Headshot of Jeff Shockley

Jeff Shockley

Associate Professor

Area: Supply Chain Management and Analytics

  • Snead Hall
  • 301 W. Main Street
  • Box 844000
  • Richmond, VA, 23284-4000
  • Office: B4149

Expertise

  • Supply Chain Management
  • Managing Innovation
  • Supply Uncertainty

Interests

Teaching
  • SCMA 320 - Production & Operations Management,
    SCMA 339 - Quantitative Solutions for Supply Chain Management,
    SCMA 675 - MBA Operations Management,
    SCMA 693 - Field Projects in Supply Chain Management & Analytics
Research
  • Supply Chain Management in Retail, Healthcare, and Food Industries, Innovation, Supply Chain Risks and Disruptions, Social Responsibility, Information-sharing and Analytics in the Global Supply Chain
Bio

Jeff Shockley (Ph.D., Clemson University) is Associate Professor of Supply Chain Management and Analytics at Virginia Commonwealth University, Richmond, VA, where he teaches graduate and undergraduate coursework in the areas of operations management, quantitative analysis, global logistics and transportation, and supply chain management. Dr. Shockley’s current work examines supply chain innovation performance and operational design effectiveness, particularly in retailing, healthcare, and other service-related industries. His papers have appeared in a number of prestigious journals including the Journal of Operations Management, Journal of Supply Chain Management, Production and Operations Management, and Decision Sciences among others. Prior to academic work, he held several corporate management positions in the retailing and healthcare industries. Dr. Shockley is an active member of the Production and Operations Management Society, the Decision Sciences Institute and the Institute for Supply Management (ISM).

Research

Published Intellectual Contributions
Journal Article
  • Smith, J. S., Shockley, J., Anderson, S., Liu, X. (2020). Tension in the Emergency Department? The Impact of Flow Stage Times on Managing Patient-Reported Experiences and Financial Productivity. Decision Sciences. DOI: http://dx.doi.org/10.1111/deci.12503