At the initial stage of economy innovative potential formation, the leading role belongs to small venture firms that provide market development of the intellectual activity results. Support for small businesses of this type is usually provided through the development of a business incubators system initiated by regional authorities and implemented through targeted budget funding. In this regard, it is important for incubators to develop an indicators system for evaluating the effectiveness of budget allocations and private investment. The paper proposes a two-level system of business incubator functioning and develops a management structure that allows analyzing the current state of the organization and the results of its work using a mathematical model. The incubator activity is determined by the state of the system at the time of starting the next cycle of work, the state of the incubated companies at each stage of incubation (pre-incubation, incubation, post-incubation) and planned tasks, taking into account resource and technological limitations. The proposed model can be used in the development of methods for continuous deviations monitoring from the planned performance indicators of the organization with the ability to pinpoint the problem and respond to it. The advantage of the proposed model is that it can be scaled up to the level of the innovation structure of the region.
The article assesses the Technology Readiness Level (TRL) according to the developed TRL checklist. The TRL approach has been applied to analyzing the technology readiness level of a Russian start-up company producing systems of multisensory and multifunction devices for Smart House. The authors approbated the modified TRL methodology, which made it possible to evaluate the readiness of technologies’ integration among themselves and to get a generalized assessment of the readiness of the technologies’ system – Integration Readiness Levels (IRL). It has been proved that the System Readiness Level (SRL) of technology corresponds to the design concept stage. Taking into account indicators and means of quality assurance at the stages of design and initiation of such production is highly relevant.
Neural network modeling based on self-organizing Kohonen maps was carried out in order to cluster the economy of one of the administrative districts of the Krasnoyarsk Territory. The research is based on statistical data on the economy of about one hundred enterprises of various spheres operating in the region. It is shown that in the process of clustering four groups of enterprises can be clearly distinguished according to the types of economic activity. Having applied the neural network modelling method, we identified three enterprises within the framework of this cluster, which can be considered as “growth areas” of the district economy. Self-organizing maps that is trained using unsupervised learning make it possible to get an idea not only of promising areas of development, but also to identify key parameters that ensure the leadership and competitiveness of the region.
Digitalization entails the application of digital technologies to a wide range of existing tasks and enables solution of new tasks. This article is based on data sets on current sales volumes of innovative products to forecast their future sales. The first stage is applying the innovation diffusion in the F. Bass model to calculate the diffusion coefficients of different modifications of Sony’s PlayStation. To estimate factors which influence innovation and related results within firms, the company IMPRINTA producing 3D printers was surveyed. It is shown that taking into account technical parameters, a cascade diffusion model of product innovation is the best for describing the process of product realization. The information obtained from the diffusion analysis of two 3D printer models can be used to improve the efficiency of key business processes, including production, procurement, marketing and advertising. The use of the diffusion model made it possible to generate three different scenarios for the release and promotion of a new modification of one of the 3D printer models depending on the selected niche, the time of market launch and the intensity of the marketing and advertising campaign. Each scenario enables adjusting the cost and technical parameters of the future modification.
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