes it possible to ensure the sustainability of regional development.
Axiom. There are two types of innovation networks: innovative processes of which are pulled by customer demand and networks pulled by technological development, new technological realities (technological networks), creating the need to develop their own R&D.
The two types of innovation networks use different marketing approaches. Demand-driven networks use response marketing, technology networks use creative marketing that shapes market demand. The two types of networks generate different types of innovation. Technology networks create proactive, discontinuous, high-risk innovations that shape new market sectors. This requires a high degree of connectivity between R&D, production, marketing and finance departments. The coordinators of this process may be new product managers or new product development departments.
The network regional economy, which forms the space of information exchange, develops according to the principles of a self-organizing dissipative system. In the process of such self-organization, information exchange performs a coordinating function. Communities of professionals participating in the exchange give birth to transformation leaders (passionaries). Active points of growth of new competencies attract traditional bodies of knowledge and enrich them. At these interdisciplinary points, exchange intensifies, a special intellectual space is formed, a multidimensional network of moving streams of living knowledge. This creates conditions for the emergence of attractors. Here, individual events of the past can precede the present and “lurk in wait for us from the future.” Innovative structures-attractors of the region represent the future of complex economic systems. Such systems will not succeed if they isolate themselves from the outside world. The presence of blurred boundaries with the external environment allows an elementary cell of the economy to enter a certain mesocommunity in which the attractor operates. Regional engineering infrastructure helps to transfer a new business process to a new scale. It is optimal if elements of the engineering external environment are directly connected to the basic innovation processes of enterprises located in the growth points of the megaregion.
The movement of technology is optimal in an environment of side information flows and know-how. This is where attractors appear. This is why complex innovation systems move along complex trajectories and are guided by vague possible paths of development (network effect).
Pattern. The main problem of modern innovation networks is the growing process of transforming innovative horizontal connections into vertical ones and their standardization. As a result, innovative leaders are endowed with additional routine bureaucratic functions, and formal communications are suppressed by informal ones. As small innovative groups become involved in a large-scale network, their innovative environment and culture are often destroyed by numerous rules, norms, bureaucratic guidelines, and bureaucratic control. The new reporting and control system eliminates a lot of initiatives and free contacts (external and internal).
Innovation networks become resilient if they successfully engage in “linking and consistent transfer of consumers.” The network effect here manifests itself in the fact that consumer loyalty to one product further spreads to other products. Product connectivity and product continuity create one of the foundations for expanding the innovation network. The consumer is in a creative, methodological flow, solving his innovative problems. This innovative connectivity is typical for the products of Microsoft and other IT technology companies. As a result, the innovative network ecosystem can acquire a global scale.
Development of innovative regional economy associated with the formation of qualitatively new network forms of organization. Without them, it is impossible to create breakthrough technologies. This problem characteristic of the Russian economy and management. Dmitry Sanatov, head of the project direction of the North-West Center for Strategic Research: “Russia has almost no rights to advanced processing technologies, we have practically not conducted R&D in this area (petrochemicals - author) for the last two decades and have fallen very far behind.”
Forms of innovation networks:
Consortium is a group of organizations that have common needs and combine their potential, for example, in joint R&D (Semiconductor R, Bell Corp.);
Mutual licensing of technology exchange.
The development of the region is associated with the action of innovative economies of scale. What is considered insignificant today may turn out to be fundamental tomorrow. Such a transformation of scale in the presence of innovative financial mechanisms and ways to increase the capitalization of companies is carried out extremely quickly. The speed of the information flow corresponds to the scale of its time vector. The movement of regional economic resources. This irrationality of the movement of resources makes it possible to increase the speed of their movement to attractor areas exponentially.
+Regularity. The innovation scale effect is associated with openness innovation complexes, innovation networks. The higher the openness, the more innovative scale.
For technology business companies, where the costs of R&D, modernization, and the introduction of technologies and competencies are extremely high, only entering global markets can provide a return on investment.
Modern researchers view innovation as an open, networked process. The first steps in this direction were taken by Henry Chesborough in the books “Open Innovation. Creating profitable technologies”, “Open business models. How to succeed in new innovative conditions." Chesbrough looks at the practicalities of implementing an open innovation strategy. This methodology was used to develop technology platforms - a new generation network innovation organization.
According to the theory and practice of open innovation, the innovation process has many levels of openness. This opens up access to the network to many innovative companies of different sizes, their divisions, and researchers. As a result, a special environment is formed, saturated with research and commercial organizations operating at various stages of the innovation cycle. At the same time, as we move to a new phase of the innovation mesocycle, partnership relations are being transformed. Thus, pioneers at an early stage take high risks and are therefore outsourced to the network or work in the network initially. Network collaboration in an open innovation network makes it possible to find common ground between the innovative and commercial interests of players of different scales, and to quickly adapt to new technological trends and consumer interests.
The transition from a closed innovation model to an open one will change the world. The network innovation organization is moving to a more multidimensional, dynamic form of development. The innovation value chain now extends beyond individual corporations. Innovation outsourcing deploys a network of innovation relationships, including complex commercialization mechanisms (in which the network revolution is also brewing). Excessive closedness and secrecy of information in the network economy leads to time delays, closing windows of opportunity and loss of competitiveness. New approaches are becoming possible thanks to effective intellectual property mechanisms and the emergence of tacit knowledge transfer schemes. Intellectual property can develop in a network information ecosystem and turns into a portfolio of living network assets. Now the first place comes not to the protection of intellectual property as an asset of a separate corporation or strategic alliance, but to the innovative selection of that part of the portfolio that corresponds to the network business model and that part that can be sold on the external innovation market. Another strategic problem is the exchange of tacit knowledge, which requires new network approaches. The latter are based on complex interdisciplinary innovative interactions that no longer fit within the framework of individual companies.
+Regularity. Interdisciplinary research and innovation trajectories are projected onto the market positioning of innovative companies and a cluster of market strategies. A new network mosaic business structure is being formed. The narrow positioning of individual companies is complemented by a presence in various cross-industry locations.
The work of company research centers increasingly serves the external market rather than the companies themselves. So the Xerox PARC Research Center for Lately sold 35 technology projects, many of which formed the basis for new companies and business lines. “The total market value of the companies that emerged from ... the eleven projects ... ended up being twice the value of Xerox itself.” This indicates that the potential capabilities of individual inventions and innovations are not always determined by manufacturing companies. An innovative vision is formed in companies in the external environment that have relevant experience and needs. If a company is ready to use certain smart products, it must find them in the appropriate market or order them. Such networking allows R&D to be dispersed across the network using innovation outsourcing. An example of this approach is Cisco, which has sharply reduced its own R&D, moving towards networked innovation collaboration.
Pattern. The intellectual property of a modern company acquires network qualities, dispersed throughout the innovation network, which has no clear boundaries.
A network built on atomistic, dynamic, renewing substances that have different life cycles allows the use of uncertainty as a resource. Gigantic and mechanistic structures are not able to withstand uncertainty; they are fenced off from it by artificial barriers, conservation of the artificial environment, and the reproduction of retrospective rituals. This leads to disasters that destroy such formations to the ground (the crisis of 1929-33). Network structures make it possible to quickly switch the resources of disappearing “atoms”, opening up new opportunities. The new generation innovative network uses tools that allow you to use a package of changing alternatives and switch from one alternative to another. This is what increases the capitalization of the network. Business models are used that can develop in the environment of subcontracts and outsourcing contracts, external licensing of unrealized projects, and venture syn-off companies.
+Axiom. The demand for applied innovation is derived from the demand for fundamental innovation. This connectivity of needs creates the basis of transfer network relations. The interaction of fundamental and applied innovation needs forms the source of innovation networks of various scales.
We are talking about the interaction of breakthrough, new and modifications of old technological flows that form the basis innovation networks of three levels. The movement of fundamental technologies is most effectively carried out in global networks (first-level networks), national/mega-regional (second-level networks) and regional (third-level networks). The presence of three network structures implies three types of synergistic effects in the economy. Accordingly, each type of network differs not only in the scale of information and resource flows, but also in specific forms of exchange and self-organization, institutional elements, infrastructure and the nature of technology transfer. In an innovation region, as scale decreases, network density increases. With three levels of networks, the economy of a country or region becomes innovative – a continuous, super-dense space of innovation networks is formed here. Thus, development simultaneously goes both in depth and in breadth.
The most important institutions innovation networks of the first type are scientific schools. They form information flows, which constitute one of the foundations of clusters of the first type. If scientific schools are destroyed (as we had with genetics and cybernetics), the country and regions limit the possibilities of increasing their wealth.
