| Machine learning and AI in marketing–Connecting computing power to human insights L Ma, B Sun International Journal of Research in Marketing 37 (3), 481-504, 2020 | 498 | 2020 |
| The squeaky wheel gets the grease—An empirical analysis of customer voice and firm intervention on Twitter L Ma, B Sun, S Kekre Marketing Science 34 (5), 627-645, 2015 | 292 | 2015 |
| Consumer click behavior at a search engine: The role of keyword popularity K Jerath, L Ma, YH Park Journal of Marketing Research 51 (4), 480-486, 2014 | 248 | 2014 |
| Crumbs of the cookie: User profiling in customer-base analysis and behavioral targeting M Trusov, L Ma, Z Jamal Marketing Science 35 (3), 405-426, 2016 | 204 | 2016 |
| A “position paradox” in sponsored search auctions K Jerath, L Ma, YH Park, K Srinivasan Marketing Science 30 (4), 612-627, 2011 | 195 | 2011 |
| Latent homophily or social influence? An empirical analysis of purchase within a social network L Ma, R Krishnan, AL Montgomery Management Science 61 (2), 454-473, 2015 | 188 | 2015 |
| Selling the premium in freemium X Gu, PK Kannan, L Ma Journal of Marketing 82 (6), 10-27, 2018 | 135 | 2018 |
| Platforms: a multiplicity of research opportunities S Sriram, P Manchanda, ME Bravo, J Chu, L Ma, M Song, S Shriver, ... Marketing Letters 26, 141-152, 2015 | 116 | 2015 |
| An empirical analysis of the impact of pre-release movie piracy on box office revenue L Ma, AL Montgomery, PV Singh, MD Smith Information Systems Research 25 (3), 590-603, 2014 | 109 | 2014 |
| Recomended for you: The impact of profit incentives on the relevance of online recommendations K Hosanagar, R Krishnan, L Ma ICIS 2008 Proceedings, 31, 2008 | 44 | 2008 |
| The dual impact of movie piracy on box-office revenue: Cannibalization and promotion L Ma, A Montgomery, MD Smith Available at SSRN 2736946, 2016 | 34 | 2016 |
| Charting the path to purchase using topic models H Li, L Ma Journal of Marketing Research 57 (6), 1019-1036, 2020 | 30 | 2020 |
| Homophily or influence? An empirical analysis of purchase within a social network L Ma, R Krishnan, A Montgomery Working paper, Heinz School, Carnegie Mellon University, Pittsburgh, 2010 | 24 | 2010 |
| How companies can get the most out of a freemium business model X Gu, PK Kannan, L Ma Harvard Business Review, Brighton, MA, USA, 2019 | 10 | 2019 |
| Only the interested learn: A model of proactive learning of product reviews L Ma Working paper, 2016 | 8 | 2016 |
| A dynamic competitive analysis of content production and link formation of Internet content developers L Ma, B Sun, K Srinivasan Working Paper, Carnegie Mellon University, 2010 | 8 | 2010 |
| Improving broader sharing to address geographic inequity in liver transplantation S Akshat, L Ma, S Raghavan Manufacturing and Service Operations Management, forthcoming, 2021 | 6 | 2021 |
| How does competition affect exploration vs. exploitation? A tale of two recommendation algorithms HH Cao, L Ma, ZE Ning, B Sun Management Science, forthcoming, 2022 | 5 | 2022 |
| Image network and interest group– A heterogeneous network embedding approach to analyze social curation on Pinterest L Ma, B Sun, K Zhang working paper, 2019 | 5 | 2019 |
| Building the b [r] and: Understanding how social media drives consumer engagement and sales YV Joshi, L Ma, WM Rand, L Raschid Marketing Science Institute, Working Paper Series, Report, 2013 | 5 | 2013 |
Baohong SunCheung Kong Graduate School of Business在 andrew.cmu.edu 的电子邮件经过验证
