IDEAS home Printed from https://ideas.repec.org/p/hig/wpaper/wpbrp07sti2013.html
   My bibliography  Save this paper

Intelligent data systems to aid decision-making at tenders for oil and gas fields development

Author

Listed:
  • Anna Khripunova

    () (Senior Research Scientist, LLC “NIIGAZECONOMIKA”, Gazprom)

  • Konstantin Vishnevskiy

    () (Research fellow, Laboratory for Science and Technology Studies, Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics)

  • Oleg Karasev

    () (Deputy Director, International Research and Educational Foresight Centre, Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics)

  • Dirk Meissner

    () (Deputy Head, Laboratory for Science and Technology Studies, Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics)

Abstract

In the last few years the world oil and gas industry has experienced a rapid development growing more strongly than many other industry branches. Modern oil and gas industry aims at the extraction of natural resources at an increasing scale. The growth of oil production is conditional upon developing new exploration fields to create auspicious investment conditions, stabilize national social and political life using and implementing state-of-the-art technologies. It is efficient and vital for oil and gas companies today to contract different companies and their competences and resources in the development of fields, oil and gas extraction, transport and refining. It allows incorporating cutting-edge know-how in extracting natural resources by means of implementing new scientific and technological solutions aimed at further leveraging profitability based on inter-company cooperation thus opening opportunities for economic and social development and improvement but also environmental protection and quality of life. The search for a suitable partner / contractor to perform the necessary duties is difficult and laborious, and usually realized in the form of a tendering process. The complicated nature of organizing tenders requires creating new means and instruments which are designed to improve the choice efficiency and reduce the term of decision making. As evidenced by world experience from other industries the most prospective decision in this field are made using Intelligent Data Systems. This article deals with structure of intelligent information systems aiding decision-making using the case of an electronic tender competition. In this paper we provide a new approach for tendering in the oil&gas industry.

Suggested Citation

  • Anna Khripunova & Konstantin Vishnevskiy & Oleg Karasev & Dirk Meissner, 2013. "Intelligent data systems to aid decision-making at tenders for oil and gas fields development," HSE Working papers WP BRP 07/STI/2013, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:wpbrp07sti2013
    as

    Download full text from publisher

    File URL: http://www.hse.ru/data/2013/04/08/1294510850/07STI2013.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Bhagat, Sanjai & Dong, Ming & Hirshleifer, David & Noah, Robert, 2005. "Do tender offers create value? New methods and evidence," Journal of Financial Economics, Elsevier, vol. 76(1), pages 3-60, April.
    2. Kathleen M. Sutcliffe & Gerry McNamara, 2001. "Controlling Decision-Making Practice in Organizations," Organization Science, INFORMS, vol. 12(4), pages 484-501, August.
    3. S. L. Liu & S. Y. Wang & K. K. Lai, 2000. "Multiple Criteria Decision Making Models For Competitive Bidding," World Scientific Book Chapters,in: New Frontiers Of Decision Making For The Information Technology Era, chapter 19, pages 349-372 World Scientific Publishing Co. Pte. Ltd..
    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. repec:kap:jtecht:v:42:y:2017:i:3:d:10.1007_s10961-015-9433-8 is not listed on IDEAS

    More about this item

    Keywords

    tender procedure; system aiding decision-making; conflict situation; intelligent data analysis; oil and gas industry; purchase innovation;

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hig:wpaper:wpbrp07sti2013. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shamil Abdulaev) or (Victoria Elkina). General contact details of provider: http://edirc.repec.org/data/hsecoru.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.