IDEAS home Printed from https://ideas.repec.org/a/spr/eaiere/v15y2018i2d10.1007_s40844-018-0098-5.html
   My bibliography  Save this article

A method of building simulation model for organizational decision-making and inter-organizational control

Author

Listed:
  • Shungo Sakaki

    (Tokyo University of technology)

Abstract

This paper presented a method on the configuration of a social simulation model intended for general-purpose application as “inter-system control model”, for analyzing real societies engaged in complex and diverse organizational decision-making. The model in this paper is a micro-agent-based model, configured using one replicator dynamics for each decision-making behavior, whether the agent is an organization or an individual. Through the model in this paper, it is possible to configure broad types of decision-making model by individuals, internal organization of corporations, inter-corporate relations and the national economy. This paper describes a method of social simulation model primarily focusing on an inter-organizational decision-making and demonstrates a configuration method for this simulation model using case studies on long-term economic growth model with technological change.

Suggested Citation

  • Shungo Sakaki, 2018. "A method of building simulation model for organizational decision-making and inter-organizational control," Evolutionary and Institutional Economics Review, Springer, vol. 15(2), pages 289-313, December.
    • Handle: RePEc:spr:eaiere:v:15:y:2018:i:2:d:10.1007_s40844-018-0098-5
    DOI: 10.1007/s40844-018-0098-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40844-018-0098-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40844-018-0098-5?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Uwe Cantner & Ivan Savin & Simone Vannuccini, 2019. "Replicator dynamics in value chains: explaining some puzzles of market selection," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(3), pages 589-611.
    2. Giovanni Dosi, 2000. "Finance, Innovation and Industrial Change," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 21, pages 621-641, Edward Elgar Publishing.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Agnieszka Zdęba-Mozoła & Remigiusz Kozłowski & Anna Rybarczyk-Szwajkowska & Tomasz Czapla & Michał Marczak, 2023. "Implementation of Lean Management Tools Using an Example of Analysis of Prolonged Stays of Patients in a Multi-Specialist Hospital in Poland," IJERPH, MDPI, vol. 20(2), pages 1-23, January.
    2. Shungo Sakaki, 2023. "The rationality of adaptive decision-making and the feasibility of optimal growth planning," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.

    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. Shungo Sakaki, 2017. "Income distribution management to sustain long-term economic growth: does the equalization of income distribution contribute to long-term economic growth?," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 363-395, December.
    2. Valérie Revest & Alessandro Sapio, 2012. "Financing technology-based small firms in Europe: what do we know?," Small Business Economics, Springer, vol. 39(1), pages 179-205, July.
    3. Cefis, Elena & Bartoloni, Eleonora & Bonati, Marco, 2020. "Show me how to live: Firms' financial conditions and innovation during the crisis," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 63-81.
    4. Tea Petrin & Dragana Radicic, 2023. "Instrument policy mix and firm size: is there complementarity between R&D subsidies and R&D tax credits?," The Journal of Technology Transfer, Springer, vol. 48(1), pages 181-215, February.
    5. Aleid E. Brouwer, 2004. "The inert firm; why old firms show a stickiness to their location," ERSA conference papers ersa04p165, European Regional Science Association.
    6. Torrecillas, Celia & Martínez, Catalina, 2022. "Patterns of specialisation by country and sector in olive applications," Technology in Society, Elsevier, vol. 70(C).
    7. Knudsen, Thorbjørn, 2008. "Reference groups and variable risk strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 66(1), pages 22-36, April.
    8. Nassreddine Garoui & Anis Jarboui, 2012. "Cognitive Approach of Corporate Governance A Visualization Test of Mental models with Cognitive Mapping Technique," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 15(43), pages 61-96, March.
    9. Brancaccio, Emiliano & Giammetti, Raffaele & Lopreite, Milena & Puliga, Michelangelo, 2019. "Monetary policy, crisis and capital centralization in corporate ownership and control networks: A B-Var analysis," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 55-66.
    10. Giovanni Dosi & Valérie Revest & Alessandro Sapio, 2016. "Financial regimes, financialization patterns and industrial performances : preliminary remarks," Post-Print halshs-01418040, HAL.
    11. Alessandro Giovannini & Maurizio Iacopetta & Raoul Minetti, 2013. "Financial Markets, Banks, and Growth : Disentangling the links," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 105-147.
    12. Max-Peter Menzel & Johannes Kammer, 2017. "Industry Evolution in Varieties of Capitalism: a Comparison of the Danish and US Wind Turbine Industries," Papers in Evolutionary Economic Geography (PEEG) 1716, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2017.
    13. Markus Becker & Thorbjorn Knudsen, 2012. "Nelson and Winter Revisited," Chapters, in: Michael Dietrich & Jackie Krafft (ed.), Handbook on the Economics and Theory of the Firm, chapter 19, Edward Elgar Publishing.
    14. Hahn, Katrin, 2019. "Innovation in times of financialization: Do future-oriented innovation strategies suffer? Examples from German industry," Research Policy, Elsevier, vol. 48(4), pages 923-935.
    15. Pietro Alessandrini & Luca Papi & Alberto Zazzaro, 2003. "Banks, regions and development," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 56(224), pages 23-55.
    16. Block, Thorsten H., 2002. "Financial systems, innovation and economic performance," Research Memorandum 013, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    17. Gérard Charreaux, 2002. "Variation sur le thème:"À la recherche de nouvelles fondations pour la finance et la gouvernance d'entreprise"," Revue Finance Contrôle Stratégie, revues.org, vol. 5(3), pages 5-68, September.
    18. Christos Triantopoulos, 2014. "Financial Structure, Income Inequality and Privatization of Risk in the EU," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 64(3), pages 49-72, July-Sept.
    19. Jesper Lindgaard Christensen & Ina Drejer, 1998. "Finance and Innovation System or Chaos," DRUID Working Papers 98-24, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    20. Shungo Sakaki, 2019. "Equality in Income and Sustainability in Economic Growth: Agent-Based Simulations on OECD Data," Sustainability, MDPI, vol. 11(20), pages 1-32, October.

    More about this item

    Keywords

    Simulation model; PDCA cycle; Decision making; Replicator dynamics; Inter-system control;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - 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:spr:eaiere:v:15:y:2018:i:2:d:10.1007_s40844-018-0098-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.