Artikel

Developing public-private partnership projects to enhance innovation capability in the defence industry

The relevance of this study resides in the need to determine the key measures for a more effective application of the mechanism of public-private partnerships (PPP) in the implementation of large-scale infrastructure projects, aimed at developing the innovation potential of the Russian defence-industrial complex (DIC). Through the analysis of foreign practices of the application of PPP in the defence industry, representing a vast body of scientific and popular literature on the development of the defence industry in the U.S. and the countries of Europe and Asia, as well as a review of the domestic regulatory framework, the authors have identified the most common and key problems that are obstacles to the effective and sustainable development of PPP mechanisms, and their application not only in the civil, but also in the defence sector. This work pays specific attention to the requirements that are imposed on public and private partners in the process of implementing PPP projects in the context of SDO performance, along with the risks that are inevitably associated with the activities of each of the parties. As a result, the authors present a graphical interpretation of the algorithm for financing the state defence order (SDO) and disclose the system of interaction between the elements of a given algorithm, as well as formulating an essential recommendation for the further development of PPP in Russia.

Language
Englisch

Bibliographic citation
Journal: Economies ; ISSN: 2227-7099 ; Volume: 9 ; Year: 2021 ; Issue: 4 ; Pages: 1-22 ; Basel: MDPI

Classification
Wirtschaft
Subject
concession agreement
defence industry
public-private partnership
state defence order

Event
Geistige Schöpfung
(who)
Pukhova, Marina Mikhailovna
Merkulina, Irina Anatolievna
Bashkov, Dmitry Yuryevich
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2021

DOI
doi:10.3390/economies9040147
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Pukhova, Marina Mikhailovna
  • Merkulina, Irina Anatolievna
  • Bashkov, Dmitry Yuryevich
  • MDPI

Time of origin

  • 2021

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