++Axiom. A condition for creating a new technological order in the region is the presence of appropriate scientific and engineering schools, infrastructure for transforming fundamental knowledge into applied knowledge, as well as institutions for the commercialization of new technologies.
++Axiom. Scientific schools should be monitored in the region. The destruction of the latter leads to structural degradation and is a harbinger of approaching disasters.
++Axiom. Scientific schools can only be sustainable in global research networks and are reproduced only in the process of network participation in international research projects.
Through global innovation networks, intellectual products of world-class scientific schools can move, which in the innovation infrastructure adapt to the needs of innovative producers. This forms first-level competitive advantages, creates new growth points, new technological structures, global brands, and NT enterprises with a high level of added value and capitalization. The regions participating in this are being integrated into global innovation value chains. This is done through the participation of regional companies in global innovation network projects. The secrecy of fundamental science, secrecy stamps, and legal actions against leading scientists are steps that destroy the competitive advantages of the first level. In addition, this makes it difficult to develop a vision and modern strategies. In order for regions to involve applied science and the innovative community of entrepreneurs in global networks, it must create an image of trust and “open up” to the world. Networks of the first type include and use the infrastructure for commercializing innovations. The financial flows that move in this infrastructure are long-term and have special instruments that support commercially promising innovative projects. This financial scheme is missing a key link - the investor investing long-term money. Namely, such an investor, as a participant in the capital market, provides long-term liabilities to the balance sheets of companies. Other actors in the capital market are long-term financing institutions (insurance, pension). The Russian market is dominated by short-term investment instruments. This hinders the development of innovation networks of the first type.
First-level networks are represented by global innovation networks, which, based on a self-improving information space, form sectors of new technologies and software. Such networks are capable of gaining a critical mass of human and financial capital, which creates the opportunity for the development and promotion of high technologies. One example of such a network is Siemens PLM, which uses software developed at Boeing and Airbus. These are also global networks related to interdisciplinary space research and environment, global warming and population aging and their corresponding cross-sectoral interactions.
Innovative second level networks (country, megaregions) obey global networks. They do not have a global, but rather high macroeconomic level and require the presence of a mega-regional innovation infrastructure. Currently, the latter is absent in most Russian regions. This is one of the reasons for the lack of second-level innovation networks. As a result, innovation areas are isolated from most of the regional economy, and innovation complexes are deprived of their basis. The exchange of innovative experience is extremely limited, most scientific and innovative teams work behind closed doors, and even products obtained through industrial espionage are not brought to industrial development. Internships for students and teachers in the largest world and national, regional scientific and engineering centers are reduced to a minimum; there is a gap between science and business. Smart products are not adaptable to industry needs. There is no machine-building engineering belt of the regional economy. The work of enterprises with intellectual products is institutionally difficult.
Innovative third level networks are of particular interest in information society. Their appearance indicates the presence of a continuous innovation space in the region and country, in which fundamental competitive advantages realize themselves at the regional level in diverse processes of innovation diffusion. Under these conditions, regional innovation complexes are capable of cluster organization. Innovation clusters enhance the effect of innovation attractors, creating new windows of opportunity. This is a prerequisite for the development of third-level networks and innovation areas in the region. In the absence of these networks, the synergy of industrial and innovation processes is impossible.
A prerequisite for the formation of networks of the third type is the activation of network growth points - a set of network counterparties that ensure high dynamics of economic growth in the region. They contain gazelle companies. This is a localized space, saturated with entrepreneurial initiatives and organizational innovations. New regional business chains are developing at growth points. Since they are characterized by a high degree of uncertainty, vertical relationships here are limited in nature; excessive bureaucratization of these processes neutralizes the dynamics of the development of horizontal partnership network relations and mutual initiatives. Self-organization here is a key process and has a number of features. At growth points, meso-level business processes are self-organized, using interspecific resources of the region, so that supplier-consumer chains develop themselves. These chains incorporate new links, increase their scale, and disperse geographically (the effect of an unwinding spiral).
At growth points there are innovative fluctuations that can move the network to a higher innovation level. In a transforming innovation system, tension accumulates, so that any small event (fluctuation) can cause an exponential deployment of a new network. In the chaos of innovation, products that can become standards for the development of DS chains and new technological priorities crystallize. As a result of the localization of innovation systems in which chaos is overcome, an innovation circuit is organized - the movement of resource flows.
The innovation network of the third level is a self-organizing information field of competencies and technologies of the meso-environment. Its participants themselves establish the rules and order of relations among themselves in the process of work. Stimulated by external influences, they themselves more or less consciously develop them in the process of analyzing the situation, evaluating alternatives, and making decisions. An element of this mesoenvironment is a modern company, its SBU. In the restructuring, highly dynamic environment of third-level networks, a company, in the process of frequent changes, loses clear boundaries and brings its structures and functions, human capital and organizational culture into line with new trends. Dissolving in the external environment, the company gradually forms a network structure, allowing it to acquire the properties of a dissipative structure located on the border of chaotic states. Time management in these conditions becomes more complicated, since it is based on the ambiguity of the future, the presence of moments of instability associated with the complication of choosing from a variety of development alternatives. It is the network form of organization, self-organization that most closely matches the characteristics of such a dissipative system.
Axiom. The modern innovation network is dynamic and is represented by innovative events and a flow of innovative projects. The latter is generated by the connectivity of innovative leaders - carriers of new competencies and is pulled out by innovation-oriented consumers.
An example of the connectivity of innovative leaders, which became the basis of the network core, is the cooperation of the Apple project team with innovators Philips, Ideo, General Magic, Connectix, WebTV in order to create the breakthrough product iPod. Portal Plaier, Wolson, Toshiba, Texas Instrument were involved in such a project network for the development of technical design, which became the basis of a network strategic alliance. Further, the network expanded as the successful promotion of the product was realized. The multi-level nature of network interaction indicates various decentralized processes, which, if they penetrated the hierarchical structure, melted vertical connections of subordination into horizontal creative connections of exchange of experience and information.
Axiom. After the completion of an inter-corporate innovation project, the innovation network disappears. Innovators are dispersed among other innovative projects, taking into account existing and new experience.
Axiom. The inter-project interval during inactivity can lead to a depreciation of a person’s capital. The interproject interval turns into a special object of economic analysis. During the inter-project interval, it is important to maintain contact with carriers of global competitive advantages (internships, etc.) in order to understand what is happening in new windows of opportunity, what are the main project actions and trends.
Axiom. The presence of a well-organized inter-project interval not only develops human capital, but also forms the potential for new project connectivity and opens up opportunities for entry into global network ecosystems.
Axiom. An innovative inter-corporate network, if there is a positive result, transforms into a three-dimensional ecosystem. Some innovators serve strategic business units formed on the basis of an innovative project. For some time, an innovative product turns into an innovative and information standard, overgrown with training programs and processes, intellectual property products, information technologies, driven by professional bureaucracy. With successful commercialization, prototypes of an innovative product turn into mass products. As a result, large-scale OS, driven by a mechanistic bureaucracy, a technostructure.
Regional innovation networks
Axiom. A regional innovation network appears in an organic type economy (in which organizational organic systems predominate). In an economy of a mechanistic type (dominant giant linear-functional and divisional structures), horizontal innovative ties are built in special “oasis” areas that encourage the development of small and medium-sized innovative entrepreneurship.
Axiom. In a mechanistic economy, R&D systems are centralized and separate from the process of commercializing inventions. This leads to spatial unevenness of the innovation process. Regions in which R&D is concentrated and regions creating innovative products are geographically separated.
“If the leading regions for creating innovations include Moscow, St. Petersburg, Novosibirsk, Tomsk. Nizhny Novgorod, then to the regions that are leading in the use of innovations - Novgorod, Samara, Perm, Tatarstan, etc.”
Axiom. Integration of the processes of creating innovations and their commercialization is the starting point for the formation of innovation networks.
Axiom. The innovation network of an individual company and its immediate environment represents a consistent process of developing an innovative product. A regional innovation network usually includes several basic processes of parallel development innovative products and related infrastructure (new product design, marketing, communications, innovative production).
In the regional innovation network, parallel development and production of a cluster of innovative products is carried out.
Pattern. The increasing complexity of the technological and production processes of the industrial economy, their saturation with non-standard, changing elements and modules create the inevitability of spatial localization R&D at points that are crossroads of technological and production flows - clusters and corresponding industrial productions.
The experience of modern industrialization in China confirms this pattern. First, the world's manufacturing giants located their divisions here, then innovative strategic business units (elements of the matrix structure) and then fragments R&D– networks.
