<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">umovest</journal-id><journal-title-group><journal-title xml:lang="ru">Статистика и Экономика</journal-title><trans-title-group xml:lang="en"><trans-title>Statistics and Economics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2500-3925</issn><publisher><publisher-name>Plekhanov Russian University of Economics</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21686/2500-3925-2021-4-35-47</article-id><article-id custom-type="elpub" pub-id-type="custom">umovest-1561</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЭКОНОМИЧЕСКОЕ РАЗВИТИЕ РЕГИОНОВ И РЕГИОНАЛЬНАЯ СТАТИСТИКА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>THE ECONOMIC DEVELOPMENT OF THE REGIONS AND REGIONAL STATISTICS</subject></subj-group></article-categories><title-group><article-title>Построение рейтинга инновационного развития российских регионов по уровню вовлечённости университетов</article-title><trans-title-group xml:lang="en"><trans-title>Preparation of Innovative Development Rating of Russian Regions by the Level of University Involvement</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9326-6024</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Выгодчикова</surname><given-names>И. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Vygodchikova</surname><given-names>Irina Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Выгодчикова Ирина Юрьевна – к.ф.-м.н, доцент, доцент кафедры дифференциальных уравнений и математической экономики.</p><p>Саратов</p></bio><bio xml:lang="en"><p>Irina Yu. Vygodchikova – Cand. Sci. (Physics and Mathematics), Associate Professor, Associate Professor of the Department of Differential Equations &amp; Mathematic Economics.</p><p>Saratov</p></bio><email xlink:type="simple">irinavigod@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Саратовский национальный исследовательский государственный университет им. Н. Г. Чернышевского</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Saratov State University named after N. G. Chernyshevsky</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>06</day><month>08</month><year>2021</year></pub-date><volume>18</volume><issue>4</issue><fpage>35</fpage><lpage>47</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Выгодчикова И.Ю., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Выгодчикова И.Ю.</copyright-holder><copyright-holder xml:lang="en">Vygodchikova I.Y.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://statecon.rea.ru/jour/article/view/1561">https://statecon.rea.ru/jour/article/view/1561</self-uri><abstract><sec><title>Введение</title><p>Введение. В статье приводится методика кластеризации и группировки показателей деятельности университетов для построения интегрального рейтинга регионов России по уровню вовлечённости университетов в региональное инновационное развитие. Рассмотрены следующие проблемы, требующие управленческого воздействия государственных структур: роль научно-исследовательской базы региональных университетов в укреплении инновационного потенциала регионов, степень вовлечённости университетов в инновационное региональное пространство.</p><p>Цель исследования – разработка системы рейтингования регионов России по степени вовлечённости университетов в инновационное развитие с использованием математического инструментария и интеллектуальной системы обработки данных.</p><p>Гипотеза статьи – существование связи регионального инновационного развития с результативностью университетского вклада.</p><p>Математический подход предполагает рассмотрение и многомерное ранжирование основных групп показателей деятельности университетов с целью получения кластерных классификаций в рамках каждой из поставленных проблем. Решение проблем состоит в построении барометра инновационной активности в виде многоцелевого проблемно-ориентированного рейтинга.</p></sec><sec><title>Материалы и методы</title><p>Материалы и методы. Применён подход, включающий оценку и многомерное ранжирование вклада университетов с использованием групп интегральных индексов, созданных на основании агрегирования нескольких важных показателей деятельности вуза. Вычислительные эксперименты проведены по данным Минобрнауки для регионов России и региональных вузов.</p><p>Рассмотрено 16 показателей регионов России за 2016 год.