Dokyun (DK) Lee

Kelli Questrom Associate Professor in Information Systems

Dokyun ”DK” Lee, is a Kelli Questrom Chair Associate Professor of Information Systems and Computing & Data Science School at Boston University. He studies the {responsible application, development, and impact} of AI in business with a focus on unstructured data. He founded Business Insights through Text Lab (www.dkBITLAB.com) (PI) and BU Digital Business Institute Generative AI Lab (Co-lead).
Specific interests are:
1) Generative AI (unintended consequence and human-integration frictions)
2) Economics of unstructured data (content extraction, understanding, engineering, marketing)
3) Unintended Consequence of AI in Business
in the context of digital consumer management, platform design, market competition, advertising, human-ai collaboration, innovation, and creativity.

He is a recipient of INFORMS ISS Gordon B David Young Scholar, INFORMS ISS Sandy Slaughter Early Career, CDO Magazine Leading Academic Data Leader, and Marketing Science Insititute Young Scholar Awards. His research has been published in journals such as Management Science, Information Systems Research, MISQ, Journal of Marketing Research, AAAI, AIES, and WWW. His work is supported by organizations such as Adobe, Bosch Institute, Google, Marketing Science Institute, McKinsey & Co, Nvidia, Net Institute, and Prudential Foundation.

DK holds a Bachelor’s degree in Computer Science from Columbia University (Machine Learning Focus), a Master’s degree in Statistics (Master’s Thesis: Johnson-Lindenstrauss Lemma and its Effect on Supervised Learning) from Yale University, and a Ph.D. from the Operation, Information, and Decisions department of the Wharton School (Thesis: Three Essays in Big Data Consumer Analytics in E-Commerce).
Before academia, DK worked at 4 tech start-ups and Blackrock as a quantitative software engineer and at Thomson Reuters as an ML contractor building a natural language processing engine for financial data.

Please contact for Academic-Industry research collaboration, consulting, and speaking inquiries.

