Abstract
As plataformas de aplicativos fazem parte de ecossistemas de inovação, onde as interações entre usuários finais e desenvolvedores autorregulam o crescimento do próprio ecossistema. Uma das informações mais importantes para esse processo são as avaliações dos usuários. Com o intuito de analisar o impacto dessas informações, este artigo utiliza uma regressão por mínimos quadrados ordinários (MQO) para o ano de 2016, com base em 19 variáveis para 60 países. É mensurado o grau de exigência do mercado consumidor, utilizando um novo indicador baseado nas avaliações dos usuários finais para verificar a consistência de relações entre qualidade da demanda (mensurada pelo novo indicador) e o desempenho inovador de diferentes países nesse segmento. Os resultados evidenciam a robustez e as novas possibilidades de pesquisa que surgem, dadas as características positivas apresentadas pelo novo indicador construído através da utilização de ferramentas de big data e data analytics. Esse indicador mostra que a qualidade da demanda apoia inovações no segmento produtivo, o que levou à concussão de que obter feedback da demanda mais sofisticada representa um estímulo potencial poderoso ao avanço no desenvolvimento de aplicativos.
Highlights
In the last decade, the amount of data generated by economic agents has expanded considerably
Innovation ecosystems can be seen as new ways of organizing goods and services through the interaction of many companies with complementary skills, who collaborate and compete to offer more complex goods and services, which are subject to greater customization according to the feedbacks offered by consumers, made possible by digital tools (JACOBIDES; DREXLER; RICO, 2014)
This article used user assessments to propose an indicator of the level of consumer demand, so that deductions could be made about the potential of consumer feedback from different countries on the process of application innovation
Summary
The amount of data generated by economic agents has expanded considerably. The Quality Index of Demand Conditions is not data intensive, being elaborated based on specialists’ perception, presenting problems such as subjectivity and low variability, which makes the use of quantitative analysis tools difficult (PORTER et al , 2008; SALA-I-MARTIN et al , 2011, 2012, 2013; SCHWAB, 2013) The dissemination of this indicator, associated with its limitations, justifies the development of a more robust indicator, through the application of Data Science intensive tools in data declared by consumers themselves. A window of opportunity is opened so that the evaluations of the application market users can be used to build more quantitative indicators, capable of capturing with greater objectivity the characteristics of the consumer market of different countries Given this context, this article has two objectives.
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