Proximity of organizations and their innovativeness in networks. Prospects for the development of innovation networks
UDC 330.3
© 2006, S.A. Chernov
Innovation Networks
The development of the modern economy is associated with the formation of qualitatively new competitive advantages of its subjects. We are talking about the following features:
1. Competitive advantages associated with the movement of interspecific resources reflect not statics, but dynamics fundamental competencies, relevant technologies. The movement of knowledge in a special intra- and inter-company information space is characterized by a special synergistic effect. Living knowledge is relative; it presupposes discussion and, accordingly, the exchange of information. In the process of this exchange, new knowledge is born, technological and organizational priorities are adjusted. The very movement of a resource is its mutual enrichment. The economy, which is based on this principle, develops according to qualitatively new laws. This exchange process 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 is how attractors appear. Here, individual events of the past can precede the present and “lurk in wait for us from the future.” Innovative attractor structures represent the future of complex economic systems. Such systems will not succeed if they isolate themselves from the outside world with a Chinese wall. The presence of blurred boundaries with the external environment allows an elementary particle of the economy to enter a certain mesocommunity in which the attractor effect operates. Michael Hammer notes that modern innovative companies in the process of reengineering are losing clear boundaries separating them from external environment. Elements of the external environment are directly connected to the basic processes of the enterprise, becoming their main coordinators and controllers.
2.Dominance informal, “intermediate” relationships and processes. Most of the knowledge of innovative companies does not take documentary form, but is in the heads of employees. A documented intellectual product is effectively implemented in the presence of developed informal information relations and innovative experience. The movement of technology is optimal in a cloud of side information flows and know-how. The future lives in intermediate worlds, which is why complex innovation systems move along complex trajectories and are guided by vague possible paths of development (network effect).
3. Availability of innovative economies of scale. What is considered insignificant today may turn out to be fundamental tomorrow. Such transformation of scale in modern conditions is carried out extremely quickly. The speed of information flows corresponds to the scale of the time vector. The movement of economic resources is subject to this rule. This irrationality of the movement of resources makes it possible to increase the speed of movement of resources to attractor areas exponentially. Hence the phenomenological nature of modern financial mechanisms. Attempts to provide a straightforward explanation of many investment phenomena and events of the movement of resources in the securities markets are associated with a primitive speculative interpretation. In reality, a new substance of money and capital movement is being formed. Just as technologies are classified as disruptive, new and modifications of old are distinguished innovative networks of three levels. The movement of fundamental technologies is most effectively carried out in global networks (first-level networks), new - national (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. As the scale decreases, the 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. Obviously, the competitiveness of a particular economy can be determined by the scale and density of the innovation network. The leadership here is for the USA. The generation of capital in this country is carried out in innovation networks; the richest people on the planet work intensively in the field of software, intelligent product movements. American universities play an important role in first-level networks, working not only for their country, but also for the whole world. The European Community today is forced to create world-class technological universities.
4.Cluster intersections networks of the first type are scientific schools. If scientific schools are destroyed (as we had with genetics and cybernetics), the country limits the possibilities of increasing its wealth. Intellectual products of world-class scientific schools can move through global innovation networks. This realizes the competitive advantages of a first-level country, creates new growth points, new technological structures, and enterprises with a high level of added value and capitalization. At the same time, the country is integrating into global innovative value chains. This is done through global innovation networks. "In the beginning was the word." Thus, the secrecy of fundamental science, classifications of secrecy, and legal actions against leading scientists are a recipe for disaster. Behind this lies a lack of vision and strategy. In order for a country to involve applied science and the innovative community of entrepreneurs in global networks, it must “open up” to the world. Unfortunately, we are becoming increasingly closed. This is a big mistake. Russia is losing its first-level competitive advantages. Its fundamental science is not in demand and is doomed to poverty. It is no coincidence that in 2005 Russia took a step back in world competitiveness rankings. But this is precisely the main parameter that evaluates the work of the President of the Russian Federation. Russia's passage of the bifurcation point in the 1990s means that a return to the past is impossible. Centralization of the economy, nationalization of its key sectors, suppression of dissent through the use of administrative resources, the judicial system, revision of history - all this has already happened. As Nikita Belykh said, “the lack of an adequate perception of the past, ... distortion of history, ... leads to the fact that people cease to see the cause-and-effect relationships of historical events.” Without solving the problem of moving forward, we are dooming scientific schools to physical extinction. Today they are left without middle management. Elders dominate here. The new national “project” leaves science and education on a residual principle - it is last in line for resources. Many experts believe that irreparable damage has already been caused to the Russian Academy of Sciences, and many scientific schools have been destroyed. In order to work in global innovation networks, perfect knowledge of the English language is required. Here's a new problem. In this regard, a national project is needed, a federal channel in English is needed, truly open education and the development of educational tourism are needed.