Axiom. Investments in regional innovation networks operating in the field of a new technological order have a large multiplier effect if ecosystems of previous technological orders are present in the region.
Regional innovation networks operating in the field of a new technological structure create demand for goods and services from a number of high added value chains, activating both old and new points of regional growth.
Network core business processes
Axiom. Network basic processes include, firstly, processes scientific research, forming the basis of new technological structures and corresponding chains D; secondly, processes OCD, design development of innovations, documentary and organizational and technological support for the release of prototypes of innovations; Thirdly, engineering processes that provide a new scale of innovative action; fourthly, processes commercialization innovations; fifthly, the processes of growing ecosystems with network interactions of innovative actors.
Network basic business processes include: generating knowledge, generating ideas, generating project initiatives, forming project teams, creating prototypes, organizing operational activities, investment processes, establishing chains of relationships with consumers.
Interactions with the consumer are extremely important. An example of such successful interaction is the network structure of EDS, which is a conglomerate of temporary project teams. The latter include consumers. " Related friend With each other, EDS project teams form a network in which each group can seek help and advice from any other group, as well as from any functional division of the company. Thus, a kind of knowledge lever is created.”
Related information.
There are two approaches to assessing the role of organizational networks in the implementation of innovation activities.
1. According to supporters of the first position (the main provisions of which are set out in the works of David Thies), only strong and integrated organizations can successfully and systematically carry out innovative activities. Looser coalitions consisting of joint ventures, alliances or virtual partners are not capable of carrying out systemic innovations, not to mention developing standards for them or monitoring their further development.
2. Proponents of another approach (the main conclusions of which are outlined in the articles of Paul de Laag) argue that, as industry structure changes from vertical to horizontal and “digital convergence” takes place, systemic innovation today can only be carried out by allied networks of organizations. Although such networks are vulnerable to “opportunism,” they are capable of developing and implementing systemic innovations because mutual relationships can be stabilized by various forms of both procedural and substantive commitments.
In other words, it is necessary first of all to understand the following: should innovation activities be carried out by individual organizations or within the framework of strategic alliances and networks of organizations. In this context, two types of innovation are distinguished: autonomous and systemic.
What is the difference between autonomous and systemic innovations?
Autonomous innovations can be built into the system without any additional approvals or adjustments. Examples of such innovations are faster microprocessors or larger computer memories.
System innovation, on the other hand, requires significant adjustments to different parts of the system. Not one, but many complementary innovations must be implemented simultaneously and applied throughout the chain of system elements. Examples here include electronic funds transfer, instant photography, jet aircraft, CD, personal computer.
Thus, in the works of D. Thiis and other supporters of the first approach, it is argued that if an organization intends to carry out innovations on a systematic basis, then the only organizational solution that guarantees success is the integration of all necessary activities within the organization itself (see, for example,). In this case, it is necessary to avoid alliances, joint ventures, etc. Note that D. Thiis does not claim that creating networks of organizations in general is not attractive. It clearly and openly recognizes the merits of networks of organizations in the case of autonomous innovation. It is only for the systemic nature of innovation that full integration within one organization is argued to be the preferred method.
Supporters of this position identify a number of organizational agreements, forms for carrying out innovative activities and rank them in accordance with such a criterion as the “amount” of organizational control that is characteristic of them.
The list of organizational forms (in descending order of organizational control), in their opinion, is as follows:
. integrated organization;
. organizations with autonomous divisions;
. joint venture;
. association (alliance);
. virtual organization.
Thus, an integrated organization is seen as the strongest of all possible forms control, while the virtual organization tying together external activities, provides the least amount of control. It should be noted that this emphasizes that a network (whether a joint venture, an alliance or virtual partners) can be considered as strong a form as an integrated organization if there is a dominant leading organization in the network.
What contributes to the formation of allied networks of innovative organizations?
However, it seems increasingly elusive that a single organization can design a system for the future, let alone create universal standards for it. There are several forces that encourage innovative organizations to create alliances and virtual networks, the most significant of which are often recognized as: the development of horizontal structures in industries, the trend of digital convergence, and increasing R&D costs.
The development of horizontal structures in innovative industries is most significant in the computer sector. Back in the 1970s. there was a vertical structure there. Vertically integrated organizations sold computers general purpose that dominated the market were IBM and DEC. Gradually, a new, more horizontal structure emerged in which companies are limited to the production of system components, such as microprocessors, personal computers, operating systems, application software, etc. Currently, competition exists within horizontal layers between component manufacturers. Such fragmentation appears to be detrimental to systemic innovation. Their development must be coordinated throughout the system, vertically, as it was before, to harmonize the different layers. The only possible way is to create networks to unite partner organizations. In the old days, IBM could transform the system by transforming itself; Today, the most appropriate approach is through networks of organizations.
What does digital convergence mean?
The trend of digital convergence reinforces the above-mentioned trend of development of horizontal structures in innovative industries. The boundaries between industries such as computer manufacturing, telecommunications, consumer electronics, leisure and publishing are rapidly disappearing or becoming porous.
As all major processes by their nature gradually become digital, controlled by computers, the significant differences between them disappear. The explosive growth of the Internet may be the best example. This trend has important implications for industry competition. Existing firms may enter new areas, increasing overall competition, leading to a chain reaction. Facing new competitors, other organizations are also forced to expand into new, broader areas. Moreover, the need to be at the level of technological progress leads to the expansion of alliances, associations, and their expansion beyond the boundaries of the industry.
Of course, for now this is only a trend and not a rigid pattern. The markets still remain fairly separate, with different firms represented. IBM is still a computer company, and Philips is still primarily a consumer electronics supplier. But the differences are becoming increasingly blurred and vague. It is important to emphasize that the trend of increasing digital convergence and all its consequences are relevant to the problem of systemic innovation - their significance is significantly expanding. An organization that intends to innovate systemically has no choice but to develop an external network (now horizontal) and try to reach parts of the system outside the areas where the organization already operates.
Increased R&D costs. In the past, R&D costs have never been an important motivator for strategic alliances. The motives for creating associations at that time were the primary desire to expand markets and enter new ones, as well as technological complementarity, complementarity, and reducing the period of time required for the implementation of innovations. However, during recent years the costs of innovation have risen sharply. As a result, it is expected that the lack of financial resources will force organizations to more actively develop partnerships.
This trend is clear for autonomous innovation. A good example is the development of dynamic memory chips (DRAM). Development costs for each subsequent generation doubled. We should not forget that the costs of building factories are also rising. It's no surprise that organizations are looking to develop partnerships. Thus, Toshiba works together with IBM, Siemens, Motorola; Hitachi with LG Semicon and with Texas Instrument; Fujitsu and Hyundai; a NEC with Samsung. Extrapolating from this trend, it should be noted that rising costs are also characteristic of system innovations.
Thus, a generalization of these trends allows us to conclude that the implementation of innovative activities increasingly makes it necessary to form networks of innovative organizations.
How and by whom are standards set for the results of systemic innovation?
What about the standard setting process? Are they necessary at all? And if so, will they be offered by individual organizations or groups of organizations? Thus, D. Ioffe argues that in the era of digital convergence, communications and interactions within networks are extremely important. They would be significantly hampered by the simultaneous, parallel existence of a large number of standards. Consumers would react negatively to a situation where there is no dominant design.
To ensure that adoption of the standard is not hampered, no innovative company should try to protect its own technology design to the point of exposing it to other companies. There needs to be an open approach to standards where other companies are fairly licensed to copy. The more systemic the innovation, the more necessary such an open approach is.
Will such system standards be established by individual organizations or groups of companies? The last option seems to be the most possible. Once organizations come together to pursue systemic innovation and the need for a standard becomes apparent, they have no choice but to continue to partner and try to establish a dominant and open standard. In order to generate maximum support in all areas, they are forced to expand the alliance of organizations as much as possible, which leads to the formation of an allied network of organizations. An individual organization can only hope to strengthen a global standard by skillfully weaving strategic alliances. The result is that, in a mutually competitive environment, one of the allied networks of organizations sets the standard.
As described above, it appears that the standard setting process is primarily a matter for commercial organizations. Do government agencies have any role in this matter? Since it is clear that, at least initially, there is no consensus, government agencies tend to avoid imposing a standard, preferring to leave the problem to market forces themselves. However, there are ways in which the state can influence this process. If government agencies account for a large share of the demand, then the format that the government offers can play a significant role in setting the standard. In addition, market competitors themselves, at some period of time, may show interest and ask government agencies to intervene in solving the problem (see, for example,). Therefore, government bodies may actually be involved in this process both as a participant and as an arbitrator.
