Big Data Approach to Firm Level Innovation in Manufacturing: Industrial Economics
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
Springer Singapore Pte. Limited
2020
|
| Schriftenreihe: | SpringerBriefs in Applied Sciences and Technology Ser
|
| Schlagworte: | |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (78 pages) |
| ISBN: | 9789811563003 |
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| 505 | 8 | |a Intro -- Contents -- 1 An Introduction on Models of Innovation and Analytical Frame Work -- 1.1 Introduction -- 1.2 The Role of Eco-innovation -- 1.3 Indicators and Measurement of Innovation -- 1.4 Models of Innovation -- 1.4.1 The Linear Model of Innovation -- 1.4.2 The Chain Linked Model -- 1.5 Conclusion -- References -- 2 The Correlates of Firm-Level Innovation -- 2.1 Introduction -- 2.2 Conditions in Individual Subsectors -- 2.3 Export Orientation -- 2.4 Market Concentration -- 2.5 Firm Characteristics that Facilitate Innovation -- 2.5.1 Firm-Size -- 2.5.2 Age of Firm -- 2.5.3 Foreign Ownership -- 2.5.4 Organizational Characteristics -- 2.6 Factors Lowering Innovation Costs -- 2.6.1 Access to Technology -- 2.6.2 Skilled Workers -- 2.6.3 Industrial Clustering -- 2.6.4 Government Policies and Incentives -- 2.7 Conclusion -- References -- 3 Firm-Level Innovation: A Conceptual Model to Firm Level Innovation -- 3.1 Introduction -- 3.2 Driver of Innovation -- 3.3 Enablers of Innovation -- 3.4 An Analytical Framework: The Cost and Benefits of Firm-Level Innovation -- 3.5 The Decision to Innovate -- 3.6 Facilitators of Innovation -- 3.7 Costs of Innovation -- 3.8 Policy Environment -- 3.9 The Benefits of Innovation -- 3.10 Classifying the Types of Innovating Firms -- 3.11 Conclusion -- References -- 4 Machine Learning Approach to Identify Predictors in an Econometric Model of Innovation -- 4.1 Introduction -- 4.1.1 Regression Based Analysis -- 4.2 Probit Model -- 4.3 Ordered Probit Model -- 4.4 The Expected Signs for the Explanatory Variables -- 4.5 How Machine Learning Techniques Can Identify Predictor of Innovation -- 4.5.1 Classification and Regression Trees -- 4.5.2 Lasso Regression -- 4.6 Conclusion -- References -- 5 Big Data and Innovation -- A Case Study on Firm Level Innovation in Manufacturing -- 5.1 Introduction | |
| 505 | 8 | |a 5.2 New Measures of Firm Level Innovation Activities -- 5.3 Factors Affecting the Decision to Innovate in Malaysian Context -- 5.4 Extent of Firm Level Innovation -- 5.5 Characteristics of Innovating and Non-innovating Firms -- 5.5.1 Innovation by Firm Size -- 5.5.2 Innovation by Ownership -- 5.5.3 Innovation by Age of Establishment -- 5.5.4 Innovation by Subsector -- 5.5.5 Mode of Access to Technology -- 5.5.6 Innovation by Other Key Variables -- 5.6 Factors Motivating Innovation -- 5.7 Pooled Sample -- 5.8 SMEs and Large Firms -- 5.9 Summary and Discussion -- References | |
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| contents | Intro -- Contents -- 1 An Introduction on Models of Innovation and Analytical Frame Work -- 1.1 Introduction -- 1.2 The Role of Eco-innovation -- 1.3 Indicators and Measurement of Innovation -- 1.4 Models of Innovation -- 1.4.1 The Linear Model of Innovation -- 1.4.2 The Chain Linked Model -- 1.5 Conclusion -- References -- 2 The Correlates of Firm-Level Innovation -- 2.1 Introduction -- 2.2 Conditions in Individual Subsectors -- 2.3 Export Orientation -- 2.4 Market Concentration -- 2.5 Firm Characteristics that Facilitate Innovation -- 2.5.1 Firm-Size -- 2.5.2 Age of Firm -- 2.5.3 Foreign Ownership -- 2.5.4 Organizational Characteristics -- 2.6 Factors Lowering Innovation Costs -- 2.6.1 Access to Technology -- 2.6.2 Skilled Workers -- 2.6.3 Industrial Clustering -- 2.6.4 Government Policies and Incentives -- 2.7 Conclusion -- References -- 3 Firm-Level Innovation: A Conceptual Model to Firm Level Innovation -- 3.1 Introduction -- 3.2 Driver of Innovation -- 3.3 Enablers of Innovation -- 3.4 An Analytical Framework: The Cost and Benefits of Firm-Level Innovation -- 3.5 The