Background

Nathan Craig is an assistant professor in the Department of Management Sciences. He earned a DBA in Technology and Operations Management from Harvard Business School as well as an MS in Operations Research and a BS in Integrated Systems Engineering from The Ohio State University.

His teaching experience includes courses in operations management and stochastic modeling as well as custom and executive-education programs at Harvard Business School and the University of Chicago Booth School of Business.

His current research interests focus on retail supply chains, including capital structure and liquidation in the retail industry as well as mechanisms for improved manufacturer service levels and their impact on retailer demand. Craig’s research has been presented at various conferences and seminars, including annual meetings of the Institute for Operations Research and the Management Sciences (INFORMS) as well as the Production and Operations Management Society (POMS).

His research has been published by Harvard Business School Press, the Journal of Operations Management, and Manufacturing & Service Operations Management. Nathan is the recipient of the Wyss Award for Excellence in Doctoral Research presented by Harvard Business School.


Areas of Expertise

  • Data Analytics
  • Retailing
  • Inventory Finance
  • Supply Chain Coordination

Education

  • DBA, Technology and Operations Management, Harvard Business School
  • MS, Operations Research, The Ohio State University
  • BS, Integrated Systems Engineering, The Ohio State University

Publications

Working Papers

  • Craig, Nathan, Nicole DeHoratius, Yan Jiang, and Diego Klabjan. 2016. “Fulfillment Errors and Chargeback Penalties in Retail Supply Chains.”
  • Bendoly, Elliot, Nathan Craig, and Nicole DeHoratius. 2016. “Consistency and Recovery in Retail Supply Chains.”
  • Bendoly, Elliot, Nathan Craig, and Somak Paul. 2016. “Rewarding Service and Serving Rewards: Strategic Complications to Order Management.”
  • Craig, Nathan and Ananth Raman. “How Local Economic Factors Affect the Liquidation Value of Retail Inventory.”
  • Craig, Nathan and Nicholas Hall. “Pricing During the Liquidation of Debt-Financed Inventory.”

 

Courses

  • MBA 6270 - Data Analysis for Managers-EMBA

    Introduction to data analysis and statistics for business. Emphasis on achieving an application-oriented understanding of statistical inference and regression analysis and their use in decision making. Prereq: Enrollment in Executive MBA program, or permission of instructor.

  • BUSOBA 3332 - Business Analytics: Application of Predictive Analytics to Business Data

    Build and test predictive models that move from data to parameter estimation. Prereq: Econ 2001.01 and 2002.01 or equiv; and Stat 3202, or BusOBA 2320 and 2321; and CSE 2111 or equiv.

  • BUSOBA 7247 - Artificial Intelligence and Machine Learning for Business: Decisions from Data

    Provides business students with an overview of artificial intelligence, focusing on modern machine learning methods and applications. We study and implement supervised and unsupervised machine learning systems using software and data from practical, business contexts. Upon completion, participants will be able to identify and capitalize on opportunities to create value with artificial intelligence. Prereq: MBA 6273 or equivalent.

  • BUSOBA 8236 - Service Operations I

    Doctoral research seminar: critical analysis of research in designing effective service delivery models, service quality, measuring service performance, service profit chains. Prereq: Enrollment in BusAdm PhD program.