IDEAS home Printed from https://ideas.repec.org/a/url/upravl/v14y2023i6p63-76.html
   My bibliography  Save this article

Methodology for regional industrial complex management: Architecture of an agent-based model

Author

Listed:
  • Andrey F. Shorikov

    (Institute of Economics of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia)

  • Grigory B. Korovin

    (Institute of Economics of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia)

  • Dmitry V. Sirotin

    (Institute of Economics of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia)

Abstract

Industry is the backbone of the economy of developed countries and individual regions. To optimize management processes in such a complex and multi-level sector, specific economic-mathematical models and practical tools have to be developed. The paper discusses the optimal architecture of the regional industrial complex management model on a modern theoretical-methodological and instrumental (program) basis. The classical management theory, optimization theory and game theory constitute the methodology of this study. Among the research methods applied are agent-based and minimax approaches. We substantiate the use of agent-based modelling to simulate administering the regional industrial complex. The paper presents a three-tiered management architecture consisting of federal, regional and company level authorities (united by type of activity). For each level, control agents are identified and a set of indicators formed, which cover the structure of the phase vector, including its attributes, key parameters, control actions used, risks, a model of the parameters’ dynamics, and a model of the data possessed by the object. We build a hierarchical structure of administration and information relationships in the model and, based on the minimax approach, create an algorithm of agents’ efforts to select optimal control actions. The proposed architecture will allow forming a flexible toolkit for assessing industrial development scenarios and producing the best step-by-step management pattern of the regional industrial complex.

Suggested Citation

  • Andrey F. Shorikov & Grigory B. Korovin & Dmitry V. Sirotin, 2023. "Methodology for regional industrial complex management: Architecture of an agent-based model," Upravlenets, Ural State University of Economics, vol. 14(6), pages 63-76, December.
  • Handle: RePEc:url:upravl:v:14:y:2023:i:6:p:63-76
    DOI: 10.29141/2218-5003-2023-14-6-5
    as

    Download full text from publisher

    File URL: https://upravlenets.usue.ru/images/106/5.pdf
    Download Restriction: no

    File URL: https://upravlenets.usue.ru/en/issues-2023/1451
    Download Restriction: no

    File URL: https://libkey.io/10.29141/2218-5003-2023-14-6-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    2. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    3. repec:hal:spmain:info:hdl:2441/5hussro0tc951q0jqpu8quliqu is not listed on IDEAS
    4. Gabbi, Giampaolo & Iori, Giulia & Jafarey, Saqib & Porter, James, 2015. "Financial regulations and bank credit to the real economy," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 117-143.
    5. Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2012. "Debt, deleveraging and business cycles: An agent-based perspective," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-49.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    2. repec:hal:spmain:info:hdl:2441/dcditnq6282sbu1u151qe5p7f is not listed on IDEAS
    3. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux," Working Papers hal-03459348, HAL.
    4. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).
    5. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    6. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    7. Teglio, Andrea & Mazzocchetti, Andrea & Ponta, Linda & Raberto, Marco & Cincotti, Silvano, 2019. "Budgetary rigour with stimulus in lean times: Policy advices from an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 59-83.
    8. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2020. "Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    9. Deryugina, Elena & Ponomarenko, Alexey & Rozhkova, Anna, 2020. "When are credit gap estimates reliable?," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 221-238.
    10. repec:hal:spmain:info:hdl:2441/1j4v8sl4fc9a49ankmnhv6bb6a is not listed on IDEAS
    11. repec:hal:spmain:info:hdl:2441/31dhti786q9k0q2i04klh6no54 is not listed on IDEAS
    12. Gurgone, Andrea & Iori, Giulia & Jafarey, Saqib, 2018. "The effects of interbank networks on efficiency and stability in a macroeconomic agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 257-288.
    13. Poledna, Sebastian & Bochmann, Olaf & Thurner, Stefan, 2017. "Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based, systemic risk-dependent financial transaction taxes," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 230-246.
    14. Gross, Marco, 2022. "Beautiful cycles: A theory and a model implying a curious role for interest," Economic Modelling, Elsevier, vol. 106(C).
    15. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    16. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    17. repec:hal:spmain:info:hdl:2441/5bnglqth5987gaq6dhju3psjn3 is not listed on IDEAS
    18. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    19. Francesco Lamperti & Antoine Mandel & Mauro Napoletano & Alessandro Sapio & Andrea Roventini & Tomas Balint & Igor Khorenzhenko, 2017. "Taming macroeconomic instability," SciencePo Working papers Main hal-03399574, HAL.
    20. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    21. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    22. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    23. Giovanni Dosi & Andrea Roventini, 2017. "Agent-Based Macroeconomics and Classical Political Economy: Some Italian Roots," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 261-283, November.
    24. Guerini, Mattia & Napoletano, Mauro & Roventini, Andrea, 2018. "No man is an Island: The impact of heterogeneity and local interactions on macroeconomic dynamics," Economic Modelling, Elsevier, vol. 68(C), pages 82-95.

    More about this item

    Keywords

    management; agent-based modelling; regional industrial complex; minimax approach; industrial management;
    All these keywords.

    JEL classification:

    • L52 - Industrial Organization - - Regulation and Industrial Policy - - - Industrial Policy; Sectoral Planning Methods
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:url:upravl:v:14:y:2023:i:6:p:63-76. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Victor Blaginin (email available below). General contact details of provider: https://edirc.repec.org/data/usueeru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.