5.Innovative second level networks subject to global networks. They are focused on national (federal) projects and assume the presence of a national innovation infrastructure. The latter is currently missing. Second-level innovation networks have not emerged in Russia. Individual innovation areas are ships in the desert. The exchange of innovative experience is extremely limited; most research teams work behind closed doors. Internships for students and teachers in the world's largest and national scientific and engineering centers are reduced to a minimum (which is well established in Eastern Europe, China and India). Smart products are not adaptable to industry needs. There is no engineering belt of the national economy. The work of enterprises with intellectual products is institutionally difficult. The disunity of the innovation community is a path to a dead end. And we are amazed why the Russian economy rejects innovation and continues to remain rent-seeking.
6.Innovative third level networks are of particular interest in the information society as a manifestation of the highest level of development. 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. In the innovative world, the global effects of attractors are realized in third-level networks, attracting innovative arrays of regions and rebuilding them. In the absence of these networks, a collective synergistic process is impossible.
7.Transition through fluctuations from one innovation scale to another, for example, from a first-level network to a second-level network, transforms a moving information field into an energy cluster. As the information flow reaches a smaller scale of the second level, tension accumulates in the transforming innovative network system, so that any small event (fluctuation) can cause a powerful explosion leading to the deployment of a new network. From the area of innovative chaos comes a package of standard products that highlights new technological priorities, defeating chaos and focusing movements and material flows. And vice versa, when moving from a lower to a higher scale, the energy space for the development of a certain need is realized in the information search movement.
8. The innovation network corresponds to the new reality - a self-organizing information field of competencies and technologies - mesoenvironment. Participants in network cooperation themselves establish the rules and order of relationships among themselves in the process of work. Stimulated by external influences, they themselves more or less consciously develop them in the process of collective activity (analysis of the current situation, assessment of alternatives, decision-making, etc.). A fragment of this mesoenvironment is a modern company. In a restructuring, highly dynamic environment, a company is forced to change its contours, bring its structures and functions, human capital and organizational culture into line. Outsourcing and insourcing are used simultaneously. This allows the complex economic system of a company to spontaneously organize its structure and the structure of its reactions to external influences of the mesoenvironment, increasing their certainty over time. Gradually, the company acquires a network structure that allows it to function as a nonequilibrium system (dissipative structure), often on the border of chaotic states (high degree of uncertainty). The new synergetic economic methodology is based on the idea of a wide range of evolutionary paths complex systems, fields of development paths. This means the ambiguity of the future, the existence of moments of instability associated with the choice of paths for further development. It is the network form of organization, self-organization that is most suitable for dissipative structures, since it presupposes the simultaneity of stability and instability, chaos and order, generated by the same factors.
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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.
Keywords: 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. The presence of organizational structures for the transfer of tacit knowledge (“tacit-knowledge”), access to the results of research activities of other subjects of innovation (hereinafter referred to as SID), the so-called spillover of knowledge (“R&D spillovers”) and the presence of partners with the necessary competencies, act as 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.
Most full classification proximity was proposed by R. Boshma, highlighting, along with geographic, 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 transmitted formally and systematically, for example, as quantitative data, formulas, drawings, regulations, algorithms, etc. Tacit knowledge, on the contrary, is difficult to formulate, but it has 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 organizational potential determines the success of an organization’s participation in innovation networks, allowing: selecting the “right” partners and receiving truly relevant and necessary information. Thus, only an 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 experiences 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” - “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 in the 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 a low level of 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.
The downside of 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 with general rules and established norms, and 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 in the literature the most widespread hypothesis is about the positive effect of 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 the different manifestations of the 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 proximity can also create unfavorable conditions for technology transfer, causing a lock-in effect that isolates the company from new opportunities and partners and hinders 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 small-scale enterprises.
Conclusion
LED communications are the basis of the innovation commercialization process. The category of “economic proximity” is qualitative characteristics communications, on the effectiveness of which the effectiveness of technology transfer depends. 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.
