Comparison between Brazil and the 30 Most Innovative Countries in the World

Authors

  • Marisa Moser Universidade Federal de São Paulo
  • Mauri Aparecido de Oliveira UNIFESP
  • Ricardo Luiz Pereira Bueno UNIFESP

DOI:

https://doi.org/10.5195/emaj.2017.141

Keywords:

Innovation, Technologic Innovation, Innovative Countries, STEM, Education, Government, Cluster Analysis

Abstract

Innovation can be defined as the implementation of a new or significantly improved product (good or service), or a process, a new marketing method, a new organizational method in business practices, workplace organization, or external relations. This innovation can be measured by several factors such as investments in research and development, the concentration of high-tech companies traded on the stock exchange, among others. The present study aims to perform a cluster analysis to investigate the behavior of the most innovative countries compared to Brazil. The study contemplates a historical series from the years 2012 to 2015 of the 30 most innovative countries in the world having been added to Brazil. In addition, a series of macroeconomic, political and social variables are considered.

Author Biographies

Marisa Moser, Universidade Federal de São Paulo

Master's Degree student: Marisa Moser
Specialist in International Business, Bachelor of Business Administration from Centro Universitário Central Paulista (UNICEP) and Master Student in Management of Policies and Public Organizations from the Federal University of São Paulo.
Has more than six (6) years of experience as a consultant for new business and account management.

Mauri Aparecido de Oliveira, UNIFESP

Professor Ph.D. – Universidade Federal de São Paulo: Mauri Aparecido Oliveira
Mechanical engineer with an emphasis in mechatronics by the School of Engineering of São Carlos of USP. In the undergraduate program, he was a research fellow at the National Council for Scientific and Technological Development (CNPq), working in the Computational Intelligence Laboratory of the Institute of Mathematical and Computational Sciences (ICMC / USP) and the Integrated Model Plant in computer integrated manufacturing projects (CIM) of EESC / USP. He holds a degree in automotive engineering from the Faculty of Industrial Engineering (FEI). He worked as a prototype development engineer in the Experimental Engineering department of General Motors do Brazil (GMB) and worked in plants in Brazil and OPEL in Germany. He studied MBA in finance at the Brazilian Institute of Capital Markets (IBMEC / SP). Master from the Faculdade de Economia, Administração e Contabilidade (FEA / USP) and has published articles in the areas of finance, econometrics, information technology, economics and manufacturing processes. He holds a Ph.D. in Administration from the Faculty of Economics, Administration, and Accounting (FEA / USP). The main topic of interest is the application of artificial neural networks in the forecast of financial time series. Post-doctorate in Applied Statistics by the Institute of Mathematics and Statistics (IME-USP). He is currently Professor of Quantitative Methods in Management, Accounting and Actuarial Sciences, Economic Sciences and International Relations at the Federal University of São Paulo (UNIFESP)

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Published

2018-05-16

Issue

Vol. 7 No. 2 (2017)

Section

Articles

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