Applied Artificial Intelligence in Business: Concepts and Cases

by Leong Chan, Liliya Hogaboam, Renzhi Cao

Overview

This book offers students an introduction to the concepts of big data and artificial intelligence (AI) and their applications in the business world. It answers questions such as what are the main concepts of artificial intelligence and big data? What applications for artificial intelligence and big data analytics are used in the business field? It offers application-oriented overviews and cases from different sectors and fields to help readers discover and gain useful insights. Each chapter features discussion questions and summaries. To assist professors in teaching, the book supplementary materials will include answers to questions, and presentation slides.

Product Details

ISBN-13:	9783031057427
Publisher:	Springer International Publishing
Publication date:	07/21/2023
Series:	Applied Innovation and Technology Management
Edition description:	1st ed. 2022
Pages:	368
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

Leong Chan is an Assistant Professor in the School of Business at Pacific Lutheran University (Washington, USA). His research focuses on the application of emerging technologies in various business sectors. He is an Associate Editor of the Engineering Management Journal and serves as editorial board member for several journals and conferences.

Liliya Hogaboam is an author, consultant and a lecturer in the fields of economics and management, healthcare assessment, decision-making and AI. She has over 20 years of experience in analytics and research. She also has 10 years of entrepreneurial experience running a software services consulting company Nascentia Corp (Oregon, USA). Liliya has a number of publications in peer-reviewed journals. She co-authored the book Healthcare Technology Innovation Adoption (Springer, 2016).

Renzhi Cao is an Assistant Professor at Pacific Lutheran University (Washington, USA). His research interest is mainly focused on developing and applying machine learning and data mining techniques to solve biomedical problems. In addition, he is interested in promoting early engagement of undergraduate students (especially for women and underrepresented students) in machine learning, and the data science field by interdisciplinary studies, and inspiring students to pursue advanced STEM education/research careers.

Table of Contents

1. Artificial Intelligence for Business.- 2. Big Data Powering Business Intelligence.- 3. Artificial Intelligence Technologies for Business Applications.- 4. Machine Learning for Business Applications.- 5. Artificial Intelligence in Marketing and Sales.- 6. Artificial intelligence for Customer Services.- 7. Artificial intelligence in Finance.- 8. Artificial intelligence in Accounting and Auditing.- 9. Artificial intelligence in Human Resources.- 10. Artificial intelligence in Supply Chain and Logistics.- 11. Artificial intelligence in Manufacturing.- 12. Artificial Intelligence in Insurance.- 13. Artificial Intelligence in Credit, Lending, and Mortgage.- 14. Artificial Intelligence in Tourism and Hospitality.- 15. Artificial Intelligence in Transportation.- 16. Artificial Intelligence in Real Estate.- 17. Artificial Intelligence in Education.- 18. Artificial Intelligence in Healthcare.- 19. Artificial Intelligence in Energy.- 20. Artificial Intelligence in Media Services.- 21. Artificial Intelligence in Fashion.- 22. Artificial Intelligence in Gaming and eSports.- 23. Artificial Intelligence in Sports.