comparative assessment of innovative activity of region s economy actors on the basis of the triple helix model

Peer-review under responsibility of the International Strategic Management Conference doi: 10.1016/j.sbspro.2015.10.172 ScienceDirect 11th International Strategic Management Conference

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Procedia - Social and Behavioral Sciences 207 ( 2015 ) 816 – 823

( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Peer-review under responsibility of the International Strategic Management Conference

doi: 10.1016/j.sbspro.2015.10.172

ScienceDirect

11th International Strategic Management Conference 2015 Comparative Assessment of Innovative Activity of Region’s Economy Actors on the Basis of the Triple Helix Model

a North-Eastern Federal University, Yakutsk, Russia

b Peter the Great St.Petersburg Polytechnic University, St.Petersburg, Russia

Abstract

The paper demonstrates an econometric method of quantitative assessment of innovative activity of region’s economy actors of different levels on the basis of innovation dimensional space model, allowing to assess the role of every Triple Helix participant

in the innovative development of the region as a whole, as well as broken down to a specific municipality, real economy sector, territory-specific innovative clusters etc

Regions of Far-East Federal District of the Russian Federation (FEFD) are taken to illustrate the research subject The paper shows the results of numeric calculations related to express-analysis of the contribution of the main innovation actors – science/education, business, state – to the innovative development of the regions on the basis of 2012 statistics It can be seen that the general level of innovative development of regions’ economy of the district under analysis is mainly determined by the innovative activity of science/education This outcome indicates insufficient mobilization and application of the creations of human mind, made in the universities and R&D centers, in the development of the region’s innovative activity

Ranking comparative analysis demonstrates, that the ranking, made according to the method of the authors, reflects the innovative development of FEFD actors in general and does not differ much from the results of other rankings, which proves this method effective

The proposed method and outcomes of the econometric calculation may be used by executive bodies of the government, business entities, research centers and educational establishments to take various managerial decisions about innovative development of region’s economy, strategies and economy development programs of different levels

Keywords: Triple Helix, econometric model, system of indicators, innovative “portrait” of the region

* Corresponding author Tel.: +7-411-235-3265

E-mail address: ene01@yandex.ru

( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

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N.E Egorov et al / Procedia - Social and Behavioral Sciences 207 ( 2015 ) 816 – 823

1 Introduction

Modern literature on economics suggests various methods and models for the evaluation of innovative development of the region (IDR) as well as in the system of strategic management (Tafti, S F., Jahani, M., Emami,

S A., 2012, Kortelainen, S., Lättilä, L., 2013) It is impossible to compare the methods of ranking agencies from the point of view of their contents, as the range of indicators, taken under consideration by various agencies, as well as how significant the each indicator is according to the opinion of the scientists, remain closed for the public at large According to those who develop such method, it is their commercial know-how (Bakhtizin, Akinfeev, 2010; Zorzoliu, R 2012) We believe the main reason for the variety of methods is the absence of a single methodological approach towards the choice of indicators, characterizing innovative resources Economic calculation, made to assess innovative resources of the region, are made on the basis of an expert inquiry and important indexes, which brings some subjectivity to the indicators, influencing the precision of evaluation results (see, for example, Bortnik and others, 2012; Rodionov D.G., Rudskaia I.A., Guzikova L.A., 2014)

At present, there are no data in Russian and foreign literature on economics about the methods of quantitative assessment of the contribution, made by science/education, business and authorities, to the innovative process (Saetre, A.S and Brun E., 2012) It shall be also noted that current methods are used mainly for expert evaluation of the state of a region’s economy without sufficient regard to nature, climate, geographic and social features of the Russian North The outcomes of the evaluation shall also depend on the structure of the main economy indicators that are different for different entities of Russia For example, the main features of the northern regions are extreme nature and climate conditions, remoteness of the northern regions from the political center, insufficiently developed system of transport infrastructure, being the reason, why it costs a lot more to manufacture products there and to provide the population with life necessities, in comparison to the central regions, as well as environmental vulnerability of the North

2 Triple Helix Model

The establishment of clusters in foreign countries shows that not only market efforts stand behind innovative clusters Their successful development is in one way or another related to the so-called “triple helix” The triple helix model is a recipe of success of “spontaneously created” Silicon Valley Though the idea of clusters of M Porter (Porter, 1993) and the idea of triple helix of Etzkowitz-Leydesdorff (Etzkowitz H., Leydesdorff L., 2000) were formed independantly of each other, they appeared to be extremely complementary Their scientific synthesis allows us to see, that the unique innovative effect, achieved in the clusters, is determined by their network institution design, while the shift of the economy to the innovative growth is determined by the success of its universal clustering That having been said, the model of M Porter tracks the mechanism of such growth “at the output” (as the result of cluster presence), and helix model – “at the input” (as a condition of their appearance) (Smorodinskaya, 2011)

