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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Improving IP Literacy among Brazilian Startups: the Design of an Innovative Learning System

Nogueira Viana, Julio Augusto 01 November 2018 (has links)
Intellectual Property (IP) is considered a valuable asset for a company and the relevance of effective IP management has been intensely discussed in the literature. However, research gets scarce when the focus is on SMEs and startups. Scholars and experts appoint the lack of knowledge on IP as one of the main reasons for the underperformance of small firms in the matter. Several initiatives attempted to solve the lack of knoweldge on IP unsuccessfully. Meanwhile, Brazil is seeking improvement in competitiveness and increasing its efforts on innovation. The number of startups sontrongly increased in the last years. This work uses Design Science Research to develop an innovative artifact to improve IP literacy among Brazilian startups. Using the design process stated in the methodology, we analyzed existing IP literacy systems and concluded with design recommendation for future systems. Additionally, we surveyed Brazilian startups to understand how these companies manage their IP and how they access knowledge. Consequently, we developed the system based on the recommendation from initial studies and evaluated it with potential users and IP experts in Brazil. Finally, Brazilian startups used the learning system and improved their knowledge on IP by increasing their capabilities of designing strategies to improve the IP value.
2

Estimação de prêmio de risco de startup

Romani, Mariana Omari 23 January 2014 (has links)
Submitted by Mariana Omari Romani (marianaorr@hotmail.com) on 2014-04-16T16:06:48Z No. of bitstreams: 1 Versão Final Tese Mariana Romani.pdf: 685378 bytes, checksum: 61ac9fb61f006080fd56406d726b7568 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2014-05-20T11:37:39Z (GMT) No. of bitstreams: 1 Versão Final Tese Mariana Romani.pdf: 685378 bytes, checksum: 61ac9fb61f006080fd56406d726b7568 (MD5) / Made available in DSpace on 2014-05-20T11:39:17Z (GMT). No. of bitstreams: 1 Versão Final Tese Mariana Romani.pdf: 685378 bytes, checksum: 61ac9fb61f006080fd56406d726b7568 (MD5) Previous issue date: 2014-01-23 / Startups, by definition, are companies that are more exposed to risks and vulnerabilities than mature companies, which have already been established in the market. The aim of this study is to identify, apply and test a possible methodology to calculate additional risk premium for startups. This study develops a methodology to calculate risk premium based in the methodology to calculate size risk premium published by the independent investment research Morningstar. The adherence of the methodology proposed in this study is tested by the Kalman filter methodology, which was applied to calculate startup additional risk premium varying over time. The results of the application of both methodologies are similar. Therefore, it is possible to conclude that the Morningstar methodology, when applied to calculate startup premium varying over time, is robust. / Por definição as empresas startups estão expostas a mais riscos e vulnerabilidades que empresas maduras e já estabelecidas no mercado. O objetivo do presente estudo é identificar, aplicar e testar uma possível metodologia para calcular prêmio de risco adicional para startups. Para tanto este trabalho desenvolve um estudo de caso no qual a conhecida metodologia para cálculo de prêmio de risco de tamanho da Morningstar é aplicada a uma startup americana. A aderência da metodologia proposta neste estudo é testada pela metodologia do filtro de Kalman, que calcula o prêmio de risco por tamanho variando ao longo do tempo. Os resultados encontrados são similares em ambas as metodologias. De forma que é possível concluir que a metodologia da Morningstar, quando aplicada para calcular prêmio por tamanho variante ao longo do tempo é robusta.

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