Big data analytics in supply chain management : theory and applications / edited by Iman Rahimi, Amir H. Gandomi, Simon James Fong and M. Ali Ülkü.
Material type:
TextPublisher: Boca Raton : CRC Press, 2021Edition: First editionDescription: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780367816384; 0367816385; 9781000326918; 1000326918; 9781000326932; 1000326934; 9781000326925; 1000326926Subject(s): Business logistics | Big data | COMPUTERS / Database Management / Data Mining | TECHNOLOGY / Manufacturing | TECHNOLOGY / Operations ResearchDDC classification: 658.70285/57 LOC classification: HD38.5Online resources: Taylor & Francis | OCLC metadata license agreement Summary: "In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Business and Engineering students, scholars, and professionals, this book is a collection of the state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge on emerging supply chain problems"-- Provided by publisher.
"In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Business and Engineering students, scholars, and professionals, this book is a collection of the state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge on emerging supply chain problems"-- Provided by publisher.
OCLC-licensed vendor bibliographic record.