Research article

Stimulating the processes of attracting investments in industry of the constituent entities of the Russian Federation

  • Received: 25 January 2024 Revised: 02 July 2024 Accepted: 08 July 2024 Published: 16 July 2024
  • JEL Codes: E22, H25, P25

  • The current conditions of the world economy development are characterized by the aggravation of the struggle between countries for technological leadership in the transition to a new technological mode on the basis of Industry 5.0, and the negative impact of barriers in international trade in goods and technologies due to sanctions against Russia, which creates windows of opportunity in the field of ensuring technological sovereignty on its own industrial base. One of the most important factors for the successful implementation of the windows of opportunity for the development of domestic production of high-tech products is the stimulation of the processes of attracting private investments in industrial enterprises of large, medium and small-sized business, including through the formation of an effective system of state support tools. The aim of the article is to improve the processes of attracting industrial investments, specifically in the context of identifying factors that can have a negative impact on the investment activities of Russian enterprises of various size groups by analyzing and adjusting the existing tools of state support for industrial enterprises, including small technology companies, in the constituent entities of the Russian Federation and developing areas for their improvement in order to ensure technological security under the conditions of sanctions. The article studies the features of the investment industrial infrastructure as exemplified by the most industrially developed regions of the Volga and Ural Federal Districts. The insufficient level of investment of small industrial enterprises in comparison to large and medium-sized business has been revealed. It has been found that the sanctions did not affect small and medium-sized business in comparison to large enterprises due to their insufficient role in the production of gross regional product and exports. The efficiency of investment resource utilization in the regions under consideration has been assessed using the data envelopment analysis model oriented on maximization of the result. According to the modeling results, the Republic of Tatarstan and the Sverdlovsk Region have been identified as efficient regions. The experience of the best practice of these regions has been analyzed, and the tools of key federal and regional development institutions has been considered, including those cofinanced by them as part of joint development projects. Promising directions for stimulating investment processes in the Republic of Bashkortostan and other regions of Russia on the basis of improving the efficiency and effectiveness of their investment industrial infrastructure for the timely implementation of the windows of opportunity to achieve technological leadership have been proposed.

    Citation: Pavel Ivanov, Tatyana Altufeva. Stimulating the processes of attracting investments in industry of the constituent entities of the Russian Federation[J]. National Accounting Review, 2024, 6(3): 352-366. doi: 10.3934/NAR.2024016

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  • The current conditions of the world economy development are characterized by the aggravation of the struggle between countries for technological leadership in the transition to a new technological mode on the basis of Industry 5.0, and the negative impact of barriers in international trade in goods and technologies due to sanctions against Russia, which creates windows of opportunity in the field of ensuring technological sovereignty on its own industrial base. One of the most important factors for the successful implementation of the windows of opportunity for the development of domestic production of high-tech products is the stimulation of the processes of attracting private investments in industrial enterprises of large, medium and small-sized business, including through the formation of an effective system of state support tools. The aim of the article is to improve the processes of attracting industrial investments, specifically in the context of identifying factors that can have a negative impact on the investment activities of Russian enterprises of various size groups by analyzing and adjusting the existing tools of state support for industrial enterprises, including small technology companies, in the constituent entities of the Russian Federation and developing areas for their improvement in order to ensure technological security under the conditions of sanctions. The article studies the features of the investment industrial infrastructure as exemplified by the most industrially developed regions of the Volga and Ural Federal Districts. The insufficient level of investment of small industrial enterprises in comparison to large and medium-sized business has been revealed. It has been found that the sanctions did not affect small and medium-sized business in comparison to large enterprises due to their insufficient role in the production of gross regional product and exports. The efficiency of investment resource utilization in the regions under consideration has been assessed using the data envelopment analysis model oriented on maximization of the result. According to the modeling results, the Republic of Tatarstan and the Sverdlovsk Region have been identified as efficient regions. The experience of the best practice of these regions has been analyzed, and the tools of key federal and regional development institutions has been considered, including those cofinanced by them as part of joint development projects. Promising directions for stimulating investment processes in the Republic of Bashkortostan and other regions of Russia on the basis of improving the efficiency and effectiveness of their investment industrial infrastructure for the timely implementation of the windows of opportunity to achieve technological leadership have been proposed.



