IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-030-94617-3_26.html
   My bibliography  Save this book chapter

Options, Structure, and Digitalization of Value Chain Management Objects

In: Digital Transformation in Industry

Author

Listed:
  • Alexey Tyapukhin

    (Orenburg Branch of the Economics Institute of the Ural Branch of Russian Academy of Sciences)

  • Zhanna Ermakova

    (Orenburg Branch of the Economics Institute of the Ural Branch of Russian Academy of Sciences)

Abstract

Although the essence and content of chain management concepts by values, demands, and supplies are worked out sufficiently, the problem of their hierarchy and relationships is not solved yet. The article aims to substantiate the options, clarify the structure, and develop the methodology for digitalizing value chain management objects. System analysis, grouping, and classification methods are used as research methods. The article substantiates the value chain management options based on the choice, adaptation, and creation of products and/or services. The management structure of this type is developed, including chain management of formalization, demands, supplies, and consumption. The classification of values is clarified, including the desired value, value prototype, value carrier, and perceived value. The main value types of chain management objects are proposed. The cipher structure of chain management objects is developed, which contains information about the management stage, objects types, stages and options of creating value, forms, and options for solving problems in value chains. The obtained results make it possible to more fully take into account the demands of end consumers; reduce the loss of lost profits when making management decisions; more effectively distribute resources, powers, and responsibilities in chain links.

Suggested Citation

  • Alexey Tyapukhin & Zhanna Ermakova, 2022. "Options, Structure, and Digitalization of Value Chain Management Objects," Lecture Notes in Information Systems and Organization, in: Vikas Kumar & Jiewu Leng & Victoria Akberdina & Evgeny Kuzmin (ed.), Digital Transformation in Industry, pages 373-389, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-94617-3_26
    DOI: 10.1007/978-3-030-94617-3_26
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:lnichp:978-3-030-94617-3_26. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.