In many ways, the identification of different types of proximity is carried out for analytical purposes, however, the application of the concept makes it possible to structure various factors of communication that arise in the process of knowledge transfer, as well as to model 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 adequate legislative framework regulation of 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 for the 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. The solution to this problem will contribute to a more accurate economic justification and improvement of 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.
Network information structure: the concept of an innovation network, principles of its formation and functioning mechanisms.
Information and network infrastructure of the economy is its substructure, part of the information infrastructure created by an association of economic agents in a computer network. This ensures the creation, storage, exchange and consumption of products produced on the basis of information and knowledge, and used to achieve the effectiveness of the development of economic relations.
Under these conditions, three main types of infrastructure entities operate– these are households, firms of various forms of ownership and size, and the state. Subjects of the information network infrastructure are economic agents who, by forming or using infrastructure elements, interact in a network with clearly defined goals. Subjects are divided into two main groups:
1) those who take an active part in the development of elements and means of labor infrastructure;
2) those who functionally use them.
The main goal of all entities in the infrastructure– using network resources in the best possible way to make a profit or gain intangible benefits. Each of the subjects performs its functions, which ensures the production of goods and services; the infrastructure is a platform that either facilitates the performance of the necessary functions, or is completely a mechanism for the production of information goods and the provision of services.
Infrastructure objects create an information-network form of interaction, as they transform the traditional interaction of subjects; Here the functions of providing information and working with it sometimes change. The objects in this case are Internet resources or individual modules that can be built into websites.
Sites are being considered not only as a finished product, but also as work items that can be used to perform many work functions. In Fig. these infrastructure objects are placed in the center and indicated by pentagons. Currently, Internet resources are not only products of labor, but also objects of economic activity, through which many economic agents can interact with each other.
Thus, infrastructure is the basis for economic development. It provides flexibility, reliability, and productivity of all processes.
Development of information and network infrastructure of the economy taking into account its specifics and features, it gives more opportunities for economic agents to work effectively, opening faster and more effective communication channels between them.
The concept of an innovation network and principles of formation, functioning mechanisms
innovation network is an open economic system consisting of many independent economic units.
Formation of innovation networks is a process of analyzing factors and circumstances, selecting and connecting suitable economic objects into a single network. Taking into account the ongoing changes associated with changes in the field of technology, information and management, the process of forming innovation networks requires the development of certain principles. The formation of innovation networks occurs in the conditions of formation and development of post-industrial society
Innovation subsystem consists of a set of interconnected economic entities that carry out the process of development, creation and production of innovations. This includes enterprises carrying out innovative activities in the development and production of intellectual products. This subsystem ensures the most efficient production of innovative and intelligent products with optimal use of its resources. Innovation infrastructure as a supporting subsystem is an association of objects that are not directly involved in the creation and production of innovations, but play an important role in ensuring this process. This subsystem provides the innovation network with the necessary resources and services. It includes three parts. The first is scientific and technical support, which includes enterprises operating in the market of technologies, information resources and services. The technology market and the information resource market are the basis that forms the level of functioning of the entire innovation network. This includes technology parks, technopolises, technocities, business incubators and other structures.
The service market includes all external services, such as the provision of transport or warehouse services, the provision of communication channels, consultations, the construction of non-productive fixed assets, etc. Second, the natural resource market is the primary source of material and raw materials for the production system of the innovation network. These markets determine the natural and climatic conditions for the functioning of the innovation network, depending on the geographical location, seasonal changes and exposure to natural disasters. natural factors. Third, self-sufficiency service subsystem. Service subsystem includes an information system, the purpose of which is to ensure internal communication between all elements of the innovation network, create and maintain a mechanism for collecting business information. Social infrastructure is associated with the reproduction of human capital of network participants. The ecological system must ensure minimization of the harmful impact of economic activities on the environment.
Innovation commercialization subsystem ensures the promotion and implementation of innovations and intellectual products. This subsystem may include enterprises that operate in the field of innovation marketing, advertising, public relations and, of course, sales. The result of the work of this subsystem largely determines the effectiveness of the innovation network as a whole. The innovation financing subsystem provides financial support to the innovation network, carries out settlements and distributes cash flows and funds, uses free cash for the development of an innovation network, participates in the work of the credit market and the securities market. The activities of enterprises included in this subsystem are aimed at the efficient use of financial resources and management of the activities of the innovation network in external financial markets. Such enterprises include banks, investment and insurance companies, venture capital firms and funds, etc. These principles for the formation of innovation networks should be taken into account when building interstate innovation networks, when building national innovation networks, regional and industry, as well as at the enterprise level when building innovation teams .