It should also be noted that the phenomenon of the formation of alliances and associations has changed the overall picture and the nature of competition. Competition now takes place primarily between networks of innovative organizations, rather than individual organizations, as was the case before. Moreover, organizations begin to compete for advantageous partners when forming networks; each of them strives to “steal away” the best partners before competitors do so. Proactive partnerships are becoming the norm (see, for example,).
Similar conclusions about the growing need for organizational networks are being made both in business circles and in management science. Ray Noorda, former CEO Novell company, introduced a new term “competition”, which can be translated into Russian as “competition”, since it is obtained by adding the first part of the word “cooperation” (cooperation) and the second part of the word “competition” (competition). The introduction of this term points to the ubiquitous phenomenon of competitive cooperation between organizations. The corporate model of the future, according to some experts, consists of internal networks of branches and external networks of strategic alliances, all of which relate to the global level (see, for example,).
Thus, it appears that the implementation of systemic innovation increasingly depends on the creation of coalitions of partner organizations. It is not one integrated organization as a center of power, but a more fragmented coalition of partners with multiple centers of power that drives the innovation process.
How can we improve the sustainability of networks of innovative organizations?
Of course, this creates the danger of “opportunism”, i.e. the fact that each partner will strive to get as much as possible and contribute as little as possible. It is not surprising that there are many complaints about cooperation within associations in the field of R&D (see, for example,). Partners often skimp on the contribution of their specialists: “Let other partners use their best specialists first! The knowledge gained by each partner will then be expropriated and used to enhance joint competitiveness. In this case, the “devastation” begins already at the R&D stage.”
Associations created for the purpose of implementing systemic innovations are especially vulnerable to opportunism. There are two main reasons for this.
. An entirely new interconnected system must be created, requiring intense face-to-face collaboration across organizational boundaries. This in itself opens the door to opportunism; the innovative organization becomes transparent.
. It is necessary to consider the type of knowledge involved in the system innovation process. Partially, this will be codified, formalized knowledge, for which legal protection tools are applicable. If a patent has been obtained or copyrights have been effectively implemented, then to a certain extent the innovation can be protected from expropriation. Contractual agreements (conditions requiring confidentiality, limiting the use of information that has been disclosed) may also be used. However, most of the knowledge and know-how involved in system innovation is tacit. Such knowledge cannot be easily absorbed or copied by others. It is for this reason that in order for innovation to occur, tacit know-how must be demonstrated openly and repeatedly to partners. Such intensive interactions involve strategic risk because it is very difficult to control how much tacit knowledge is actually absorbed and expropriated by partners. Since tacit knowledge cannot be specified in any formal sense, it appears that there are no legal or procedural means of protecting it.
However, the experience of R&D partnerships over the past two decades has led to the development of a number of mechanisms that can stabilize and strengthen the relationships between partners in an innovation network. These are mainly various forms of obligations that partners undertake. They voluntarily provide assurances that they will adhere to agreements honestly. Two types of such obligations can be distinguished: material, real and procedural.
What are the forms of real and procedural obligations of innovation network partners?
Material, real obligations of partners of innovation networks. Throughout history, material obligations have been actively used. For example, when concluding a treaty, kings sent their sons as hostages or handed over fortified castles as collateral. What is the corporate equivalent of such real, tangible obligations?
First, organization-specific knowledge must be made known to partners. As noted above, especially in systems innovation projects, this can "open the door" to opportunistic behavior - knowledge that has been disclosed can be expropriated. But there is another side to the coin. This sharing of knowledge is not only a risk, it at the same time represents an investment in a relationship that cannot be undone. Secondly, of course, it is necessary to take into account investments in research equipment, buildings, etc., which also tie the hands of investors.
Here are a few examples that, although related to autonomous innovation, illustrate the latest statements. Toshiba and Motorola began working together in 1986. The agreement between them required Toshiba to share its know-how on memory chips, and Motorola to share its knowledge about microprocessors. Moreover, both companies agreed to build a joint plant in Japan in order to use the knowledge they exchanged. Such obligations, which are largely irrevocable (they cannot be canceled), of course, bound the partners, which determined the duration of their cooperation.
Similar to IBM, Siemens and Toshiba in the late 1980s. joined forces to conduct R&D to develop dynamic memory chips. At first, researchers from the three firms only exchanged some knowledge, which could not be called close cooperation. However, in 1992, the task was set to develop the next generation chip, which was a very expensive task, since it required $1 billion for R&D and $3 billion to build factories. But in addition to these investments, such an alliance implied the sharing of the latest know-how. To do this, a team of 200 specialists was created, representing these three companies, who worked in the new IBM research center near New York. It is obvious what this represented effective way“linking” these companies. Later, Motorola joined this alliance and also sent its researchers to this center.
In addition, the association of partners can also occur through the purchase and exchange of shares of each other. This intertwining of equity capital creates connections that discourage opportunism. Partners become interdependent - by harming a partner, the company harms itself. If the partners are approximately equal in size, then both take part in each other's share capital. However, if there is a difference in size, then, as a rule, it is advised to buy shares only to the larger partner and thus demonstrate their dedication, loyalty to the agreement.
So, the main attention in the analysis of networks of innovative organizations has so far been paid to the creation of associations in the field of R&D. In actual practice, many innovative companies not only have such alliances with several partners, but also often enter into several alliances with each partner. Most players in innovation markets support dozens and even hundreds of alliances at the same time.
In addition, as many experts note, in practice, the formation of alliances does not just happen at random; there is usually a tendency to create clusters or groups of innovative organizations, which often interact with each other. The formation of such groups of organizations automatically provides for more mutual guarantees. In this case, the stability of networks of innovative organizations often increases for the following reasons. First, if two organizations (A and B) have a whole set of agreements with each other, then this serves as a kind of mutual guarantee, since if you put one agreement at risk, you risk putting the whole set at risk. Secondly, if organization A, by violating the agreement, infringes on the interests of organization B, then the latter has at its disposal effective weapons to discipline the violator - organization B may threaten to reveal to the public the opportunism of organization A. As a result, the entire cluster of relationships of organization A may disintegrate - if not immediately, then after some time. A tarnished reputation is difficult to restore, and membership itself or acceptance into the community of a given cluster may be at stake in the present and future.
Procedural obligations of innovation network partners.
In addition to real commitments, organizations strive to find ways to bind each other through procedures that limit potential opportunism. Of course, in every alliance, as a rule, there is some form of agreement or contract. If things go badly, the partners can go to court. Therefore, litigation constitutes a kind of main line of the approval procedure. However, contracts cannot effectively address the vague, uncertain characteristics of R&D alliances. Therefore, organizations gradually developed other forms of procedures (see, for example,).
Thus, organizations often try to involve not a judge, but another figure to resolve conflicts. In advance, the partners agree on mediation in case of complications in the situation. Such a mediator must make every possible effort and use all means to restore agreement between the partners. He is not bound by legal restrictions and can act more flexibly, although he may not have any power. A stronger figure is the arbitrator, the arbitrator, in whose person mediation and power are combined, since the partners ex ante promise to respect his decisions. However, mediation and dispute resolution by an arbitration court or arbitration are all forms of special intervention, the entry into the matter of a third party as a consequence of a far-reaching conflict. Therefore, as a more radical approach, the appointment of a “guarantor” as a third party who would monitor the partners’ cooperation at all times is often considered. The guarantor should be hired from outside, such as industry associations, government agencies, research institutes, universities, etc. At the same time, its powers must be clearly defined.
Of course, these agreements do not exhaust the possibilities for limiting opportunism in allied networks of innovative organizations. Thus, an interesting method is the so-called Chinese wall, which, however, is only used for alliances in the field of R&D in the case of carrying out innovative activities on a separate third site. Typically, each partner sends a certain amount researchers to work on a joint innovation project. They constantly exchange knowledge with each other. However, a lot of effort is usually put in by project participants to obtain know-how that could be quickly applied in their home company. This is achieved mainly through mechanisms for staff rotation at such research sites and visits to these sites by teams of employees from participating firms. But this knowledge “repatriation” policy creates strong incentives to cheat. Participating innovative companies may choose to “go it alone” at some point. To prevent this kind of renegade, apostasy, it is recommended to build a “Chinese wall”, i.e. suspend the repatriation of knowledge back to your company until the innovation project is completed. Although such agreements are extremely rarely used in practice, experiments in this regard seem interesting and promising.
