Assessing the impact of regional scientific environment on the performance of scientific organizations: the example of Russia
Keywords:
Regional scientific environment, scientific organizations, performance, regression analysis
Abstract
The goal of the study is to determine the impact of the regional scientific environment on the performance of scientific organizations. The indicators of a regional scientific environment, which were used as predictors in a regression model built to assess the dependence of the effectiveness of scientific organizations has been identified during the study. In the model, the category of scientific organizations was assigned as a dependent variable, according to the results of the federal monitoring conducted in 2016 for 541 scientific organizations located in 65 Russian regions. The study showed that there were no significant differences between regions when comparing factors determining the regional scientific environment and the performance of scientific organizations.Downloads
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Dranev, Y., Kotsemir, M. and Syomin, B. (2018). Diversity of research publications: relation to agricultural productivity and possible implications for STI policy, Scientometrics, 116(3), 1565-1587
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Fedotov, Y.V. (2012). DEA Method: Analysis of Data Convolution, Russian Journal of Management, 10(2).
Fitjar, R.D. and Rodríguez-Pose, A. (2015). Networking, Context and Firm-Level Innovation: Cooperation Through the Regional Filter in Norway. CEPR Discussion Paper No. DP10624. URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2610759
Fritsch, M. and Wyrwich, M. (2018). Regional knowledge, entrepreneurial culture, and innovative start-ups over time and space―an empirical investigation, Small Business Economics, 51(2), 337-353.
Garfield, E. (1979). Citation Indexing: Its Theory and Application in Science, Technology, and Humanities. New York. John Wiley.
Girdauskiene, L. and Savaneviciene, A. (2015). Exposition of Internal Factors Enhancing Creativity and Knowledge Creation. In: Fred A., Dietz J., Liu K., Filipe J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2013. Communications in Computer and Information Science, vol 454. Springer. Berlin. Heidelberg
Hanssen, TE.S., Jørgensen, F. and Larsen, B. (2018). The relation between the quality of research, researchers’ experience, and their academic environment, Scientometrics, 114, 933-950. doi: 10.1007/s11192-017-2580-y
Hazelkorn, E. and Gibson, A. (2017). Global science, national research, and the question of university rankings, Palgrave Communications, 3(1).
Hemlin, S., Allwood, C.M. and Martin, B.R. (2008). Creative Knowledge Environments, Creativity Research Journal, 20(2), 196-210, doi: 10.1080/10400410802060018
Kulagin, A.S. (2011). Ocenka i samoocenka nauchnoj organizacii, Innovations, 10 (156), 20-30.
Kulagin, A.S. (2018). Ocenka i samoocenka nauchnoj organizacii. Teorija i praktika. Moscow. IPRAN RAS.
Leonidova, G.V., Golovchin, M.A., Lastochkina, M.A. and Ustinova, K.A. (2016). “Knowledge Workers” and Modernization in the Region, Economic and Social Changes: Facts, Trends, Forecast, 3 (45), 138-153.
Lewandowska, A. and Stopa, M. (2018). SMEs innovativeness and institutional support system: the local experiences in qualitative perspective. Polish case study, Oeconomia Copernicana, 9(2), 333–351. doi: 10.24136/oc.2018.017
Maltseva, A.A., Monakhov, I.A. and Bedenko, N.N. (2017). The approaches to evaluating public scientific organizations: the experience of leading countries and possibility of using it in Russia, PONTE, 73(10). doi: 10.21506/j.ponte.2017.10.2
Martinez-Noya, A. and Rajneesh, N. (2018). What more can we learn from R&D alliances? A review and research agenda, BRQ Business Research Quarterly, 21, 195-212.
OECD, 2011. Public research institutions: mapping sector trends. OECD Publishing. doi: 10.1787/9789264119505-en
Oinas, P., Trippl, M. and Höyssä, M. (2018). Regional industrial transformations in the interconnected global economy, Cambridge Journal of Regions, Economy and Society, 11(2), 227-240.
Organizational behaviour and the physical environment (2020). London : New York ; Routledge Taylor & Francis Group, 2020. 339 p.
Price, D. J. de Solla (1976). A general theory of bibliometric and other cumulative advantage processes, Journal of the American Society for Information Science, 27(5), 292-306
Rhaiem, M. (2017). Measurement and determinants of academic research efficiency: a systematic review of the evidence, Scientometrics, 110(2), No.3, 581-615. doi: 10.1007/s11192-016-2173-1
Roesler, C. and Broekel, T. (2017). The role of universities in a network of subsidized R&D collaboration: The case of the biotechnology-industry in Germany, Review of Regional Research, 37(2), 135-160.
Rørstad, K. and Aksnes, D.W. (2015). Publication rate expressed by age, gender and academic position – A large-scale analysis of Norwegian academic staff, Journal of Informetrics, 9(2), 317-333.
Streltsova, E.A. (2018). Technology specialization of Russia. URL: https://issek.hse.ru/data/2018/11/28/1141484660/NTI_N_112_28112018.pdf
Zhang, Y., Chen, K. and Zhu, G. (2016). Inter-organizational scientific collaborations and policy effects: an ego-network evolutionary perspective of the Chinese Academy of Sciences, Scientometrics, 108, 1383. doi: 10.1007/s11192-016-2022-2
Published
2019-11-21
How to Cite
Maltseva, A., Monakhov, I., Veselov, I., Gridchina, A., Apanasenok, A., Brikoshina, I., & Dobryshina, L. (2019). Assessing the impact of regional scientific environment on the performance of scientific organizations: the example of Russia. Amazonia Investiga, 8(24), 441-451. Retrieved from https://amazoniainvestiga.info/index.php/amazonia/article/view/823
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