    Let C be the complex plane. Denote by CN the N-dimensional complex Euclidean space with the inner product z,w=Nj=1zj¯wj; by |z|2=z,z; by H(CN) the set of all holomorphic functions on CN; and by I the identity operator on CN.

    The Fock space F2(CN) is a Hilbert space of all holomorphic functions fH(CN) with the inner product

    f,g=1(2π)NCNf(z)¯g(z)e12|z|2dν(z),

    where ν(z) denotes Lebesgue measure on CN. To simplify notation, we will often use F2 instead of F2(CN), and we will denote by f the corresponding norm of f. The reproducing kernel functions of the Fock space are given by

    Kw(z)=ez,w2,zCN,

    which means that if fF2, then f(z)=f,Kz for all zCN. It is easy to see that Kw=e|w|2/4. Therefore, the following evaluation holds:

    |f(z)|e|z|24f

    for fF2 and zCN. If kw is the normalization of Kw, then

    kw(z)=ez,w2|w|24,zCN.

    Indeed, F2 is used to describe systems with varying numbers of particles in the states of quantum harmonic oscillators. On the other hand, the reproducing kernels in F2 are used to describe the coherent states in quantum physics. See [17] for more about the Fock space, and see [1,7,11] for the studies of some operators on the Fock space.

    For a given holomorphic mapping φ:CNCN and uH(CN), the weighted composition operator, usually denoted by Wu,φ, on or between some subspaces of H(CN) is defined by

    Wu,φf(z)=u(z)f(φ(z)).

    When u=1, it is the composition operator, usually denoted by Cφ. While φ(z)=z, it is the multiplication operator, usually denoted by Mu.

    Forelli in [8] proved that the isometries on Hardy space Hp defined on the open unit disk (for p2) are certain weighted composition operators, which can be regarded as the earliest presence of the weighted composition operators. Weighted composition operators have also been used in descriptions of adjoints of composition operators (see [4]). An elementary problem is to provide function-theoretic characterizations for which the symbols u and φ induce a bounded or compact weighted composition operator on various holomorphic function spaces. There have been many studies of the weighted composition operators and composition operators on holomorphic function spaces. For instance, several authors have recently worked on the composition operators and weighted composition operators on Fock space. For the one-variable case, Ueki [13] characterized the boundedness and compactness of weighted composition operators on Fock space. As a further work of [13], Le [10] found the easier criteria for the boundedness and compactness of weighted composition operators. Recently, Bhuia in [2] characterized a class of C-normal weighted composition operators on Fock space.

    For the several-variable case, Carswell et al. [3] studied the boundedness and compactness of composition operators. From [3], we see that the one-variable case composition operator Cφ is bounded on Fock space if and only if φ(z)=az+b, where |a|1, and if |a|=1, then b=0. Let A:CNCN be a linear operator. Zhao [14,15,16] characterized the unitary, invertible, and normal weighted composition operator Wu,φ on Fock space, when φ(z)=Az+b and u=kc. Interestingly enough, Zhao [15] proved that for φ(z)=Az+b and u(z)=Kc(z), weighted composition operator Wu,φ is bounded on Fock space if and only if A1 and Aζ,b+Ac=0 whenever |Aζ|=|ζ| for ζCN.

    Motivated by the above-mentioned interesting works, for the special symbols φ(z)=Az+b and u=Kc, here we study the adjoint, self-adjointness, and hyponormality of weighted composition operators on Fock space. Such properties of the abstract or concrete operators (for example, Toeplitz operators, Hankel operators, and composition operators) have been extensively studied on some other holomorphic function spaces. This paper can be regarded as a continuation of the weighted composition operators on Fock space.

    In this section, we characterize the adjoints of weighted composition operators Wu,φ on Fock space, where φ(z)=Az+b and u=Kc.

    We first have the following result:

    Lemma 2.1. Let A, B:CNCN be linear operators with A1 and B1, φ(z)=Az+a, ψ(z)=Bz+b for a,bCN, and the operators Cφ and Cψ be bounded on F2. Then

    CφCψ=WKa,BAz+b,

    where A is the adjoint operator of A.