Firstly, the demographic factor. Demographic crisis of the 21st century. will be expressed in two trends. In some countries, the overpopulation crisis will continue, associated with the growing demographic burden on nature and the economy, with the problem of employment and poverty. In others, there is a depopulation crisis, causing a deterioration in the age structure of the population and a decline in its innovativeness. Population decline and an aging trend are observed in more developed regions of the world, but may subsequently cover the entire planet. Even China is projected to have a population decline after 2040. This means increasing conservatism and the difficulty of implementing radical innovations, the possibility of increasing gaps and conflicts between successive symbolic generations.
Secondly, the environmental factor. It also manifests itself in two trends. On the one hand, the rapid increase in population and even higher growth rates of its needs and consumption will lead to a significant increase in population density and pressure on natural resources, especially non-renewable ones. In these conditions, fundamentally new solutions and innovations are needed that sharply reduce society’s needs for fossil fuels and raw materials, forest and water resources, and cultivable land. On the other hand, there is growing environmental pollution. Under these conditions, it is impossible to cross the line when irreversible changes in the environment begin. natural environment leading to a global environmental disaster. This requires the widespread introduction of environmental innovations that reduce and prevent environmental pollution.
Thirdly, the technological factor. It represents the implementation of a wave of epoch-making and basic innovations that will open the way to a post-industrial technological mode of production, allowing for a manifold increase in labor productivity and an absolute reduction in the consumption of natural resources and harmful emissions into the environment.
These development factors create conditions for the formation of innovation networks. These conditions primarily include: Firstly , humanization of technological progress, its structure, the focus of intellectual and engineering forces, discoveries, inventions and innovations to meet human needs for organic food, fight diseases and improve health, increase the level of education, preserve and enrich cultural heritage in all its diversity. Secondly , greening technological progress, development and dissemination of fundamentally new waste-free technologies, renewable energy sources, environmental monitoring tools, which will reduce the growth rate of consumed resources and emissions into the environment. Thirdly, the demilitarization of science and technology, which is manifested in the use of the conversion potential of the military-technical sector, where a huge amount of dual-use technologies has accumulated. Such technologies can be a source
highly efficient technological systems in the civilian sector of the economy and the humanitarian sector. Fourthly, the globalization of the scientific and technological revolution, the rapid dissemination of its achievements across all countries and civilizations to reduce the technological and economic gap between them.
These factors and conditions give rise to the need to form a new innovative paradigm for the development of humanity and all countries, and to develop methodological principles for the formation of innovation networks. The principles for building innovation networks include the following.
First principle- This is the voluntariness of participants in their actions. This principle is reflected in the decision-making process about network participation. Innovation network
- is an association of independent entities on the basis of partnership and contract; therefore, the voluntary participation of all its members in joint innovation activities is of paramount importance. Without this, it is impossible to form a viable economic network. Each potential candidate for an innovation network must independently conduct a comprehensive analysis of internal and external conditions, without assistance from the network organizers, and voluntarily decide on their participation in this system. In this case, it is necessary to take into account the characteristics and your own goals. Voluntariness involves acting of one's own free will. In this case, in accordance with the objective of this work, voluntariness is own wish each network participant, which is reflected in the relationship of all network participants to the problem posed. Based on the degree of this relationship, we can distinguish the general and strategic voluntariness of the innovation network.
General voluntariness assumes that the decision made by one of the participants in the innovation network corresponds to the wishes of all or the majority of network participants. This is the ideal state to which all participants in the innovation network should strive. Practice has already proven that if agreement in an organization reaches 65% of the total number of its participating members, then this is already a big guarantee of the success of the decision made.
Strategic voluntariness reflects the own desire of each decision-making participant in the innovation network. Such voluntariness provides insight into the degree of psychological and economic readiness of each network participant, and also alerts parties making decisions about future liability.
The main mechanisms ensuring the voluntariness of the decision to participate in an innovation network include:
- an accurate description of the situation is necessary in order to convey information about the current situation to each participant;
- clear formation of the essence of the proposed solution, which describes in detail the structure of the proposed solution, including reasons, goals, principle of operation, expected result;
- comprehensive information support, consists of creating a mechanism that provides high-quality, objective and complete information;
Large-scale discussion aimed at creating a platform for entry and establishing the different points of view of all participants;
- final analyzes and conclusions provide a deep understanding of the problem, and the conclusions play the role of a guideline for correct decision-making, help to have an overall picture of the position of network members, their main reactions and actions before the proposed solution;
- openness of the results of decisions made.
