Objective: We have analyzed Brazil’s initial COVID-19 combat actions by the regional innovation ecosystem actors.Methodology/approach: This is a descriptive and qualitative study using documentary research. In total, 471 reports collected via web scraping were submitted to content analysis (using a codebook and intercoder test) and correspondence analysis.Originality/relevance: From an innovation ecosystem perspective, this study fulfills an identified need to understand how different actors have proposed initial solutions to the COVID-19 pandemic, considering different geographic regions.Main results: According to the seminal literature, in the more economically and socially favored regions, the government-industry dyadic model was corroborated, while in the less favored regions, the most innovative actors were universities and society. Our results have not shown the quintuple helix’s performance, which leads us to ponder the use of this model in crises. Furthermore, although the quadruple helix model was observed in our analyses, in the Brazilian geographic regions the helices were not designed in a transversal way.Theoretical contributions: We propose that the geography of a pandemic combat occurs unevenly by the innovation ecosystem actors. Moreover, the helices ordering refers to the theoretical development process and not to the complementarity of the role between actors.Practical implications: This article highlights the need for integrated management of the innovation ecosystem’s initial actions in a pandemic, preventing regions from being neglected, especially those with lower levels of wealth or quality of life.

PurposeThe paper describes patterns of study on innovation in the regional economic resilience literature regarding methods and findings.Design/methodology/approachThis study is a descriptive one and it uses, as a method, the scoping review based on Scopus and Web of Science databases. Forty-eight theoretical-empirical papers were thematically coded, and analyses were conducted using R packages and MaxQDA.FindingsInnovation has been used narrowly in the regional resilience literature, considering the variables, the types of shocks and the analyzed loci. From the sampled papers, this study suggests that, depending on the operationalization, the addressed relationship can be positive or negative, which still needs further investigation. In addition, the study identified two lines of research. The first, characterized by quantitative research, secondary sources and multivariate analyses, focuses on testing predictive regional resilience models based on innovation-related variables. The second, characterized by qualitative or multi-method approaches, is more concerned with explaining the knowledge accumulation and the learning capacity related to regional innovation.Research limitations/implicationsThe paper’s findings show a restricted view of the innovation–resilience relationship. Although this study does not present a meta-analysis, it reveals gaps for future research. Some suggestions can be highlighted, such as (1) expanding knowledge about innovation as a predictor of resilience, (2) the theoretical development of this relationship to guide empirical investigations and (3) studies that consider the meso or micro level, approaching the role of actors in fostering innovation in the regional resilience process.Originality/valueThis paper fulfills an identified need to investigate how innovation has been operationalized in regional resilience empirical research.

PurposeThis study aims to empirically investigate how an industrial region has reacted to different shocks – competitive, market and environmental – through its economic subsystems – its firms, workers and institutions – in a longitudinal perspective for the period 1985–2021.Design/methodology/approachThe authors used a mixed-method approach applied to a case study of the Brazilian T&C industrial region. The authors used two data sources and two stages for data collection. The first stage involved documentary research and the second in-depth interviews. The analysis of qualitative data took place in two stages. In the first, the authors applied content analysis, and in the second stage, the authors used the exploratory statistical technique of simple correspondence analysis and the categorical data.FindingsThe results provide evidence that different types of shock provoke different reactions. However, the shock–reaction relationship is invariable over time. The authors observed proportionality in the size of the shock and the regional actors involved in the regional response – firms, workers and institutions.Originality/valueThe authors went a step further, presenting empirical research on the shock–reaction relationship using the “type of shock” as a variable. This paper provides a holistic understanding of the factors behind regional resilience through insights into the role that resources, structures, institutions and actors play in the regional response to distinct types of shocks, reaching four main conclusions.

A competitividade trazida pelas empresas de aplicativos, tais como a Uber, para o mercado de transporte individual, é frequentemente enfatizada. No entanto, uma pergunta importante segue sem resposta: quais as estratégias implementadas pelas empresas de táxi, em termos de melhorias e inovações, para se manterem competitivas no mercado? O presente estudo buscou responder essa pergunta ao identificar como a uberização causa a ruptura na dependência de trajetória das empresas de táxis, segundo preceitos da Teoria da Dependência da Trajetória e de Estratégia Competitiva. Nesse sentido, a presente investigação é um estudo de caso que aborda o Distrito Federal, um dos pioneiros da uberização no Brasil. Para tanto, dados qualitativos secundários foram coletados via pesquisa documental em jornais locais de grande circulação. Aplicou-se a Análise de Conteúdo e a Análise Processual de Dados nas 178 reportagens coletadas, as quais englobaram o período de 2008 a 2017. Os resultados sugerem que, antes da entrada das empresas por aplicativos, as empresas de táxis implementavam inovações de sustentação voltadas para si mesmas. Após a uberização, os táxis passaram a adotar inovações disruptivas voltadas para os passageiros, rompendo a dependência de trajetória vigente até então.