Big Data Analytics in Supply Chain Management: Theory and Applications
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- Editors -- Contributors -- Chapter 1 Big Data Analytics in Supply Chain Management: A Scientometric Analysis -- 1.1 Introduction -- 1.2 Analysis -- 1.2.1 Data Collection -- 1.3 Sci...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Milton
Taylor & Francis Group
2020
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| Schlagworte: | |
| Online-Zugang: | FHR01 https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6401873 |
| Zusammenfassung: | Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- Editors -- Contributors -- Chapter 1 Big Data Analytics in Supply Chain Management: A Scientometric Analysis -- 1.1 Introduction -- 1.2 Analysis -- 1.2.1 Data Collection -- 1.3 Scientometric Analysis -- 1.3.1 An Analysis on Keywords -- 1.3.2 A Short Analysis on Countries and Affiliations -- 1.3.3 Co-author Analysis -- 1.3.4 An Analysis on Sources -- 1.3.5 Co-citation Analysis -- 1.3 Discussion and Conclusion -- References -- Chapter 2 Supply Chain Analytics Technology for Big Data -- 2.1 Introduction -- 2.1.1 Introduction to Supply Chain Analytics Technology -- 2.1.2 Necessity for Supply Chain Analytics for Big Data -- 2.2 Features of Supply Chain Analytics -- 2.3 Opportunities and Applications for Supply Chain Analytics -- 2.3.1 Opportunities for Supply Chain Analytics -- 2.3.2 Process Specific applications of Big Data Analytics -- 2.4 Tools for Supply Chain Analytics -- 2.5 Supply Chain Analytics Methods -- 2.5.1 Descriptive Analytics -- 2.5.2 Predictive Analytics -- 2.5.3 Prescriptive Analytics -- 2.6 Supply Chain Challenges in Adopting Big Data Analytics -- 2.7 Future of Supply Chain Analytics -- 2.8 Conclusion -- References -- Chapter 3 Prioritizing the Barriers and Challenges of Big Data Analytics in Logistics and Supply Chain Management Using MCDM Method -- 3.1 Introduction to Big Data Analytics -- 3.2 Barriers to BDA: Background -- 3.3 Methodology -- 3.3.1 The Steps of HBWM -- 3.3.2 Determining the Consistency Rate -- 3.4 Results and Discussion -- 3.5 Conclusion -- References -- Chapter 4 Big Data in Procurement 4.0: Critical Success Factors and Solutions -- 4.1 Introduction -- 4.2 Macroenvironment -- 4.3 Literature Review -- 4.4 Methodology -- 4.5 Critical Success Factors for Procurement 4.0 -- 4.5.1 Cybernetics |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 online resource (211 pages) |
| ISBN: | 9781000326932 9780367816384 |
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| 520 | 3 | |a Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- Editors -- Contributors -- Chapter 1 Big Data Analytics in Supply Chain Management: A Scientometric Analysis -- 1.1 Introduction -- 1.2 Analysis -- 1.2.1 Data Collection -- 1.3 Scientometric Analysis -- 1.3.1 An Analysis on Keywords -- 1.3.2 A Short Analysis on Countries and Affiliations -- 1.3.3 Co-author Analysis -- 1.3.4 An Analysis on Sources -- 1.3.5 Co-citation Analysis -- 1.3 Discussion and Conclusion -- References -- Chapter 2 Supply Chain Analytics Technology for Big Data -- 2.1 Introduction -- 2.1.1 Introduction to Supply Chain Analytics Technology -- 2.1.2 Necessity for Supply Chain Analytics for Big Data -- 2.2 Features of Supply Chain Analytics -- 2.3 Opportunities and Applications for Supply Chain Analytics -- 2.3.1 Opportunities for Supply Chain Analytics -- 2.3.2 Process Specific applications of Big Data Analytics -- 2.4 Tools for Supply Chain Analytics -- 2.5 Supply Chain Analytics Methods -- 2.5.1 Descriptive Analytics -- 2.5.2 Predictive Analytics -- 2.5.3 Prescriptive Analytics -- 2.6 Supply Chain Challenges in Adopting Big Data Analytics -- 2.7 Future of Supply Chain Analytics -- 2.8 Conclusion -- References -- Chapter 3 Prioritizing the Barriers and Challenges of Big Data Analytics in Logistics and Supply Chain Management Using MCDM Method -- 3.1 Introduction to Big Data Analytics -- 3.2 Barriers to BDA: Background -- 3.3 Methodology -- 3.3.1 The Steps of HBWM -- 3.3.2 Determining the Consistency Rate -- 3.4 Results and Discussion -- 3.5 Conclusion -- References -- Chapter 4 Big Data in Procurement 4.0: Critical Success Factors and Solutions -- 4.1 Introduction -- 4.2 Macroenvironment -- 4.3 Literature Review -- 4.4 Methodology -- 4.5 Critical Success Factors for Procurement 4.0 -- 4.5.1 Cybernetics | |