    Proof. From Lemma 2 in [3], it follows that

    CφCψ=MKaCAzCBz+b=MKaC(Bz+b)Az=MKaCBAz+b=WKa,BAz+b,

    from which the result follows. The proof is complete.

    In Lemma 2.1, we prove that the product of the adjoint of a composition operator and another composition operator is expressed as a weighted composition operator. Next, we will see that in some sense, the converse of Lemma 2.1 is also true. Namely, we will prove that if φ(z)=Az+b, where A:CNCN is a linear operator with A<1, and u=Kc, then the operator Wu,φ on F2 can be written as the product of the adjoint of a composition operator and another composition operator.

    Lemma 2.2. Let A:CNCN be a linear operator with A<1. If A and c satisfy the condition Aζ,c=0 whenever |Aζ|=|ζ|, then there exists a positive integer n such that the operator Wu,φ on F2 defined by φ(z)=Az+b and u(z)=Kc(z) is expressed as

    Wu,φ=Cn+1nAz+cCnn+1z+b.

    Proof. From Theorem 2 in [3], we see that the operator CAz+c is bounded on F2. Since A<1, there exists a large enough positive integer n such that

    (1+1n)A1.

    Also, by Theorem 2 in [3], the operator Cn+1nAz+c is bounded on F2, which implies that the operator Cn+1nAz+c is also bounded on F2. Since |nn+1Iζ|=|ζ| if and only if ζ=0, nn+1Iζ,b=0 whenever |nn+1Iζ|=|ζ|. By Theorem 2 in [3], the operator Cnn+1Iz+b is bounded on F2. Then, it follows from Lemma 2.1 that

    Cn+1nAz+cCnn+1Iz+b=WKc,Az+b.

    The proof is complete.

    Now, we can obtain the adjoint for some weighted composition operators.

    Theorem 2.1. Let φ(z)=Az+b, u(z)=Kc(z), and A and c satisfy Aζ,c=0 whenever |Aζ|=|ζ|. Then it holds that

    Wu,φ=WKb,Az+c.

    Proof. In Lemma 2.2, we have

    Wu,φ=Cn+1nAz+cCnn+1Iz+b. (2.1)

    It follows from (2.1) that

    Wu,φ=Cnn+1Iz+bCn+1nAz+c. (2.2)

    Therefore, from (2.2) and Lemma 2.1, the desired result follows. The proof is complete.

    By using the kernel functions, we can obtain the following result:

    Lemma 2.3. Let the operator Wu,φ be a bounded operator on F2. Then it holds that

    Wu,φKw=¯u(w)Kφ(w).

    Proof. Let f be an arbitrary function in F2. We see that

    Wu,φKw,f=Kw,Wu,φf=¯Wu,φf,Kw=¯u(w)f(φ(w))=¯u(w)Kφ(w),f.

    From this, we deduce that Wu,φKw=¯u(w)Kφ(w). The proof is complete.

    Here, we characterize the self-adjoint weighted composition operators.

    Theorem 2.2. Let A:CNCN be a linear operator, b,cCN, φ(z)=Az+b, u(z)=Kc(z), and the operator Wu,φ be bounded on F2. Then the operator Wu,φ is self-adjoint on F2 if and only if A:CNCN is self-adjoint and b=c.

    Proof. In Lemma 2.3, we have

    Wu,φKw(z)=¯u(w)Kφ(w)=¯Kc(w)ez,φ(w)2=ec,w2ez,Aw+b2. (2.3)

    On the other hand,

    Wu,φKw(z)=u(z)Kw(φ(z))=ez,c2eAz+b,w2. (2.4)

    It is clear that operator Wu,φ is self-adjoint on F2 if and only if

    Wu,φKw=Wu,φKw.

    From (2.3) and (2.4), it follows that

    ec,w2ez,Aw+b2=ez,c2eAz+b,w2. (2.5)

    Letting z=0 in (2.5), we obtain that ec,w2=eb,w2 which implies that

    c,wb,w=4kπi, (2.6)

    where kN. Also, letting w=0 in (2.6), we see that k=0. This shows that c,wb,w=0, that is, c,w=b,w. From this, we deduce that b=c. Therefore, (2.5) becomes ez,Aw2=eAz,w2. From this, we obtain that z,Aw=Az,w, which implies that Az,w=Az,w. This shows that A=A, that is, A:CNCN is self-adjoint.