The triple helix symbolizes a union of authority, business and university (actors) that represent key elements of the innovative system of any country Particularly there, where these elements partially overlap, people meet and new ideas are being generated: this is how innovations are born So such model becomes well balanced And in this well-balanced model institutions acquire a new function of other institutions, apart from performing their regular functions

According to the competitiveness theory of M Porter (Porter, 2005) and triple helix model of H Etzkowitz (Etzkowitz, 2010) all the resources of innovative process participants are concentrated where the areas of focus of the mentioned actors overlap, which gives a synergetic effect for the development of new breakthrough technologies

At the moment, the triple helix of Russia is at its very first stage of development It is not a system yet, but preliminary bilateral relations: science-business, state-science and state-business It has the following characteristic features First of all, supremacy of state over science and business Over-involvement of state has a negative impact

on the development of network interactions, on new grassroots initiatives and their natural spread Secondly, the larger part of fundamental R&D takes place not in the universities (higher education institutions), as in the most

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countries all over the world, but in the institutes of the Russian Academy of Science (Dezhina I.G., 2011; Glukhov V.V., Ilin I.V 2014)

The basic principle of the Triple Helix Model is understanding of a university as a key player The model presupposes the establishment of the universities of the new type that will play an active role in society, change their key functions and be responsible for the implementation of innovations In modern Russian conditions the model of cooperation between the universities, business and state can be realized in a limited number of regions in the form of

an innovative cluster in the facilities of technic and scientific universities, academic and industry-specific scientific centers in close cooperation between federal and regional authorities within the framework of realization of the national economy development strategy (Monastirscky, Uvarov, 2011)

3.Methodology

This paper presents an econometric model of dimensional space of innovations that was developed on the basis of the “Triple helix” model, known in the world science, and allows making numeric calculations for quantitative assessment of the role, that each helix participant plays in the innovative development of a region’s economy (Egorov N and Egorov E., 2014) The proposed econometric model allows us to make a quantitative assessment of the contribution that each helix participant makes to the innovative development of economy actors of different levels on the basis of known trigonometric expressions It shall be noted that a similar model of vector relations between university, industry and government is described in the papers of I Ivanova and L Leydesdorff (Ivanova I., Leydesdorff L., 2014)

According to S.V Kazantsev (Kazantsev, 2012), while doing research of a specific item with a specific target, one should not over-expand the set of indicators, taken into consideration, and should not increase the precision of their quantitative representation to the fullest extent Appropriate research tools can be chosen according to the features and precision of analyzed characteristics of a studied item We should not simply choose powerful tools from what is known and available Even with a simple set of tools and limited information it is possible to receive important results that can be used to develop the elements of economic policy In the light of this statement, we can say, that in order to conduct a quick express-evaluation of a region’s innovative activity, we can use a simplified system of the main indicators, characterizing participation of science/education, business and state in the innovative development of the region in general

Table 1 demonstrates a list of the main indicators that, according to the authors, are sufficient to determine the activity level of the main actors of innovative activity and to conduct express-evaluation of a region's innovative development

Table 1 The system of indicators for express-analysis of the contribution of Triple helix participants to the innovative development of the regions

Innovative activity actor Name of the indicators*

Science/education (I 1 )

Business (market)(I 2 )

State (policy)(I 3 )

Share of organizations, doing R&D Share of personnel, doing R&D For the number of intellectual property item Level of organizations' innovative activity Share of expenditures for technological innovations Specific weight of the volume of innovative goods, work, services in the total volume of shipped goods, performed work, services

For legislative acts, laws and regulations regarding innovative policy For the number of innovative infrastructure organizations

For R&D costs

* All indicators are given in percentage ratio to the corresponding general indicators regarding the analyzed district

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4.Results of calculations

For illustrative purposes, regions of the Far-East Federal District of the Russian Federation (FEFD) were taken as

a target of research All the calculations were made on the basis of the official federal and regional data of 2012 The outcomes of ranking calculations regarding FEFD entities demonstrated that the leaders are Primorkiy region, Khabarovskiy region, and the Republic of Sakha (Yakutia) They are the ones that make the most significant contribution (67.9%) to the innovative development of FEFD (table 2)

Table 2 Ranking of FEFD entities' innovative development

Region contribution, % Percentage of Ranking

Republic of Sakha (Yakutia) Kamchatka region Primorsky region Khabarovsk region Amur district Magadan district Sakhalin district Jewish Autonomous Province Chukotka Autonomous Province

15.4 8.0 31.8 20.7 9.5 8.0 6.7 0.0 0.0

3 5-6

1

2

4 5-6

7 8-9 8-9

Fig.1 illustrates how the contributions of the “triad” to the innovative development if FEFD entities are distributed As the figure shows, the main contribution is made by “science/education”, on the second place there is

