IDEAS home Printed from https://ideas.repec.org/a/igg/jssmet/v14y2023i1p1-21.html
   My bibliography  Save this article

Using Artificial Intelligence for Retail Value Chain

Author

Listed:
  • Aigerim Burakhanova

    (Narxoz University, Kazakhstan)

  • Gulshat Baizhaxynova

    (Almaty Management University, Kazakhstan)

  • Aizhan Duisebayeva

    (Narxoz University, Kazakhstan)

  • Maira Davletova

    (Turan University, Kazakhstan)

  • Botagoz Nurakhova

    (Narxoz University, Kazakhstan)

Abstract

The present study aims to prove hypotheses regarding artificial intelligence integration in retail value chains in the post-Soviet economic space. Hypotheses were proven within a comprehensive research project based on the use of quantitative research methods (questionnaires), which allowed studying the opinions of 512 retail managers in Azerbaijan, Kazakhstan, and Tajikistan. A specially designed questionnaire eliminated ambiguity in results interpretation by including both simple closed questions with a single choice and questions using a Likert scale. All the formulated hypotheses were proven, leading to the conclusion that the retail market of the post-Soviet economic space is not ready for the introduction of robotization and full automation of retail stores. The study results can be used by retail managers in the post-Soviet economic space as they choose the direction of artificial intelligence integration.

Suggested Citation

  • Aigerim Burakhanova & Gulshat Baizhaxynova & Aizhan Duisebayeva & Maira Davletova & Botagoz Nurakhova, 2023. "Using Artificial Intelligence for Retail Value Chain," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 14(1), pages 1-21, January.
    • Handle: RePEc:igg:jssmet:v:14:y:2023:i:1:p:1-21
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSSMET.330018
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kerem Akkaya & Tolga Ovatman, 2022. "A Comparative Study of Meta-Data-Based Microservice Extraction Tools," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 13(1), pages 1-26, January.
    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. Jon A. Chilingerian & Mitchell P. V. Glavin, 2024. "Evaluating Cardiac Surgeon Performance: A Retrospective and Exploratory Study," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 15(1), pages 1-27, January.

    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:igg:jssmet:v:14:y:2023:i:1:p:1-21. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.