It must be emphasized that real and procedural obligations are the most common guarantee mechanisms that can be used in various types of alliances of innovative organizations. They protect against many types of opportunism. But their applicability depends on the specific characteristics of the alliance. For example, shared knowledge can serve as a form of real commitment if close R&D collaboration is a central element of the alliance. As noted earlier, interlocking equity will only be beneficial if the partners are approximately equal in size; if there is a size discrepancy, then it is preferable for the larger partner to unilaterally purchased shares. The construction of a “Chinese wall” makes sense only if the mutual exchange of know-how is intensive and constant, and the partners are also active competitors.
Examples
Reasons for geographical concentration of firms
There are three main reasons for the geographic concentration of firms.
- First reason is associated with the opportunity to benefit from the distribution of costs for maintaining and developing resources common to several companies.
- The second reason comes down to geographic proximity itself, which ensures low cost and fast delivery of a product or service necessary for a business.
- Third reason is that the concentration of firms within one area contributes to the spread of tacit knowledge, that is, that knowledge and experience that cannot be easily formalized and transferred, and is closely tied to the people who carry it. Thus, according to MacDonald, " Individuals' work for firms and much of their value to employers lies in their network membership, but network membership is a fundamentally personal matter that transcends firms and even loyalty to firms." (Macdonald, S. (1992) “Formal Collaboration and Informal Information Flow.” International Journal of Technology Management, 7(1/2/3): 49-60).
Geographical proximity to some extent facilitates the exchange of this tacit knowledge, and also allows the creation of a market for qualified labor, which allows, instead of organizing the transfer of knowledge, to involve the holder of the knowledge into the ranks of the company. It is these circumstances that explain that individual species crafts or approaches to craft are usually developed and practiced within strictly limited territorial limits.
Likewise, the possibility of informal communication between company representatives and product consumers located in its area is also important.
Thus, Geographical proximity is important not for the dissemination of formalized scientific knowledge, but for the dissemination of less formal tacit knowledge.
Numerous examples from world practice confirm that the cluster form of production organization is the most prepared for the innovation process.
The long-term decline in transport and communication costs has an ambiguous effect on geographic concentration. On the one hand, the importance of geographic proximity for the successful interaction of firms is partially reduced. On the other hand, the transfer of tacit knowledge continues to be based primarily on personal contact, and low transport and information costs contribute to a further division of labor on a global scale and regional specialization.
Renowned economist Michael Porter gave a different explanation for the geographic concentration of companies. In his opinion, the root cause is competition. If a highly competitive company appears on the local market, the choice for others becomes extremely tough - either increase their competitiveness or leave the market. A community of firms with very high competitiveness is gradually emerging. By entering other regions and foreign markets, these firms easily destroy local competitors who have not passed such a strict selection process. As a result, the industry market is dominated by a cluster of firms concentrated in one territory.
Two purposes of using the concept cluster
Concept cluster can be used both for analysis purposes and for practical purposes.
In the first case, a cluster is an alternative object of study and, in particular, forecasting to an individual enterprise or industry.
In the second case, the cluster is an object of support within the framework of regional development strategies, the developers of which often provide measures for the formation of clusters, counting on the fact that clusters increase productivity, innovation, competitiveness, profitability and employment in firms located in a given region.
Characteristic features of a cluster
The characteristic features of the cluster are:
- maximum geographical proximity;
- relatedness of technologies;
- common raw material base;
- presence of an innovative component.
Cluster policy
Activities to support clusters are called “cluster policy” and usually include:
- eliminating barriers to innovation;
- investments in human capital and physical infrastructure;
- supporting the geographic concentration of related firms.
Typically, cluster policy is seen as an alternative to anti-competitive measures of traditional “industrial policy”, which supports specific enterprises or industries.
Critics of cluster policy point out that:
- concentration of production in a given territory within a cluster reduces the stability of the regional economy, reducing its diversification;
- the predominance of people employed in a cluster in a given territory reduces innovation, since it is largely a consequence of the contact of people with significantly different knowledge and experience; the opposite approach generates self-perpetuating groupthink, the reproduction of old ideas, stereotypes and approaches;
- stimulating cluster formation is the same subsidy as traditional industrial policy measures.
On this moment in the Russian Federation the concept cluster not enshrined in law.
see also
Literature
- Pierre Desrochers and Frédéric Sautet, Cluster-Based Economic Strategy, Facilitation Policy and the Market Process
Notes
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Localization of innovation processes: beyond the concept of geographical proximity
V.V. Platonov,
d.e. Sc., Professor, Department of Economics and Enterprise Management, St. Petersburg State Economic University
E. Yu. Statovskaya, D. A. Statovsky,
k.e. Sc., Committee on Economics, Department of Economics and Management
policy and strategic enterprises of St. Petersburg State Economic University;
planning of St. Petersburg LLC "UENSi Media",
The article is devoted to the concept of economic proximity of subjects of innovation activity, description of types of economic proximity and study of the possibilities of using the concept for analyzing the processes of technological transfer and modeling the system of relations of its participants. The authors propose a new approach to assessing the qualitative state of innovation systems based on an analysis of the degree of economic proximity of its components.
Key words: localization of innovation processes, economic proximity, geographic proximity, innovation activity, transfer of innovations, regional innovation system, communications, microsystem of innovation, technology brokerage.
P | after Michael Porter re-populated, two forms of proximity were distinguished - geographical, or-
Having raised the forgotten idea of Alfred Marshall that innovation activity is a geographically localized process, the problems of regional innovation systems continue to be the focus of scientific research. Existing empirical studies today (including A. Jaffe; Z. Aksa, D. Audretsch, M. Feldman; A. Torre, A. Ralit and a number of others) confirm the hypothesis that innovative processes are prone to localization. Availability of organizational structures for the transfer of tacit knowledge (“tacit-knowledge”), access to the results of scientific research activities other subjects of innovation activity (hereinafter referred to as SIA), the so-called knowledge spillover (“R&D spillovers”) and the presence of partners with the necessary competencies are key factors in the effective transfer of innovations, while the economic proximity of the participants in the innovation process plays the role of their catalyst.
In the classical sense, the proximity of LEDs means the spatial distance between them. However, in the 1990s. The French school of proximity dynamics (a research group of French scientists: A. Thor, J. Gilly, etc.) made a significant contribution to the study of innovation processes, putting forward a hypothesis about several forms of proximity and their impact on innovation potential. Traditionally representatives of the French school
ganizational. Also, institutional proximity is sometimes added to this classification to take into account the fact that the activities of the IED can be shaped or limited by the external institutional environment. The types of proximity of LEDs existing in the scientific description are united by one common property - they reduce uncertainty and solve the problem of coordinating innovative activities.
The most complete classification of proximity was proposed by R. Boschma, highlighting, along with geographical, cognitive, organizational, social and institutional proximity. Using the concept of proximity allows us to systematize analytical and applied tools for managing technology transfer.
The most important forms of economic proximity and their positive effect
Geographical proximity
Geographical proximity refers to the spatial distance between EDMS. Numerous studies demonstrate that high-tech companies tend to be located in close proximity to skilled labor, research institutions, and a favorable economic environment. The effect of geography is based
The concepts of knowledge spillovers, formulated by Alfred Marshall, and tacit knowledge by Michael Polanyi lie in close proximity. Knowledge spillovers refer to the emergence of externalities from research activities (e.g., universities) that are used by other SIEs (e.g., small innovative enterprises). Thus, in the work of Z. Ax, D. Audretsch and M. Feldman, the role of universities in the commercialization of R&D by small enterprises, as well as the influence of the proximity of enterprises to universities, is analyzed and confirmed by empirical calculations. Geographic proximity reduces the communication gap between universities, research centers, and enterprises, facilitating the process of technology transfer. Explicit knowledge is knowledge that is communicated in a formal manner and systematically, for example, as quantitative data, formulas, drawings, regulations, algorithms, etc. Tacit knowledge, on the other hand, is difficult to formulate, but is of great importance in technological know-how and, Since tacit knowledge is inherent in specific people, their carriers, their transfer is greatly facilitated in the case of the geographical proximity of SID.
In the light of modern concepts, geographic proximity is not the only proximity factor acting in isolation, but enhances cognitive, organizational, social proximity, and also stimulates the formation and development of a favorable institutional environment (institutional proximity) for the implementation of innovative activities.
Cognitive proximity
When determining cognitive proximity, one should proceed from the hypothesis of the limited rationality of subjects of economic or scientific activity when creating new knowledge. This limitation is associated with the framework of cognitive activity characteristic of each organization, the so-called “cognitive constraints”, which are determined by the knowledge base and competencies that the company has. The closer the level of knowledge and competencies of companies, the higher the level of their cognitive proximity. V. Cohen and D. Levinthal, in their work devoted to this issue, argue that effective knowledge transfer requires the organization to have absorptive capacity for the acquisition and subsequent interpretation and application of new knowledge. This part of the organizational potential determines the success of the organization’s participation in innovation networks, allowing: selecting the “right” partners and receiving truly relevant and necessary information. Thus, only SID with sufficient absorptive capacity can benefit from the presence of cognitive proximity.