“State” and the smallest contribution is made by “Business” This outcome demonstrates that we do not pay appropriate attention and do not fully use the results of human intellectual activity of universities and scientific centers for the development of a region’s innovative activity Participation of state authorities in the innovative development of region’s economy is determined by the presence of legislation related to the innovative activity and how big the expenditures for R&D are However, these indicators do not have a big influence on the real state of innovations in the regions

Fig 1 The level of activity of the main innovation actors in FEFD regions

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Primorsky region takes a leading place mostly thanks to a large number of received intellectual property assets (IPA) (268 items) and personnel, doing R&D (5482 people) The same indicators are also quite high in Khabarovsk region (236 IPA and 1612 people) and the Republic of Sakha (Yakutia) (90 IPA and 2378 people)

The calculation results show, that scientific and educational resources make a significant contribution to the innovative development of FEFD regions (75.7%), while the activity of business enterprises and authorities accounts for only 6.5% and 17.8% correspondently (Fig.2) The main scientific and educational resources are located in 5 entities of the Far East (66.8%), while North-Eastern regions account for only 8.9%

Fig 2 The distribution of triad's contribution to the innovative development of FEFD

As far as analysis results with a breakdown into regions are concerned, mainly 3 entities make a key contribution

to the innovative development of FEFD regions: Primorsky region (31.88%), Khabarovsky region (20.65%), and the Republic of Sakha (Yakutia) (15.36%) (Fig.3) The contribution of macroregion’ South (Primorsky region, Khabarovsk region, Amur region, Sakhalin district, and Jewish Autonomous Province) makes up 67.65%, four regions of the northern part of macroregion (the Republic of Sakha (Yakutia), Kamchatka region, Magadan region, and Chukotka Autonomous Province) make up 32.43%

Fig 3 Contribution of the triad's members to the innovative development of FEFD

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The ranking comparative analysis shows that according to the method, proposed by the authors, the ranking reflects innovative development of FEFD entities and does not differ much from the outcomes of other rankings, which proves the efficiency of the method At the same time it is worth mentioning that the differences in assessments are most probably caused by the quality and quantity of chosen indicators in each group, different data,

as well as differences between the minimum and maximum value of an indicator related to the Russian Federation and FEFD By no means unimportant are validity and scarcity of statistic data related to the main indicators of the regions’ innovative activity, processed according to “#4 Innovations” form

This method also allows forming an innovative “portrait” of a certain region similar to the method of Association

of innovative development of the regions (AIDR, Bortnik and others, 2014) Fig.4 illustrates an innovative “portrait”

of the region, showing the level of the main innovative activity indicators in the Republic of Sakha (Yakutia) We believe that a comparative analysis of the figures shows, that the main indicators, chosen for express-analysis, according to the method of the authors reflect an overall reality of modern state of republic’s innovative development It is possible to formulate specific recommendations for managerial decisions on their basis

Fig 4 Innovative «portrait» of the Republic of Sakha (Yakutia)

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5 Conclusion

In order to make economic and mathematician calculations related to the evaluation and monitoring of the activity of economy actors according to the proposed method, it is required to make a system of indicators, characterizing innovative resources of science/education and business, as well as state innovative policy

Numeric calculations, performed according to the described method, generally allow evaluating the role of every triad participant in the innovative development of the region on the whole, as well as broken down to specific municipalities, real economy sectors, territory-specific innovative clusters etc In such a case the outcomes of calculations will depend on chosen economic indicators of the analyzed item, their number may be increased depending on the set target

The outcomes of the calculations may be used by executive authorities, business enterprises, scientific and educational establishments to analyze and forecast the establishment and development of innovative system, strategies, economic development programs of different levels

6 Results

1 The authors have developed an econometric method of quantitative assessment of innovative activity of region’s economy actors of different levels on the basis of innovation dimensional space model, allowing to assess the role of every Triple Helix participant in the innovative development of the region as a whole, as well as broken down to a specific municipality, real economy sector, territory-specific innovative clusters etc

2 There is shown the system of the main economic indicators to determine the level of activity of the main subjects of innovative activity

3 There are shown the results of numeric calculations related to express-analysis of the contribution of the main innovation actors – science/education, business, state – to the innovative development of the regions on the basis of statistics

4 There is proved that the general level of innovative development of regions’ economy of the district under analysis is mainly determined by the innovative activity of science/education

7 Directions of further studies

A future-oriented aspect of the next research is related to the use of the proposed method in the resolution of the issues related to the clusterization of the basic industries of the region, as well as in the evaluation of the impact that the innovations have on the society, which means expansion of the indicator system by including social indicators of human life

Acknowledgments

Research is done within the framework of the projects No 01201460076, No 01201460078, No 26.1303.2014/К

of the state task of the Ministry of education and science of the Russian Federation, grant of Russian Fundamental

Research Foundation No 15-06-00600-А

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