Modelling the dynamics of the &amp;#x201C;Smarter Region&amp;#x201D;

Akopov, Andranik S.; Beklaryan, Gayane

doi:10.1109/cifer.2014.6924074

Cited by 10 publications

(11 citation statements)

References 7 publications

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“…At the same time, applying methods of agent-based modelling (Akopov et al, 2019;Akopov et al, 2017;Baindur and Viegas, 2011) allows the possibilities of the analysis of the production and investment characteristics of Russian regions to be extended, in particular, to forecast the total number of enterprises and investors at the regional level ( Figure 7). The agent model developed in this work can be employed to develop a decision-making system for rational management at the regional level (Akopov and Beklaryan, 2014;Beklaryan, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…The research methodology is based on previous methods of system dynamics and agent-based modelling developed for regional systems (Akopov and Beklaryan, 2014;Akopov et al, 2017). At the present time, ABM methods are applied for the research of regional economies (Berger, 2001;Baindur and Viegas, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

“…There is a line of research related to the analysis of the economic state of the Russian regions (Akopov and Beklaryan, 2014;Zinovyeva et al, 2016;Veselovsky et al, 2017;Berezhnaya et. al., 2018;Miloradov et al, 2018;Voronkova et al, 2018;Zelinskaya et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…This research is mostly devoted to some aspects of regional economics based on statistical data. For example, the regional CGE (Common General Equilibrium Model) is discussed in a study by Akopov and Beklaryan (2014) that aimed to identify the best forms of economic policy at the regional level. This model uses system dynamics methods developed by Forrester for the first time in the middle of the 20th century (Forrester, 1958).…”

Section: Introductionmentioning

confidence: 99%

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Modelling the Efficiency of the Use of Production and Investment Resources at the Regional Level: The Case of Russia

Gayane¹,

Andranik²

2019

IJEBA

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The important feature of the suggested approach is to take into account the average (normative) return of sectoral resources by computing the efficiency scores of regions. Methods of agent-based modelling (ABM) were applied in the investigation using the 'gravity effects' that described the behaviour of agent-enterprises. Moreover, agent-investors regarding agent-regions are considered. Findings: The key findings are: (1) There is a significant inequality and a gap between the leading regions of Russia (such as Moscow, Moscow Oblast and Saint Petersburg) and other regions. At the same time, many non-leading regions are more stable and attractive; (2) A complex classification of Russian regions based on solving four tasks, namely the 'ratio of production to labour', 'ratio of production to assets', 'ratio of investments to labour' and 'ratio of investments to assets' is an effective approach to estimate region states; (3) In the leading regions e.g., Moscow, has decreasing efficiency scores after 2014, which is probably due to the large influence of crisis phenomena on the largest Russian agglomerations in comparison with other regions; (4) The 'gravity model' explains the behaviour of economic agents and allows forecasting the number of regional enterprises and investors. Practical implications: The developed method can be practically applied for other countries with non-homogeneous regional economies. Originality/Value: For the first time the dynamical model of the efficiency of the use of production and investment resources at the regional level of Russia is suggested. Such model allows examining regional changes.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling the Efficiency of the Use of Production and Investment Resources at the Regional Level: The Case of Russia

Gayane¹,

Andranik²

2019

IJEBA

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“…Nowadays, in order for the simulation of an emergency evacuation to be as efficient as possible, the simulation's model must impersonate reality as well as possible. Obtaining the most authentic data is a challenge as they can be extremely diverse when it comes to human behavior, which leads to an increased difficulty in developing the model [17,18]. At the same time, these simulations are an efficient procedure for estimating evacuation times depending on various factors, variable or not.…”

Section: Introductionmentioning

confidence: 99%

Cybernetics Approach Using Agent-Based Modeling in the Process of Evacuating Educational Institutions in Case of Disasters

2021

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In the context of an emergency, evacuating people from a location in the shortest possible time is essential, as is the high degree of safety that people should expect when evacuating. Lately, in Romania there have been more and more fire events generated by different causes. This article will use agent-based modeling to simulate an emergency evacuation model in NetLogo. The model has been used to perform and analyze various scenarios. With the help of NetLogo, we managed to perform 400 simulations with the evacuation of 180 people (students, teachers, and non-teaching staff) based on which we developed several recommendations to streamline the evacuation process in order to reduce the possibility of death. The present research will help to identify the evacuation times from a school, but it will also highlight certain aspects that may occur during the evacuation. The model that was used in this research took into account the individual particularities of the people taking part in the evacuation, emphasizing the effects that form in a crowd of people when evacuating; effects such as the funnel effect, which is caused by the formation of bottlenecks around narrow areas. All these things are part of the analysis of the measurement of entropy of the exhaust system, a problem that has captured all of the specialists’ attention. Finally, solutions have been proposed to improve evacuation time in case of disasters.

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Decision support system for sustainable economic development of the Far Eastern Federal District

Beklaryan¹

2018

Bus. Inform.

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Modelling the dynamics of the “Smarter Region”

Cited by 10 publications

References 7 publications

Modelling the Efficiency of the Use of Production and Investment Resources at the Regional Level: The Case of Russia

Modelling the Efficiency of the Use of Production and Investment Resources at the Regional Level: The Case of Russia

Cybernetics Approach Using Agent-Based Modeling in the Process of Evacuating Educational Institutions in Case of Disasters

Decision support system for sustainable economic development of the Far Eastern Federal District

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