</p></sec><sec><title>Результаты и дискуссия</title><p>Результаты и дискуссия. Выполнено ранжирование и сопоставление вузов по степени вовлечённости в инновационное развитие региона с использованием индикаторной модели и агрегирования в зависимости от целевой проблемы. Получены количественные показатели качества деятельности вузов по регионам, позволяющие получить интегральный рейтинг российских регионов по уровню вовлечённости университетов. В отличие от других подходов, авторский метод включает три составляющих, которые являются самостоятельными интегральными индексами и указывают на уровень вовлечённости университетов в региональное инновационное развитие. Выполнена обработка статистических данных по ведущим показателям российских вузов за 2016 год. Авторская методика Наука – модель с тремя факторами – модель с перегруппировкой, названная автором А-В-С, показала высокий потенциал вузов России по сбалансированности востребования научных центров вузов на региональном уровне в региональном управлении наукой и инновациями.</p></sec><sec><title>Заключение</title><p>Заключение. Результаты исследования сопоставлены с рейтингами известных агентств. Автор надеется, что в скором времени в России появится надёжная наукометрическая система на уровне рейтингования вузов по их вовлечённости в инновационное развитие России, такой рейтинг будет бесспорным аргументом в пользу финансирования региональных вузов. Автор заложил высокое требование: соответствие трём моделям, только в таком случае региональные вузы могут получить финансирование из муниципалитета, после перераспределения от центра. При этом необходимо тщательно выбирать вузы, в которых проекты получат развитие и перспективу. Региональные органы власти должны выполнить требования для получения необходимых инвестиций в перспективные проекты. Научный потенциал и востребованность теоретических исследований для их полноценного применения на всех предприятиях, соединение сфер теоретической науки и практического внедрения позволят снизить затраты на содержание устаревших технологий во всех областях знаний и задействовать опыт старших поколений и силы молодёжи для развития высокотехнологичного производства в России. Поэтому результаты исследования будут полезны федеральным органам власти и финансово-кредитным организациям, осуществляющим финансирование.</p></sec><sec><title> </title><p> </p></sec></abstract><trans-abstract xml:lang="en"><p>The paper presents method of clustering and grouping the university performance indicators to prepare an integral rating of Russian regions by the level of university involvement in innovative development of Russian regions. The following problems that require the management influence of state structures are considered: the role of the research base of regional universities in strengthening the innovative potential of regions, the degree of involvement of universities in the innovative regional space.</p><p>The aim of the study is to develop a rating system for Russian regions according to the degree of university involvement in innovative development using mathematical tools and an intelligent data processing system. The main hypothesis of the article is the existence of a link between regional innovative development and the effectiveness of university contributions. The mathematical approach involves the consideration and multidimensional ranking of the main groups of university performance indicators in order to obtain cluster classifications within each of the problems posed. The solution to the problems is to build a barometer of innovation activity in the form of a multi-purpose problem-oriented rating.</p><sec><title>Materials and methods</title><p>Materials and methods. An approach is applied that includes the assessment and multidimensional ranking of the contribution of universities using groups of integral indices created on the basis of aggregation of several important indicators of the university’s activity. Computational experiments were conducted according to the data of the Ministry of Education and Science for the regions of Russia and regional universities. 16 indicators of Russian regions for 2016 are considered.</p></sec><sec><title>Results and discussion</title><p>Results and discussion. The ranking and comparison of universities according to the degree of involvement in the innovative development of the region was performed using an indicator model and aggregation depending on the target problem. Quantitative indicators of the quality of university’s activities by regions are obtained, which allow us to obtain an integral rating of Russian regions by the level of university involvement. Unlike other approaches, the author’s method includes three components, which are independent integral indexes and indicate the level of involvement of universities in regional innovative development. Statistical data on the leading indicators of Russian universities for 2016 were processed. The methodology Science-model with three factors - the model with regrouping, named by the author A-B-C, showed the high potential of Russian universities to balance their regional demand as management research centers.