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
- Wang, Li, Luo, Wang (2022), “Deep Reinforcement Learning for Sequential Targeting,” Management Science, Forthcoming
- Wang, Qin, Luo, Kou (2022), “How Support for Black Lives Matter Impacts Consumer Responses on Social Media,” Marketing Science, Forthcoming
- Zhang S, T. Chen, X. Luo, X. Wang (2022), “Time-inconsistent Preferences and Strategic Self-Control in Digital Content Consumption,” Marketing Science, Forthcoming.
- Sun C, Panos, A. Ghose, X. Luo (2022), “Predicting Stages in Omnichannel Path to Purchase: A Deep-Learning Model,” Information Systems Research, Forthcoming.
- Tong, Jia, Luo, Fang (2021), “The Janus Face of Artificial Intelligence Feedback: Deployment Versus Disclosure Effects on Employee Performance,” Strategic Management Journal, 42 (September), 1600-1631.
- Luo X, Qin S, Fang Z, Qu Z (2021), “Artificial Intelligence Coach for Sales Agents: Caveats and Solutions,” Journal of Marketing, 85 (March), 14-32.
- Luo X, Tong S, Lin Z, Zhang C (2021), “The Impact of Platform Protection Insurance on Buyers and Sellers in the Sharing Economy: A Natural Experiment,” Journal of Marketing, 85 (March), 50-69
- Li J, Luo X, Lu, X, Moriguchi T (2021), “The Double-Edged Effects of E-Commerce Cart Retargeting: Does Too Early Retargeting Backfire?” Journal of Marketing, 85 (July). 123-140.
- Luo, X, Zhang Y, Zeng F. Qu Z, (2020), “Complementarity and Cannibalization of Offline-to-Online Targeting: A Field Experiment on Omnichannel Commerce,” MIS Quarterly, 44 (June), 957-82.
- Luo, X, Tong S, Fang Z, Qu Z. (2019), “Frontiers: Machines versus Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases,” Marketing Science, 38 (November), 937–947.
- “Targeted Promotions on an E-Book Platform: Crowding Out, Heterogeneity, and Opportunity Costs,” (with Fong N, Zhang Y, Wang X), Journal of Marketing Research, 2019, 56 (April), 310-323. PPT presentation.
- “When and How to Leverage E-commerce Cart Targeting: The Relative and Moderated Effects of Scarcity and Price Incentives with a Two-Stage Field Experiment and Causal Forest Optimization,” (with X Lu and A Li), Information Systems Research, 2019, 30 (December), 1203-1227.
- “Personalized Mobile Targeting with User Engagement Stages: Combining a Structural Hidden Markov Model and Field Experiment,” (with Zhang Y, Li B, Wang X), Information Systems Research, 2019, 30 (September), 787–804. PPT presentation.
- Competitive Price Targeting with Smartphone Coupons (with JP Dube, Z Fang, N Fong), Marketing Science, 2017, 36(6), November, 944-975. PPT presentation
- Sunny, Rainy, Cloudy with a Chance of Mobile Promotion Effectiveness: 10-Million-User Field Study (with C Li, C Zhang, X Wang), Marketing Science, 2017 36 (5), September, 762–779. PPT presentation.
- Self-Signaling and Pro-Social Behavior: a cause marketing mobile field experiment (with JP Dube and Z Fang), Marketing Science, 2017, 36(2), 161–186. PPT presentation
- Zhang, C, D Phang, Q. Wu, X Luo (2017), “Nonlinear Role of Social Interactions for Individual Goal Pursuit and Spending,” Journal of Marketing, 81(Nov), 132-155.
- Luo, X, J. Zhang, Bin Gu, and Z. Phang (2017), “Expert Blogs and Consumer Perceptions of Competing Brands,” MIS Quarterly, 41(2), June, 371-395.
- Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness (with M Andrews, Z. Fang, and A Ghose), Marketing Science, 2016, 35(2), 218-233. PPT presentation
- Fang, Z, B Gu, X Luo, and Y. Xu (2015), “Contemporaneous and Delayed Sales Impact of Location-Based Mobile Promotions,” Information Systems Research, 26 (September), 552-564. PDF
- N Fong, Z Fang, and X Luo (2015), “Geo-Conquesting: Competitive Locational Mobile Promotions,” Journal of Marketing Research, 52 (October), 726-735.PDF, PPT presentation
- Luo, X, M. Andrews, Z. Fang, and Z. Phang (2014), “Mobile Targeting,” Management Science, 60 (7), July, 1738-56.PDF, PPT presentation
Nonlinear Role of Social Influence for Individual Goal Pursuit and Spending (with C Zhang, D Pang, Q Wu), Journal of Marketing, 2017, 81(November), 762-779.
- Expert Blogs and Consumer Perceptions of Competing Brands (with J Zhang, B Gu, and D Phang), 2017, MIS Quarterly, June, 41(2), 371-395.
