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Big Data Approach to Firm Level Innovation in Manufacturing: Industrial Economics 2020 Edition
Contributor(s): Parvin Hosseini, Seyed Mehrshad (Author), Azizi, Aydin (Author)
ISBN: 9811562997     ISBN-13: 9789811562990
Publisher: Springer
OUR PRICE:   $61.74  
Product Type: Paperback
Published: August 2020
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Additional Information
BISAC Categories:
- Technology & Engineering | Industrial Engineering
- Business & Economics | Production & Operations Management
- Business & Economics | Economics - Comparative
Physical Information: 0.1" H x 7.7" W x 9.2" (0.30 lbs) 72 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

This book discusses utilizing Big Data and Machine Learning approaches in investigating five aspects of firm level innovation in manufacturing; (1) factors that determine the decision to innovate (2) the extent of innovation (3) characteristics of an innovating firm (4) types of innovation undertaken and (5) the factors that drive and enable different types of innovation. A conceptual model and a cost-benefit framework were developed to explain a firm's decision to innovate. To empirically demonstrate these aspects, Big data and machine learning approaches were introduced in the form of a case study. The result of Big data analysis as an inferior method to analyse innovation data was also compared with the results of conventional statistical methods. The implications of the findings of the study for increasing the pace of innovation are also discussed.