Dr. Dong Soo Kim is an Assistant Professor of Marketing at the Ohio State University’s Fisher College of Business. He received his PhD in Management Engineering at KAIST and joined Fisher as a tenure-track faculty member in 2018. His research focuses on understanding consumer choice and demand using quantitative methods. His research interests include choice and demand models, Bayesian estimation, machine learning and entertainment markets. His research has appeared in Marketing Science and Quantitative Marketing and Economics and he has taught several courses introducing quantitative methods at the undergrad and graduate levels, such as Advanced Marketing Research, Customer Relationship Management and Analytics for Macro-Marketing Data. He enjoys traveling, snowboarding and playing video games (with his kids).

Areas of Expertise

  • Quantitative Marketing


  • Ph.D. in Management Engineering, Korea Advanced Institute of Science and Technology (KAIST), 2012
  • M.S. in Management Engineering, Korea Advanced Institute of Science and Technology (KAIST), 2007
  • B.S. in Management Engineering, Korea Advanced Institute of Science and Technology (KAIST), 2005


  • Kim, Dong Soo, Sanghak Lee, Taegyu Hur, Jaehwan Kim, and Greg M. Allenby (2023), "A Direct Utility Model for Access Costs and Economies of Scope," Management Science, forthcoming.

  • Kim, Hyowon, Dong Soo Kim, and Greg M. Allenby (2020), "Benefit Formation and Enhancement," Quantitative Marketing and Economics, 18 419-468. [download]

  • Kim, Dong Soo, Roger A. Bailey, Nino Hardt, Greg M. Allenby (2017), "Benefit-Based Conjoint Analysis," Marketing Science, 36(1) 54-69. [download]

  • Kim, Youngju, Dong Soo Kim, and Jaehwan Kim (2014), "Non-compensatory Decision Making for Movie Choice: Role of Genre and Online Word of Mouth," Journal of Korean Marketing Association, Vo. 29, February, pp. 1-20 (manuscript in Korean). [download]

  • Jun, Duk Bin, Dong Soo Kim, Sungho Park, and Myoung Hwan Park (2012), "Parameter Space Restrictions in State Space Models," Journal of Forecasting, Vol. 31, No. 2, pp. 109-123. [download]

Working Papers

  • Kim, Dong Soo and Mingyu Joo (2023), "Quality-Adjusted Reference Price for Differentiated Goods," under review at Marketing Science.

  • Kim, Dong Soo, Chul Kim, Mingyu Joo, and Hai Che (2023), "Counterfactual Demand Prediction by Theory-Regularized Deep Learning."


BUSML 4212 - Customer Relationship Management
Examines the theories of methods used to identify profitable customers, understand their needs and wants, and how to build a bond with them by developing customer-centric products and services directed toward providing customer value. Prereq: 4201 (750), 4202 (758), and BusMHR 2292 (BusAdm 499.01), or equiv.
BUSML 8252 - Marketing Models
A study of recent model-based research in the marketing literature; emphasis on the strengths and weaknesses of various modeling approaches in specific problem areas and evaluation of model-based research. Prereq: Doct standing in BusAdm, or permission of instructor. Not open to students with credit for 951. Repeatable to a maximum of 8 cr hrs or 4 completions. This course is progress graded.
BUSML 7247 - Analytics for Macro Marketing Data
A 'macro' approach to understanding the marketing decision process with implications stretching beyond the firm: i.e., consumers privacy, search and recommendation. Emphasis on data structures arising from online platforms and marketplaces as well as the prevalent technological and regulatory landscape in the industry. Prereq: Enrollment in SMB-Analytics program.
BUSML 7230 - Customer Analytics
Tools for the analysis of survey and marketplace data. Topics include deign of the surveys, scale development, analysis of the recency, frequency and monetary value of transactions, web-based 'click-stream' data and others. Prereq: MBA 6250, 6252, or 6253.
BUSML 8253 - Recent Advancements in Marketing Research
Provide students with exposure to leading marketing scholars and their most current research and give them an opportunity to critically evaluate it. Prereq: Doct standing in BusAdm, or permission of instructor. Repeatable to a maximum of 9 cr hrs or 6 completions.