    Now, assume that A is a self-adjoint operator on CN and b=c. A direct calculation shows that (2.5) holds. Then Wu,φ is a self-adjoint operator on F2. The proof is complete.

    In [14], Zhao proved that the operator Wu,φ on F2 is unitary if and only if there exist an unitary operator A:CNCN, a vector bCN, and a constant α with |α|=1 such that φ(z)=Azb and u(z)=αKA1b(z). Without loss of generality, here we characterize the self-adjoint unitary operator Wu,φ on F2 for the case α=1 and obtain the following result from Theorem 2.2.

    Corollary 2.1. Let A:CNCN be a unitary operator and bCN such that φ(z)=Azb and u(z)=KA1b(z). Then the operator Wu,φ is self-adjoint on F2 if and only if A:CNCN is self-adjoint and Ab+b=0.

    First, we recall the definition of hyponormal operators. An operator T on a Hilbert space H is said to be hyponormal if AxAx for all vectors xH. T is called co-hyponormal if T is hyponormal. In 1950, Halmos, in his attempt to solve the invariant subspace problem, extended the notion of normal operators to two new classes, one of which is now known as the hyponormal operator (see [9]). Clearly, every normal operator is hyponormal. From the proof in [6], it follows that T is hyponormal if and only if there exists a linear operator C with C1 such that T=CT. In some sense, this result can help people realize the characterizations of the hyponormality of some operators. For example, Sadraoui in [12] used this result to characterize the hyponormality of composition operators defined by the linear fractional symbols on Hardy space. On the other hand, some scholars studied the hyponormality of composition operators on Hardy space by using the fact that the operator Cφ on Hardy space is hyponormal if and only if

    Cφf2Cφf2

    for all f in Hardy space. For example, Dennis in [5] used the fact to study the hyponormality of composition operators on Hardy space. In particular, this inequality for norms is used when f is a reproducing kernel function Kw for any wCN. Actually, to the best of our knowledge, there are few studies on the hyponormality of weighted composition operators. Here, we consider this property of weighted composition operators on Fock space.

    First, we have the following result, which can be proved by using the reproducing kernel functions.

    Lemma 3.1. Let wCN and the operator Wu,φ be bounded on F2. Then

    Wu,φKw2=Wu,φWu,φKw(w).

    Proof. From the inner product, we have

    Wu,φKw2=Wu,φKw,Wu,φKw=Wu,φWu,φKw,Kw=Wu,φWu,φKw(w).

    The proof is complete.

    Theorem 3.1. Let A:CNCN be a linear operator, φ(z)=Az+b, u=kc, and the operator Wu,φ be bounded on F2. If the operator Wu,φ is hyponormal on F2, then Abb=Acc and |b||c|.

    Proof. From a direct calculation, we have

    Wu,φKw(z)=u(z)Kw(φ(z))=kc(z)Kw(Az+b)=ez,c2|c|24eAz+b,w2=ez,Aw+c+b,w2|c|24=eb,w2|c|24KAw+c(z). (3.1)

    From (3.1), it follows that

    Wu,φWu,φKw(z)=eb,w2|c|24Wu,φKAw+c(z)=eb,w2|c|24¯u(Aw+c)Kφ(Aw+c)(z)=eb,w2+c,Aw+c2+z,AAw+Ac+b2|c|22=eb+Ac,w2+z,AAw2+z,Ac+b2. (3.2)

    On the other hand, we also have

    Wu,φWu,φKw(z)=¯u(w)Wu,φKφ(w)(z)=¯u(w)u(z)Kφ(w)(φ(z))=ec,w2+z,c2+Az+b,Aw+b2|c|22=ec+Ab,w2+|b|22+z,AAw2+z,c+Ab2|c|22. (3.3)

    From Lemma 3.1, (3.2), and (3.3), it follows that

    Wu,φKw2=Wu,φWu,φKw(w)=ec+Ab,w2+|b|22+|Aw|22+w,c+Ab2|c|22

    and

    Wu,φKw2=Wu,φWu,φKw(w)=eb+Ac,w2+|Aw|22+w,Ac+b2.

