Abstract
This article presents the methodology and tools for the econometric analysis and assessment of the innovation development of the Russian Arctic regions, under the Triple Helix concept. The econometric calculations based on this methodology allow the express assessment of innovation development of a region and the contribution of the science and education complex (SEdC), industries, and the government, to the integral index of innovation development of this region, using minimum key statistical indicators in the field of science and innovation. The calculation results obtained using the author’s methodology show the adequacy of the express rating, with respect to the rating data obtained using other methodologies. The main advantage of the proposed methodology is the elimination of the human factors arising from the weighing coefficients and the results of the expert assessments used in the other rating methodologies The calculation results obtained using this methodology might be useful to the executive bodies of state authorities, business entities, and scientific and educational institutions, for an express assessment and for making various organizational and managerial decisions on innovation development in a region.
Highlights
The efficiency of innovative policy implementation depends largely on the system of indicators that provide the grounds for the detection of innovative activity, and the monitoring of its development.In this regard, one of the main tasks in this direction is to form a set of indicators to assess the level of innovation development of a region, which would take into account the necessary capabilities and resources [1,2,3,4]
We present an author’s model and methodology to perform econometric assessments of the level of an economic entity innovation development (EEID), basedentity on theinnovation
Performance is the objects of intellectual property, which are certified and registered by Rospatent, and are in demand by the innovative business represented in the form of the statistical indicator “the number of patents issued in Russia for inventions, utility models, and industrial designs, per 1000 labor potential (LP)”
Summary
The efficiency of innovative policy implementation depends largely on the system of indicators that provide the grounds for the detection of innovative activity, and the monitoring of its development. Assessments of regional innovative potential are mainly conducted on the basis of expert survey data, which introduces subjectivity of indicators that leads to inaccuracy of the assessment results. In this regard, we present an author’s model and methodology to perform econometric assessments. Resources 2019, 8, 72 to inaccuracy of the assessment results In this regard, we present an author’s model and methodology to perform econometric assessments of the level of an economic entity innovation development (EEID), basedentity on theinnovation. Of the level of an economic development (EEID), based on the Triple Helix model concept [10,11,12,13]
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