</p></sec><sec><title>Conclusion</title><p>Conclusion. The results of the study are compared with the ratings of the well-known agencies. The author hopes that soon Russia will have a reliable scientometric system at the level of rating universities on their involvement in the innovative development of Russia, such a rating will be an indisputable argument in favor of financing regional universities. The author laid down a high requirement: compliance with the three models, only in this case, regional universities can receive funding from the municipality, after redistribution from the center. At the same time, it is necessary to carefully choose universities in which projects will receive development and perspective. Regional authorities must meet the requirements to receive the necessary investments in promising projects. The scientific potential and demand for theoretical research for their full application at all enterprises, the combination of theoretical science and practical implementation will reduce the cost of stabilizing outdated technologies in all areas of knowledge and use the experience of older generations and the strength of young people for high-tech production growth in Russia. Therefore, the results of the study will be useful to federal authorities and financial and credit organizations that provide financing.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>регион</kwd><kwd>университет</kwd><kwd>инновации</kwd><kwd>интегральный рейтинг</kwd><kwd>системный анализ</kwd></kwd-group><kwd-group xml:lang="en"><kwd>region</kwd><kwd>university</kwd><kwd>innovation</kwd><kwd>integral rating</kwd><kwd>system analysis</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Нижегородцев, Р.М. (2017). Прогнозирование показателей социально-экономического развития региона / Р.М. Нижегородцев, Е.И. Пискун, В.В. Кудревич // Экономика региона. Т. 13, № 1, c. 38-48.</mixed-citation><mixed-citation xml:lang="en">Nizhegorodtsev R.M., et al. (2017). Prognozirovanie pokazatelej social'no-jekonomicheskogo razvitija regiona  [The forecasting of regional social and economic development] // Economy of region, vol. 13, № 1, pp. 38-48 (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Клюев А.К. (2010). Программы инновационного развития региона и университетов: поиск соответствия // Университетское управление: практика и анализ. № 1, c. 30-34.</mixed-citation><mixed-citation xml:lang="en">Klyuev A.K. (2010). Programmy innovatsionnogo razvitiya regiona i universitetov: poisk sootvetstviya [Programs of innovative region and university development: search of equivalence] // University Management: Practice and Analysis. № 1, pp. 30-34 (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Blind, K. &amp; Grupp, H. (1999). Interdependencies between the science and technology infrastructure and innovation activities in German regions: empirical findings and policy consequences // Research Policy, № 28 (2), pp. 451-468.</mixed-citation><mixed-citation xml:lang="en">Blind K. &amp; Grupp H. (1999). Interdependencies between the science and technology infrastructure and innovation activities in German regions: empirical findings and policy consequences. Research Policy, 28 (2), pp. 451-468.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Griliches, Z. (1979). Issues in assessing the contribution of R&amp;D to productivity growth // Bell Journal of Economics. № 10(1), pp. 92-116.</mixed-citation><mixed-citation xml:lang="en">Griliches Z. (1979). Issues in assessing the contribution of R&amp;D to productivity growth. Bell Journal of Economics, 10(1), pp. 92-116.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Jaffe, A. (1989). Real effects of academic research // American Economic Review. № 79, pp. 957–970.</mixed-citation><mixed-citation xml:lang="en">Jaffe A. Real effects of academic research  // American Economic Review. 1989. № 79, pp. 957–970.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Сио К.К. (2000). Управленческая экономика. Пер. с англ. М.: ИНФРА-М, 671 с.</mixed-citation><mixed-citation xml:lang="en">Seo. К.