    Then, we have

    Wu,φKw2Wu,φKw2=e|Aw|22(ec+Ab,w2+|b|22+w,c+Ab2|c|22eb+Ac,w2+w,Ac+b2),

    which shows that

    Wu,φKw2Wu,φKw20

    for all wCN if and only if

    ec+Ab,w2+|b|22+w,c+Ab2|c|22eb+Ac,w2+w,Ac+b2. (3.4)

    It is clear that (3.4) holds if and only if

    c+Ab,w+|b|2+w,c+Ab|c|2b+Ac,w+w,Ac+b. (3.5)

    From (3.5), we see that (3.4) holds if and only if

    AbAc+cb,w+w,AbAc+cb+|b|2|c|20. (3.6)

    Therefore, we deduce that (3.4) holds for all wCN if and only if |b||c| and Abb=Acc. The proof is complete.

    If b=c=0 in Theorem 3.1, then Wu,φ is reduced into the composition operator CAz. For this case, Theorem 3.1 does not provide any useful information on the operator A:CNCN when CAz is hyponormal on F2. However, we have the following result, which completely characterizes the hyponormal composition operators:

    Theorem 3.2. Let A:CNCN be a linear operator such that CAz is bounded on F2. Then the operator CAz is hyponormal on F2 if and only if A:CNCN is co-hyponormal.

    Proof. Assume that A:CNCN is co-hyponormal. Then there exists an operator B:CNCN with B1 such that A=BA. We therefore have

    CAz=CAz=CABz=CBzCAz.

    Next, we want to show that CBz=1. By Theorem 4 in [3], we have

    CBz=e14(|w0|2|Bw0|2), (3.7)

    where w0 is any solution to (IBB)w=0. From this, we obtain that w0=BBw0, and then

    |Bw0|2=Bw0,Bw0=w0,BBw0=w0,w0=|w0|2. (3.8)

    Thus, by considering (3.7) and (3.8), we see that CBz=1. It follows that the operator CAz is hyponormal on F2.

    Now, assume that the operator CAz is hyponormal on F2. Then there exists a linear operator C on F2 with C1 such that CAz=CCAz. By Lemma 2 in [3], we have CAz=CAz. This shows that CCAz is a composition operator. This result shows that there exists a holomorphic mapping φ:CNCN such that C=Cφ. So Az=A(φ(z)) for all zCN, which implies that there exists a linear operator B:CNCN such that φ(z)=Bz, and then C=CBz. Therefore, A=AB, that is, A=BA. Since C1, this shows that the operator C=CBz is bounded on F2. From Lemma 2.3 in [15], we obtain that B1, which also shows that B1 since B=B. We prove that A:CNCN is co-hyponormal. The proof is complete.

    Remark 3.1. In the paper, we only obtain a necessary condition for the hyponormality of weighted composition operators on Fock space. We hope that the readers can continuously consider the problem in Fock space.

    In this paper, I give a proper description of the adjoint Wu,φ on Fock space for the special symbol functions u(z)=Kc(z) and φ(z)=Az+b. However, it is difficult to give a proper description of the general symbols. On the other hand, I consider the hyponormal weighted composition operators on Fock space and completely characterize hyponormal composition operators on this space. I hope that people are interested in the research in this paper.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    This study was supported by Sichuan Science and Technology Program (2024NSFSC0416).

    The author declares that he has no competing interests.



