Headshot of Brett Massimino

Brett Massimino

Department Chair
Associate Professor

Area: Supply Chain Management and Analytics

  • Snead Hall
  • 301 W. Main Street
  • Box 844000
  • Richmond, VA, 23284-4000
  • Office: B4155

Expertise

  • Digital Supply Chains
  • Information Security
  • Process Compliance

Interests

Teaching
  • Operations Management. Data Analytics. Data Mining. Web Scraping. Information Security.
Research
  • Digital Transformations and Information Security in Supply Chain Management
Bio

Brett Massimino (PhD, The Ohio State University) is an Assistant Professor of Supply Chain and Analytics at the Virginia Commonwealth University at School of Business, joining in December 2019. Previously, he was a faculty member for four years at Cornell University’s Johnson College of Business. His research interests include supply chain management within digital economies, the confidentiality of digital assets exchanged among supply chain partners, and the operational challenges of transitioning from traditional to digital environments. He has published articles in Production and Operations Management and Journal of Business Logistics, and has several working papers under publication consideration for top Operations Management scientific journals.

Research

Published Intellectual Contributions
Journal Article
  • Lan, Y., Gray, J., Chandrasekaran, A., Massimino, B. J. (2020). The effects of product development network positions on product performance and confidentiality performance. (7-8 ed., vol. 66). Journal of Operations Management.
  • Massimino, B. J., Lawrence, B. (2019). Supersize Me? Franchisee size and voluntary compliance with corporate brand-building initiatives. Journal of Operations Management.
  • Massimino, B. J., Gray, J., Lan, Y. (2018). On the Inattention to Digital Confidentiality in Operations and Supply Chain Research. (8 ed., vol. 27, pp.1492-1515). Production and Operations Management. DOI: 10.1111/poms.12879
  • Massimino, B. J. (2016). Accessing Online Data: Web-Crawling and Information-Scraping Techniques to Automate the Assembly of Research Data. (1 ed., vol. 37, pp.34-42). Journal of Business Logistics. DOI: 10.1111/jbl.12120