    Education
  • Phd, The Wharton School, 2015
  • MA, Yale University, 2010
  • BA, Columbia University, 2009
    Publications
  • Lee, D., Anandasivam, G., Lee, D., Dongwook, S. (In Press). "Nudging Private Ryan: Mobile Micro-giving under Economic Incentives and Audience Effects", MIS Quarterly
  • Manzoor, E., Chen, G., Lee, D., Smith, M. (In Press). "Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online", Management Science
  • Zhang, S., Lee, D., Singh, P., Srinivasan, K. (In Press). "How Much Is an Image Worth? Airbnb Property Demand Estimation Leveraging Large Scale Image Analytics", SSRN Electronic Journal
  • Hsu, P., Lee, D., Tambe, P., Hsu, D. (In Press). "Deep Learning, Text, and Patent Valuation", SSRN Electronic Journal
  • Ahn, D., Lee, D., Hosanagar, K. (In Press). "Interpretable Deep Learning Approach to Churn Management", SSRN Electronic Journal
  • Burtch, G., He, Q., Hong, Y., Lee, D. (In Press). "Peer Awards Retain New Users and Encourage Exploitation in Users’ Production of Creative UGC", SSRN Electronic Journal
  • Lee, D., Hosanagar, K. (In Press). "How Do Product Attributes Moderate the Impact of Recommender Systems?", SSRN Electronic Journal
  • Shi, Z., Liu, X., Lee, D., Srinivasan, K. (2023). "How Do Fast-Fashion Copycats Affect the Popularity of Premium Brands? Evidence from Social Media", Journal of Marketing Research, 60 (6), 1027-1051
  • Hosanagar, K., Lee, D. (2023). "AI in Personalized Product Recommendations", Management and Business Review
  • Burtch, G., He, Q., Hong, Y., Lee, D. (2022). "How Do Peer Awards Motivate Creative Content? Experimental Evidence from Reddit", Management Science, 68 (5), 3488-3506
  • Zhang, S., Lee, D., Singh, P., Srinivasan, K. (2021). "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features", Management Science
  • Zhang, S., Lee, D., Singh, P., Mukhopadhyay, T. (2021). "EXPRESS: Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft", Journal of Marketing Research 002224372110621-002224372110621
  • Wang, W., Zhao, H., Lee, D., Chen, G. (2021). "Machine Learning for Consumers and Markets", Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  • Lee, D., Hosanagar, K. (2021). "How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?", Management Science, 67 (1), 524-546
  • Proserpio, D., Hauser, J., Liu, X., Amano, T., Burnap, A., Guo, T., Lee, D., Lewis, R., Misra, K., Schwarz, E., Timoshenko, A., Xu, L., Yoganarasimhan, H. (2020). "Soul and machine (learning)", Marketing Letters, 31 (4), 393-404
  • Liu, X., Lee, D., Srinivasan, K. (2019). "Large-Scale Cross-Category Analysis of Consumer Review Content on Sales Conversion Leveraging Deep Learning", Journal of Marketing Research, 56 (6), 918-943
  • Lee, D., Hosanagar, K. (2019). "How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment", Information Systems Research, 30 (1), 239-259
  • Burtch, D. (2019). "Peer Symbolic Awards Increase User Content Generation but Reduce Content Novelty",
  • Lee, D., Hosanagar, K., Nair, H. (2018). "Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook", Management Science, 64 (11), 5105-5131
  • Lee, D., Gopal, A., Lee, D. (2018). "Micro-Giving: On the Use of Mobile Devices and Monetary Subsidies in Charitable Giving", Academy of Management Proceedings, 2018 (1), 15011-15011
  • Lee, D., Hosanagar, K. (2016). "When do Recommender Systems Work the Best?", Proceedings of the 25th International Conference on World Wide Web
  • Hosanagar, K., Fleder, D., Lee, D., Buja, A. (2014). "Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation", Management Science, 60 (4), 805-823
    Research Presentations
  • Lee, D. Generative AI, Human Creativity, and Art, University of Arizona, 2024
  • Lee, D. Generative AI, Human Creativity, and Art, University of Florida, 2024
  • Lee, D. Generative AI, Human Creativity, and Art, CCNY Baruch College, 2024
  • Lee, D. Generative AI, Human Creativity, and Art, Purdue University, 2024
  • Lee, D. Generative AI, Human Creativity, and Art, Case Western University, 2024
  • Lee, D. Generative AI, Human Creativity, and Art, MIT, 2023
  • Lee, D. Generative AI, Human Creativity, and Art, University of Tennessee, Knoxville, 2023
  • Lee, D. Generative AI, Human Creativity, and Art, UT Dallas, 2023
  • Lee, D. Generative AI, Human Creativity, and Art, UW Milwaukee, 2023
  • Lee, D. Invited University Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, Nova SBE Lisbon, 2023
  • Lee, D. Invited University Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, Tel Aviv University, 2023
  • Lee, D. Invited University Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, Temple University, 2023
  • Lee, D. Digital Marketing Symposium: Relevance and Privacy- Leveraging Personalized Marketing for Responsible Growth, Questrom School, 2023
  • Lee, d. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, Nanyang Technological University, 2023
  • Lee, D. DBI + Susilo Institute Symposium: The Emerging Impact of AI on Consumer Engagement, Questrom School, 2023
  • Lee, D. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, American University, 2023
  • Cheng, Z. , Jin, G. , Leccese, M. , Lee, D. , Wagman, L. Startup Buyout and Patentable Innovation: New Evidence from PatentsView, AEA, 2023
  • Kim, K. , McCarthy, D. , Lee, D. Deep Learning Methods for Customer Base Analysis: Evidence from 1000 companies over 6 years, WISE, Denmark, 2022
  • Zhou, E. , Hui, X. , Lee, D. Virtue Signaling Via Image in Second-Hand Markets: Evidence from the GPU Market, WISE, Denmark, 2022
  • Lee, D. Innovation Information Initiative Technical Working Group Meeting, NBER, 2022
  • Srinivasan, S. , Jing, C. , Lee, D. , Fournier, S. Managing and Mitigating Sociopolitical Firm Risk Events, Marketing Dynamics Conference, Georgia State University, 2022
  • Kim, K. , McCarthy, D. , Lee, D. Deep Learning Methods for Customer Base Analysis: Evidence from 1000 companies over 6 years, MARKETING DYNAMICS CONFERENCE, 2022
  • Lee, D. Human Flourishing and the futures of Intelligence, Stanford, 2022
  • Lee, D. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, University of Illinois Chigago, 2022
  • Srinivasan, S. , Jing, C. , Lee, D. , Fournier, S. Managing and Mitigating Firm Socio-Political Risk Events, Marketing Strategy Meets Wall Street, Chicago, 2022
  • Kim, K. , McCarthy, D. , Lee, D. Deep Learning Methods for Customer Base Analysis: Evidence from 1000 companies over 6 years, Marketing Strategy Meets Wall Street Conference, 2022
  • Lee, D. The future of customer analytics, driven by AI, Meta NYC, 2022
  • Cheng, Z. , Lee, D. , Tambe, S. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, NUS, Singapore, 2022
  • Cheng, Z. , Lee, D. , Tambe, S. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, The Chinese University of Hong Kong, 2022
  • Cheng, Z. , Lee, D. , Tambe, S. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, University of Rochester, 2022
  • Cheng, Z. , Lee, D. , Tambe, S. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, University of Florida, 2022
  • Jing, C. , Lee, d. , Srinivasan, S. , Fournier, S. Managing and Mitigating Firm Risk Events, Questrom Data Blitz, Questrom, 2021
  • Srinivasan, S. , Lee, D. , Fournier, S. , Jing, C. Managing and Mitigating Firm Risk Events, 2021 Conference on Artificial Intelligence, Machine Learning, and Business Analytics, Philadelphia, online, 2021
    Awards and Honors
  • 2023, ISS Sandra A. Slaughter Early Career Award
  • 2022, Best Student Paper Award Finalist at WISE
  • 2021, MSI Young Scholar 2021
  • 2021, MSBA Faculty Excellent Award for Teaching
  • 2021, Management Science ISR Division 2018-2020 Best Paper Award Finalist
  • 2021, Best Paper in Psychology of Technology Award
  • 2020, WISE 2020 Best Student Paper Award
  • 2020, Best Student Paper Runner Up
  • 2020, Best Paper Award In Information System Research 2021
  • 2020, CDO Magazine 2021 List of Leading Academic Data Leaders
  • 2020, ISS Inaugural Gordon B. Davis Young Scholar
  • 2020, Management Science ISR Division 2017-2019 Best Paper Award Finalist
  • 2019, INFORMS Best Paper in E-Business - Nominated
  • 2019, Management Science Distinguished Service Award
  • 2019, Management Science ISR Division 2016-2018 Best Paper Award Finalist
  • 2018, INFORMS Best Paper Runner Up
  • 2018, Academy of Management Best Student Paper Award
  • 2017, ICIS 2017 Best Track Paper - IT and Social Change
  • 2017, ICIS 2017 Best Conference Paper
  • 2017, CIST Best Student Paper Award
  • 2016, ISS Nunamaker-Chen Dissertation Award Runner Up
  • 2016, CIST Best Student Paper Award
  • 2016, The Lave Weil Faculty Research Award
  • 2016, Management Science ISR Division 2012-2014 Best Paper Award Finalist
  • 2014, WISE 2014 Best Student Paper Award Runner Up