Global entrepreneurship analytics: using GEM data

By:

Cusi, Milenka Linneth Argote

Material type: Text

TextPublication details: Routledge London 2021Description: 78 pISBN:

9780367542092

Subject(s):

Industrial management

DDC classification:

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 (EDQ), and a new methodology for the estimation of Specific Entrepreneurship Rates (SER) and the Global Entrepreneurship Rate (GER) is proposed. At the same time the authors present artificial intelligence techniques such as Fuzzy Time Series (FTS) 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 dataset 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 through the scientific method and through the methodology of construction of more accurate metrics in entrepreneurship, 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.

List(s) this item appears in: Public Policy & General Management | Fiction

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	338 CUS (Browse shelf(Opens below))	1	Available		004256

Table of Contents
1. Methodology for the Evaluation of Data Quality: The GEM Case 2. The Global Entrepreneurship Rate: A Methodological Proposal 3. Forecast Entrepreneurship Population with Fuzzy Time Series 4. A Case Study of the Application of Big Data in Entrepreneurship

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 (EDQ), and a new methodology for the estimation of Specific Entrepreneurship Rates (SER) and the Global Entrepreneurship Rate (GER) is proposed. At the same time the authors present artificial intelligence techniques such as Fuzzy Time Series (FTS) 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 dataset 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 through the scientific method and through the methodology of construction of more accurate metrics in entrepreneurship, 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.

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