Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
Condeixa, Gustavo Abrantes
 |
| Orientador(a): |
Borges Junior, Cândido Vieira
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| Banca de defesa: |
Borges Junior, Cândido Vieira,
Monsueto, Sandro Eduardo,
Emmendoerfer, Magnus Luiz,
Mesquita, Albenones José de |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Administração (FACE)
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| Departamento: |
Faculdade de Administração, Ciências Contábeis e Ciências Econômicas - FACE (RG)
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/7519
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Resumo: |
High growth is a phenomenon that occurs for a small group of companies and, it is related to fast growth caused by new jobs creation or superior growth compared to other companies. Researchers and public politics makers showing interest for companies with high growth is motivated by the fact that those companies are perceived as important factors for a dynamic economy and, job creation. They are also known for creating and diffusing new technologic knowledge, contributing for regional development. To analyze the relation between science, technology and innovation's regional indicators, as well as the entrepreneurship indicators of high growth in the Brazilian states, the collected data composed a cross-section within the 27 Brazilian federation states, between the years of 2008 and 2012, having its explanatory variables grouped into four indicators of ST&I that corresponds to ST&I infrastructure, ST&I Human Resources, Investment in R&D and Innovation. Stacked data was utilized and the estimated method adopted was the Ordinary Least Squares (OLS).To better adjust the proposed model the dependent variable TEAC general was segregated for the Service, Industry and Commerce sectors.16 logistics regression specifications was studied in reference to the four proposed equations, segregated in function of the four dependent variables mentioned. The results shown in this work demonstrate the existence of a low correlation between ST&I and TEAC general. It also suggests that the activities sector is an important component in relation between ST&I and TEAC, although the ST&I indicators present larger impact for Industry Sector's TEAC. Another significant result was that a better human resources qualification results in better TEAC. To prove the theory, it was verified a strong correlation among people hired with bachelor's degree while a person holding a master or Ph.D. degree didn't present significance to the study. |