К. (2000). Managerial economics. Translation from English, Moscow: INFRA- M, 2000.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Goddard, J. B., Chatterton, Р. (2000). The response of universities to regional needs // European Journal of Education. № 35(4), pp. 475-496.</mixed-citation><mixed-citation xml:lang="en">Goddard J. B., Chatterton Р. The response of universities to regional needs // European Journal of Education. 2000.  № 35(4), pp. 475-496.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Teece D.J., Peteraf M., Leih S. (2016). Dynamic Capabilities and Organizational Agility: Risk, Uncertainty, and Strategy in the Innovation Economy. California Management Review, 58 (4), pp. 13-35.</mixed-citation><mixed-citation xml:lang="en">Teece D.J., Peteraf M., Leih S. (2016). Dynamic Capabilities and Organizational Agility: Risk, Uncertainty, and Strategy in the Innovation Economy.  California Management Review, 58 (4), pp. 13-35.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Fratesi U., Senn L. (2009). Growth and Innovation of Competitive Regions: the Role of Internal and External Connections. Berlin: Springer-Verlag Berlin Heidelberg. – 368 р.</mixed-citation><mixed-citation xml:lang="en">Fratesi U. &amp; Senn L. (2009). Growth and Innovation of Competitive Regions: The Role of Internal and External Connections. Springer-Verlag Berlin Heidelberg, p. 368.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Benneworth, P. (2013). University Engagement With Socially Excluded Communities. Publisher: Springer Netherlands, Copyright Holder: Springer Science+Business Media Dordrecht,. – 352 p. DOI 10.1007/978-94-007-4875-0.</mixed-citation><mixed-citation xml:lang="en">Benneworth, P. (2013). University Engagement With Socially Excluded Communities. Publisher: Springer Netherlands, Copyright Holder: Springer Science+Business Media Dordrecht,. –  352 p. DOI 10.1007/978-94-007-4875-0.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Etzkowitz, H. &amp; Leydesdorff, L. (1995). The triple helix–university–industry–government relations: a laboratory for knowledge-based economic development // EASST Review. № 14 (1), pp. 14–19.</mixed-citation><mixed-citation xml:lang="en">Etzkowitz H. &amp; Leydesdorff L. (1995). The triple helix–university–industry–government relations: a laboratory for knowledge-based economic development. EASST Review, 14 (1), pp. 14–19.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Vygodchikova, Irina Yurievna et al. (2017). Estimation of Bond Risks using Minimax. Journal of Advanced Research in Law and Economics, [S.l.], v. 7, n. 7, p. 1899-1907, mar. 2017. ISSN 2068-696X. Available at: &lt;http://journals.aserspublishing.eu/jarle/article/view/784&gt;. Date accessed: 15 mar. 2017. doi: http://dx.doi.org/10.14505//jarle.v7.7(21).38.</mixed-citation><mixed-citation xml:lang="en">Vygodchikova I.Yu. et al. (2017). Estimation of Bond Risks using Minimax. Journal of Advanced Research in Law and Economics, [S.l.], v. 7, n. 7, p. 1899-1907, mar. 2017. ISSN 2068-696X. Available at: &lt;http://journals.aserspublishing.eu/jarle/article/view/784&gt;. Date accessed: 15 mar. –  doi: http://dx.doi.org/10.14505//jarle.v7.7(21).38.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Awrejcewicz, J., et al. (2015). Quantifying chaos of curvilinear beam via exponents. Communications in Nonlinear Science and Numerical Simulation. № 27(1-3), pp. 81-92.</mixed-citation><mixed-citation xml:lang="en">Awrejcewicz J., et al. (2015). Quantifying chaos of curvilinear beam via exponents. Communications in Nonlinear Science and Numerical Simulation, 27(1-3), 81-92.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Fritsch, et al. (2007). Universities and Innovation in Space // Industry and Innovation. № 14 (2), pp. 201-218.</mixed-citation><mixed-citation xml:lang="en">Fritsch et al. (2007). Universities and Innovation in Space. Industry and Innovation, 14 (2), pp. 201-218.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Autant-Bernard, C. (2001). Science and knowledge flows: evidence from the French case // Research Policy. № 30 (7), pp. 1069-1078.</mixed-citation><mixed-citation xml:lang="en">Autant-Bernard C. (2001). Science and knowledge flows: evidence from the French case. Research Policy, 30 (7), pp. 1069-1078.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Derunova, et al. (2014). The study of the dynamics of innovative development of economy on the endogenous growth through multi-sector extension of the Solow model // Biosci. Biotech. Res. Asia. № 11(3), pp. 1581-1589.