Product Innovation Efficiency of Russian Electronic Industry: DEA Approach and Cluster Analysis; Advances in Social Science, Education and Humanities Research; Vol. 53 : International Conference on Social Science and Higher Education (ICSSHE 2016)

Product Innovation Efficiency of Russian Electronic Industry: DEA Approach and Cluster Analysis; Advances in Social Science, Education and Humanities Research; Vol. 53 : International Conference on Social Science and Higher Education (ICSSHE 2016)

Bibliographic Details
Parent link:Advances in Social Science, Education and Humanities Research.— , 2016
Vol. 53 : International Conference on Social Science and Higher Education (ICSSHE 2016).— 2016.— [P. 607-610]
Corporate Authors: Национальный исследовательский Томский политехнический университет (ТПУ) Институт социально-гуманитарных технологий (ИСГТ) Кафедра менеджмента (МЕН), Национальный исследовательский Томский политехнический университет (ТПУ) Физико-технический институт (ФТИ) Кафедра высшей математики и математической физики (ВММФ), Национальный исследовательский Томский политехнический университет (ТПУ) Институт социально-гуманитарных технологий (ИСГТ) Кафедра экономики (ЭКОН)
Other Authors: Spitsin V. V. Vladislav Vladimirovich, Mikhalchuk A. A. Aleksandr Alexandrovich, Spitsina (Spitsyna) L. Yu. Lubov Yurievna, Shabaldina N. V. Nataliya Vladimirovna, Novoseltseva D. A. Darjya Andreevna, Shinkeev M. L. Mikhail Leonidovich
Summary:Title screen
This paper investigates product innovationsefficiency in innovative subsection DL «Manufacture of electricaland optical equipment» at the level of Russian regions on thebasis of the DEA approach. Leading regions on productinnovations efficiency were identified by absolute and relativeindicators. We found that only a few regions in Russia arecharacterized by intensive innovation processes. Most regions lag far behind the leaders on indicators of intensity of innovationprocesses and innovation efficiency. We proposed and testedcluster analysis method to rank the objects (regions) on theirDEA coordinates and to assess the statistical significance ofdifferences between objects.
Language:English
Published: 2016
Subjects:
электронный ресурс
труды учёных ТПУ
statistics
инновационная продукция
электронная промышленность
российские регионы
кластерный анализ
статистика
Online Access:http://dx.doi.org/10.2991/icsshe-16.2016.20
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654429

Similar Items

Similar Items