In relation to the innovation sphere, the result of activity, including the cost of obtaining it, largely depends on the cognitive proximity of its participants.
cov. The smaller the gap between the knowledge of participants in the innovation process (for example, organizations of regional innovation infrastructure, universities, enterprises), the greater the innovative potential they have and the higher the efficiency of innovation transfer. Thus, cognitive proximity (as well as other forms of proximity) can be considered as one of the criteria for assessing the quality of the system under consideration (including the regional innovation system).
Each subject has its own coordinate system. One of the tasks of regulating and managing innovation activities, including within the framework of performing the function of technology brokerage, is to reduce the “cognitive gap” and adapt participants in the innovation process to a single coordinate system - the minimum required set of knowledge, competencies and tools for managing innovation activities that are effectively used in international practice.
Organizational proximity
Although the availability of publicly available knowledge and competencies is a prerequisite for the interaction of companies in the process of innovation, the effectiveness of this interaction also depends on the organizational capabilities of the company, including the ability to coordinate and exchange knowledge and information.
Thus, according to R. Boschma, an organizational structure, for example, a network, acts not only as a mechanism for coordinating scientific activity, but also as an effective tool for the transfer of information and knowledge in conditions of uncertainty, as is known, characteristic of innovative activity.
Obviously, organizing the process of commercialization of new knowledge requires building a well-functioning system of interaction both between participants in the innovation process and within innovation-oriented organizations themselves, including through business process reengineering.
Social intimacy
Economic relations based on trusting contacts or positive interaction experience characterize a high level of social proximity of participants in the innovation process. The social proximity of an organization or its employees can be defined as the degree of its involvement (management, employees and the organization as a whole) in social connections and relationships. Closely related to this form of intimacy is the concept of social capital. Establishing trusting relationships can speed up the process of transferring so-called “tacit knowledge”, the implementation of which requires direct interaction between the parties. Modern practice of introducing the concept of an entrepreneurial university, as well as organizing project support systems at early stages life cycle (for example, within the framework of
business acceleration gram) is a clear confirmation of the importance of social connections in the processes of supporting innovation activities. The effectiveness of the measures taken directly depends on the social involvement of universities and infrastructure organizations - on the scale, frequency and effectiveness of their communications and the communication opportunities that they provide to the initiators of innovative projects.
An important aspect of the social involvement (proximity) of participants in innovative activities is their connection with the consumer. Social proximity can be considered within the framework of the system of producer-consumer relations (Customer Active Paradigm). The development of the idea of the role of the consumer in innovation processes today has made it possible to formulate the concept of the “fourth helix”, which becomes “the activity of a human consumer in the creation and production of goods.”
Institutional proximity
innovation infrastructure organizations) and regulators of innovation activities (government authorities), there may be an institutional gap. It makes it difficult to transform the local innovation market, formed by individual participants, into a regional market capable of satisfying the economic interests of an entire city. The reason for this gap is the lack of necessary institutions (regulatory legal framework) and the competencies of the participants. This organizational structure can be described as a system of relations within the framework of a regional innovation system (hereinafter - RIS), which is characterized by low level institutional proximity of its elements. It is important that this institutional gap can be compensated by other players, such as the business sector, network structures, and universities. In this case, they formally assume the functions of the RIS regulator.
back side economic proximity
The effectiveness of innovation transfer is largely determined by the quality of the institutional environment - the presence and efficiency of norms, laws and rules governing various aspects of innovation activity: from communication mechanisms for participants in the innovation process, through ensuring the protection of intellectual property rights, to measures to support innovation activity. Institutions can act as a tool for regulating innovative activity of both individual elements of the innovation system (hereinafter - IS) and IS as a whole.
S. Edquist and B. Johnson define institutions as a set of common habits and established practices, rules and laws that regulate the interactions of individuals or groups of individuals. At their core, institutions create conditions for collective action taken as part of the creation of innovative products or other processes, reducing uncertainty and reducing the level of transaction costs. Thus, compliance general rules and established norms, the implementation of activities by organizations within a single legal space characterizes the state of their high institutional proximity, which has a beneficial effect on innovation activities.
As M. Gertler noted, the presence of organizational or social proximity may not be enough for effective interaction between companies (exchange of knowledge, resources aimed at creating innovative products or services) when they operate in different institutional conditions, or if these institutional conditions are imperfect .
At the regional management level, communication is identified as one of the leading components. It represents the ability to establish communication channels between the regional authorities and business, as well as between businesses inside and outside the region. However, between participants in the innovation process (in particular, universities, enterprises,
It is important to note that the most widespread hypothesis in the literature is that positive effect proximity, designed to increase the degree of integration of participants in innovation activities and the efficiency of innovation processes. However, proximity can also have a negative impact on innovation processes - the so-called problems of closed system.
The effect of cognitive distance manifests itself in fundamentally different ways in the situations of searching for new knowledge (exploration) and exploitation of accumulated knowledge (exploitation) identified by J. March. The cognitive distance between partners turns out to be very favorable for the search for innovative opportunities, new ideas, in other words, for radical innovation. Thus, with significant cognitive distance, individuals and organizations perceive and interpret information differently. This is a very important advantage for finding new approaches, non-trivial solutions, etc. On the contrary, in the process of exploiting accumulated knowledge, cognitive distance complicates mutual understanding and coordination of innovative activities. B. Nutboom and his colleagues found that the relationship between cognitive distance and the intensity of innovation activity has the shape of a parabola, the branches of which are directed downward, indicating the presence of optimal cognitive distance. Along with different manifestations effect of cognitive distance for situations of searching and exploiting knowledge, B. Nutboom and colleagues point to a change in the absorptive potential described above, which falls with increasing cognitive distance, negating the benefits of cognitive diversity even in the case of searching for new knowledge.
According to R. Boshma, too high a level of organizational closeness can also create unfavourable conditions technology transfer, cause a lock-in effect, isolating the company from new opportunities and partners and holding back its development. The consequence is too
a high level of organizational proximity is a loss of flexibility of participants in the innovation process, leading to increased risks and a decrease in the effectiveness of the innovation management system. An example of the consequences of excessive organizational proximity can be the artificially created barriers for new companies by old market participants who are not interested in the loss of profitability due to the entry of new technological solutions into the market.
And finally, the effect of knowledge spillover during the intensification of innovation activity manifests itself most clearly when this knowledge has previously been accumulated by relatively isolated SIEs. This accumulation is facilitated not by economic proximity, but by the presence of barriers. In this case, the effect of knowledge spillover is realized either through the efforts of a technology broker, or by the formation of special organizational mechanisms at the regional level, for example, the establishment of formal innovation clusters that accompany the establishment of economic proximity in all its forms between SIDs.
Conclusion
LED communications are the basis of the innovation commercialization process. The category of “economic proximity” is a qualitative characteristic of communications, the effectiveness of which determines the effectiveness of technological transfer. Assessing the degree of proximity of participants in the innovation process can serve as an effective tool for analyzing the structure of connections and analyzing the qualitative state of the innovation system under consideration (both a “microsystem” that unites some participants in innovation activity, and a macrosystem - a regional, state or international innovation system). This aspect is of utmost importance in the performance of the technology brokerage function.
Largely highlighting various types proximity is carried out for analytical purposes, but the application of the concept allows you to structure various factors communications arising in the process of knowledge transfer, as well as modeling systems of relations between participants in innovation processes (for example, universities and enterprises), including end consumers.
Thus, despite the conditions of geographical proximity, IEDs can be located at a large “institutional distance”, for example, in the absence of an appropriate legislative framework for regulating innovation activities. Conversely, IDS, geographically located at a large distance, can be in organizational proximity and represent a highly organized system of innovation management (international innovation system).
In connection with the above, a very promising direction of research is opening up for scientists: to what extent is geographic proximity a necessary condition formation
LED relationship systems. In other words, whether and to what extent individual components of the innovation process that are a consequence of this proximity can be compensated by other forms of proximity. The answer to this question is not only of purely scientific interest. Solving this problem will contribute to more accurate economic justification and improving the direction of activity of innovation infrastructure organizations, primarily those performing
functions of technology brokers.
The article was prepared with the support of the Russian Humanitarian Foundation: project No. 15-02-00042.
