IDEAS home Printed from https://ideas.repec.org/a/bla/rmgtin/v24y2021i3p311-331.html
   My bibliography  Save this article

Determinants of the market choice and the consumers behavior on the Macedonian MTPL insurance market: Empirical application of the Markov chain model

Author

Listed:
  • Angela Blazheska
  • Igor Ivanovski

Abstract

Markov chain models are widely used for capturing the switching behavior of economic agents and its impact on the prospective market developments in various industries. The aim of this paper is to analyze the customers' altered behavior on the Motor Third Party Liability Insurance market in Republic of North Macedonia for the period of 2016–2018, in a setting where the policy tariff rates are equal for all the Insurance providers, that is, prices are excluded as a factor of transition. For that purpose, a stationary, homogeneous, first‐order Markov Chain model is deployed to detect the flows and the reasoning behind the decisions for customers' transition across companies. This approach is applied for the first time on the Macedonian Insurance Market and the findings offer valuable information to many interested parties including policymakers, insurance providers, as well as researchers in the field.

Suggested Citation

  • Angela Blazheska & Igor Ivanovski, 2021. "Determinants of the market choice and the consumers behavior on the Macedonian MTPL insurance market: Empirical application of the Markov chain model," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 24(3), pages 311-331, September.
    • Handle: RePEc:bla:rmgtin:v:24:y:2021:i:3:p:311-331
    DOI: 10.1111/rmir.12192
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rmir.12192
    Download Restriction: no
    File URL: https://libkey.io/10.1111/rmir.12192?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. Jacob B. Feldman & Huseyin Topaloglu, 2017. "Revenue Management Under the Markov Chain Choice Model," Operations Research, INFORMS, vol. 65(5), pages 1322-1342, October.
    2. Jeong-Gil Choi & Jin-Won Mok & Jin-Soo Han, 2011. "The Use of Markov Chains to Estimate Destination Switching and Market Share," Tourism Economics, , vol. 17(6), pages 1181-1196, December.
    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. Patricia Born & Douglas Bujakowski, 2022. "Insurance research in Central, Eastern, and Southeastern Europe: What we can learn from XPRIMM data," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(2), pages 219-231, June.

    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. David Simchi-Levi & Rui Sun & Huanan Zhang, 2022. "Online Learning and Optimization for Revenue Management Problems with Add-on Discounts," Management Science, INFORMS, vol. 68(10), pages 7402-7421, October.
    2. Kameng Nip & Zhenbo Wang & Zizhuo Wang, 2021. "Assortment Optimization under a Single Transition Choice Model," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2122-2142, July.
    3. Wang, Mengmeng & Zhang, Xun & Li, Xiaolong, 2023. "Multiple-purchase choice model: estimation and optimization," International Journal of Production Economics, Elsevier, vol. 265(C).
    4. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
    5. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    6. Menezes, Mozart B.C. & Pinto, Roberto, 2022. "Product proliferation, cannibalisation, and substitution: A first look into entailed risk and complexity," International Journal of Production Economics, Elsevier, vol. 243(C).
    7. Da Huo, 2013. "Cluster Analysis of Market Potential in Emerging Markets: A Dynamic Research based on Markov Chain," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 218-231, December.
    8. Xingxing Chen & Jacob Feldman & Seung Hwan Jung & Panos Kouvelis, 2022. "Approximation schemes for the joint inventory selection and online resource allocation problem," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3143-3159, August.
    9. Fatemeh Nosrat, 2022. "Assortment Optimization with Customer Choice Modeling in a Crowdfunding Setting," Papers 2207.07222, arXiv.org.
    10. Kris Johnson Ferreira & Joel Goh, 2021. "Assortment Rotation and the Value of Concealment," Management Science, INFORMS, vol. 67(3), pages 1489-1507, March.
    11. Laumer, Simon & Barz, Christiane, 2023. "Reductions of non-separable approximate linear programs for network revenue management," European Journal of Operational Research, Elsevier, vol. 309(1), pages 252-270.
    12. Boxiao Chen & Xiuli Chao, 2020. "Dynamic Inventory Control with Stockout Substitution and Demand Learning," Management Science, INFORMS, vol. 66(11), pages 5108-5127, November.
    13. Çömez-Dolgan, Nagihan & Fescioglu-Unver, Nilgun & Cephe, Ecem & Şen, Alper, 2021. "Capacitated strategic assortment planning under explicit demand substitution," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1120-1138.
    14. Will Ma, 2023. "When Is Assortment Optimization Optimal?," Management Science, INFORMS, vol. 69(4), pages 2088-2105, April.
    15. Ali Aouad & Retsef Levi & Danny Segev, 2019. "Approximation Algorithms for Dynamic Assortment Optimization Models," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 487-511, May.
    16. Çömez-Dolgan, Nagihan & Moussawi-Haidar, Lama & Jaber, Mohamad Y. & Cephe, Ecem, 2022. "Capacitated assortment planning of a multi-location system under transshipments," International Journal of Production Economics, Elsevier, vol. 251(C).
    17. Strauss, Arne K. & Klein, Robert & Steinhardt, Claudius, 2018. "A review of choice-based revenue management: Theory and methods," European Journal of Operational Research, Elsevier, vol. 271(2), pages 375-387.
    18. Peng Shi, 2022. "Optimal Priority-Based Allocation Mechanisms," Management Science, INFORMS, vol. 68(1), pages 171-188, January.
    19. Victor Martínez-de-Albéniz & Sumit Kunnumkal, 2022. "A Model for Integrated Inventory and Assortment Planning," Management Science, INFORMS, vol. 68(7), pages 5049-5067, July.
    20. Kameng Nip & Changjun Wang & Zizhuo Wang, 2022. "Competitive and Cooperative Assortment Games under Markov Chain Choice Model," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 1033-1051, March.

    More about this item

    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:bla:rmgtin:v:24:y:2021:i:3:p:311-331. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1098-1616 .

    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.