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Chul Kim, Marketing, Baruch, CUNY, University of Maryland (UMD), College Park, KAIST

Chul Kim

Assistant Professor of Marketing
Baruch College
City University of New York

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Email: chul[dot]kim[at]baruch[dot]cuny[dot]edu

Employment & Education

  • Assistant Professor (2017- ), Marketing, Baruch College, CUNY

  • Lecturer (2015-2017), Marketing, University of Maryland

  • Data Scientist (2013-2015), Samsung Economic Research Institute

  • Ph.D. (2013), Management Engineering, KAIST

  • B.S. (2007), Industrial Engineering, KAIST

Research Interest

  • Substantive

    • ​Crowdfunding, Social Media, Online Search, Multi- channel Attribution

  • Methodology

    • ​Dynamic Structural Econometric Models, Optimal Sequential Search Models, Economic Modeling for Consumers’ Choice, Bayesian Statistics in Marketing Research

  • Skills in Data Science

    • ​Deep Learning, Classification, Dimension Reduction, Topic Model, R, Python, C++, MATLAB, SAS, SQL

Publications

  • “Theory-Regularized Deep Learning for Demand Curve Estimation and Prediction”, Chul Kim, Dong Soo Kim, Mingyu (Max) Joo, and Hai Che (2024). Proceedings of the IEEE International Conference on Artificial Intelligence X Business 2024

  • “Unveiling the web of interactions:Analyzing dynamic customer engagements across multiple websites”, Hyungsoo Lim, Chul Kim, and P.K. Kannan (2024). Journal of Business Research, 183

  • “Outside Good Utility and Substitution Patterns in Direct Utility Models”, Chul Kim, Adam Smith, Greg Allenby, and Jaehwan Kim (2023), Journal of Choice Modeling, 49

  • “Copula-based Direct Utility Models for Correlated Choice Alternatives”, Chul Kim, D.B. Jun, and Sungho Park (2022), Quantitative Marketing and Economics, 20, 69-99

  • “The Secret to Finding a Match: A Field Experiment on Choice Capacity Design in an Online Dating Platform”, Jaehwuen Jung, Hyungsoo Lim, Dongwon Lee, and Chul Kim (2021), Information Systems Research, 33(4)

  • “Modeling Dynamics in Crowdfunding”,Chul Kim, PK Kannan, Michael Trusov, and Andrea Ordanini (2020),
    Marketing Science, 39(2)

  • “Capturing Flexible Correlations in Multiple-Discrete Choice Outcomes using Copulas”,
    Chul Kim, D.B. Jun, and Sungho Park (2018), International Journal of Research in Marketing, 35(1)

  • “Modeling Structural Heterogeneity in Reference Price Formation”,
    Chul Kim and Youngju Kim (2016), Journal of Korean Marketing Association, 31(3)

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