AI-Based Data Analytics: Applications for Business Management

by Kiran Chaudhary (Editor), Mansaf Alam (Editor)

Overview

This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include:

• The role of Explainable AI in improving customer experiences in e-commerce
• Sentiment analysis of social media
• Data analytics in business intelligence
• Federated learning for business intelligence
• AI-based planning of business management
• An AI-based business model innovation in new technologies
• An analysis of social media marketing and online impulse buying behaviour

AI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.

Product Details

ISBN-13:	9781003812661
Publisher:	CRC Press
Publication date:	12/29/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	260
File size:	6 MB

About the Author

Dr. Kiran Chaudhary is an Assistant Professor in the Department of Commerce, Shivaji College, University of Delhi and has 12 years of teaching and research experience. She earned a Ph.D. in Marketing from Kurukshetra University, India. Her areas of research include marketing, human resource management, organizational behavior, and business and corporate law. A distinguished student winning various awards of recognition, she is a book author as well as conference and journal paper author.

Dr. Mansaf Alam is an Associate Professor in the Department of Computer Science, Faculty of Natural Sciences, Jamia Millia Islamia University, New Delhi, India. He has also been Young Faculty Research Fellow for the Ministry of Electronics and Information Technology in India and the Editor-in-Chief for Journal of Applied Information Science. A journal and conference paper author, he conducts research in such area as big data analytics, machine learning & deep learning, cloud computing, cloud database management systems, object- oriented database systems, information retrieval, and data mining. His other academic activities include journal reviewer, member of conference program committees, journal editorial board member, and book author.

Table of Contents

Preface. Acknowledgements. List of Abbreviations. About the Editors. List of Contributors. Chapter 1 Use of AI in E-Commerce. Chapter 2 Sentiment Analysis of Social Media with AI. Chapter 3 Unlocking the Power of Explainable AI to Improve Customer Experiences in E-Commerce. Chapter 4 Business Intelligence. Chapter 5 Sentiment Analysis of Social Media: Bibliometric Analysis. Chapter 6 Exploring Hugging Face Transformer Library Impact on Sentiment Analysis: A Case Study. Chapter 7 Data Analytics in Business Intelligence. Chapter 8 Federated Learning for Business Intelligence: Predictive Maintenance in Industry 4.0. Chapter 9 Role of IoT in Smart Cities: Proliferation and Challenges. Chapter 10 AI-Based Planning of Business Management. Chapter 11 AI-Based Business Model Innovation in New Technologies. Chapter 12 Cloud Computing: Storage Management, Security, and Privacy. Chapter 13 Social Media Marketing and Online Impulse Buying Behaviour: An Analysis through Website Quality as Moderator. Chapter 14 Effect of Blockchain Technology on the Future of E-Commerce in India. Chapter 15 Assessing the Usage of Various Data Mining Techniques for Analysis of Online Social Networks. Index.