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| id | DE-604.BV047217623 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:56:16Z |
| indexdate | 2024-07-10T09:05:56Z |
| institution | BVB |
| isbn | 9781000326932 9780367816384 |
| language | English |
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| spelling | Rahimi, Iman Verfasser aut Big Data Analytics in Supply Chain Management Theory and Applications Milton Taylor & Francis Group 2020 1 online resource (211 pages) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- Editors -- Contributors -- Chapter 1 Big Data Analytics in Supply Chain Management: A Scientometric Analysis -- 1.1 Introduction -- 1.2 Analysis -- 1.2.1 Data Collection -- 1.3 Scientometric Analysis -- 1.3.1 An Analysis on Keywords -- 1.3.2 A Short Analysis on Countries and Affiliations -- 1.3.3 Co-author Analysis -- 1.3.4 An Analysis on Sources -- 1.3.5 Co-citation Analysis -- 1.3 Discussion and Conclusion -- References -- Chapter 2 Supply Chain Analytics Technology for Big Data -- 2.1 Introduction -- 2.1.1 Introduction to Supply Chain Analytics Technology -- 2.1.2 Necessity for Supply Chain Analytics for Big Data -- 2.2 Features of Supply Chain Analytics -- 2.3 Opportunities and Applications for Supply Chain Analytics -- 2.3.1 Opportunities for Supply Chain Analytics -- 2.3.2 Process Specific applications of Big Data Analytics -- 2.4 Tools for Supply Chain Analytics -- 2.5 Supply Chain Analytics Methods -- 2.5.1 Descriptive Analytics -- 2.5.2 Predictive Analytics -- 2.5.3 Prescriptive Analytics -- 2.6 Supply Chain Challenges in Adopting Big Data Analytics -- 2.7 Future of Supply Chain Analytics -- 2.8 Conclusion -- References -- Chapter 3 Prioritizing the Barriers and Challenges of Big Data Analytics in Logistics and Supply Chain Management Using MCDM Method -- 3.1 Introduction to Big Data Analytics -- 3.2 Barriers to BDA: Background -- 3.3 Methodology -- 3.3.1 The Steps of HBWM -- 3.3.2 Determining the Consistency Rate -- 3.4 Results and Discussion -- 3.5 Conclusion -- References -- Chapter 4 Big Data in Procurement 4.0: Critical Success Factors and Solutions -- 4.1 Introduction -- 4.2 Macroenvironment -- 4.3 Literature Review -- 4.4 Methodology -- 4.5 Critical Success Factors for Procurement 4.0 -- 4.5.1 Cybernetics Electronic books Gandomi, Amir H. ctb Fong, Simon James ctb Ülkü, M. Ali ctb X:EBC https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6401873 Aggregator |
| spellingShingle | Rahimi, Iman Big Data Analytics in Supply Chain Management Theory and Applications |
| title | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_auth | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_exact_search | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_exact_search_txtP | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_full | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_fullStr | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_full_unstemmed | Big Data Analytics in Supply Chain Management Theory and Applications |
| title_short | Big Data Analytics in Supply Chain Management |
| title_sort | big data analytics in supply chain management theory and applications |
| title_sub | Theory and Applications |
| url | https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6401873 |
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