Xueming Luo
Marketing
Charles Gilliland Distinguished Chair Professor
  • Office LocationAlter Hall 511
  • SSRN Profile View
  • Curriculum Vitae View
  • Website Visit
  • Titles & RolesFounder/Director of Global Institute for Artificial Intelligence and Business Analytics

Biography

Xueming Luo is Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategic Management, Professor of Management Information Systems. He is the Founder/Director of the Global Institute for Artificial Intelligence and Business Analytics in the Fox School of Business at Temple University. He is interested in digital mobile marketing, omnichannel customer analytics, and social responsibility with machine learning, artificial intelligence, engineering models, and big data field experiments. His current research focuses on sharing economy platform algorithms, unstructual audio/image/video data, and smart city analytics for personalized recommendations, promotions, competitive pricing, omnichannel, social media networks advertising, and customer equity metrics. His work has been featured by most top ranking journals in Marketing, Strategy, Information Systems, and Management, as well as popular trade press such as the Wall Street Journal, ScienceDaily, Forbes, Financial Times, Harvard Business Review, MIT Sloan Management Review, and others.

Selected Research Publications

The Global Institute for Artificial Intelligence and Business Analytics (AIBA)

Mission and Objectives

The mission of this Global Institute for Artificial Intelligence and Business Analytics (AIBA), formally known as Global Center for Big Data in Mobile Analytics, is to become an inter-disciplinary leader in artificial intelligence and machine learning applications for research and education in Marketing, IS, Finance, Accounting, Strategy, Management, and other business disciplines. Internally, AIBA will empower faculty and doctoral students with a library of cutting-edge AI/ML models and algorithms via hands-on coding exercises, real-world business problems, and top journal publication for higher research productivity and contributions to their respective disciplines. Externally, AIBA will collaborate with academic scholars and industry practitioners world-wide to leverage unstructured text/audio/image/video data and explore AI, 5G, AR, VR, IoT, blockchain applications in social media, banking, health care, education, digital commerce, sharing economy platforms, and other domains to benefit consumers, companies, and society.

AIBA Conferences

  • November 2013, ‘Big Data Mobile Analytics Symposium’ at Temple University, Philadelphia
  • July 2014, ‘Big + Small Data Marketing Analytics Conference’ at Fudan University, Shanghai, China
  • October 2014, ‘Big Data Marketing Analytics Conference’ at University of Chicago, ChicagoBooth School, Chicago
  • March 2015, ‘Mobile Big Data Marketing Analytic Conference’ at LMU Munich, Germany
  • October 2015, ‘Smart Life Big Data Marketing Analytic Conference’ at New York University, Stern School of Business, New York
  • June 2016, ‘Mobile Big Data Conference’ at Chinese University of Hong Kong Business School, Hong Kong, China
  • December 2016, ‘Digital Marketing Conference’ at Stanford University, Stanford Business School, Stanford
  • December 2017, ‘Digital, Mobile Marketing, Social Media Analytics Conference’ at New York University, Stern School of Business, New York
  • December 2018, ‘Digital Marketing and Machine Learning Conference’ at Carnegie Mellon University, Tepper School of Business
  • December 2019, Co-hosted ‘Artificial Intelligence, Machine Learning, and Business Analytics Conference’ at Temple University Fox School of Business (co-chaired with NYU Stern and CMU Heinz)
  • December 2020, Co-hosted Virtual Conference on ‘Artificial Intelligence, Machine Learning, and Business Analytics (co-chaired with NYU Stern and CMU Heinz)

Quantitative Research in Marketing: PhD Class (MKTG9003)

Special Topics in Quant Marketing Models II: PhD Class (MKTG9090:002)

Advanced Topics of AI and Machine Learning for Business Decisions: PhD Class (MKTG 9006)

International Marketing: Undergraduate Class (MARK 4325)

International Marketing: MBA Class (MARK 5331)


Research Interests

large-scale field experiment mobile marketing, customer analytics with machine learning and big data, deep learning for personalized promotions, competitive pricing, omnichannel targeting, social media networking ads, artificial intelligence and recommendation algorithms

Knowledge Hub