The voluntariness of the innovation network in its actions is reflected in the understanding of the voluntariness of each of its members when participating in the discussion process, analyzing an emerging issue, in the ability to draw their own conclusions and express their point of view.
The second is the principle of unity. As you know, any organization or system works effectively only if it adheres to the principle of unity. In the process of forming innovation networks, the basis of which is the connection of independent innovative enterprises and organizations, it is of particular importance. The unity of the innovation network is expressed in different aspects: in common goals, common development strategies, and a unified structure. We can identify the main types of unity that should be paid attention to when forming innovation networks.
Legal unity
. Despite the fact that each participant in an innovation network can have full legal independence, when forming it, it is necessary to determine in advance the form of the future organization. Having a certain legal status, the innovation network asserts its existence in the general socio-economic system. The organizational and legal forms of innovation networks can be different (partnerships, cooperatives, joint-stock companies, unitary organizations and institutions, etc.), but the essence of their choice lies in maximizing the efficiency of each participant individually and the network itself as a whole.
Economic unity
creates conditions through which all members of the innovation network can constructively contribute to each other to achieve common goals. Each participant in the innovation network has its own goals and resources. In the process of forming a single economic space, each participant is provided with the maximum possible benefit with minimal use of common and individual resources. Economic unity is formed taking into account economic, legal and social factors. Such unity is formed on the basis of the concept of sustainable development of the network.
Targeted strategic unity
is that when developing a plan for the strategic development of an innovation network, it is necessary to consider the network as a single organization or system. General strategies, missions, goals, objectives always take priority over any participant in the system. In general, the process of forming a single target strategic development of an innovation network, as for other organizations, includes a set of standard management actions proposed in the works of Mescon M, Albert M., Khedouri F, Ansof I., Thompson A., Strickland A. . These include:
- formation, justification and choice of mission;
- formation of a strategic concept, doctrine;
- definition of goals (goals);
Comprehensive analysis at micro and macro levels;
- identifying the characteristics of the organization, its strengths and weaknesses in the current conditions;
- development of alternative opportunities, development models;
- choosing the best option that meets the goals;
- the process of implementing the chosen strategy, program;
- control and evaluation of strategy;
- making necessary adjustments.
The use of this set of management actions will allow the created innovation network to function as a single system moving towards a specific goal under a clear mission statement.
The third is the principle of determining the scope of activities of participants, their significance and place in the future network. All participants in the innovation network can be conditionally divided into four groups. The diagram of the relationship between the participants in the innovation system is presented in Figure 1.
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, looks like in the following way:
. 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, 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 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 various 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. Faced with 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, 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. 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 large quantity 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 hope to strengthen a global standard only 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, the former CEO of Novell, 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 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 or 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. Obviously, this represented an effective way of “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 by 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 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.
Foreign researchers include the advantages of network organizations as their information openness, adaptability to rapidly changing market conditions, and the possibility of organically incorporating an innovative component into a network of interacting entities. Recognition of the effectiveness of a network organization in terms of reducing management costs has given rise to the currently widespread understanding of the network as an optimal hybrid form, occupying a certain position between the market and the hierarchy. A number of foreign works 1 emphasize that the opportunity to find knowledge and then apply it in practice can be embodied in various forms of cooperation, and the variety of cooperation forms not bound by a single “roof” of ownership is constantly growing, thereby providing a more effective environment for discovery of new knowledge. The issues of identification and use of non-codable knowledge are becoming increasingly important in cooperation research. High level integration of scientific, organizational, material and financial resources, which is achieved in innovation networks, can significantly reduce the time for developing and bringing new products and services to market.
The concept of “innovation network” is relatively new in economic science. Innovation networks, as one of the types of inter-firm networks, do not yet have a known classification. There are many terms that imply different types of network interaction between organizations in innovation activities. In the most general interpretation found in modern literature 2, an innovation network consists of an innovation, support, financing subsystem, as well as a commercialization subsystem. The innovation subsystem includes organizations that carry out innovative activities in the development and production of innovative and intellectual products (with optimal use of their resources).
