Modeling the influence of age on the technical efficiency by sector and time periods
In today’s competitive economy, technological leadership and technical efficiency are key to the successful development of enterprises, countries and territories. This paper investigates the influence of factors on the technical efficiency of a business. Situations where technical efficiency is calc...
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Publishing House of the State University of Management
2021
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oai:doaj.org-article:1bbb17cfb78540298636a696313779fa2021-12-03T07:43:37ZModeling the influence of age on the technical efficiency by sector and time periods1816-42772686-841510.26425/1816-4277-2021-10-59-68https://doaj.org/article/1bbb17cfb78540298636a696313779fa2021-12-01T00:00:00Zhttps://vestnik.guu.ru/jour/article/view/3144https://doaj.org/toc/1816-4277https://doaj.org/toc/2686-8415In today’s competitive economy, technological leadership and technical efficiency are key to the successful development of enterprises, countries and territories. This paper investigates the influence of factors on the technical efficiency of a business. Situations where technical efficiency is calculated by the DEA method, and its determinants are defined in regression models, including tobit regression models, have been considered. The determinants of technical efficiency identified by foreign researchers have been systematised. Modeling of the influence of the “Age” factor on the technical efficiency of enterprises in six leading sectors of Russia’s economy over the period 2015–2019 has been performed. It has been found that the “Age” factor has different effects on technical efficiency in different industry sectors. Particularly, in the food industry younger companies are more technically efficient, while mature companies are more technically efficient in the information technology sector. Accordingly, the directions and priorities for incentives should differ across sectors of the economy. In particular, the technological development of the food industry requires support for the generation processes of young enterprises and start-ups. In the information technology sector, the priority should be to support mature enterprises and the growth processes of young enterprises to maturity.V. V. SpitsinL. Yu. SpitsinaE. B. GribanovaPublishing House of the State University of Managementarticletechnological leadershiptechnical efficiencydeterminantsage of firmyoung enterprisesold enterprisesindustryservicesdea methodtobit modelsregression analysiseconometric modelinginnovative developmentrussiaSociology (General)HM401-1281Economics as a scienceHB71-74RUВестник университета, Vol 0, Iss 10, Pp 59-68 (2021) |
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DOAJ |
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DOAJ |
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| topic |
technological leadership technical efficiency determinants age of firm young enterprises old enterprises industry services dea method tobit models regression analysis econometric modeling innovative development russia Sociology (General) HM401-1281 Economics as a science HB71-74 |
| spellingShingle |
technological leadership technical efficiency determinants age of firm young enterprises old enterprises industry services dea method tobit models regression analysis econometric modeling innovative development russia Sociology (General) HM401-1281 Economics as a science HB71-74 V. V. Spitsin L. Yu. Spitsina E. B. Gribanova Modeling the influence of age on the technical efficiency by sector and time periods |
| description |
In today’s competitive economy, technological leadership and technical efficiency are key to the successful development of enterprises, countries and territories. This paper investigates the influence of factors on the technical efficiency of a business. Situations where technical efficiency is calculated by the DEA method, and its determinants are defined in regression models, including tobit regression models, have been considered. The determinants of technical efficiency identified by foreign researchers have been systematised. Modeling of the influence of the “Age” factor on the technical efficiency of enterprises in six leading sectors of Russia’s economy over the period 2015–2019 has been performed. It has been found that the “Age” factor has different effects on technical efficiency in different industry sectors. Particularly, in the food industry younger companies are more technically efficient, while mature companies are more technically efficient in the information technology sector. Accordingly, the directions and priorities for incentives should differ across sectors of the economy. In particular, the technological development of the food industry requires support for the generation processes of young enterprises and start-ups. In the information technology sector, the priority should be to support mature enterprises and the growth processes of young enterprises to maturity. |
| format |
article |
| author |
V. V. Spitsin L. Yu. Spitsina E. B. Gribanova |
| author_facet |
V. V. Spitsin L. Yu. Spitsina E. B. Gribanova |
| author_sort |
V. V. Spitsin |
| title |
Modeling the influence of age on the technical efficiency by sector and time periods |
| title_short |
Modeling the influence of age on the technical efficiency by sector and time periods |
| title_full |
Modeling the influence of age on the technical efficiency by sector and time periods |
| title_fullStr |
Modeling the influence of age on the technical efficiency by sector and time periods |
| title_full_unstemmed |
Modeling the influence of age on the technical efficiency by sector and time periods |
| title_sort |
modeling the influence of age on the technical efficiency by sector and time periods |
| publisher |
Publishing House of the State University of Management |
| publishDate |
2021 |
| url |
https://doaj.org/article/1bbb17cfb78540298636a696313779fa |
| work_keys_str_mv |
AT vvspitsin modelingtheinfluenceofageonthetechnicalefficiencybysectorandtimeperiods AT lyuspitsina modelingtheinfluenceofageonthetechnicalefficiencybysectorandtimeperiods AT ebgribanova modelingtheinfluenceofageonthetechnicalefficiencybysectorandtimeperiods |
| _version_ |
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