Decision to Innovate -- 3.6 Facilitators of Innovation -- 3.7 Costs of Innovation -- 3.8 Policy Environment -- 3.9 The Benefits of Innovation -- 3.10 Classifying the Types of Innovating Firms -- 3.11 Conclusion -- References -- 4 Machine Learning Approach to Identify Predictors in an Econometric Model of Innovation -- 4.1 Introduction -- 4.1.1 Regression Based Analysis -- 4.2 Probit Model -- 4.3 Ordered Probit Model -- 4.4 The Expected Signs for the Explanatory Variables -- 4.5 How Machine Learning Techniques Can Identify Predictor of Innovation -- 4.5.1 Classification and Regression Trees -- 4.5.2 Lasso Regression -- 4.6 Conclusion -- References -- 5 Big Data and Innovation -- A Case Study on Firm Level Innovation in Manufacturing -- 5.1 Introduction 5.2 New Measures of Firm Level Innovation Activities -- 5.3 Factors Affecting the Decision to Innovate in Malaysian Context -- 5.4 Extent of Firm Level Innovation -- 5.5 Characteristics of Innovating and Non-innovating Firms -- 5.5.1 Innovation by Firm Size -- 5.5.2 Innovation by Ownership -- 5.5.3 Innovation by Age of Establishment -- 5.5.4 Innovation by Subsector -- 5.5.5 Mode of Access to Technology -- 5.5.6 Innovation by Other Key Variables -- 5.6 Factors Motivating Innovation -- 5.7 Pooled Sample -- 5.8 SMEs and Large Firms -- 5.9 Summary and Discussion -- References |
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| spelling | Parvin Hosseini, Seyed Mehrshad Verfasser aut Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics Singapore Springer Singapore Pte. Limited 2020 ©2020 1 Online-Ressource (78 pages) txt rdacontent c rdamedia cr rdacarrier SpringerBriefs in Applied Sciences and Technology Ser Description based on publisher supplied metadata and other sources Intro -- Contents -- 1 An Introduction on Models of Innovation and Analytical Frame Work -- 1.1 Introduction -- 1.2 The Role of Eco-innovation -- 1.3 Indicators and Measurement of Innovation -- 1.4 Models of Innovation -- 1.4.1 The Linear Model of Innovation -- 1.4.2 The Chain Linked Model -- 1.5 Conclusion -- References -- 2 The Correlates of Firm-Level Innovation -- 2.1 Introduction -- 2.2 Conditions in Individual Subsectors -- 2.3 Export Orientation -- 2.4 Market Concentration -- 2.5 Firm Characteristics that Facilitate Innovation -- 2.5.1 Firm-Size -- 2.5.2 Age of Firm -- 2.5.3 Foreign Ownership -- 2.5.4 Organizational Characteristics -- 2.6 Factors Lowering Innovation Costs -- 2.6.1 Access to Technology -- 2.6.2 Skilled Workers -- 2.6.3 Industrial Clustering -- 2.6.4 Government Policies and Incentives -- 2.7 Conclusion -- References -- 3 Firm-Level Innovation: A Conceptual Model to Firm Level Innovation -- 3.1 Introduction -- 3.2 Driver of Innovation -- 3.3 Enablers of Innovation -- 3.4 An Analytical Framework: The Cost and Benefits of Firm-Level Innovation -- 3.5 The Decision to Innovate -- 3.6 Facilitators of Innovation -- 3.7 Costs of Innovation -- 3.8 Policy Environment -- 3.9 The Benefits of Innovation -- 3.10 Classifying the Types of Innovating Firms -- 3.11 Conclusion -- References -- 4 Machine Learning Approach to Identify Predictors in an Econometric Model of Innovation -- 4.1 Introduction -- 4.1.1 Regression Based Analysis -- 4.2 Probit Model -- 4.3 Ordered Probit Model -- 4.4 The Expected Signs for the Explanatory Variables -- 4.5 How Machine Learning Techniques Can Identify Predictor of Innovation -- 4.5.1 Classification and Regression Trees -- 4.5.2 Lasso Regression -- 4.6 Conclusion -- References -- 5 Big Data and Innovation -- A Case Study on Firm Level Innovation in Manufacturing -- 5.1 Introduction 5.2 New Measures of Firm Level Innovation Activities -- 5.3 Factors Affecting the Decision to Innovate in Malaysian Context -- 5.4 Extent of Firm Level Innovation -- 5.5 Characteristics of Innovating and Non-innovating Firms -- 5.5.1 Innovation by Firm Size -- 5.5.2 Innovation by Ownership -- 5.5.3 Innovation by Age of Establishment -- 5.5.4 Innovation by Subsector -- 5.5.5 Mode of Access to Technology -- 5.5.6 Innovation by Other Key Variables -- 5.6 Factors Motivating Innovation -- 5.7 Pooled Sample -- 5.8 SMEs and Large Firms -- 5.9 Summary and Discussion -- References Manufacturing processes-Technological innovations Azizi, Aydin Sonstige oth Erscheint auch als Druck-Ausgabe Parvin Hosseini, Seyed Mehrshad Big Data Approach to Firm Level Innovation in Manufacturing Singapore : Springer Singapore Pte. Limited,c2020 9789811562990 |
