IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vxxy2017i3bp686-707.html
   My bibliography  Save this article

Tendencies of Interaction between Russian Universities and Companies Implementing Innovative Development Programs

Author

Listed:
  • Vladimir A. Pastukhov
  • Nikolay S. Kliman
  • Dmitry S. Alekseev

Abstract

The main aim of this article is to analyze key indicators and trends of global innovative development and their role in development. Attention is given to the consideration of several mechanisms of interaction between universities and state companies, with concrete measures and steps that can be used in economic policy.The authors analyze the real experience of the Russian economy now. Based on collected data for the total volume of R&D, revenues and the number of patents, regression models were constructed to determine the relationship between the named indicators.Recommendations and innovative ideas to improve the economic policy are given to achieve the goals and to justify the use of mechanisms of "compulsion to innovate" in state companies for the implementation of more productive development programs.

Suggested Citation

  • Vladimir A. Pastukhov & Nikolay S. Kliman & Dmitry S. Alekseev, 2018. "Tendencies of Interaction between Russian Universities and Companies Implementing Innovative Development Programs," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 686-707.
  • Handle: RePEc:ers:journl:v:xx:y:2017:i:3b:p:686-707
    as

    Download full text from publisher

    File URL: https://www.ersj.eu/dmdocuments/2018_XXI_1_57.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicole M. Fortin & Andrew J. Hill & Jeff Huang, 2014. "Superstition In The Housing Market," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 974-993, July.
    2. Shum, Matthew & Sun, Wei & Ye, Guangliang, 2014. "Superstition and “lucky” apartments: Evidence from transaction-level data," Journal of Comparative Economics, Elsevier, vol. 42(1), pages 109-117.
    3. Thomas Kramer & Lauren Block, 2008. "Conscious and Nonconscious Components of Superstitious Beliefs in Judgment and Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(6), pages 783-793, October.
    4. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.
    5. Torgler, Benno, 2007. "Determinants of superstition," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 36(5), pages 713-733, October.
    6. Brown, Philip & Chua, Angeline & Mitchell, Jason, 2002. "The influence of cultural factors on price clustering: Evidence from Asia-Pacific stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 10(3), pages 307-332, June.
    7. repec:cup:judgdm:v:10:y:2015:i:6:p:590-592 is not listed on IDEAS
    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. Baturina O.E. & Erokhina T.B. & Fedko V.P. & Shaginyan S.G., 2019. "Development of the University Image Positioning Methods in the Context of its Marketing Strategy," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(Special 2), pages 309-316.
    2. S.I. Gilmanshina & R.N. Sagitova & I.R. Gilmanshin, 2018. "Science Education: Development of Environmental Thinking," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 690-704.
    3. S.I. Gilmanshina & R.N. Sagitova & I.R. Gilmanshin, 2018. "Science Education: Development of Environmental Thinking," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 690-704.

    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. Bai, Min & Xu, Limin & Yu, Chia-Feng (Jeffrey) & Zurbruegg, Ralf, 2020. "Superstition and stock price crash risk," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    2. Tao Chen, 2018. "Dragon CEOs and Firm Value," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 51(3), pages 382-395, September.
    3. Evgeny A. Antipov & Elena B. Pokryshevskaya, 2015. "Are buyers of apartments superstitious? Evidence from the Russian real estate market," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(6), pages 590-592, November.
    4. Dmitry Burakov, 2018. "Do discounts mitigate numerological superstitions? Evidence from the Russian real estate market," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(5), pages 467-470, September.
    5. Bhattacharya, Haimanti & Dugar, Subhasish, 2022. "Business norm versus norm-nudge as a contract-enforcing mechanism: Evidence from a real marketplace," European Economic Review, Elsevier, vol. 144(C).
    6. Bayer, Ya'akov M. & Ruffle, Bradley J. & Shtudiner, Zeev & Zultan, Ro'i, 2018. "Costly superstitious beliefs: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 30-43.
    7. Utpal Bhattacharya & Wei-Yu Kuo & Tse-Chun Lin & Jing Zhao, 2018. "Do Superstitious Traders Lose Money?," Management Science, INFORMS, vol. 64(8), pages 3772-3791, August.
    8. Ke, Wen-Chyan & Chen, Hueiling & Lin, Hsiou-Wei W. & Liu, Yo-Chia, 2017. "The impact of numerical superstition on the final digit of stock price," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 145-157.
    9. Jan Fidrmuc & J. D. Tena, 2015. "Friday the 13th: The Empirics of Bad Luck," Kyklos, Wiley Blackwell, vol. 68(3), pages 317-334, August.
    10. repec:cup:judgdm:v:13:y:2018:i:5:p:467-470 is not listed on IDEAS
    11. Elena B. Pokryshevskaya & Evgeny A. Antipov, 2015. "A study of numerological superstitions in the apartments market," Economics Bulletin, AccessEcon, vol. 35(1), pages 83-88.
    12. repec:cup:judgdm:v:11:y:2016:i:3:p:243-259 is not listed on IDEAS
    13. Tong V. Wang & Rogier J. D. Potter van Loon & Martijn J. van den Assem & Dennie van Dolder, 2016. "Number preferences in lotteries," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(3), pages 243-259, May.
    14. repec:cup:judgdm:v:10:y:2015:i:6:p:590-592 is not listed on IDEAS
    15. Invernizzi, Giovanna M. & Miller, Joshua B. & Coen, Tommaso & Dufwenberg, Martin & Oliveira, Luiz Edgard R., 2021. "Tra i Leoni: Revealing the preferences behind a superstition," Journal of Economic Psychology, Elsevier, vol. 82(C).
    16. Maria De Paola & Francesca Gioia & Vincenzo Scoppa, 2013. "Overconfidence, Omens And Emotions: Results From A Field Experiment," Working Papers 201303, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    17. Roger, Patrick & D’Hondt, Catherine & Plotkina, Daria & Hoffmann, Arvid, 2022. "Number 19: Another Victim of the COVID‐19 Pandemic?," LIDAM Discussion Papers LFIN 2022007, Université catholique de Louvain, Louvain Finance (LFIN).
    18. Nicole M. Fortin & Andrew J. Hill & Jeff Huang, 2014. "Superstition In The Housing Market," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 974-993, July.
    19. Wen-Chieh Wu & Yu-Chun Ma & Steven C. Bourassa, 2018. "Folk Customs and Home Improvement Decisions," International Real Estate Review, Global Social Science Institute, vol. 21(3), pages 317-341.
    20. Kwong Wing Chau & Danika Wright & Ervi Liusman, 2018. "The cost of a lucky price," ERES eres2018_240, European Real Estate Society (ERES).
    21. Brad R. Humphreys & Adam Nowak & Yang Zhou, 2016. "Cultural Superstitions and Residential Real Estate Prices: Transaction-level Evidence from the US Housing Market," Working Papers 16-27, Department of Economics, West Virginia University.
    22. Maggie Rong Hu & Xiaoyang Li & Yang Shi & Xiaoquan (Michael) Zhang, 2023. "Numerological Heuristics and Credit Risk in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 34(4), pages 1744-1760, December.
    23. Brad R. Humphreys & Adam Nowak & Yang Zhou, 2017. "Chinese Superstition and Real Estate Prices: Transaction-level Evidence from the US Housing Market," Working Papers 17-18, Department of Economics, West Virginia University.

    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:ers:journl:v:xx:y:2017:i:3b:p:686-707. 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: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    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.