IDEAS home Printed from https://ideas.repec.org/a/url/upravl/v13y2022i6p2-14.html
   My bibliography  Save this article

Managing industrial complexes: A hierarchical agent-oriented model

Author

Listed:
  • Viktoriya V. Akberdina

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

  • Andrey F. Shorikov

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

Abstract

Among the system problems in managing an industrial complex are the difficulties in determining its composition, coordinating the goals of management subjects, and formalizing the conditions for optimal management. The paper examines the processes of forecasting the state of an industrial complex and managing its potential most effectively at different hierarchical levels. The theoretical framework of the study is the network approach to the subject-object structure of the industrial complex viewed as a complex dynamic system. The method of agent-oriented modelling was used as having certain advantages in comparison with neoclassical equilibrium models. For the processes in question, we propose utilizing a deterministic economicmathematical model, in which the dynamics of the main factors (phase vectors) is described by the relevant vector linear discrete recurrent equations in the presence of control actions. The developed management system has three levels of decision-making: (1) the dominating (federal) level controlled by an aggregated federal agent; (2) the first subordinate (regional) level controlled by aggregated regional agents; and (3) the second subordinate (enterprises) level controlled by production agents. The article presents a general scheme for solving the problems of forecasting the state of and optimizing the management of the production potential using the developed three-level hierarchical discrete controlled dynamic system. The results obtained can be used in the design of intelligent computer systems for information supply and managerial decision-making.

Suggested Citation

  • Viktoriya V. Akberdina & Andrey F. Shorikov, 2022. "Managing industrial complexes: A hierarchical agent-oriented model," Upravlenets, Ural State University of Economics, vol. 13(6), pages 2-14, January.
    • Handle: RePEc:url:upravl:v:13:y:2022:i:6:p:2-14
    DOI: 10.29141/2218-5003-2022-13-6-1
    as

    Download full text from publisher

    File URL: https://upravlenets.usue.ru/images/100/1.pdf
    Download Restriction: no
    File URL: https://upravlenets.usue.ru/en/issues-2022/1143
    Download Restriction: no
    File URL: https://libkey.io/10.29141/2218-5003-2022-13-6-1?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. Gordon Walker & Bruce Kogut & Weijian Shan, 1997. "Social Capital, Structural Holes and the Formation of an Industry Network," Organization Science, INFORMS, vol. 8(2), pages 109-125, April.
    2. Amir, Rabah & Lazzati, Natalia, 2011. "Network effects, market structure and industry performance," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2389-2419.
    3. Luigi Orsenigo & Fabio Pammolli & Massimo Riccaboni & Andrea Bonaccorsi & Giuseppe Turchetti, 1997. "The Evolution of Knowledge and the Dynamics of an Industry Network," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 1(2), pages 147-175, June.
    4. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    5. G. B. Korovin, 2020. "Architecture of the agent-based model for the region’s industrial complex digital transformation," Journal of New Economy, Ural State University of Economics, vol. 21(3), pages 158-174, October.
    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. Sidonia von Proff & Thomas Brenner, 2011. "The Dynamics of Inter-Regional Collaboration – An Analysis of Co-Patenting," Working Papers on Innovation and Space 2011-06, Philipps University Marburg, Department of Geography.
    2. Sidonia Proff & Thomas Brenner, 2014. "The dynamics of inter-regional collaboration: an analysis of co-patenting," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(1), pages 41-64, January.
    3. Cantner, Uwe & Rake, Bastian, 2014. "International research networks in pharmaceuticals: Structure and dynamics," Research Policy, Elsevier, vol. 43(2), pages 333-348.
    4. Ozman, Müge, 2003. "Self-Organizing Inter-Firm Networks," Research Memorandum 022, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    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. Luigi Orsenigo & Fabio Pammolli & Massimo Riccaboni & Andrea Bonaccorsi & Giuseppe Turchetti, 1997. "The Evolution of Knowledge and the Dynamics of an Industry Network," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 1(2), pages 147-175, June.
    7. 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.
    8. Shenglan Huang & Zhi Chen, 2017. "The Effects of Social Capital on Innovation Performance: From Complex Adaptive System Perspective," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(3), pages 191-191, February.
    9. Carroll, Charles, 1998. "Interdependence and the social structure of rivalry," Research Report 98B24, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    10. G. Rejikumar & Aswathy Asokan-Ajitha & Sofi Dinesh & Ajay Jose, 2022. "The role of cognitive complexity and risk aversion in online herd behavior," Electronic Commerce Research, Springer, vol. 22(2), pages 585-621, June.
    11. Lori Rosenkopf & Paul Almeida, 2003. "Overcoming Local Search Through Alliances and Mobility," Management Science, INFORMS, vol. 49(6), pages 751-766, June.
    12. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    13. Zhiang (John) Lin & James A. Kitts & Haibin Yang & J. Richard Harrison, 2008. "Elucidating strategic network dynamics through computational modeling," Computational and Mathematical Organization Theory, Springer, vol. 14(3), pages 175-208, September.
    14. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    15. Sándor Juhász & Balázs Lengyel, 2016. "Tie creation versus tie persistence in cluster knowledge networks," Papers in Evolutionary Economic Geography (PEEG) 1613, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised May 2016.
    16. Luigi Balletta & Antonio Tesoriere, 2020. "Cumulative innovation, open source, and distance to frontier," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(6), pages 1875-1920, December.
    17. Kudic, Muhamed & Pyka, Andreas & Günther, Jutta, 2012. "Determinants of Evolutionary Change Processes in Innovation Networks – Empirical Evidence from the German Laser Industry," IWH Discussion Papers 7/2012, Halle Institute for Economic Research (IWH).
    18. Laussel, Didier & Resende, Joana, 2014. "Dynamic price competition in aftermarkets with network effects," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 106-118.
    19. Ferretti, Marco & Guerini, Massimiliano & Panetti, Eva & Parmentola, Adele, 2022. "The partner next door? The effect of micro-geographical proximity on intra-cluster inter-organizational relationships," Technovation, Elsevier, vol. 111(C).
    20. Adomako, Samuel & Amankwah-Amoah, Joseph & Donbesuur, Francis & Ahsan, Mujtaba & Danso, Albert & Uddin, Moshfique, 2022. "Strategic agility of SMEs in emerging economies: Antecedents, consequences and boundary conditions," International Business Review, Elsevier, vol. 31(6).

    More about this item

    Keywords

    agent-oriented model; controlled dynamic systems; management model; industrial complex; industrial development;
    All these keywords.

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    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:13:y:2022:i:6:p:2-14. 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.