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Localization of innovation processes: beyond the concept of geographical proximity V. V. Platonov, doctor of Sciences (Economics), professor, Department of the Economics of Enterprises and Industrial Management, St. Petersburg State University of Economics. E. Yu. Statovskaja, PhD in Economics, head of department, Committee for Economic Policy and Strategic Planning of St. Petersburg. D. A. Statovskiy, CEO, UNC MEDIA LLC.
The article concerns the concept of innovation actors proximity and its utility for the purposes of transfer processes analyzes and modeling the system of relationships between its participants. The authors propose the new approach to qualitative evaluation of innovation systems through estimation of its "components proximity.
Keywords: localization of innovation processes, proximity, geographical proximity, innovation activities, innovation transfer, regional innovation system, communications, microsystem of innovation, technology brokerage.
There are two approaches to assessing the role of organizational networks in the implementation of innovation activities.
1. According to supporters of the first position (the main provisions of which are set out in the works of David Thies), only strong and integrated organizations can successfully and systematically carry out innovative activities. Loose coalitions of joint ventures, alliances, or virtual partners are unable to implement systemic innovations, let alone set standards for them or monitor their further development.
2. Proponents of another approach (the main conclusions of which are presented in the articles of Paul de Laag) argue that, since the industry structure is changing from vertical to horizontal and “digital convergence” is taking place, systemic innovation today can only be carried out allied networks of organizations. Although such networks are vulnerable to “opportunism,” they are capable of developing and implementing systemic innovations because mutual relationships can be stabilized by various forms of both procedural and substantive commitments.
In other words, it is necessary first of all to understand the following: should innovation activities be carried out by individual organizations or within the framework of strategic alliances and networks of organizations. In this context, two types of innovation are distinguished: autonomous and systemic.
What is the difference between autonomous and systemic innovations?
Autonomous Innovation can be built into the system without any additional approvals or adjustments. Examples of such innovations are faster microprocessors or larger computer memories.
System innovations, on the contrary, they require significant adjustment of various parts of the system. Not one, but many complementary innovations must be implemented simultaneously and applied throughout the chain of system elements. Examples include electronic funds transfer, instant photography, jet aircraft, CD, Personal Computer.
Thus, in the works of D. Thiis and other supporters of the first approach, it is argued that if an organization intends to carry out innovations on a systematic basis, then the only organizational solution that guarantees success is the integration of all necessary activities within the organization itself (see, for example,). In this case, it is necessary to avoid alliances, joint ventures, etc. Note that D. Thiis does not claim that creating networks of organizations in general is not attractive. It clearly and openly recognizes the merits of networks of organizations in the case of autonomous innovation. It is only for the systemic nature of innovation that full integration within one organization is argued to be the preferred method.
Supporters of this position identify a number of organizational agreements, forms for implementing innovative activities and rank them in accordance with such criteria as "amount" of organizational control, which is typical for them.
The list of organizational forms (in descending order of organizational control), in their opinion, is as follows:
Integrated organization;
Organizations with autonomous divisions;
Joint venture;
Association (alliance);
Virtual organization.
Thus, the integrated organization is seen as the strongest of all possible forms of control, while the virtual organization, which links external activities together, provides the least amount of control. It should be noted that this emphasizes that a network (whether a joint venture, alliance or virtual partners) can be considered as strong a form as an integrated organization if there is a dominant lead organization in the network.
What contributes to the formation of allied networks of innovative organizations?
However, it seems increasingly elusive that a single organization can design a system for the future, let alone create universal standards for it. There are several forces that encourage innovative organizations to create alliances and virtual networks, the most significant of which are often recognized: the development of horizontal structures in industries, the trend of digital convergence, and increasing R&D costs.
Development of horizontal structures in innovative industries most notably in the computer sector. Back in the 1970s. there was a vertical structure there. Vertically integrated organizations sold general purpose computers that dominated the market - IBM And DEC. Gradually, a new, more horizontal structure emerged in which companies are limited to the production of system components, such as microprocessors, personal computers, operating systems, application software, etc. Currently, competition exists within horizontal layers between component manufacturers. Such fragmentation appears to be detrimental to systemic innovation. Their development must be coordinated throughout the system, vertically, as it was before, to harmonize the different layers. The only possible way is to create networks to unite partner organizations. In old times IBM could transform the system by transforming herself; Today, the most appropriate approach is through networks of organizations.
What does digital convergence mean?
Digital Convergence Trend strengthens the above-mentioned trend of development of horizontal structures in innovative industries. The boundaries between industries such as computers, telecommunications, consumer electronics, leisure and publishing are rapidly disappearing or becoming porous.
As all major processes by their nature gradually become digital, controlled by computers, the significant differences between them disappear. The explosive growth of the Internet may be the best example. This trend has important implications for industry competition. Existing firms may enter new areas, increasing overall competition, leading to a chain reaction. Facing new competitors, other organizations are also forced to expand into new, broader areas. Moreover, the need to be at the level of technological progress leads to the expansion of alliances, associations, and their expansion beyond the boundaries of the industry.
Of course, for now this is only a trend and not a rigid pattern. The markets still remain fairly separate, with different firms represented. IBM - it's still a computer company, a Philips - still primarily a supplier of consumer electronics. But the differences are becoming increasingly blurred and vague. It is important to emphasize that the trend of increasing digital convergence and all its consequences are relevant to the problem of systemic innovation - their significance is significantly expanding. An organization that intends to innovate systemically has no choice but to develop an external network (now horizontal) and try to reach parts of the system outside the areas where the organization already operates.
Increased R&D costs. In the past, R&D costs have never been an important motivator for strategic alliances. The motives for creating associations at that time were the primary desire to expand markets and enter new ones, as well as technological complementarity, complementarity, and reducing the period of time required for the implementation of innovations. However, the costs of innovation have risen sharply in recent years. As a result, it is expected that the lack of financial resources will force organizations to more actively develop partnerships.
This trend is clear for autonomous innovation. A good example is the development of dynamic memory chips ( DRAM). Development costs for each subsequent generation doubled. We should not forget that the costs of building factories are also rising. It's no surprise that organizations are looking to develop partnerships. So, Toshiba works together with companies IBM, Siemens, Motorola; Hitachi With LG Semicon and with Texas Instrument; company FujitsuWithHyundai; a NECWith company Samsung. Extrapolating from this trend, it should be noted that rising costs are also characteristic of system innovations.
Thus, a generalization of these trends allows us to conclude that the implementation of innovative activities increasingly makes it necessary to form networks of innovative organizations.
Like Who sets the standards for the results of systemic innovation?
What can you say about the process? setting standards? Are they necessary at all? And if so, will they be offered by individual organizations or groups of organizations? Thus, D. Ioffe argues that in the era of digital convergence, communications and interactions within networks are extremely important. They would be significantly hampered by the simultaneous, parallel existence of a large number of standards. Consumers would react negatively to a situation where there is no dominant design.
To ensure that adoption of the standard is not hampered, no innovative company should try to protect its own technology design to the point of exposing it to other companies. There needs to be an open approach to standards where other companies are fairly licensed to copy. The more systemic the innovation, the more necessary such an open approach is.
Will such system standards be set by individual organizations or groups of companies? The last option seems to be the most possible. Once organizations come together to pursue systemic innovation and the need for a standard becomes apparent, they have no choice but to continue to partner and try to establish a dominant and open standard. In order to generate maximum support in all areas, they are forced to expand the alliance of organizations as much as possible, which leads to the formation of an allied network of organizations. An individual organization can only hope to strengthen a global standard by skillfully weaving strategic alliances. The result is that, in a mutually competitive environment, one of the allied networks of organizations sets the standard.
As described above, it appears that the standard setting process is primarily a matter for commercial organizations. Do government agencies have any role in this matter? Since it is clear that, at least initially, there is no consensus, government agencies tend to avoid imposing a standard, preferring to leave the problem to market forces themselves. However, there are ways in which the state can influence this process. If government agencies account for a large share of the demand, then the format that the government offers can play a significant role in setting the standard. In addition, market competitors themselves, at some period of time, may show interest and ask government agencies to intervene in solving the problem (see, for example,). Therefore, government bodies may actually be involved in this process both as a participant and as an arbitrator.
It should also be noted that the phenomenon of the formation of alliances and associations has changed the overall picture and the nature of competition. Competition now takes place primarily between networks of innovative organizations, and not by separate organizations, as was before. Moreover, organizations begin to compete for advantageous partners when forming networks; each of them strives to “steal away” the best partners before competitors do so. Proactive partnership becomes the norm (see, for example,).
