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Sustainable development through data...
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Sustainable Development Goals.
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Sustainable development through data analytics and innovation = techniques, processes, models, tools, and practices /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Sustainable development through data analytics and innovation/ edited by Jorge Marx Gomez, Lawal O. Yesufu.
其他題名:
techniques, processes, models, tools, and practices /
其他作者:
Gomez, Jorge Marx.
出版者:
Cham :Springer International Publishing : : 2022.,
面頁冊數:
x, 189 p. :ill., digital ;24 cm.
內容註:
Chapter 1. The Impact of Business Analytics on Industry, Education and Professional Development -- Chapter 2. Green Purchasing Behavior on Social Media: A Goal-framing Theory Perspective -- Chapter 3. Business Analytics and Sustainability -- Chapter 4. Data Science and External Audit -- Chapter 5. Digitalization in Passengers' Air Travel -- Chapter 6. Application of Blockchain Innovative Technology in Logistics and Supply Chain Management: A New Paradigm for Future Logistics -- Chapter 7. Industry 4.0: Drivers and Challenges in Developing the Smart Supply Chain Management -- Chapter 8. Reimaging Corporate Reporting in a Digital Economy Through Accounting Data Analytics -- Chapter 9. Responding to Covid-19 Emergency: The Packaging Machinery Sector in Italy -- Chapter 10. Achieving Sustainable Development Through Green HRM: The Role of HR Analytics -- Chapter 11. Understanding Malaysian B40 Schoolchildren's Lifestyle and Educational Patterns Using Data Analytics.
Contained By:
Springer Nature eBook
標題:
Sustainable development - Technological innovations. -
電子資源:
https://doi.org/10.1007/978-3-031-12527-0
ISBN:
9783031125270
Sustainable development through data analytics and innovation = techniques, processes, models, tools, and practices /
Sustainable development through data analytics and innovation
techniques, processes, models, tools, and practices /[electronic resource] :edited by Jorge Marx Gomez, Lawal O. Yesufu. - Cham :Springer International Publishing :2022. - x, 189 p. :ill., digital ;24 cm. - Progress in IS,2196-8713. - Progress in IS..
Chapter 1. The Impact of Business Analytics on Industry, Education and Professional Development -- Chapter 2. Green Purchasing Behavior on Social Media: A Goal-framing Theory Perspective -- Chapter 3. Business Analytics and Sustainability -- Chapter 4. Data Science and External Audit -- Chapter 5. Digitalization in Passengers' Air Travel -- Chapter 6. Application of Blockchain Innovative Technology in Logistics and Supply Chain Management: A New Paradigm for Future Logistics -- Chapter 7. Industry 4.0: Drivers and Challenges in Developing the Smart Supply Chain Management -- Chapter 8. Reimaging Corporate Reporting in a Digital Economy Through Accounting Data Analytics -- Chapter 9. Responding to Covid-19 Emergency: The Packaging Machinery Sector in Italy -- Chapter 10. Achieving Sustainable Development Through Green HRM: The Role of HR Analytics -- Chapter 11. Understanding Malaysian B40 Schoolchildren's Lifestyle and Educational Patterns Using Data Analytics.
Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs) The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.
ISBN: 9783031125270
Standard No.: 10.1007/978-3-031-12527-0doiSubjects--Corporate Names:
3377897
Sustainable Development Goals.
Subjects--Topical Terms:
1085805
Sustainable development
--Technological innovations.
LC Class. No.: HC79.E5 / S87 2022
Dewey Class. No.: 338.927
Sustainable development through data analytics and innovation = techniques, processes, models, tools, and practices /
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Chapter 1. The Impact of Business Analytics on Industry, Education and Professional Development -- Chapter 2. Green Purchasing Behavior on Social Media: A Goal-framing Theory Perspective -- Chapter 3. Business Analytics and Sustainability -- Chapter 4. Data Science and External Audit -- Chapter 5. Digitalization in Passengers' Air Travel -- Chapter 6. Application of Blockchain Innovative Technology in Logistics and Supply Chain Management: A New Paradigm for Future Logistics -- Chapter 7. Industry 4.0: Drivers and Challenges in Developing the Smart Supply Chain Management -- Chapter 8. Reimaging Corporate Reporting in a Digital Economy Through Accounting Data Analytics -- Chapter 9. Responding to Covid-19 Emergency: The Packaging Machinery Sector in Italy -- Chapter 10. Achieving Sustainable Development Through Green HRM: The Role of HR Analytics -- Chapter 11. Understanding Malaysian B40 Schoolchildren's Lifestyle and Educational Patterns Using Data Analytics.
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Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs) The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.
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