Artificial Intelligence in Marketing
This book can be opened with
Note on our eBooks and Audiobooks: you can read our eBooks (ePUB or PDF) and listen to audiobooks on the free Emerald Books app on iOS, Android, and desktop. Or read and listen on Emerald's online reader (ePUB eBooks and audiobooks only). To purchase a digital book you will need to create an account if you don’t already have one. After purchasing you will receive instructions on how to get started.
- Description
- Contents
- About
Review of Marketing Research pushes the boundaries of marketing—broadening the marketing concept to make the world a better place.
Here, leading scholars explore how marketing is currently shaping, and being shaped by, the evolution of Artificial Intelligence (AI). Topics covered include the effects of AI on: economics; personalisation; pricing; content generation; the identification, structuring, and prioritization of customer needs; customer feedback; Natural Language Processing; image analytics; deep learning; and the anthropomorphism of AI, such as in virtual assistants and chatbots.
Each chapter provides thought provoking discussions which will be relevant to researchers, professionals, and students.
Introduction. The State of AI Research in Marketing: Active, Fertile, and Ready for Explosive Growth; K. Sudhir and Olivier Toubia
- Chapter 1. The Economics of Artificial Intelligence: A Marketing Perspective; MengQi (Annie) Ding and Avi Goldfarb
- Chapter 2. AI and Personalization; Omid Rafieian and Hema Yoganarasimhan
- Chapter 3. Artificial Intelligence and Pricing; Diego Aparicio and Kanishka Misra
- Chapter 4. Leveraging AI for Content Generation: A Customer Equity Perspective; David Schweidel, Martin Reisenbichler, Thomas Reutterer, and Kunpeng Zhang
- Chapter 5. Artificial Intelligence and User-Generated Data are Transforming how Firms Come to Understand Customer Needs; John R. Hauser, Zelin Li, and Chengfeng Mao
- Chapter 6. AI Applications to Customer Feedback Research: A Review; Peter S. Lee, Ishita Chakraborty, and Shrabastee Banerjee
- Chapter 7. Natural Language Processing in Marketing; Jochen Hartmann and Oded Netzer
- Chapter 8. Marketing through the Machine’s Eyes: Image Analytics and Interpretability; Shunyuan Zhang, Flora Feng, and Kannan Srinivasan
- Chapter 9. Deep Learning in Marketing: A Review and Research Agenda; Xiao Liu
- Chapter 10. Anthropomorphism in Artificial Intelligence: A Review of Empirical Work Across Domains and Insights for Future Research; Ertugrul Uysal, Sascha Alavi and Valéry Bezençon
Naresh K. Malhotra is Senior Fellow, Georgia Tech CIBER, and Regents’ Professor Emeritus, Scheller College of Business, Georgia Institute of Technology (Georgia Tech), USA.
K. Sudhir is James L. Frank ’32 Professor of Marketing at the Yale School of Management. His recent research uses AI methods such as NLP, video and music analytics to address questions on advertising, salesforce hiring, online reviews, bias and privacy.
Olivier Toubia is the Glaubinger Professor of Business at Columbia Business School. His research combines methods from social sciences and data science, in order to study human processes such as motivation, choice, and creativity.