Similar conclusions about the growing need for organizational networks are being made both in business circles and in management science. Ray Noorda, former CEO of the company Novell, coined a new term « competition» , which can be translated into Russian as "competition", since it is obtained by adding the first part of the word « cooperation» (cooperation) and the second part of the word « competition» (competition). The introduction of this term indicates a widespread phenomenon competitive cooperation between organizations. The corporate model of the future, according to some experts, consists of internal networks of branches and external networks of strategic alliances, all of which relate to the global level (see, for example,).
Thus, it appears that the implementation of systemic innovation increasingly depends on the creation of coalitions of partner organizations. Not just one integrated organization as a center of power, but more fragmented coalition of partners With multiple centers of power manages the innovation process.
How can we improve the sustainability of networks of innovative organizations?
Of course, this creates danger of “opportunism”, those. the fact that each partner will strive to get as much as possible and contribute as little as possible. It is not surprising that there are many complaints about cooperation within associations in the field of R&D (see, for example,). Partners often skimp on the contribution of their specialists: “Let other partners use their best specialists first! The knowledge gained by each partner will then be expropriated and used to enhance joint competitiveness. In this case, the “devastation” begins already at the R&D stage.”
Associations created for the purpose of implementing systemic innovations are especially vulnerable to opportunism. There are two main reasons for this.
An entirely new interconnected system must be created, requiring intense face-to-face collaboration across organizational boundaries. This in itself opens the door to opportunism; the innovative organization becomes transparent.
It is necessary to consider the type of knowledge involved in the system innovation process. Partially, this will be codified, formalized knowledge, for which legal protection tools are applicable. If a patent has been obtained or copyright has been effectively enforced, then to a certain extent the innovation can be protected from expropriation. Contractual agreements (conditions requiring confidentiality, limiting the use of information that has been disclosed) may also be used. However, most of the knowledge and know-how involved in system innovation is tacit. Such knowledge cannot be easily absorbed or copied by others. It is for this reason that in order for innovation to occur, tacit know-how must be demonstrated openly and repeatedly to partners. Such intensive interactions involve strategic risk because it is very difficult to control how much tacit knowledge is actually absorbed and expropriated by partners. Since tacit knowledge cannot be specified in any formal sense, there appears to be no legal or procedural means of protecting it.
However, the experience of R&D partnerships over the past two decades has led to the development of a number of mechanisms that can stabilize and strengthen the relationships between partners of the innovation network. These are mainly various forms of obligations that partners undertake. They voluntarily provide assurances that they will adhere to agreements honestly. Two types of such obligations can be distinguished: material, real and procedural.
What are the forms of real and procedural obligations of innovation network partners?
Material, real obligations of partners of innovation networks. Throughout history, material obligations have been actively used. For example, when concluding a treaty, kings sent their sons as hostages or handed over fortified castles as collateral. What is the corporate equivalent of such real, tangible obligations?
First, organization-specific knowledge must be made known to partners. As noted above, especially in systems innovation projects, this can "open the door" to opportunistic behavior - knowledge that has been disclosed can be expropriated. But there is another side to the coin. This sharing of knowledge is not only a risk, it also represents investment in relationships, which cannot be annulled, cancelled. Secondly, of course, it is necessary to take into account investments in research equipment, buildings, etc., which also tie the hands of investors.
Here are a few examples that, although related to autonomous innovation, illustrate the latest statements. Toshiba And Motorola began working together in 1986. The agreement between them required that Toshiba shared her know-how on memory chips, a Motorola had to reveal her knowledge about microprocessors. Moreover, both companies agreed to build a joint plant in Japan in order to use the knowledge they exchanged. Such obligations, which are largely irrevocable (they cannot be canceled), of course, bound the partners, which determined the duration of their cooperation.
Likewise IBM, Siemens And Toshiba in the late 1980s joined forces to conduct R&D to develop dynamic memory chips. At first, researchers from the three firms only exchanged some knowledge, which could not be called close cooperation. However, in 1992, the task was set to develop the next generation chip, which was a very expensive task, since it required $1 billion for R&D and $3 billion to build factories. But in addition to these investments, such an alliance implied the sharing of the latest know-how. For this purpose, a team of 200 specialists was created, representing these three companies, who worked in the new research center IBM near New York. Obviously, this represented an effective way of “linking” these companies. Later the company joined this alliance Motorola, which also sent its researchers to this center.
In addition, the association of partners can also occur through the purchase and exchange of shares of each other. This intertwining of equity capital creates connections that discourage opportunism. Partners become interdependent - by harming a partner, the company harms itself. If the partners are approximately equal in size, then both take part in each other's share capital. However, if there is a difference in size, then, as a rule, it is advised to buy shares only to the larger partner and thus demonstrate their dedication, loyalty to the agreement.
So, the main attention in the analysis of networks of innovative organizations has so far been paid to the creation of associations in the field of R&D. In actual practice, many innovative companies not only have such alliances with several partners, but also often enter into several alliances with each partner. Most players in innovation markets support dozens and even hundreds of alliances at the same time.
In addition, as many experts note, in practice, the formation of alliances does not occur simply at random; there is usually a tendency to create clusters or groups of innovative organizations, which often interact with each other. The formation of such groups of organizations automatically provides for more mutual guarantees. In this case, the stability of networks of innovative organizations often increases for the following reasons. First, if two organizations (A and B) have a whole set of agreements with each other, then this serves as a kind of mutual guarantee, since if you put one agreement at risk, you risk putting the whole set at risk. Secondly, if organization A, by violating the agreement, infringes on the interests of organization B, then the latter has at its disposal effective weapons to discipline the violator - organization B may threaten to reveal to the public the opportunism of organization A. As a result, the entire cluster of relationships of organization A may disintegrate - if not immediately, then after some time. A tarnished reputation is difficult to restore, and membership or acceptance into the community of a given cluster may be at stake in the present and future.
Procedural obligations of innovation network partners.
In addition to real commitments, organizations strive to find ways to bind each other through procedures that limit potential opportunism. Of course, in every alliance there is usually some form of agreement or contract. If things go badly, the partners can go to court. Therefore, litigation constitutes a kind of main line of the approval procedure. However, contracts cannot effectively address the vague, uncertain characteristics of R&D alliances. Therefore, organizations gradually developed other forms of procedures (see, for example,).
Thus, organizations often try to involve not a judge, but another figure to resolve conflicts. In advance, the partners agree on mediation in case of complications in the situation. Such a mediator must make every possible effort and use all means to restore agreement between the partners. He is not bound by legal restrictions and can act more flexibly, although he may not have any power. A stronger figure is the arbitrator, the arbitrator, in whose person mediation and power are combined, since the partners ex ante promise to respect his decisions. However, mediation and dispute resolution by an arbitration court or arbitration are all forms of special intervention, the entry into the matter of a third party as a consequence of a far-reaching conflict. Therefore, as a more radical approach, the appointment of a “guarantor” as a third party who would monitor the partners’ cooperation at all times is often considered. The guarantor should be hired from outside, such as industry associations, government agencies, research institutes, universities, etc. At the same time, its powers must be clearly defined.
Of course, these agreements do not exhaust the possibilities for limiting opportunism in allied networks of innovative organizations. So, an interesting way is the so-called Chinese Wall, which, however, applies only to alliances in the field of R&D in the case of carrying out innovative activities on a separate third site. Typically, each partner sends a certain number of researchers to work on a joint innovation project. They constantly exchange knowledge with each other. However, a lot of effort is usually put in by project participants to obtain know-how that could be quickly applied in their home company. This is achieved mainly through mechanisms for staff rotation at such research sites and visits to these sites by teams of employees from participating firms. But this knowledge “repatriation” policy creates strong incentives to cheat. Participating innovative companies may choose to “go it alone” at some point. To prevent this kind of renegade, apostasy, it is recommended to build a “Chinese wall”, i.e. suspend the repatriation of knowledge back to your company until the innovation project is completed. Although such agreements are extremely rarely used in practice, experiments in this regard seem interesting and promising.
It must be emphasized that real and procedural obligations are the most common guarantee mechanisms that can be used in various types of alliances of innovative organizations. They protect against many types of opportunism. But their applicability depends on the specific characteristics of the alliance. For example, shared knowledge can serve as a form of real commitment if close R&D collaboration is a central element of the alliance. As noted earlier, interlocking equity will only be beneficial if the partners are approximately equal in size; if there is a size discrepancy, it is preferable for the larger partner to unilaterally acquire the shares. The construction of a “Chinese wall” makes sense only if the mutual exchange of know-how is intensive and constant, and the partners are also active competitors.