    [1] Altufeva TY, Ivanov PA, Sakhapova GR (2019) Financing the development of municipal entities at different life cycle stages: Public and private resources. Proceedings of the RAS Ufa Scientific Centre 3: 53–60. https://doi.org/10.31040/2222-8349-2019-0-3-53-60 doi: 10.31040/2222-8349-2019-0-3-53-60
    [2] Bank of Russia (2023) Granted Funds and Borrowings. Available from: https://www.cbr.ru/statistics/bank_sector/sors/.
    [3] Bashinform (2024) Bashkiria entered the Top 3 ranking of economic adaptability of Russian regions in 2022. Available from: https://www.bashinform.ru/articles/economy/2023-03-31/bashkiriya-voshla-v-top-3-reytinga-ekonomicheskoy-adaptivnosti-regionov-rossii-v-2022-godu-3199205.
    [4] Davy E, Hansen U (2023) A firm-level perspective on windows of opportunity. Technol Soc 75. https://doi.org/10.1016/j.techsoc.2023.102374 doi: 10.1016/j.techsoc.2023.102374
    [5] Dementyev VE (2009) Catching up development through the prism of the theory of "long-wave" technological dynamics: the aspect of "Windows of Opportunity" in crisis conditions. Russian Econ J, 34–48.
    [6] Dunlap DR, Santos RS, Latham SF (2023) A window of opportunity: Radical versus repurposing innovation under conditions of environmental uncertainty and crisis. IEEE Trans Eng Manage 71: 6540–6552. https://doi.org/10.1109/TEM.2023.3282803 doi: 10.1109/TEM.2023.3282803
    [7] Edler J, Blind K, Kroll H, et al. (2023) Technology sovereignty as an emerging frame for innovation policy. Defining rationales, ends and means. Res Policy 52. https://doi.org/10.1016/j.respol.2023.104765 doi: 10.1016/j.respol.2023.104765
    [8] Elmarzouky M, Hussainey K, Abdelfattah T, et al. (2022) Corporate risk disclosure and key audit matters: The egocentric theory. Int J Account Inf Manag 30: 230–251. https://doi.org/10.1108/IJAIM-10-2021-0213 doi: 10.1108/IJAIM-10-2021-0213
    [9] Expert report (2022) Small and medium-sized business as a form of national identity. Available from: https://disk.yandex.ru/i/M6xoJvnYky-xog.
    [10] Financial Times (2022) European industry pivots to US as Biden subsidy sends 'dangerous signal'. Available from: https://www.ft.com/content/59a8d135-3477-4d0a-8d12-20c7ef94be07.
    [11] Garrido E, Giachetti C, Maicas JP (2023) Navigating windows of opportunity: The role of international experience. Strateg Manage J 44: 1911–1938. https://doi.org/10.1002/smj.3485 doi: 10.1002/smj.3485
    [12] Giachetti C, Mensah TD (2023) Catching-up during technological windows of opportunity: An industry product categories perspective. Res Policy 52. https://doi.org/10.1016/j.respol.2022.104677 doi: 10.1016/j.respol.2022.104677
    [13] Giannopoulos G, Lianou A, Elmarzouky M. (2023) The impact of M & As on shareholders' wealth: Evidence from Greece. J Risk Financ Manag 16: 199. https://doi.org/10.3390/jrfm16030199 doi: 10.3390/jrfm16030199
    [14] Glazyev SY (2018) Leap into the future. Russia in new technological and world economic structures, Royal Collins Publishing Company.
    [15] Guo H, Li X, Wang C (2023) When the window of opportunity opens: how does open search impact the business model design of digital startups? Asia Pac Bus Rev 29: 1–24. https://doi.org/10.1080/13602381.2023.2191451 doi: 10.1080/13602381.2023.2191451
    [16] Guo L, Zhang MY, Dodgson M, et al. (2016) Windows of opportunity, technological innovation and globalization: A framework of Huawei's global catchup. Acad Manage Proc. https://doi.org/10.5465/ambpp.2016.66 doi: 10.5465/ambpp.2016.66
    [17] Hamdali Y, Skade L (2023) When the time is made right: constructing windows of opportunity for innovation in practice. Acad Manage Proc. https://doi.org/10.5465/AMPROC.2023.174bp doi: 10.5465/AMPROC.2023.174bp
    [18] International Federation of Robotics, Global Robotics Race: Korea, Singapore and Germany in the Lead, 2024. Available from: https://ifr.org/ifr-press-releases/news/global-robotics-race-korea-singapore-and-germany-in-the-lead.