</mixed-citation><mixed-citation xml:lang="en">Derunova et al. (2014). The study of the dynamics of innovative development of economy on the endogenous growth through multi-sector extension of the Solow model. Biosci. Biotech. Res. Asia, 11(3), pp. 1581-1589.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Pisano G. P. (2010). The Evolution of Science-Based Business: Innovating, How we Innovate // Industrial and Corporate Change. Vol. 19(2), pp. 465–482.</mixed-citation><mixed-citation xml:lang="en">Pisano G. P. (2010). The Evolution of Science-Based Business: Innovating, How we Innovate. Industrial and Corporate Change, 19(2), pp. 465–482. doi: 10.1093/icc/dtq013</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Innovation Union Scoreboard 2013. Belgium: European Union. 2013. — 80 p.</mixed-citation><mixed-citation xml:lang="en">Innovation Union Scoreboard. (2013). European Union Belgium, 80.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Подиновский В.В. (2013). Метод взвешенной суммы критериев в анализе многокритериальных решений: pro et contra / В.В. Подиновский, М.А.Потапов // Бизнес-информатика, № 3 (25), c. 41-48.</mixed-citation><mixed-citation xml:lang="en">Podinovski V., Potapov M. (2013). Metod vzveshennoi summy kriteriev v analize mnogokriterial'nykh reshenii: pro et contra [Weighted sum method in the analysis of multicriterial decisions: pro et contra // Business informatics, no 3 (25), pp. 41-48 (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">van Vught, F., Westerheijden, Don F. (2010). Multidimensional ranking: a new transparency tool for higher education and research // Higher education management and policy, vol. 22, № 3, pp. 6-11.</mixed-citation><mixed-citation xml:lang="en">van Vught F., Westerheijden Don F. (2010). Multidimensional ranking: a new transparency tool for higher education and research. Higher Education Management and Policy. Volume 22/3, OECD. Higher education management and policy, 22(3), pp. 6-11.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Козлова О. А., Гаркавенко А. Н., Андреева Е. Л. (2008). Роль университета в инновационном развитии региональной экономики // Экономика региона. № 2 (14), c. 64-74.</mixed-citation><mixed-citation xml:lang="en">Kozlova O. A., Garkavenko A. N., Andreev E. L. (2008). Role of the university in the innovative development of regional economy. Economy of Region. №2 (14), pp. 64-74. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Varga, A., Sebestyén, T., Szabó, N., Szerb, L. (2020). Estimating the economic impacts of knowledge network and entrepreneurship development in smart specialization policy. Regional Studies 54, 48-59. https://doi.org/10.1080/00343404.2018.1527026</mixed-citation><mixed-citation xml:lang="en">Varga, A., Sebestyén, T., Szabó, N., Szerb, L. (2020). Estimating the economic impacts of knowledge network and entrepreneurship development in smart specialization policy. Regional Studies 54, 48-59. https://doi.org/10.1080/00343404.2018.1527026</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Бутко Е.Я. (2016). Индикаторы как инструмент сравнительного анализа образования // Дистанционное и виртуальное обучение. № 1 (103), c. 31-37.</mixed-citation><mixed-citation xml:lang="en">Butko E.Ya. (2016). Indikatory kak instrument sravnitel'nogo analiza obrazovaniya [Indicators as a Tool for Comparative Analysis of Education] // Distance and virtual learning, № 1 (103), pp. 31-37. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Курочкин Д.А. (2014). Инновационная среда региона и особенности ее формирования (на примере Московской области) // Вопросы региональной экономики. Т. 20, № 3, с. 59-66.</mixed-citation><mixed-citation xml:lang="en">Kurochkin D.A. (2014). Innovacionnaja sreda regiona i osobennosti ee formirovanija (na primere Moskovskoj oblasti) [Innovation environment of the region and features of its formation (for example, Moscow region)] // Вопросы региональной экономики. Vol. 20, no. 3, pp. 59-66. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Нижегородцев Р.М. Перспективы генерации знаний в XXI веке: функции и барьеры // Экономический вестник ИПУ РАН. 2020. Т. 1. № 1. С. 3-11.</mixed-citation><mixed-citation xml:lang="en">Nizhegorodtsev R.M. Outlooks of knowledge generation in 21st century: functions and barriers// Economic Bulletin of ICS RAS. 2020, vol. 1. no 1, pp. 3-11 (in Russian).</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
