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Valuing of Economic Efficiency of University Spin-Offs: Case of Peter the Great St. Petersburg Polytechnic University

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Advances in Human Factors in Training, Education, and Learning Sciences (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 596))

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Abstract

The goal of the paper is to propose the method of valuing of economic efficiency and present the results of this method application to the spin-off of Peter the Great St. Petersburg Polytechnic University. The study of profitability and efficiency of performance of the one university spin-off based on proposed method shows the economically stable position of the entity during the decade under study and, thus, thoroughly confirms the undoubted scientific and technical potential of the company on the one hand, and high economic efficiency of innovations on the other hand. Thus the results of analysis and valuing of efficiency of the university spin-off performance prove the ability of proposed method to work. The method may be used as the source of information for decision making by managers of university spin-offs and potential investors.

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Author information

Authors and Affiliations

  1. International Graduate School of Management, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, Saint-Petersburg, 195251, Russia

    Olga Miroliubova & Aleksandr Kozlov

  2. University of Economy in Bydgoszcz, ul. Garbary, 2, 85-229, Bydgoszcz, Poland

    Aleksandr Kozlov

Authors
  1. Olga Miroliubova
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  2. Aleksandr Kozlov
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Corresponding author

Correspondence to Aleksandr Kozlov .

Editor information

Editors and Affiliations

  1. TiER1 Performance Solutions, Colorado Springs, Colorado, USA

    Terence Andre

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Miroliubova, O., Kozlov, A. (2018). Valuing of Economic Efficiency of University Spin-Offs: Case of Peter the Great St. Petersburg Polytechnic University. In: Andre, T. (eds) Advances in Human Factors in Training, Education, and Learning Sciences. AHFE 2017. Advances in Intelligent Systems and Computing, vol 596. Springer, Cham. https://doi.org/10.1007/978-3-319-60018-5_30

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  • DOI: https://doi.org/10.1007/978-3-319-60018-5_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60017-8

  • Online ISBN: 978-3-319-60018-5

  • eBook Packages: EngineeringEngineering (R0)

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