Global entrepreneurship analytics : using GEM data / Milenka Linneth Argote Cusi, León Darío Parra Bernal.
Material type:
TextSeries: Publisher: New York, NY : Routledge, 2021Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781000178586; 1000178587; 9780429316715; 0429316712; 9781000178623; 1000178625; 9781000178609; 1000178609Subject(s): Entrepreneurship -- Statistical methods | BUSINESS & ECONOMICS / Entrepreneurship | BUSINESS & ECONOMICS / Management | BUSINESS & ECONOMICS / Small BusinessDDC classification: 338 LOC classification: HB615 | .A746 2021ebOnline resources: Taylor & Francis | OCLC metadata license agreement Summary: "This innovative book proposes new methodologies for the measurement of entrepreneurship by applying techniques of demography, engineering, mathematics and statistics. Using the data from the Global Entrepreneurship Monitor (GEM), statistical demographic techniques are used for the evaluation of data quality and for the estimation of key indicators, a new methodology for the calculation of Specific Entrepreneurship Rates and Global Entrepreneurship Rate is proposed, at the same time the authors present artificial intelligence techniques such as Fuzzy Time Series to forecast data series of the entrepreneurial population. Finally, they present a case study of the implementation of Big Data in Entrepreneurship using GEM Data, that shows the latest technological trends for the management of data, in support of making more accurate decisions. Being a methodological book, the techniques presented can be applied to any data set in different areas. Readers will learn new methodologies of analysis and measurement of entrepreneurship using data from the Global Entrepreneurship Monitor. They will be able to access the experience of the authors through each of the applied cases in which the reader is taken by the hand both in the scientific method and in the methodology of construction of more accurate metrics in entrepreneurship or with less error. This book will be of value to students at an advanced level, academics, and researchers in the fields of Entrepreneurship, Business analytics and Research Methodology"-- Provided by publisher.
"This innovative book proposes new methodologies for the measurement of entrepreneurship by applying techniques of demography, engineering, mathematics and statistics. Using the data from the Global Entrepreneurship Monitor (GEM), statistical demographic techniques are used for the evaluation of data quality and for the estimation of key indicators, a new methodology for the calculation of Specific Entrepreneurship Rates and Global Entrepreneurship Rate is proposed, at the same time the authors present artificial intelligence techniques such as Fuzzy Time Series to forecast data series of the entrepreneurial population. Finally, they present a case study of the implementation of Big Data in Entrepreneurship using GEM Data, that shows the latest technological trends for the management of data, in support of making more accurate decisions. Being a methodological book, the techniques presented can be applied to any data set in different areas. Readers will learn new methodologies of analysis and measurement of entrepreneurship using data from the Global Entrepreneurship Monitor. They will be able to access the experience of the authors through each of the applied cases in which the reader is taken by the hand both in the scientific method and in the methodology of construction of more accurate metrics in entrepreneurship or with less error. This book will be of value to students at an advanced level, academics, and researchers in the fields of Entrepreneurship, Business analytics and Research Methodology"-- Provided by publisher.
OCLC-licensed vendor bibliographic record.