Cross-Industry Spatially Localized Innovation Networks

Karlik, Aleksandr E.; Платонов, В. В.

doi:10.17059/2016-4-22

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…When investigating the sustainability issues, one cannot but recollect the functioning efficiency indicators of industrial complexes and enterprises, as well as approaches to assessment and modelling of these indicators. Main areas of the researches related to sustainable economic growth, as well as competitive strengths and efficiency evaluation of industrial enterprises and complexes were contemplated by A. Karlik, A. Melnik, V. Meshalkin, A. Shinkevich, M. Zotov [10][11][12][13][14]. Some authors, namely, D. Kovalev, V. Rodionova, A. Sheremet, J. Schumpeter equate sustainability with financial standing of an enterprise, whereby unprofitability of the enterprise is regarded as the most critical point, with bankruptcy being considered as one of the institutions fostering sustainability the enterprise [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Modelling sustainable development of industrial systems

Dyrdonova

2023

E3S Web Conf.

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This paper describes a methodological approach that has been developed by the authors for assessment and modelling of sustainable development of industrial systems. Based on experimental testing of this methodological approach applied to the Republic of Tatarstan as an exemplary region, the authors have determined the industry-specific trends in terms of sustainable development of industrial complexes, which are regarded as the dominant elements of the sustainable economic growth process with prevalence of the upstream and high-tech sectors of the economy, along with unstable industries represented by low-tech sectors, as well as the so-called economic growth reinforcing industries. For each identified industrial group, prospects of growth and development have been evaluated as well. In this study the authors have also developed the sustainable growth models involving the models of production functions relevant to definite industrial groups (clusters). The authors furthermore have identified the key factors that are instrumental in better functioning of such groups (clusters). In the course of the production functions modelling, a closer connection between the economic potential and human capital has been tracked, which is particularly exemplified by two out of the three clusters being under review in this paper, namely, in volatile sectors of the economy, as well as in the economic growth reinforcing industries, but with one exception, however, involving the cluster of the economic development dominant elements – the upstream sector of the economy. As such, based on the resulting data, this study sets out the proofs of the “growing heaviness” of the economic development process due to the capital-intensive elements of the upstream sector of the economy, as opposed to a more flexible factor – the human capital.

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Section: Introductionmentioning

confidence: 99%

Modelling sustainable development of industrial systems

Dyrdonova

2023

E3S Web Conf.

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“…Hertem et al conducted an empirical study on the innovation network of the equipment manufacturing industry cluster in Shenyang, but it mainly focused on the node elements and connection mode elements of the equipment manufacturing industry cluster innovation network [4]. Karlik and Platonov analyzed the composition of the equipment manufacturing cluster innovation network from a static perspective and described the innovation network [5]. Zhong summarized and analyzed the structural characteristics of the cluster innovation network, took the typical three types of industrial clusters in the west as an example, and studied the structural characteristics of the cluster innovation network [6].…”

Section: Introductionmentioning

confidence: 99%

Evolution Mechanism of Advanced Equipment Manufacturing Innovation Network Structure from the Perspective of Complex System

Wang

Xing

2021

Complexity

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Our country’s equipment manufacturing industry ranks among the best in all developing countries, but compared with developed countries, there is still a long way to go. It is not only the backwardness of various technologies, but also the interference of other countries. Although our country's equipment manufacturing industry is not as advanced as the advanced technology of developed countries, we still have to stick to our original aspirations, do not underestimate ourselves, and be good at absorbing and learning from the strengths of others to make up for our own weaknesses. While not working behind closed doors and while absorbing technology from other countries, we can make use of our strengths to make up for our weaknesses and develop our own industrial technology. This paper studies the evolution trend of innovation network structure and at the same time studies the evolution mechanism of advanced equipment manufacturing innovation network structure from the perspective of complex systems. The explained variable in this article is green total factor productivity. The variable adopts the Malmquist–Luenberger global super-efficiency index model. There are two main explanatory variables. One is the heterogeneity that affects the efficiency of industrial evolution, including factor heterogeneity, structural heterogeneity, and environmental heterogeneity, and the other is the interaction term of equipment manufacturing specialization agglomeration degree dummy variable multiplied by factor heterogeneity. The regional economic development level is added to the model as a control variable. In the selection of measurement indicators, the per capita GDP is used as the control variable. The experimental results show that each sample is tested in pairs, and the standard error level of the mean is 0.018, which is less than 0.05, indicating that the efficiency of the equipment manufacturing industry’s economic correlation spatial network has a significant impact on the overall economic development level of the industry. The reduction in spur helps to increase economic output.

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