Evaluation of Intellectual Capital in Regions of Volga Federal District of Russian Federation

Kotenkova, Svetlana; Korablev, Maksim

doi:10.1016/s2212-5671(14)00722-9

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Relational capital embodies the knowledge that is generated by the relationship between the region and the environment. It involves the ability to implant and self-generate value, product demand, investment potential, and joint projects [57]. It is not only important to create relationship capital, but a successful organization should also be able to maintain its relationship capital [58].…”

Section: Literature Review 21 Components Of Intellectual Capitalmentioning

confidence: 99%

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A Hybrid Multiple Criteria Decision-Making Technique to Evaluate Regional Intellectual Capital: Evidence from China

Liu

Jiang

et al. 2021

Mathematics

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With the dawn of economic globalization and the knowledge economy, intellectual capital has become the most important factor to determine economic growth. However, due to resource endowment, location conditions, policy differences, and other factors, provinces in China show sizeable differences in regional intellectual capital (RIC), which affects the coordinated development of the regional economy. Evaluating RIC is a typical multiple-criteria decision-making (MCDM) problem. Therefore, this study employs a set of MCDM techniques to solve this problem. First, the Delphi method is used to determine the formal decision structure based on a systematic literature review. A novel hybrid method, namely, the Grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP), i.e., GDANP, is employed to obtain the relative weight of each criterion. Finally, based on the data of 31 provinces in China, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to evaluate the RIC. According to the questionnaires filled out by an expert panel, we establish an evaluation index of RIC with 21 criteria. Based on the results of empirical study, the level of RIC in different regions in China is quite different. Furthermore, the RIC ranking is largely consistent with the provincial gross domestic product (GDP) ranking, in line with the current status of development in the regions. Indeed, this paper shows that the proposed hybrid method can effectively measure the level of RIC.

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Section: Literature Review 21 Components Of Intellectual Capitalmentioning

confidence: 99%

“…The number of doctors per 10,000 people [46] The number of medical beds per 10,000 people [46] Total health expenditure [44] Employment status The number of employed persons [59] Unemployment rate [57,59]…”

Section: Educational Developmentmentioning

confidence: 99%

A Hybrid Multiple Criteria Decision-Making Technique to Evaluate Regional Intellectual Capital: Evidence from China

Liu

Jiang

et al. 2021

Mathematics

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“…199-211), including regional IC in the Russian Federation (Kireeva & Galiakhmetov, 2015, pp. 240-247;Kotenkova & Korablev, 2014, pp. 342-348, Tsertseil & Ordov, 2017.…”

Section: Introductionmentioning

confidence: 99%

The spread of the regional intellectual capital: the case of the Russian Federation

Markhaichuk

Zhuckovskaya

2019

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Research background: The positive relationship between the availability of intellectual capital and the ability of the state, region or firm to develop economically stimulates an increase in the intellectual capital. In order to manage intellectual capital, it is necessary to have a clear idea of its availability, capacity, features, growth reserves, as well as concentration in certain territories and ability to spread. Many studies are devoted to the measurement of intellectual capital, its diffusion and impact on the economic efficiency of the organization, region, and nation. However, in the case of the Russian Federation there is a gap in the study of the spread of intellectual capital over the country. Purpose of the article: The purpose of the article is to evaluate intellectual capital in the federal districts of the Russian Federation and to model the spread of intellectual capital. Methods: Data on 8 Russian federal districts for the 2017 year from Unified Inter-departmental Information and Statistical System (EMISS) of the Russian Federation were taken as a basis for the research. Based on three-component model (human capital, structural capital, and relational capital), we formed a set of indicators for assessing regional intellectual capital, relevant to the Russian Federation. This allowed us to evaluate the integrated indicators of intellectual capital in federal districts and to determine the probability of intellectual capital spreading from each federal district to neighboring federal districts. We used percolation theory methods to model the spread of intellectual capital. Findings & Value added: The study contributes to the Russian regional knowledge on intellectual capital. Intellectual capital in the Russian Federation is disproportionately distributed, concentrating closer to the capital, and has a lower level in remote territories. It spreads unevenly, flowing from the Central Federal District to neighboring federal districts, however, other federal districts develop almost in isolation.

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High Education, Professional Insertion and Economic Development in Romania

Serban

Istrate

2017

Advances in Applied Economic Research

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Evaluation of Intellectual Capital in Regions of Volga Federal District of Russian Federation

Cited by 4 publications

References 5 publications

A Hybrid Multiple Criteria Decision-Making Technique to Evaluate Regional Intellectual Capital: Evidence from China

A Hybrid Multiple Criteria Decision-Making Technique to Evaluate Regional Intellectual Capital: Evidence from China

The spread of the regional intellectual capital: the case of the Russian Federation

High Education, Professional Insertion and Economic Development in Romania

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