The supporting subsystem unites objects that are not directly involved in the creation and production of innovations, but plays an important role in ensuring this process. This subsystem consists of 3 parts:
Scientific and technical support – organizations operating in the market of technologies, information resources and services.
Providing material and raw materials for the production system of the innovation network.
Ensuring internal communication between all agents of the innovation network, as well as creating and maintaining an information collection mechanism.
The innovation financing subsystem provides financial support to the innovation network, carries out settlements and distributes cash flows, uses funds for the development of the innovation network, participates in the work of the credit market and the securities market (banks, investment and insurance companies, venture capital firms, etc.)
It is possible to give a narrower definition of an innovation network. This is a collection of scientific, educational organizations and companies connected by partnerships and united by a single specific goal.
According to experts 1, an organizational form can work effectively within certain limits. Two types of typical mistakes are characteristic of the development of various organizational forms: 1) expansion of the form beyond its boundaries internal capabilities; 2) the emergence of modifications that do not correspond to the internal logic of a given organizational entity. In this regard, the primary task is to classify network organizations, with the help of which it would be possible to determine how the evolution of different types of networks will proceed, what strategic problems they will face in the future, what the consequences of partnership activities will be. The type of network is determined by the goals that partners set for themselves. Innovation networks must ensure the implementation of the full innovation cycle - from the generation of new knowledge to its implementation in a specific product or service.
Researchers identify the following types of foreign innovation networks 1 (Table 1).
Table 1
Types of Innovation Networks
|
Type |
Characteristic |
|
R&D cooperation network |
A collection of scientific teams cooperating to carry out complex research projects (emphasis on generating new knowledge) |
|
Technology Transfer Network |
A set of strong partnerships between scientific and industrial teams, ensuring rapid commercialization of research results (emphasis on the commercialization of new knowledge) |
|
Competence transfer network |
An actively interacting expert community, the goal of which is to increase overall competence on key scientific issues through the synergy effect (emphasis on generating new knowledge) |
|
Research and innovation networks |
A set of scientific, educational and industrial organizations - partners, united by a common goal (emphasis on supporting the pre-competitive stages of the full innovation cycle) |
The purpose of networks, time periods, forms of existence, and levels can be used as classification criteria.
Let's look at some types of network organizations
Strategic alliances (SA). These types of unions are common among all types of companies. Based on the results of SA studies conducted by foreign experts, the following conclusions can be drawn:
Partnerships between strong competitors (such alliances can create great synergies over a short period of time by consolidating overlapping market and product positions) are usually short-lived. And, as a rule, one of the partners fails to achieve its strategic and financial goals. Most of these alliances end in dissolution.
An alliance of weak companies does not improve the situation of partners. Partnership agreements are quickly terminated or the alliance is acquired by a third party.
Partnerships between a strong company and a weak company are short-lived. Usually a strong partner buys a weak company.
Alliances of complementary strong partners, in which there is no asymmetry in the positions of partners during the life cycle of the alliance, are preserved long time. Such alliances are built on real cooperation between partners. Both partners own important patents on which the alliance depends, so their market relations remain relatively equal, and the risk of unplanned divestitures is low.
To achieve strategic goals, partners can use various forms of intercompany cooperation, however, according to experts, the best partnerships should strive to meet certain criteria:
Both partners are strong and have some value that they bring to their relationship.
The presence of long-term goals for each partner, in which their relationship plays a key role.
Interdependence of partners. They have complementary assets and skills. Neither of them can achieve success alone.
Long-term commitment to the alliance through mutual investment.
Open exchange of information within reasonable limits.
Virtual organization 1 . According to foreign experts (David Teece and Henry Chesbrough) 2, the type of innovation network is determined by the type of innovation. For example, system innovation may require interrelated changes in product development, supply chain management, and information technology. Systemic innovations are associated with tacit knowledge, which is dissolved among specific employees and cannot be transferred except with the transition of a specific employee to a new job. Mature companies can protect such knowledge by disclosing only codified information to counterparties. The open knowledge sharing that underlies systemic innovation is usually easier to establish and protect within a single organization than across multiple companies. System innovations are associated with special management problems specifically in the field of information exchange. By their nature, such innovations require that information be made available and its use coordinated and regulated throughout the product's production system.
Industrial cooperation between small innovative businesses and large corporations. Thanks to such cooperation, innovative firms immediately gain access to proven technologies, and in addition, it is significantly easier for them to enter sales markets. However Russian practice revealed the following disadvantages of such cooperation: 1) price dictate from the outside large companies, 2) dictate of non-monetary terms of the contract (terms, technological requirements, quality standards).