| spellingShingle | Parvin Hosseini, Seyed Mehrshad Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics Intro -- Contents -- 1 An Introduction on Models of Innovation and Analytical Frame Work -- 1.1 Introduction -- 1.2 The Role of Eco-innovation -- 1.3 Indicators and Measurement of Innovation -- 1.4 Models of Innovation -- 1.4.1 The Linear Model of Innovation -- 1.4.2 The Chain Linked Model -- 1.5 Conclusion -- References -- 2 The Correlates of Firm-Level Innovation -- 2.1 Introduction -- 2.2 Conditions in Individual Subsectors -- 2.3 Export Orientation -- 2.4 Market Concentration -- 2.5 Firm Characteristics that Facilitate Innovation -- 2.5.1 Firm-Size -- 2.5.2 Age of Firm -- 2.5.3 Foreign Ownership -- 2.5.4 Organizational Characteristics -- 2.6 Factors Lowering Innovation Costs -- 2.6.1 Access to Technology -- 2.6.2 Skilled Workers -- 2.6.3 Industrial Clustering -- 2.6.4 Government Policies and Incentives -- 2.7 Conclusion -- References -- 3 Firm-Level Innovation: A Conceptual Model to Firm Level Innovation -- 3.1 Introduction -- 3.2 Driver of Innovation -- 3.3 Enablers of Innovation -- 3.4 An Analytical Framework: The Cost and Benefits of Firm-Level Innovation -- 3.5 The Decision to Innovate -- 3.6 Facilitators of Innovation -- 3.7 Costs of Innovation -- 3.8 Policy Environment -- 3.9 The Benefits of Innovation -- 3.10 Classifying the Types of Innovating Firms -- 3.11 Conclusion -- References -- 4 Machine Learning Approach to Identify Predictors in an Econometric Model of Innovation -- 4.1 Introduction -- 4.1.1 Regression Based Analysis -- 4.2 Probit Model -- 4.3 Ordered Probit Model -- 4.4 The Expected Signs for the Explanatory Variables -- 4.5 How Machine Learning Techniques Can Identify Predictor of Innovation -- 4.5.1 Classification and Regression Trees -- 4.5.2 Lasso Regression -- 4.6 Conclusion -- References -- 5 Big Data and Innovation -- A Case Study on Firm Level Innovation in Manufacturing -- 5.1 Introduction 5.2 New Measures of Firm Level Innovation Activities -- 5.3 Factors Affecting the Decision to Innovate in Malaysian Context -- 5.4 Extent of Firm Level Innovation -- 5.5 Characteristics of Innovating and Non-innovating Firms -- 5.5.1 Innovation by Firm Size -- 5.5.2 Innovation by Ownership -- 5.5.3 Innovation by Age of Establishment -- 5.5.4 Innovation by Subsector -- 5.5.5 Mode of Access to Technology -- 5.5.6 Innovation by Other Key Variables -- 5.6 Factors Motivating Innovation -- 5.7 Pooled Sample -- 5.8 SMEs and Large Firms -- 5.9 Summary and Discussion -- References Manufacturing processes-Technological innovations |
| title | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_auth | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_exact_search | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_exact_search_txtP | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_full | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_fullStr | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_full_unstemmed | Big Data Approach to Firm Level Innovation in Manufacturing Industrial Economics |
| title_short | Big Data Approach to Firm Level Innovation in Manufacturing |
| title_sort | big data approach to firm level innovation in manufacturing industrial economics |
| title_sub | Industrial Economics |
| topic | Manufacturing processes-Technological innovations |
| topic_facet | Manufacturing processes-Technological innovations |
| work_keys_str_mv | AT parvinhosseiniseyedmehrshad bigdataapproachtofirmlevelinnovationinmanufacturingindustrialeconomics AT aziziaydin bigdataapproachtofirmlevelinnovationinmanufacturingindustrialeconomics |