    [19] Ivanov PA (2021) Theoretical and methodological aspects of assessing the investment activity of regions. Ars Administrandi 13: 495–515. https://doi.org/10.17072/2218-9173-2021-4-495-515 doi: 10.17072/2218-9173-2021-4-495-515
    [20] Kwak K, Yoon D (2020) Unpacking transnational industry legitimacy dynamics, windows of opportunity, and latecomers' catch-up in complex product systems. Research Policy 49. https://doi.org/10.1016/j.respol.2020.103954 doi: 10.1016/j.respol.2020.103954
    [21] Lee K, Malerba F (2017) Catch-up cycles and changes in industrial leadership: windows of opportunity and responses of firms and countries in the evolution of sectoral systems. Res Policy 46: 338–351. https://doi.org/10.1016/j.respol.2016.09.006 doi: 10.1016/j.respol.2016.09.006
    [22] Ministry of Industry and Trade, 2023. Navigator of support measures for industrial enterprises. Available from: https://gisp.gov.ru/nmp/.
    [23] Mitrofanov A (2015) Windows of opportunity. Available from: https://www.razumei.ru/lib/article/2652.
    [24] Moscow Financial Forum, Mikhail Mishustin took part in the Moscow Financial Forum, 2023. Available from: http://government.ru/news/49623/.
    [25] Peng X, He L, Ma S, et al. (2023) Windows of opportunity, alliance portfolio and catch-up of latecomer firms: a longitudinal case study of sunny from 1984 to 2018. Nankai Bus Rev Int 15: 438–460. https://doi.org/10.1108/NBRI-01-2023-0001 doi: 10.1108/NBRI-01-2023-0001
    [26] Perez C, Soete L (1988) Catching up in technology: entry barriers and windows of opportunity. In: Dosi, G.(ed.), Technical Change and Economic Theory, New York: Columbia University Press and Pinter, 458–479.
    [27] Reuters, Fears of European industry exodus to U.S. may be overdone, 2023. Available from: https://www.reuters.com/business/fears-european-industry-exodus-us-may-be-overdone-2023-03-03/.
    [28] Rosstat, 2023. Available from: https://rosstat.gov.ru.
    [29] Samarina V, Skufina T, Savon D, et al. (2021) Technological windows of opportunity for Russian Arctic regions: modeling and exploitation prospects. J Risk Financial Manag 14. https://doi.org/10.3390/jrfm14090400 doi: 10.3390/jrfm14090400
    [30] Shinkevich AI, Shinkevich MV, Zaraichenko IA (2010) Technological "windows of opportunity": managing transaction costs of innovative development. Bulletin of Kazan Technological University, 207–214.
    [31] SMB Corporation, SMB Digital Platform, 2023. Available from: https://xn--l1agf.xn--p1ai/services/antikrizisnye-mery/kakuyu-podderzhku-malyy-i-sredniy-biznes-mozhet-poluchit-v-korporatsii-msp_/.
    [32] SPIEF, Plenary session of Saint Petersburg International Economic Forum, 2024. Available from: https://forumspb.com/programme/business-programme/131550/#broadcast.
    [33] Topoleva T (2023) Decomposition of factors of innovative development of regional-oriented production systems. Vestnik of The Kazan State Agrarian University 18: 193–201. https://doi.org/10.12737/2073-0462-2023-193-201 doi: 10.12737/2073-0462-2023-193-201
    [34] Xiong J, Wang K, Yan J, et al. (2021) The window of opportunity brought by the COVID-19 pandemic: an ill wind blows for digitalization leapfrogging. Technol Anal Strateg Manage 35. https://doi.org/10.1080/09537325.2021.1979212 doi: 10.1080/09537325.2021.1979212
    [35] World Bank Group, Research and development expenditure (% of GDP), 2024. Available from: https://data.worldbank.org/indicator/GB.XPD.RSDV.GD.ZS?view = chart.
    [36] Zelentsova L, Spesivtseva M (2022) Mechanism to detect windows of opportunities for implementing new technical and technological solutions for the purpose of industrial organizations sustainable development. Vestnik Universiteta 8: 68–76. https://doi.org/10.26425/1816-4277-2022-8-68-76 doi: 10.26425/1816-4277-2022-8-68-76
    [37] Zhu J (2014) Quantitative models for performance evaluation and benchmarking. Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-06647-9
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