Innovation clusters 1 . The core of an innovation cluster is usually a network of scientific and industrial organizations connected to each other through a large number of innovative projects and having an internal information space for the transfer of innovations 2 .
According to experts, in their economic essence, clusters combine the features of four types of economic systems - object, process, project and environmental 3. In this regard, the innovation strategy of the cluster should include four types of strategies:
strategic plans of enterprises included in the cluster, taking into account their comprehensive relationships (cluster object strategy);
strategic plans for the development and interrelation of processes (cluster process strategy);
strategic description of projects of various types (research, innovation, organizational) implemented by cluster participants (cluster project strategy);
strategic plans for the functioning and development of communities formed from individuals related to cluster organizations (cluster environmental strategy).
Cluster relationships are manifested in the continuous circulation of knowledge, technology transfer, joint research projects, and mobility of qualified personnel. But when identifying a cluster, it is necessary to take into account the fact that it operates within a single value chain. Therefore, his research involves a detailed analysis of barriers to entry, the process of obtaining innovation rent, specific mechanisms for managing transactions, as well as system efficiency.
The results of the study of the functioning of the innovation cluster of Novosibirsk 1 are summarized in table. 2.
table 2
Characteristics of the Novosibirsk innovation cluster
|
Indicators |
IT - cluster |
PR - cluster |
|
Resource Providers |
They gravitate towards the resource market of Akademgorodok and the external market |
They gravitate towards the markets of Novosibirsk and Russia |
|
Labor resources |
Over 90% of qualified labor resources are attracted from the local market. Company managers in both clusters note higher preparedness of engineering and technical personnel than managers |
|
|
Intensity of productive competition |
For knowledge-intensive companies, a tendency has emerged for increased competition as the market becomes larger. This trend indicates the dependence of the local market on the external one, which means the possibility of new competitors entering the local market with the quality of products and processes below the world level |
|
|
Competition for the acquisition of factors of production |
Firms are under intense competitive pressure to acquire qualified personnel as well as premises; weak - when purchasing services; very weak – in the struggle for components and equipment |
|
|
Sources of funding 1 |
Main source – own funds. Funds from cooperation partners are considered as an alternative to our own funds |
The main source of financing is own funds. Grants and government orders are widely used |
|
Competitive advantages |
Value for money; exclusivity of products |
|
|
Main types of business strategies |
Minimizing costs |
Specialization (focus) |
|
Origin and implementation of developments |
About 90% of enterprises in both clusters use developments created by on our own. However, PR companies commercialize developments that are to one degree or another related to public science, while IT companies use developments created in third-party organizations that are not related to science. |
|
|
Cluster life cycle stage |
Developing, as evidenced by the formation of formal and informal alliances between firms and the involvement of new members in the cluster |
|
|
Efficiency of cluster functioning |
Both clusters demonstrate higher growth rates in numbers, revenue and profitability than similar small enterprises on average in Russia. |
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The study made it possible to identify the following priority areas for increasing the competitiveness of the innovation cluster:
development of cooperation between commercial and educational structures in the field of training personnel with the required qualifications;
expansion and deepening of interactions between cluster entities (including between business and science)
creation of the production infrastructure necessary for the functioning of small and medium-sized high-tech businesses (production space, access to financial resources, etc.);
creation of joint innovation-technological and marketing-logistics centers;
improving the institutional environment (legislative, certification and other conditions, improving the system of standards).
The final conclusion is this. For the successful formation and functioning of innovation networks in Russia, the following tasks must be solved:
1) increasing the mobility of scientific personnel; creating conditions for rotation between institutions, scientific disciplines, economic sectors, countries;
2) creation of a world-class innovative infrastructure integrated into a single scientific network through the active use of the latest information and communication technologies;
3) organizing effective exchange of knowledge, especially that created using budget funds (creating open access to this kind of knowledge);
4) improving the coordination of research programs and priorities.
1 Teece D. J. Economies of scope and the scope of the enterprise // Journal of Economic Behavior and Organization. 1980. - N 1. - P. 223 – 247; Nonaka I., Takeuchi H. The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation. - Oxford: Oxford University Press, 1995; Edvinsson L., Malone M. S. Intellectual Capital: Realizing Your Company`s True Value by Finding Its Hidden Brainpower. - N.Y.: Harper Business, 1997; Grant R., Baden-Fuller C. The knowledge-based view of strategic alliance formation: Knowledge accessing versus organizational learning // Cooperative Strategies and Alliances Ed. by Contractor F., Lorange P. – Amsterdam: Elsevier Science Ltd., 2003.
