Objective: Investigate the impact of human, social, and financial capital on the variation of innovation capability of nascent ventures over time. Methodology/design: Quantitative research, developed using a longitudinal secondary database (Panel Study of Entrepreneurship Dynamics 2 -PSED 2). Multiple linear regression technique was used to test the research hypothesis. Main results: Among all types of capital analyzed in the study, level of education, personal finances, and physical social capital were determinant of the nascent ventures' capability of developing innovation over time. Innovation capability influenced the creation of innovation, as well. Theoretical/methodological contributions: Considering the longitudinal design, the research presents which types of capital are relevant along time for nascent ventures to develop innovation capabilities. Relevance/originality: From the methodological perspective, the research has a longitudinal design, as suggested by entrepreneurship and innovation capability scholars since both phenomena are process oriented. It also differentiates innovation and innovation capability, which are two constructs used interchangeably by research, although being different. Social/management contributions: The results contribute to qualify which resources of a company in its initial phase have greater potential for generating long-term innovation.
Objective of the study: this editorial aims to present an overview of Brazilian quantitative research in entrepreneurship, as well as describing possibilities for advancing this methodological approach. Methodology and approach: the article consists of an editorial publication, built from bibliographic research of entrepreneurship literature and theoretical reflections. Main Results: Most national entrepreneurship research follows a qualitative approach. Despite its relevance, quantitative research also has multiple potentialities, especially associated with the use of data originating from secondary sources. Main theoretical and methodological contributions: We present public databases that can be used by entrepreneurship researchers to advance theory. Some strategies for using these bases are exemplified through a brief tutorial in R language. We further debate about strategies to strengthen quantitative research in the area. Finally, we bring a research agenda. Relevance/Originality: contents that are still little explored in the national literature are presented, such as the use of secondary data and machine learning. Social and managerial contributions: some of the databases presented in the study come from government sources and can be used to support the construction of public policies for entrepreneurship. In addition, the precepts on quantitative research presented in this editorial can support managers who work with data analysis to perform more robust studies, regardless of the area, whether practical or academic.
Objetivo do estudo: o presente texto visa apresentar um panorama sobre pesquisa quantitativa em empreendedorismo no Brasil, bem como descrever possibilidades para o avanço desta abordagem. Metodologia e abordagem: o artigo consiste em uma publicação conduzida a partir de levantamentos bibliográficos na literatura científica de empreendedorismo e discussões teóricas. Principais Resultados: maior parte das pesquisas nacionais em empreendedorismo são de natureza qualitativa. Apesar da relevância desta abordagem, acredita-se que a pesquisa quantitativa possui múltiplas potencialidades, sobretudo associada ao uso de dados oriundos de fontes secundárias. Principais Contribuições teóricas e metodológicas: apresentamos bases de dados públicas que podem ser empregadas por pesquisadores de empreendedorismo para avançar na teoria. Algumas estratégias de uso destas bases são exemplificadas por meio de um breve tutorial em linguagem R. Finalmente, debatemos acerca de estratégias para robustecer pesquisas quantitativas da área, bem como trazemos uma agenda de pesquisa. Relevância/Originalidade: são apresentados conteúdos que ainda são pouco explorados na literatura nacional, como o uso de dados secundários e machine learning. Contribuições sociais e gerenciais: algumas das bases apresentadas no estudo são de fonte governamental e podem ser utilizadas para fundamentar a construção de políticas públicas para o empreendedorismo. Ademais, os preceitos sobre pesquisa quantitativa apresentados neste editorial podem apoiar gestores que atuam com análises de dados na formulação de estudos mais robustos, independente da área de atuação, seja prático ou acadêmico.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.