1.

Record Nr.

UNINA9910416135803321

Autore

Parvin Hosseini Seyed Mehrshad

Titolo

Big Data Approach to Firm Level Innovation in Manufacturing : Industrial Economics / / by Seyed Mehrshad Parvin Hosseini, Aydin Azizi

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020

ISBN

981-15-6300-4

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (78 pages) : illustrations

Collana

SpringerBriefs in Applied Sciences and Technology, , 2191-530X

Disciplina

810

Soggetti

Economic history

Industrial engineering

Production engineering

Business

Management science

Engineering design

Economy-wide Country Studies

Industrial and Production Engineering

Business and Management, general

Engineering Design

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Chapter 1: Introduction to innovation activities -- Chapter 2: The role of SME’s in innovation activities -- Chapter 3: Overview of innovation activities in Southeast Asia -- Chapter 4: From Linear model to Chain Linked model of innovation in reaching firm characteristics that facilitate and lowering the cost of innovation -- Chapter 5: Predicting level of innovation -- Chapter 6: Factors affecting the decision to innovate and related policies .

Sommario/riassunto

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.