2 Titov L. Yu. Principles of formation of innovation networks in the real sector of the economy // Problems of modern economics. 2009. - No. 1 (29).
1 Milner B.Z. Organization theory. Textbook. – 7th ed. Reworked and additional – M.: INFRA-M, 2009. - P. 772.
1 Voronina L.A., Ratner S.V. Scientific and innovation networks in Russia: experience, problems, prospects. – M.: INFRA-M, 2010. - P. 72.
1 Founders and members of MSITA - International Institute of Pitirim Sorokin and Nikolai Kondratiev, Institute of Economic Strategies, St. Petersburg State University of Engineering and Economics, St. Petersburg State politechnical University, Moscow State Institute of Radio Electronics and Automation, Russian Academy of Public Administration under the President of the Russian Federation, Russian Peoples' Friendship University, Scientific and Technical Holding "Pasarat" (Kazakhstan), Dnieper Institute of Economics and Law, Research Institute "RINKCE", JSCB "My Bank", and also a group of individuals from different countries. The Alliance is forming a network of regional branches and branches: Northern European (St. Petersburg), Central Asian (Almaty), Southern European (Dnepropetrovsk), Western European (Munich), Far Eastern, Islamic, South Asian, Latin American, African, etc. As a result, a global structural network of the Alliance will be created , focused on attracting investment for the implementation of highly effective innovative projects ( http://www. Globefuture. Newparadigm. ru /glfuture 15. htm).
2 http://www. russba. ru /… / article _ id/ 148.
1 Its distinctive feature is the presence of many companies (usually small and medium-sized) pooling resources to implement projects that they are not able to implement individually. Members of a virtual organization achieve significant expansion of the boundaries of their capabilities by achieving significant “virtual” size while maintaining the flexibility inherent in small companies. Such a network is able to cover a wide range of competencies, while each member concentrates its efforts on individual core competencies. Virtual organizations differ from other forms of networks: by a relatively stable pool of partners, which, depending on the order, either forms a new combination of performers or leaves the old one; project coordination that varies depending on the order (not a single enterprise takes on coordination tasks for a long time); weak communication between partner enterprises; modular integration of production services.
2 Strategic alliances. Per. from English – M.: Alpina Business Books, 2008. - P. 180 – 184.
1 A cluster is understood as a geographical concentration of organizations in one or more industries, competing, but at the same time cooperating with each other, benefiting from specific local assets, co-location and social embeddedness. The participants of the cluster are enterprises, educational and research institutions, financial institutions, and government bodies. Their interactions form an environment that directly affects specialized firms, the totality of which represents the “core” of the cluster, which is the essence of the cluster.
2 Experts distinguish three levels of innovation transfer: 1) transfer of only the material component of innovation and a minimal part of its information component, which allows the use of innovation, but does not provide information about its internal structure or the scientific principles on which its functioning is based; 2) transfer, together with the material component, of the technological and/or organizational principles of its operation, which makes it possible to recreate the specified material component either by copying or making the necessary changes to its structure for the purpose of adaptation; 3) transfer of the information component of innovation, which not only allows you to develop this innovation, but also to understand the technological and/or organizational principles that underlie it. As foreign practice shows, the main part of the diffusion of innovation in a cluster from one economic agent to another occurs at the first level.
3 Kleiner G.B., Kachalov R.M., Nagrudnaya N.B. System paradigm in economic research: strategic planning of clusters // Eighth All-Russian Symposium “Strategic planning and development of enterprises”. Abstracts of reports and messages. Section 1. - M.: CEMI RAS, 2007.
1 The foundation of the innovation cluster consists of the intellectual capital of Novosibirsk universities and research institutes, as well as the infrastructure of the NSC SB RAS. Innovation cluster includes two subclusters: information technology (IT - cluster) and innovation and production (PR - cluster). Firms of the first cover the following types of activities: software production, automation, communications and telecommunications, information security. Firms in the second cluster primarily operate in the fields of scientific instrumentation, industrial technology, new materials, biotechnology and medicine. The research was carried out in the context of two subclusters (http: //www. sibai. ru /content/view/506/620/).
1 No respondents mentioned venture capital as a financing method used.