Tese
Modelo de maturidade para o uso de Big Data Analytics em startups
Fecha
2023-02-15Autor
Romio, Alexsandra Matos
Institución
Resumen
With the advancement of internet use, the term startup became popular to designate
innovative companies in their initial prospecting phase. In addition, the internet gathers
a large amount of data which is constantly being generated from various sources,
becoming Big Data. In this context, the new era of the data economy enables new
disruptive business models based on the analysis of said data, which can be supported
by startups. Amidst this, startups can use maturity models as a tool for selfassessment, which makes it possible to verify their preparation in incorporating data
analysis into their business models. Given this scenario, this thesis sought to build a
maturity model to evaluate and guide startups in their journey of using Big Data
Analytics. In addition, the levels, dimensions, items and sub-items necessary for Big
Data Analytics usage in startups were identified, and a Delphi debate panel was
established on the elements necessary for Big Data Analytics usage in startups. This
model was consolidated through the arguments and evaluations of the panel of experts
and, then, the model behavior in the research field was analyzed via startups feedback
during the application of the real model. For this, DRS - Design Science Research -
was adopted as a research method. Thus, we used the nature of applied research
through the generation of practical and prescriptive knowledge through the
presentation of use feasibility. The research approach was qualitative and processoriented. Based on the DSR procedure, two literature reviews were performed. In a
second moment, a field study with startups and the analysis of the thematic axes of
EnAnpad outlined the class of problems. Thus, a maturity model was proposed through
abductive reasoning and was submitted to the survey through the Delphi method. The
outlined model evaluation took place during its practical application in startups of
excellence in Big Data Analytics usage and, for the necessary adjustments, notes from
the field were used and an interview with a specialist was carried out. A useful and
applicable maturity model was then obtained to support the solution of the problem
and, in addition to it, a calculation spreadsheet was built to automate the results. Also,
an analysis of the theoretical development on the field, on the instrument and on the
research object was presented. Furthermore, a non-linear and a helical maturity model
were proposed. Thus, this study brought advances to the academic field and
managerial contributions.