- Luo, X, H. Wang, S. Raithel, and Q. Zheng (2015), “Corporate Social Responsibility, Analyst Stock Recommendations, and Firm Future Returns,” Strategic Management Journal, 36 (1), 123–136.PDF
- M Andrews, X Luo, Z.Fang, and J Aspara (2014), “Cause Marketing Effectiveness and the Moderating Role of Price Promotions” Journal of Marketing, 78 (6), November, 120-42.PDF, PPT presentation
- Luo, Xueming, Vamsi Kanuri, and Michelle Andrews (2014), “How Does CEO Tenure Matter? The Mediating Role of Firm-Employee and Firm-Customer Relations,” Strategic Management Journal, 35 (4), April, 492-511.PDF
- Luo, Xueming, M. Andrews, Y. Song, and J. Aspara (2014), “Group-Buying Deal Popularity,” Journal of Marketing, 78: 20-33.PDF
- Fang, Zheng, X Luo, and M. Keith (2014), “How Effective is Location-Targeted Mobile Advertising?” MIT Sloan Management Review, Forthcoming.
- Fang, Zheng, Xueming Luo,M. Andrews, and C. Phang (2014), “Mobile Discounts: A Matter of Distance and Time,” Harvard Business Review, May, 92(5), 30.
- Luo, Xueming, Michael Wiles, and Sascha Raithel (2013), “How Polarizing is Your Brand?” Harvard Business Review, November.
- Luo, Xueming, Sascha Raithel, and Michael Wiles (2013), “The Impact of Brand Dispersion on Firm Value,” Journal of Marketing Research, June, 399-415.PDF
- Luo, Xueming, Jennifer Zhang, and Wenjing Duan (2013), “Social Media and Firm Equity Value,” Information Systems Research, 24:146-163.PDF
- Luo, Xueming, V. Kanuri, and M. Andrews (2013), “Why Too Long CEO Tenure May Hurt Firm Performance?” Harvard Business Review, March.
- Luo, Xueming and Shuili Du (2012), “Good Companies Introduce More Innovations” Harvard Business Review, 90 (4), April, 28-28.
- Luo, Xueming, Christian Homburg, and Jan Wieseke (2010), “Customer Satisfaction, Analyst Stock Recommendations, and Firm Value,” Journal of Marketing Research, 47(6), 1041-1058.PDF
- Luo, Xueming (2009), “Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flow and Stock Price Volatility,” Marketing Science, 28(1), 148-65.PDF
- Luo, Xueming and CB Bhattacharya (2009), “Debate over Doing Good: Corporate Social Performance, Strategic Marketing Levers, and Firm-idiosyncratic Risk,” Journal of Marketing, 73(6), 198-213.PDF
- Luo, Xueming (2008), “When Marketing Strategy First Meets Wall Street: Marketing Spendings and Firms’ Initial Public Offerings (IPOs),” Journal of Marketing, 72(5), 98-109.PDF
- Luo, Xueming and Christian Homburg (2008), “Satisfaction, Complaint, and the Stock Value Gap,” Journal of Marketing, 72(4), 29-43.PDF
- Luo, Xueming (2007), “Consumer Negative Voice and Firm-Idiosyncratic Stock Returns,” Journal of Marketing, 71 (3), 75-88.PDF
- Luo, Xueming and Christian Homburg (2007), “Neglected Outcomes of Customer Satisfaction,” Journal of Marketing, 71 (2), 133-49.PDF
- Luo, Xueming, Aric Rindfleisch, and David Tse (2007), “Working with Rivals: The Impact of Competitor Alliances on Financial Returns to Competitor-Oriented Firms,” Journal of Marketing Research, 44(1), 73-83.PDF
- Wu, Weiping, Lianxi Zhou, and Xueming Luo (2007), “Internationalization and Performance of Born-Global SMEs: The Mediating Role of Guanxi Networks,” Journal of the International Business Studies, 38(4), 673-90.PDF
- Luo, Xueming and CB Bhattacharya (2006), “Corporate Social Responsibility, Customer Satisfaction, and Market Value,” Journal of Marketing, 70 (4), 1-18.PDF
- Luo, Xueming and Naveen Donthu (2006), “Marketing’s Credibility: A Longitudinal Study of Marketing Communication Productivity and Shareholder Value,” Journal of Marketing, 70 (4), 70-91.PDF
- Luo, Xueming, Rebecca Slotegraaf, and Xing Pan (2006), “Cross-Functional Coopetition: The Simultaneous Role of Cooperation and Competition within Firms,” Journal of Marketing,70 (2), 67-80.PDF
- Luo, Xueming (2004), “Data Envelopment Analysis: A Management Science Tool for Scientific Marketing Research,” Journal of Marketing Research, 42 (3), Book Review, 113-116.PDF
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.
- 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)
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