IDEAS home Printed from https://ideas.repec.org/a/zna/indecs/v13y2015i3p472-478.html
   My bibliography  Save this article

Comparison of Different Simulations Methods in Case of Service-Providing Companies

Author

Listed:
  • Biserka Runje

    (University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, Croatia)

  • Elizabeta Krstic Vukelja

    (University of Zagreb - School of Dental Medicine, Zagreb, Croatia)

  • Amalija Horvatic

    (University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, Croatia)

Abstract

Optimal functioning of a market oriented company, in particular the service providing company, is an important example of optimisation of actions within the context of complex environment. In this article we discuss the prospective approach to represent reliably the quality dynamics of such a company, in order to contribute to possible future its quality management. The agent-based modelling is extracted, among the set of modelling methods, to serve as a frame for representing the generic service providing company and to analyse its dynamics with emphasis on extracting the quality dynamics.

Suggested Citation

  • Biserka Runje & Elizabeta Krstic Vukelja & Amalija Horvatic, 2015. "Comparison of Different Simulations Methods in Case of Service-Providing Companies," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 13(3), pages 472-478.
  • Handle: RePEc:zna:indecs:v:13:y:2015:i:3:p:472-478
    as

    Download full text from publisher

    File URL: http://indecs.eu/2015/indecs2015-pp472-478.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kaihara, Toshiya, 2003. "Multi-agent based supply chain modelling with dynamic environment," International Journal of Production Economics, Elsevier, vol. 85(2), pages 263-269, August.
    2. Elizabeta Krstic Vukelja & Biserka Runje, 2014. "Quality Service Evaluation through the System of Complaints and Praise," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 12(1), pages 78-91.
    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. repec:zna:indecs:v:13:y:2015:i:2:p:472-478 is not listed on IDEAS
    2. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    3. Papapostolou, Christiana & Kondili, Emilia & Kaldellis, John K., 2011. "Development and implementation of an optimisation model for biofuels supply chain," Energy, Elsevier, vol. 36(10), pages 6019-6026.
    4. Arthur Huang & David Levinson, 2011. "Why Retailers Cluster: An Agent Model of Location Choice on Supply Chains," Environment and Planning B, , vol. 38(1), pages 82-94, February.
    5. Mosahar Tarimoradi & M. H. Fazel Zarandi & Hosain Zaman & I. B. Turksan, 2017. "Evolutionary fuzzy intelligent system for multi-objective supply chain network designs: an agent-based optimization state of the art," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1551-1579, October.
    6. Massari, Giovanni Francesco & Giannoccaro, Ilaria, 2021. "Investigating the effect of horizontal coopetition on supply chain resilience in complex and turbulent environments," International Journal of Production Economics, Elsevier, vol. 237(C).
    7. Tsiakis, Panagiotis & Papageorgiou, Lazaros G., 2008. "Optimal production allocation and distribution supply chain networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 468-483, February.
    8. Lo, Wei-Shuo & Hong, Tzung-Pei & Jeng, Rong, 2008. "A framework of E-SCM multi-agent systems in the fashion industry," International Journal of Production Economics, Elsevier, vol. 114(2), pages 594-614, August.
    9. de la Fuente, M. Victoria & Ros, Lorenzo & Cardos, Manuel, 2008. "Integrating Forward and Reverse Supply Chains: Application to a metal-mechanic company," International Journal of Production Economics, Elsevier, vol. 111(2), pages 782-792, February.
    10. Meng, Qingfeng & Li, Zhen & Liu, Huimin & Chen, Jingxian, 2017. "Agent-based simulation of competitive performance for supply chains based on combined contracts," International Journal of Production Economics, Elsevier, vol. 193(C), pages 663-676.
    11. Xu, Liming & Mak, Stephen & Brintrup, Alexandra, 2021. "Will bots take over the supply chain? Revisiting agent-based supply chain automation," International Journal of Production Economics, Elsevier, vol. 241(C).
    12. Roberto Dominguez & Salvatore Cannella, 2020. "Insights on Multi-Agent Systems Applications for Supply Chain Management," Sustainability, MDPI, vol. 12(5), pages 1-13, March.
    13. Niels Bugert & Rainer Lasch, 2023. "Analyzing upstream and downstream risk propagation in supply networks by combining Agent-based Modeling and Bayesian networks," Journal of Business Economics, Springer, vol. 93(5), pages 859-889, July.
    14. Tao Zhang & Quanyan Zhu, 2020. "Implementability of Honest Multi-Agent Sequential Decision-Making with Dynamic Population," Papers 2003.03173, arXiv.org, revised May 2020.
    15. Kowalski, MichaƂ & Lee, Zach W.Y. & Chan, Tommy K.H., 2021. "Blockchain technology and trust relationships in trade finance," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    16. Soroor, Javad & Tarokh, Mohammad J. & Shemshadi, Ali, 2009. "Initiating a state of the art system for real-time supply chain coordination," European Journal of Operational Research, Elsevier, vol. 196(2), pages 635-650, July.
    17. Fu-ren Lin & Shyh-ming Lin, 2006. "Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(4), pages 1-1.

    More about this item

    Keywords

    agent based modelling; service providing company; simulation modelling;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure

    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:zna:indecs:v:13:y:2015:i:3:p:472-478. 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: Josip Stepanic (email available below). General contact details of provider: .

    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.