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182 0 _ab
200 1 _aTechnical Efficiency of High-Technology Industries in the Crisis: Evidence from Russia
_fV. V. Spitsin, A. A. Mikhalchuk, D. Vukovic, L. Yu. Spitsina (Spitsyna)
203 _aText
_celectronic
300 _aTitle screen
330 _aThe aim of the paper is to study the statics and dynamics of the technical efficiency of enterprises, in the context of high-technology industries and with further detailing by territory of location of enterprises (regions-agglomeration centers; other regions) and the size of enterprises (large, medium, and small). We considered the case of Russia a large country with a transition economy. We applied the following methods: the Data Envelopment Analysis for calculating technical efficiency, the methods for calculating the Malmquist productivity index and its components, ANOVA, and Tobit regression models. The sample consisted of 1150 companies. The study period is 2013–2017. We found that the most high-technology industries are characterized by the negative impact of the crisis on technical efficiency. We also found that enterprises located in regions-agglomeration centers are characterized by higher TE values in three of the four studied sectors (except for pharmaceutical industry). Tobit regression showed that large enterprises, enterprises located in agglomeration centers, and enterprises using borrowed capital receive benefits in terms of technical efficiency. By adding moderators to the Tobit model, we revealed that the positive impact of leverage on technical efficiency is enhanced for large businesses and businesses located in the agglomeration centers. We also found less positive influence of financial leverage on technical efficiency in the period of crisis.
333 _aРежим доступа: по договору с организацией-держателем ресурса
461 _tJournal of the Knowledge Economy
463 _tVol. XX
_v[29 p.]
_d2022
610 1 _aэлектронный ресурс
610 1 _aтруды учёных ТПУ
610 1 _ahigh-technology industries
610 1 _atechnical efficiency
610 1 _acapital embodiment theory
610 1 _aDEA
610 1 _amalmquist productivity index
610 1 _atobit regression models
610 1 _acrisis
610 1 _aRussia
610 1 _aвысокотехнологичные отрасли
610 1 _aтехническая эффективность
610 1 _aрегрессионные модели
610 1 _aкризис
610 1 _aРоссия
701 1 _aSpitsin
_bV. V.
_ceconomist
_cAssociate Professor of Tomsk Polytechnic University, Candidate of economic sciences
_f1976-
_gVladislav Vladimirovich
_2stltpush
_3(RuTPU)RU\TPU\pers\30957
701 1 _aMikhalchuk
_bA. A.
_cmathematician
_cAssociate Professor of Tomsk Polytechnic University, Candidate of physical and mathematical sciences
_f1954-
_gAleksandr Alexandrovich
_2stltpush
_3(RuTPU)RU\TPU\pers\31925
701 1 _aVukovic
_bD.
_ceconomist
_cLeading researcher of Tomsk Polytechnic University
_f1978-
_gDarko
_2stltpush
_3(RuTPU)RU\TPU\pers\39826
701 1 _aSpitsina (Spitsyna)
_bL. Yu.
_cEconomist
_cAssociate Professor of Tomsk Polytechnic University, Candidate of economic sciences
_f1976-
_gLubov Yurievna
_2stltpush
_3(RuTPU)RU\TPU\pers\35245
712 0 2 _aНациональный исследовательский Томский политехнический университет
_bШкола инженерного предпринимательства
_c(2017- )
_h7949
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712 0 2 _aНациональный исследовательский Томский политехнический университет
_bШкола базовой инженерной подготовки
_bОтделение математики и информатики
_h8031
_2stltpush
_3(RuTPU)RU\TPU\col\23555
712 0 2 _aНациональный исследовательский Томский политехнический университет
_bШкола базовой инженерной подготовки
_bОтделение социально-гуманитарных наук
_h8033
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_b63413507
_c20220623
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856 4 _uhttps://doi.org/10.1007/s13132-021-00877-9
942 _cCF